NostalgiaForInfinityX3

import copy
import logging
import pathlib
import rapidjson
import freqtrade.vendor.qtpylib.indicators as qtpylib
import numpy as np
import talib.abstract as ta
import pandas as pd
import pandas_ta as pta
from freqtrade.strategy.interface import IStrategy
from freqtrade.strategy import merge_informative_pair
from freqtrade.strategy import DecimalParameter, CategoricalParameter
from pandas import DataFrame, Series
from functools import reduce
from freqtrade.persistence import Trade
from datetime import datetime, timedelta
import time
from typing import Optional
import warnings

log = logging.getLogger(__name__)
# log.setLevel(logging.DEBUG)
warnings.simplefilter(action="ignore", category=pd.errors.PerformanceWarning)

#############################################################################################################
##                NostalgiaForInfinityX3 by iterativ                                                       ##
##           https://github.com/iterativv/NostalgiaForInfinity                                             ##
##                                                                                                         ##
##    Strategy for Freqtrade https://github.com/freqtrade/freqtrade                                        ##
##                                                                                                         ##
#############################################################################################################
##               GENERAL RECOMMENDATIONS                                                                   ##
##                                                                                                         ##
##   For optimal performance, suggested to use between 4 and 6 open trades, with unlimited stake.          ##
##   A pairlist with 40 to 80 pairs. Volume pairlist works well.                                           ##
##   Prefer stable coin (USDT, USDC etc) pairs, instead of BTC or ETH pairs.                              ##
##   Highly recommended to blacklist leveraged tokens (*BULL, *BEAR, *UP, *DOWN etc).                      ##
##   Ensure that you don't override any variables in you config.json. Especially                           ##
##   the timeframe (must be 5m).                                                                           ##
##     use_exit_signal must set to true (or not set at all).                                               ##
##     exit_profit_only must set to false (or not set at all).                                             ##
##     ignore_roi_if_entry_signal must set to true (or not set at all).                                    ##
##                                                                                                         ##
#############################################################################################################
##               DONATIONS                                                                                 ##
##                                                                                                         ##
##   BTC: bc1qvflsvddkmxh7eqhc4jyu5z5k6xcw3ay8jl49sk                                                       ##
##   ETH (ERC20): 0x83D3cFb8001BDC5d2211cBeBB8cB3461E5f7Ec91                                               ##
##   BEP20/BSC (USDT, ETH, BNB, ...): 0x86A0B21a20b39d16424B7c8003E4A7e12d78ABEe                           ##
##   TRC20/TRON (USDT, TRON, ...): TTAa9MX6zMLXNgWMhg7tkNormVHWCoq8Xk                                      ##
##                                                                                                         ##
##  Patreon: https://www.patreon.com/iterativ                                                              ##
##                                                                                                         ##
##               REFERRAL LINKS                                                                            ##
##                                                                                                         ##
##  Binance: https://www.binance.com/join?ref=C68K26A9 (20% discount on trading fees)                      ##
##  Kucoin: https://www.kucoin.com/r/af/QBSSS5J2 (20% lifetime discount on trading fees)                   ##
##  Gate: https://www.gate.io/share/nfinfinity (20% lifetime discount on trading fees)                     ##
##  OKX: https://www.okx.com/join/11749725931 (20% discount on trading fees)                               ##
##  MEXC: https://promote.mexc.com/a/luA6Xclb (10% discount on trading fees)                               ##
##  ByBit: https://partner.bybit.com/b/nfi                                                                 ##
##  Bitget: https://bonus.bitget.com/fdqe83481698435803831 (lifetime 20% +10% extra spot rebate)           ##
##  BitMart: https://www.bitmart.com/invite/nfinfinity/en-US (20% lifetime discount on trading fees)       ##
##  HTX: https://www.htx.com/invite/en-us/1f?invite_code=ubpt2223                                          ##
##         (Welcome Bonus worth 241 USDT upon completion of a deposit and trade)                           ##
##  Bitvavo: https://bitvavo.com/invite?a=D22103A4BC (no fees for the first € 10000)                       ##
#############################################################################################################


class NostalgiaForInfinityX3(IStrategy):
  INTERFACE_VERSION = 3

  def version(self) -> str:
    return "v13.2.9"

  stoploss = -0.99

  # Trailing stoploss (not used)
  trailing_stop = False
  trailing_only_offset_is_reached = True
  trailing_stop_positive = 0.01
  trailing_stop_positive_offset = 0.03

  use_custom_stoploss = False

  # Optimal timeframe for the strategy.
  timeframe = "5m"
  info_timeframes = ["15m", "1h", "4h", "1d"]

  # BTC informatives
  btc_info_timeframes = ["5m", "15m", "1h", "4h", "1d"]

  # Backtest Age Filter emulation
  has_bt_agefilter = True
  bt_min_age_days = 3

  # Exchange Downtime protection
  has_downtime_protection = False

  # Do you want to use the hold feature? (with hold-trades.json)
  hold_support_enabled = True

  # Run "populate_indicators()" only for new candle.
  process_only_new_candles = True

  # These values can be overridden in the "ask_strategy" section in the config.
  use_exit_signal = True
  exit_profit_only = False
  ignore_roi_if_entry_signal = True

  # Number of candles the strategy requires before producing valid signals
  startup_candle_count: int = 800

  # Long Normal mode tags
  long_normal_mode_tags = ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14"]
  # Long Pump mode tags
  long_pump_mode_tags = ["21", "22", "23", "24", "25", "26"]
  # Long Quick mode tags
  long_quick_mode_tags = ["41", "42", "43", "44", "45", "46", "47", "48", "49", "50", "51", "52", "53"]
  # Long rebuy mode tags
  long_rebuy_mode_tags = ["61", "62"]
  # Long high profit mode tags
  long_mode_tags = ["81", "82"]
  # Long rapid mode tags
  long_rapid_mode_tags = ["101", "102", "103", "104", "105", "106", "107", "108", "109", "110"]
  # Long grind mode tags
  long_grind_mode_tags = ["120"]

  long_normal_mode_name = "long_normal"
  long_pump_mode_name = "long_pump"
  long_quick_mode_name = "long_quick"
  long_rebuy_mode_name = "long_rebuy"
  long_high_profit_mode_name = "long_hp"
  long_rapid_mode_name = "long_rapid"
  long_grind_mode_name = "long_grind"

  # Shorting

  # Short normal mode tags
  short_normal_mode_tags = ["500", "501"]
  # Short Pump mode tags
  short_pump_mode_tags = ["521", "522", "523", "524", "525", "526"]
  # Short Quick mode tags
  short_quick_mode_tags = ["541", "542", "543", "544", "545", "546", "547", "548", "549", "550"]
  # Short rebuy mode tags
  short_rebuy_mode_tags = ["561"]
  # Short mode tags
  short_mode_tags = ["581", "582"]
  # Short rapid mode tags
  short_rapid_mode_tags = ["601", "602", "603", "604", "605", "606", "607", "608", "609", "610"]
  # Short grind mode tags
  short_grind_mode_tags = ["620"]

  short_normal_mode_name = "short_normal"
  short_pump_mode_name = "short_pump"
  short_quick_mode_name = "short_quick"
  short_rebuy_mode_name = "short_rebuy"
  short_high_profit_mode_name = "short_hp"
  short_rapid_mode_name = "short_rapid"

  is_futures_mode = False
  futures_mode_leverage = 3.0
  futures_mode_leverage_rebuy_mode = 3.0
  futures_mode_leverage_grind_mode = 3.0

  # Stop thresholds. 0: Doom Bull, 1: Doom Bear, 2: u_e Bull, 3: u_e Bear, 4: u_e mins Bull, 5: u_e mins Bear.
  # 6: u_e ema % Bull, 7: u_e ema % Bear, 8: u_e RSI diff Bull, 9: u_e RSI diff Bear.
  # 10: enable Doom Bull, 11: enable Doom Bear, 12: enable u_e Bull, 13: enable u_e Bear.
  stop_thresholds = [-0.2, -0.2, -0.025, -0.025, 720, 720, 0.016, 0.016, 24.0, 24.0, False, False, True, True]
  # Based on the the first entry (regardless of rebuys)
  stop_threshold = 4.0
  stop_threshold_futures = 12.0
  stop_threshold_futures_rapid = 12.0
  stop_threshold_spot_rapid = 4.0
  stop_threshold_spot_rebuy = 2.0
  stop_threshold_futures_rebuy = 4.0

  # user specified fees to be used for profit calculations
  custom_fee_open_rate = None
  custom_fee_close_rate = None

  # Rebuy mode minimum number of free slots
  rebuy_mode_min_free_slots = 2

  # Position adjust feature
  position_adjustment_enable = True

  # Grinding feature
  grinding_enable = True

  # Grinding
  grind_derisk_spot = -0.40
  grind_derisk_futures = -0.50

  grind_1_stop_grinds_spot = -0.70
  grind_1_profit_threshold_spot = 0.018
  grind_1_stakes_spot = [0.22, 0.24, 0.26]
  grind_1_sub_thresholds_spot = [-0.065, -0.075, -0.085]

  grind_1_stop_grinds_futures = -0.70
  grind_1_profit_threshold_futures = 0.018
  grind_1_stakes_futures = [0.22, 0.24, 0.26]
  grind_1_sub_thresholds_futures = [-0.065, -0.075, -0.085]

  grind_2_stop_grinds_spot = -0.70
  grind_2_profit_threshold_spot = 0.018
  grind_2_stakes_spot = [0.16, 0.26, 0.32]
  grind_2_sub_thresholds_spot = [-0.065, -0.075, -0.085]

  grind_2_stop_grinds_futures = -0.70
  grind_2_profit_threshold_futures = 0.018
  grind_2_stakes_futures = [0.16, 0.26, 0.32]
  grind_2_sub_thresholds_futures = [-0.065, -0.075, -0.085]

  grind_3_stop_grinds_spot = -0.70
  grind_3_profit_threshold_spot = 0.018
  grind_3_stakes_spot = [0.16, 0.18, 0.20]
  grind_3_sub_thresholds_spot = [-0.065, -0.075, -0.085]

  grind_3_stop_grinds_futures = -0.70
  grind_3_profit_threshold_futures = 0.018
  grind_3_stakes_futures = [0.16, 0.18, 0.20]
  grind_3_sub_thresholds_futures = [-0.065, -0.075, -0.085]

  grind_4_stop_grinds_spot = -0.70
  grind_4_profit_threshold_spot = 0.018
  grind_4_stakes_spot = [0.16, 0.18, 0.20]
  grind_4_sub_thresholds_spot = [-0.065, -0.075, -0.085]

  grind_4_stop_grinds_futures = -0.70
  grind_4_profit_threshold_futures = 0.018
  grind_4_stakes_futures = [0.16, 0.18, 0.20]
  grind_4_sub_thresholds_futures = [-0.065, -0.075, -0.085]

  grind_5_stop_grinds_spot = -0.70
  grind_5_profit_threshold_spot = 0.048
  grind_5_stakes_spot = [0.16, 0.18, 0.20]
  grind_5_sub_thresholds_spot = [-0.065, -0.075, -0.085]

  grind_5_stop_grinds_futures = -0.70
  grind_5_profit_threshold_futures = 0.048
  grind_5_stakes_futures = [0.16, 0.18, 0.20]
  grind_5_sub_thresholds_futures = [-0.065, -0.075, -0.085]

  grind_6_stop_grinds_spot = -0.70
  grind_6_profit_threshold_spot = 0.018
  grind_6_stakes_spot = [0.05, 0.057, 0.065, 0.074, 0.084, 0.095, 0.107, 0.121, 0.137]
  grind_6_sub_thresholds_spot = [-0.03, -0.035, -0.04, -0.045, -0.05, -0.055, -0.06, -0.065, -0.07]

  grind_6_stop_grinds_futures = -0.70
  grind_6_profit_threshold_futures = 0.018
  grind_6_stakes_futures = [0.05, 0.057, 0.065, 0.074, 0.084, 0.095, 0.107, 0.121, 0.137]
  grind_6_sub_thresholds_futures = [-0.03, -0.035, -0.04, -0.045, -0.05, -0.055, -0.06, -0.065, -0.07]

  grind_1_derisk_1_stop_grinds_spot = -0.70
  grind_1_derisk_1_profit_threshold_spot = 0.018
  grind_1_derisk_1_stakes_spot = [0.25, 0.30, 0.35]
  grind_1_derisk_1_sub_thresholds_spot = [-0.07, -0.08, -0.09]

  grind_1_derisk_1_stop_grinds_futures = -0.70
  grind_1_derisk_1_profit_threshold_futures = 0.018
  grind_1_derisk_1_stakes_futures = [0.25, 0.30, 0.35]
  grind_1_derisk_1_sub_thresholds_futures = [-0.07, -0.08, -0.09]

  grind_2_derisk_1_stop_grinds_spot = -0.70
  grind_2_derisk_1_profit_threshold_spot = 0.018
  grind_2_derisk_1_stakes_spot = [0.16, 0.22, 0.28]
  grind_2_derisk_1_sub_thresholds_spot = [-0.065, -0.075, -0.085]

  grind_2_derisk_1_stop_grinds_futures = -0.70
  grind_2_derisk_1_profit_threshold_futures = 0.018
  grind_2_derisk_1_stakes_futures = [0.16, 0.22, 0.28]
  grind_2_derisk_1_sub_thresholds_futures = [-0.065, -0.075, -0.085]

  # Non rebuy modes
  regular_mode_stake_multiplier_spot = [0.5]
  regular_mode_stake_multiplier_futures = [0.5]
  regular_mode_use_grind_stops = False

  regular_mode_rebuy_stakes_spot = [0.10, 0.10, 0.10]
  regular_mode_rebuy_thresholds_spot = [-0.12, -0.14, -0.16]
  regular_mode_grind_1_stakes_spot = [0.22, 0.24, 0.26]
  regular_mode_grind_1_thresholds_spot = [-0.06, -0.07, -0.09]
  regular_mode_grind_1_stop_grinds_spot = -0.20
  regular_mode_grind_1_profit_threshold_spot = 0.018
  regular_mode_grind_2_stakes_spot = [0.14, 0.20, 0.26]
  regular_mode_grind_2_thresholds_spot = [-0.04, -0.06, -0.08]
  regular_mode_grind_2_stop_grinds_spot = -0.20
  regular_mode_grind_2_profit_threshold_spot = 0.018
  regular_mode_grind_3_stakes_spot = [0.18, 0.20, 0.22]
  regular_mode_grind_3_thresholds_spot = [-0.03, -0.06, -0.08]
  regular_mode_grind_3_stop_grinds_spot = -0.20
  regular_mode_grind_3_profit_threshold_spot = 0.018
  regular_mode_grind_4_stakes_spot = [0.18, 0.20, 0.22]
  regular_mode_grind_4_thresholds_spot = [-0.03, -0.06, -0.08]
  regular_mode_grind_4_stop_grinds_spot = -0.20
  regular_mode_grind_4_profit_threshold_spot = 0.018
  regular_mode_grind_5_stakes_spot = [0.18, 0.20, 0.22]
  regular_mode_grind_5_thresholds_spot = [-0.03, -0.06, -0.08]
  regular_mode_grind_5_stop_grinds_spot = -0.20
  regular_mode_grind_5_profit_threshold_spot = 0.048
  regular_mode_grind_6_stakes_spot = [0.05, 0.057, 0.065, 0.074, 0.084, 0.095, 0.107, 0.121, 0.137]
  regular_mode_grind_6_thresholds_spot = [-0.025, -0.03, -0.035, -0.04, -0.045, -0.05, -0.055, -0.06, -0.065]
  regular_mode_grind_6_stop_grinds_spot = -0.20
  regular_mode_grind_6_profit_threshold_spot = 0.018
  regular_mode_derisk_1_spot = -2.0
  regular_mode_derisk_1_spot_old = -2.0
  regular_mode_derisk_1_reentry_spot = -0.08
  regular_mode_derisk_spot = -4.0
  regular_mode_derisk_spot_old = -4.0

  regular_mode_rebuy_stakes_futures = [0.10, 0.10, 0.10]
  regular_mode_rebuy_thresholds_futures = [-0.12, -0.14, -0.16]
  regular_mode_grind_1_stakes_futures = [0.22, 0.24, 0.26]
  regular_mode_grind_1_thresholds_futures = [-0.06, -0.07, -0.09]
  regular_mode_grind_1_stop_grinds_futures = -0.20
  regular_mode_grind_1_profit_threshold_futures = 0.018
  regular_mode_grind_2_stakes_futures = [0.14, 0.20, 0.26]
  regular_mode_grind_2_thresholds_futures = [-0.04, -0.06, -0.08]
  regular_mode_grind_2_stop_grinds_futures = -0.20
  regular_mode_grind_2_profit_threshold_futures = 0.018
  regular_mode_grind_3_stakes_futures = [0.18, 0.20, 0.22]
  regular_mode_grind_3_thresholds_futures = [-0.03, -0.06, -0.08]
  regular_mode_grind_3_stop_grinds_futures = -0.20
  regular_mode_grind_3_profit_threshold_futures = 0.018
  regular_mode_grind_4_stakes_futures = [0.18, 0.20, 0.22]
  regular_mode_grind_4_thresholds_futures = [-0.03, -0.06, -0.08]
  regular_mode_grind_4_stop_grinds_futures = -0.20
  regular_mode_grind_4_profit_threshold_futures = 0.018
  regular_mode_grind_5_stakes_futures = [0.18, 0.20, 0.22]
  regular_mode_grind_5_thresholds_futures = [-0.03, -0.06, -0.08]
  regular_mode_grind_5_stop_grinds_futures = -0.20
  regular_mode_grind_5_profit_threshold_futures = 0.048
  regular_mode_grind_6_stakes_futures = [0.05, 0.057, 0.065, 0.074, 0.084, 0.095, 0.107, 0.121, 0.137]
  regular_mode_grind_6_thresholds_futures = [-0.025, -0.03, -0.035, -0.04, -0.045, -0.05, -0.055, -0.06, -0.065]
  regular_mode_grind_6_stop_grinds_futures = -0.20
  regular_mode_grind_6_profit_threshold_futures = 0.018
  regular_mode_derisk_1_futures = -4.0
  regular_mode_derisk_1_futures_old = -4.0
  regular_mode_derisk_1_reentry_futures = -0.08  # without leverage
  regular_mode_derisk_futures = -8.0
  regular_mode_derisk_futures_old = -8.0

  # Rebuy mode
  rebuy_mode_stake_multiplier = 0.2
  rebuy_mode_stake_multiplier_alt = 0.3
  rebuy_mode_max = 3
  rebuy_mode_derisk_spot = -0.9
  rebuy_mode_derisk_futures = -2.0
  rebuy_mode_stakes_spot = [1.0, 2.0, 4.0]
  rebuy_mode_stakes_futures = [1.0, 2.0, 4.0]
  rebuy_mode_thresholds_spot = [-0.08, -0.10, -0.12]
  rebuy_mode_thresholds_futures = [-0.08, -0.10, -0.12]

  # Grind mode
  grind_mode_stake_multiplier_spot = [0.20, 0.30, 0.40, 0.50, 0.60, 0.70]
  grind_mode_stake_multiplier_futures = [0.20, 0.30, 0.40, 0.50]
  grind_mode_first_entry_profit_threshold_spot = 0.018
  grind_mode_first_entry_profit_threshold_futures = 0.018
  grind_mode_first_entry_stop_threshold_spot = -0.30
  grind_mode_first_entry_stop_threshold_futures = -0.30
  grind_mode_max_slots = 1
  grind_mode_coins = [
    "MATIC",
    "ADA",
    "ARB",
    "DOT",
    "XLM",
    "ALGO",
    "RNDR",
    "XMR",
    "AVAX",
    "NEAR",
    "DOGE",
    "ETC",
    "FTM",
    "KAS",
    "HBAR",
    "SUI",
    "TON",
    "XRP",
    "UNI",
    "LTC",
    "FIL",
    "ATOM",
    "GRT",
    "LINK",
    "VET",
    "THETA",
    "EOS",
    "LRC",
    "QTUM",
    "CELR",
  ]

  # Profit max thresholds
  profit_max_thresholds = [0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.05, 0.05]

  # Max allowed buy "slippage", how high to buy on the candle
  max_slippage = 0.012

  # BTC/ETH stakes
  btc_stakes = ["BTC", "ETH"]

  #############################################################
  # Buy side configuration

  long_entry_signal_params = {
    # Enable/Disable conditions
    # -------------------------------------------------------
    "long_entry_condition_1_enable": True,
    "long_entry_condition_2_enable": True,
    "long_entry_condition_3_enable": True,
    "long_entry_condition_4_enable": True,
    "long_entry_condition_5_enable": True,
    "long_entry_condition_6_enable": True,
    "long_entry_condition_7_enable": True,
    "long_entry_condition_8_enable": True,
    "long_entry_condition_9_enable": True,
    "long_entry_condition_10_enable": True,
    "long_entry_condition_11_enable": True,
    "long_entry_condition_12_enable": True,
    "long_entry_condition_13_enable": True,
    "long_entry_condition_14_enable": True,
    "long_entry_condition_21_enable": True,
    "long_entry_condition_22_enable": True,
    "long_entry_condition_23_enable": True,
    "long_entry_condition_24_enable": True,
    "long_entry_condition_25_enable": True,
    "long_entry_condition_26_enable": True,
    "long_entry_condition_41_enable": True,
    "long_entry_condition_42_enable": True,
    "long_entry_condition_43_enable": True,
    "long_entry_condition_44_enable": True,
    "long_entry_condition_45_enable": True,
    "long_entry_condition_46_enable": True,
    "long_entry_condition_47_enable": True,
    "long_entry_condition_48_enable": True,
    "long_entry_condition_49_enable": True,
    "long_entry_condition_50_enable": True,
    "long_entry_condition_51_enable": True,
    "long_entry_condition_52_enable": True,
    "long_entry_condition_53_enable": True,
    "long_entry_condition_61_enable": True,
    "long_entry_condition_62_enable": True,
    "long_entry_condition_81_enable": True,
    "long_entry_condition_82_enable": True,
    "long_entry_condition_101_enable": True,
    "long_entry_condition_102_enable": True,
    "long_entry_condition_103_enable": True,
    "long_entry_condition_104_enable": True,
    "long_entry_condition_105_enable": True,
    "long_entry_condition_106_enable": True,
    "long_entry_condition_107_enable": True,
    "long_entry_condition_108_enable": True,
    "long_entry_condition_109_enable": True,
    "long_entry_condition_110_enable": True,
    "long_entry_condition_120_enable": True,
  }

  short_entry_signal_params = {
    # Enable/Disable conditions
    # -------------------------------------------------------
    "short_entry_condition_500_enable": True,
    "short_entry_condition_501_enable": True,
  }

  buy_protection_params = {}

  #############################################################

  entry_24_close_max_12 = DecimalParameter(00.50, 0.95, default=0.80, decimals=2, space="buy", optimize=True)
  entry_24_close_max_24 = DecimalParameter(00.50, 0.95, default=0.75, decimals=2, space="buy", optimize=True)
  entry_24_close_max_48 = DecimalParameter(00.50, 0.95, default=0.70, decimals=2, space="buy", optimize=True)
  entry_24_high_max_24_1h = DecimalParameter(00.40, 0.95, default=0.60, decimals=2, space="buy", optimize=True)
  entry_24_high_max_24_4h = DecimalParameter(00.40, 0.95, default=0.50, decimals=2, space="buy", optimize=True)
  entry_24_high_max_6_1d = DecimalParameter(00.30, 0.95, default=0.45, decimals=2, space="buy", optimize=True)
  entry_24_hl_pct_change_6_1h = DecimalParameter(00.30, 0.90, default=0.80, decimals=2, space="buy", optimize=True)
  entry_24_hl_pct_change_12_1h = DecimalParameter(00.40, 1.00, default=0.90, decimals=2, space="buy", optimize=True)
  entry_24_hl_pct_change_24_1h = DecimalParameter(00.50, 1.20, default=1.10, decimals=2, space="buy", optimize=True)
  entry_24_hl_pct_change_48_1h = DecimalParameter(00.60, 1.60, default=1.20, decimals=2, space="buy", optimize=True)
  entry_24_sup_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=True)
  entry_24_res_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=True)
  entry_24_sup_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=True)
  entry_24_res_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=True)
  entry_24_sup_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=True)
  entry_24_res_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=True)
  entry_24_ema_200_not_dec_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=True)
  entry_24_ema_200_not_dec_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=True)
  entry_24_ema_200_not_dec_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=True)
  entry_24_not_downtrend_15m_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=True)
  entry_24_not_downtrend_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=True)
  entry_24_not_downtrend_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=True)
  entry_24_not_downtrend_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=True)
  entry_24_ema_50_over_ema_200_enabled = CategoricalParameter([True, False], default=True, space="buy", optimize=True)
  entry_24_ema_12_1h_over_ema_200_1h_enabled = CategoricalParameter(
    [True, False], default=True, space="buy", optimize=True
  )
  entry_24_rsi_3_min = DecimalParameter(00.0, 30.0, default=2.0, decimals=0, space="buy", optimize=True)
  entry_24_rsi_3_max = DecimalParameter(30.0, 70.0, default=46.0, decimals=0, space="buy", optimize=True)
  entry_24_rsi_3_15m_min = DecimalParameter(00.0, 36.0, default=2.0, decimals=0, space="buy", optimize=True)
  entry_24_rsi_3_1h_min = DecimalParameter(00.0, 36.0, default=8.0, decimals=0, space="buy", optimize=True)
  entry_24_rsi_3_4h_min = DecimalParameter(00.0, 36.0, default=8.0, decimals=0, space="buy", optimize=True)
  entry_24_rsi_3_1d_min = DecimalParameter(00.0, 30.0, default=8.0, decimals=0, space="buy", optimize=True)
  entry_24_cti_20_1h_max = DecimalParameter(0.0, 0.99, default=0.95, decimals=2, space="buy", optimize=True)
  entry_24_rsi_14_1h_max = DecimalParameter(50.0, 90.0, default=80.0, decimals=0, space="buy", optimize=True)
  entry_24_cti_20_4h_max = DecimalParameter(0.0, 0.99, default=0.95, decimals=2, space="buy", optimize=True)
  entry_24_rsi_14_4h_max = DecimalParameter(50.0, 90.0, default=80.0, decimals=0, space="buy", optimize=True)
  entry_24_cti_20_1d_max = DecimalParameter(0.0, 0.99, default=0.95, decimals=2, space="buy", optimize=True)
  entry_24_rsi_14_1d_max = DecimalParameter(50.0, 90.0, default=90.0, decimals=0, space="buy", optimize=True)
  entry_24_r_14_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=True)
  entry_24_r_14_4h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=True)
  entry_24_r_480_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=True)
  entry_24_r_480_4h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=True)
  entry_24_rsi_14_min = DecimalParameter(20.0, 60.0, default=26.0, decimals=0, space="buy", optimize=True)
  entry_24_rsi_14_max = DecimalParameter(20.0, 60.0, default=46.0, decimals=0, space="buy", optimize=True)
  entry_24_cti_20_max = DecimalParameter(-0.99, -0.60, default=-0.75, decimals=2, space="buy", optimize=True)
  entry_24_r_14_max = DecimalParameter(-100.0, 80.0, default=-97.0, decimals=0, space="buy", optimize=True)
  entry_24_ewo_50_200_min = DecimalParameter(2.0, 10.0, default=7.0, decimals=1, space="buy", optimize=True)
  entry_24_ewo_50_200_max = DecimalParameter(10.0, 30.0, default=24.0, decimals=1, space="buy", optimize=True)
  entry_24_sma_offset = DecimalParameter(0.960, 0.999, default=0.972, decimals=3, space="buy", optimize=True)

  entry_25_close_max_12 = DecimalParameter(00.50, 0.95, default=0.80, decimals=2, space="buy", optimize=False)
  entry_25_close_max_24 = DecimalParameter(00.50, 0.95, default=0.75, decimals=2, space="buy", optimize=False)
  entry_25_close_max_48 = DecimalParameter(00.50, 0.95, default=0.70, decimals=2, space="buy", optimize=False)
  entry_25_high_max_24_1h = DecimalParameter(00.40, 0.95, default=0.60, decimals=2, space="buy", optimize=False)
  entry_25_high_max_24_4h = DecimalParameter(00.40, 0.95, default=0.50, decimals=2, space="buy", optimize=False)
  entry_25_high_max_6_1d = DecimalParameter(00.30, 0.95, default=0.45, decimals=2, space="buy", optimize=False)
  entry_25_hl_pct_change_6_1h = DecimalParameter(00.30, 0.90, default=0.5, decimals=2, space="buy", optimize=False)
  entry_25_hl_pct_change_12_1h = DecimalParameter(00.40, 1.00, default=0.75, decimals=2, space="buy", optimize=False)
  entry_25_hl_pct_change_24_1h = DecimalParameter(00.50, 1.20, default=0.90, decimals=2, space="buy", optimize=False)
  entry_25_hl_pct_change_48_1h = DecimalParameter(00.60, 1.60, default=1.00, decimals=2, space="buy", optimize=False)
  entry_25_sup_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_25_res_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_25_sup_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_25_res_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_25_sup_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_25_res_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_25_ema_200_not_dec_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_25_ema_200_not_dec_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_25_ema_200_not_dec_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_25_not_downtrend_15m_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_25_not_downtrend_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_25_not_downtrend_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_25_not_downtrend_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_25_rsi_3_min = DecimalParameter(00.0, 30.0, default=6.0, decimals=0, space="buy", optimize=False)
  entry_25_rsi_3_max = DecimalParameter(30.0, 60.0, default=60.0, decimals=0, space="buy", optimize=False)
  entry_25_rsi_3_15m_min = DecimalParameter(00.0, 30.0, default=8.0, decimals=0, space="buy", optimize=False)
  entry_25_rsi_3_1h_min = DecimalParameter(00.0, 30.0, default=8.0, decimals=0, space="buy", optimize=False)
  entry_25_rsi_3_4h_min = DecimalParameter(00.0, 30.0, default=8.0, decimals=0, space="buy", optimize=False)
  entry_25_rsi_3_1d_min = DecimalParameter(00.0, 30.0, default=8.0, decimals=0, space="buy", optimize=False)
  entry_25_cti_20_1h_max = DecimalParameter(0.0, 0.99, default=0.95, decimals=2, space="buy", optimize=False)
  entry_25_rsi_14_1h_max = DecimalParameter(50.0, 90.0, default=75.0, decimals=0, space="buy", optimize=False)
  entry_25_cti_20_4h_max = DecimalParameter(0.0, 0.99, default=0.95, decimals=2, space="buy", optimize=False)
  entry_25_rsi_14_4h_max = DecimalParameter(50.0, 90.0, default=75.0, decimals=0, space="buy", optimize=False)
  entry_25_cti_20_1d_max = DecimalParameter(0.0, 0.99, default=0.95, decimals=2, space="buy", optimize=False)
  entry_25_rsi_14_1d_max = DecimalParameter(50.0, 90.0, default=90.0, decimals=0, space="buy", optimize=False)
  entry_25_r_14_1h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_25_r_14_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_25_r_14_4h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_25_r_14_4h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_25_r_480_1h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_25_r_480_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_25_r_480_4h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_25_r_480_4h_max = DecimalParameter(-40.0, -0.0, default=-20.0, decimals=0, space="buy", optimize=False)
  entry_25_rsi_14_max = DecimalParameter(20.0, 46.0, default=46.0, decimals=0, space="buy", optimize=False)
  entry_25_cti_20_max = DecimalParameter(-0.9, 0.0, default=-0.9, decimals=1, space="buy", optimize=False)
  entry_25_ewo_50_200_min = DecimalParameter(1.0, 8.0, default=2.6, decimals=1, space="buy", optimize=False)
  entry_25_sma_offset = DecimalParameter(0.920, 0.950, default=0.942, decimals=3, space="buy", optimize=False)

  entry_26_close_max_12 = DecimalParameter(00.50, 0.95, default=0.80, decimals=2, space="buy", optimize=False)
  entry_26_close_max_24 = DecimalParameter(00.50, 0.95, default=0.75, decimals=2, space="buy", optimize=False)
  entry_26_close_max_48 = DecimalParameter(00.50, 0.95, default=0.70, decimals=2, space="buy", optimize=False)
  entry_26_high_max_24_1h = DecimalParameter(00.40, 0.95, default=0.60, decimals=2, space="buy", optimize=False)
  entry_26_high_max_24_4h = DecimalParameter(00.40, 0.95, default=0.50, decimals=2, space="buy", optimize=False)
  entry_26_high_max_6_1d = DecimalParameter(00.30, 0.95, default=0.45, decimals=2, space="buy", optimize=False)
  entry_26_hl_pct_change_6_1h = DecimalParameter(00.30, 0.90, default=0.80, decimals=2, space="buy", optimize=False)
  entry_26_hl_pct_change_12_1h = DecimalParameter(00.40, 1.00, default=0.90, decimals=2, space="buy", optimize=False)
  entry_26_hl_pct_change_24_1h = DecimalParameter(00.50, 1.20, default=1.10, decimals=2, space="buy", optimize=False)
  entry_26_hl_pct_change_48_1h = DecimalParameter(00.60, 1.60, default=1.20, decimals=2, space="buy", optimize=False)
  entry_26_sup_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_26_res_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_26_sup_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_26_res_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_26_sup_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_26_res_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_26_ema_200_not_dec_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_26_ema_200_not_dec_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_26_ema_200_not_dec_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_26_not_downtrend_15m_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_26_not_downtrend_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_26_not_downtrend_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_26_not_downtrend_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_26_rsi_3_min = DecimalParameter(00.0, 30.0, default=2.0, decimals=0, space="buy", optimize=False)
  entry_26_rsi_3_max = DecimalParameter(30.0, 70.0, default=46.0, decimals=0, space="buy", optimize=False)
  entry_26_rsi_3_15m_min = DecimalParameter(00.0, 36.0, default=4.0, decimals=0, space="buy", optimize=False)
  entry_26_rsi_3_1h_min = DecimalParameter(00.0, 36.0, default=6.0, decimals=0, space="buy", optimize=False)
  entry_26_rsi_3_4h_min = DecimalParameter(00.0, 36.0, default=6.0, decimals=0, space="buy", optimize=False)
  entry_26_rsi_3_1d_min = DecimalParameter(00.0, 30.0, default=6.0, decimals=0, space="buy", optimize=False)
  entry_26_cti_20_1h_max = DecimalParameter(0.0, 0.99, default=0.95, decimals=2, space="buy", optimize=False)
  entry_26_rsi_14_1h_max = DecimalParameter(50.0, 90.0, default=90.0, decimals=0, space="buy", optimize=False)
  entry_26_cti_20_4h_max = DecimalParameter(0.0, 0.99, default=0.95, decimals=2, space="buy", optimize=False)
  entry_26_rsi_14_4h_max = DecimalParameter(50.0, 90.0, default=90.0, decimals=0, space="buy", optimize=False)
  entry_26_cti_20_1d_max = DecimalParameter(0.0, 0.99, default=0.95, decimals=2, space="buy", optimize=False)
  entry_26_rsi_14_1d_max = DecimalParameter(50.0, 90.0, default=90.0, decimals=0, space="buy", optimize=False)
  entry_26_r_14_1h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_26_r_14_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_26_r_14_4h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_26_r_14_4h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_26_r_480_1h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_26_r_480_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_26_r_480_4h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_26_r_480_4h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_26_bb_offset = DecimalParameter(0.978, 0.999, default=0.992, decimals=3, space="buy", optimize=False)
  entry_26_ema_open_offset = DecimalParameter(0.0100, 0.0400, default=0.018, decimals=3, space="buy", optimize=False)
  entry_26_ewo_50_200_1h_min = DecimalParameter(1.0, 8.0, default=1.2, decimals=1, space="buy", optimize=False)

  entry_45_close_max_12 = DecimalParameter(00.50, 0.95, default=0.88, decimals=2, space="buy", optimize=False)
  entry_45_close_max_24 = DecimalParameter(00.50, 0.95, default=0.84, decimals=2, space="buy", optimize=False)
  entry_45_close_max_48 = DecimalParameter(00.50, 0.95, default=0.8, decimals=2, space="buy", optimize=False)
  entry_45_high_max_24_1h = DecimalParameter(00.40, 0.95, default=0.7, decimals=2, space="buy", optimize=False)
  entry_45_high_max_24_4h = DecimalParameter(00.40, 0.95, default=0.66, decimals=2, space="buy", optimize=False)
  entry_45_high_max_6_1d = DecimalParameter(00.30, 0.95, default=0.6, decimals=2, space="buy", optimize=False)
  entry_45_hl_pct_change_6_1h = DecimalParameter(00.30, 0.90, default=0.56, decimals=2, space="buy", optimize=False)
  entry_45_hl_pct_change_12_1h = DecimalParameter(00.40, 1.00, default=0.86, decimals=2, space="buy", optimize=False)
  entry_45_hl_pct_change_24_1h = DecimalParameter(00.50, 1.20, default=0.9, decimals=2, space="buy", optimize=False)
  entry_45_hl_pct_change_48_1h = DecimalParameter(00.60, 1.60, default=1.36, decimals=2, space="buy", optimize=False)
  entry_45_sup_level_1h_enabled = CategoricalParameter([True, False], default=True, space="buy", optimize=False)
  entry_45_res_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_45_sup_level_4h_enabled = CategoricalParameter([True, False], default=True, space="buy", optimize=False)
  entry_45_res_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_45_sup_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_45_res_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_45_rsi_3_min = DecimalParameter(00.0, 30.0, default=5.0, decimals=0, space="buy", optimize=False)
  entry_45_rsi_3_max = DecimalParameter(30.0, 60.0, default=46.0, decimals=0, space="buy", optimize=False)
  entry_45_rsi_3_15m_min = DecimalParameter(00.0, 30.0, default=6.0, decimals=0, space="buy", optimize=False)
  entry_45_rsi_3_1h_min = DecimalParameter(00.0, 30.0, default=6.0, decimals=0, space="buy", optimize=False)
  entry_45_rsi_3_4h_min = DecimalParameter(00.0, 30.0, default=6.0, decimals=0, space="buy", optimize=False)
  entry_45_rsi_3_1d_min = DecimalParameter(00.0, 30.0, default=6.0, decimals=0, space="buy", optimize=False)
  entry_45_cti_20_1h_max = DecimalParameter(0.0, 0.99, default=0.92, decimals=2, space="buy", optimize=False)
  entry_45_rsi_14_1h_max = DecimalParameter(50.0, 90.0, default=80.0, decimals=0, space="buy", optimize=False)
  entry_45_cti_20_4h_max = DecimalParameter(0.0, 0.99, default=0.92, decimals=2, space="buy", optimize=False)
  entry_45_rsi_14_4h_max = DecimalParameter(50.0, 90.0, default=75.0, decimals=0, space="buy", optimize=False)
  entry_45_cti_20_1d_max = DecimalParameter(0.0, 0.99, default=0.92, decimals=2, space="buy", optimize=False)
  entry_45_rsi_14_1d_max = DecimalParameter(50.0, 90.0, default=75.0, decimals=0, space="buy", optimize=False)
  entry_45_r_480_1h_max = DecimalParameter(-40.0, -0.0, default=-6.0, decimals=0, space="buy", optimize=False)
  entry_45_r_480_4h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_45_rsi_14_min = DecimalParameter(10.0, 40.0, default=26.0, decimals=0, space="buy", optimize=False)
  entry_45_rsi_14_max = DecimalParameter(20.0, 60.0, default=40.0, decimals=0, space="buy", optimize=False)
  entry_45_cti_20_max = DecimalParameter(-0.99, -0.50, default=-0.54, decimals=2, space="buy", optimize=False)
  entry_45_sma_offset = DecimalParameter(0.940, 0.984, default=0.952, decimals=3, space="buy", optimize=False)

  entry_46_close_max_12 = DecimalParameter(00.50, 0.95, default=0.80, decimals=2, space="buy", optimize=False)
  entry_46_close_max_24 = DecimalParameter(00.50, 0.95, default=0.75, decimals=2, space="buy", optimize=False)
  entry_46_close_max_48 = DecimalParameter(00.50, 0.95, default=0.70, decimals=2, space="buy", optimize=False)
  entry_46_high_max_24_1h = DecimalParameter(00.40, 0.95, default=0.60, decimals=2, space="buy", optimize=False)
  entry_46_high_max_24_4h = DecimalParameter(00.40, 0.95, default=0.50, decimals=2, space="buy", optimize=False)
  entry_46_high_max_6_1d = DecimalParameter(00.30, 0.95, default=0.45, decimals=2, space="buy", optimize=False)
  entry_46_hl_pct_change_6_1h = DecimalParameter(00.30, 0.90, default=0.5, decimals=2, space="buy", optimize=False)
  entry_46_hl_pct_change_12_1h = DecimalParameter(00.40, 1.00, default=0.75, decimals=2, space="buy", optimize=False)
  entry_46_hl_pct_change_24_1h = DecimalParameter(00.50, 1.20, default=0.90, decimals=2, space="buy", optimize=False)
  entry_46_hl_pct_change_48_1h = DecimalParameter(00.60, 1.60, default=1.00, decimals=2, space="buy", optimize=False)
  entry_46_sup_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_46_res_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_46_sup_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_46_res_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_46_sup_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_46_res_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_46_ema_200_not_dec_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_46_ema_200_not_dec_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_46_ema_200_not_dec_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_46_not_downtrend_15m_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_46_not_downtrend_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_46_not_downtrend_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_46_not_downtrend_1d_enabled = CategoricalParameter([True, False], default=True, space="buy", optimize=False)
  entry_46_rsi_3_min = DecimalParameter(00.0, 30.0, default=6.0, decimals=0, space="buy", optimize=False)
  entry_46_rsi_3_max = DecimalParameter(30.0, 60.0, default=60.0, decimals=0, space="buy", optimize=False)
  entry_46_rsi_3_15m_min = DecimalParameter(00.0, 30.0, default=20.0, decimals=0, space="buy", optimize=False)
  entry_46_rsi_3_1h_min = DecimalParameter(00.0, 30.0, default=20.0, decimals=0, space="buy", optimize=False)
  entry_46_rsi_3_4h_min = DecimalParameter(00.0, 30.0, default=20.0, decimals=0, space="buy", optimize=False)
  entry_46_rsi_3_1d_min = DecimalParameter(00.0, 30.0, default=20.0, decimals=0, space="buy", optimize=False)
  entry_46_cti_20_1h_max = DecimalParameter(0.0, 0.99, default=0.9, decimals=2, space="buy", optimize=False)
  entry_46_rsi_14_1h_max = DecimalParameter(50.0, 90.0, default=80.0, decimals=0, space="buy", optimize=False)
  entry_46_cti_20_4h_max = DecimalParameter(0.0, 0.99, default=0.9, decimals=2, space="buy", optimize=False)
  entry_46_rsi_14_4h_max = DecimalParameter(50.0, 90.0, default=80.0, decimals=0, space="buy", optimize=False)
  entry_46_cti_20_1d_max = DecimalParameter(0.0, 0.99, default=0.9, decimals=2, space="buy", optimize=False)
  entry_46_rsi_14_1d_max = DecimalParameter(50.0, 90.0, default=80.0, decimals=0, space="buy", optimize=False)
  entry_46_r_14_1h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_46_r_14_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_46_r_14_4h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_46_r_14_4h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_46_r_480_1h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_46_r_480_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_46_r_480_4h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_46_r_480_4h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_46_rsi_14_max = DecimalParameter(26.0, 60.0, default=60.0, decimals=0, space="buy", optimize=False)

  entry_47_close_max_12 = DecimalParameter(00.50, 0.95, default=0.80, decimals=2, space="buy", optimize=False)
  entry_47_close_max_24 = DecimalParameter(00.50, 0.95, default=0.75, decimals=2, space="buy", optimize=False)
  entry_47_close_max_48 = DecimalParameter(00.50, 0.95, default=0.70, decimals=2, space="buy", optimize=False)
  entry_47_high_max_24_1h = DecimalParameter(00.40, 0.95, default=0.60, decimals=2, space="buy", optimize=False)
  entry_47_high_max_24_4h = DecimalParameter(00.40, 0.95, default=0.50, decimals=2, space="buy", optimize=False)
  entry_47_high_max_6_1d = DecimalParameter(00.30, 0.95, default=0.45, decimals=2, space="buy", optimize=False)
  entry_47_hl_pct_change_6_1h = DecimalParameter(00.30, 0.90, default=0.5, decimals=2, space="buy", optimize=False)
  entry_47_hl_pct_change_12_1h = DecimalParameter(00.40, 1.00, default=0.75, decimals=2, space="buy", optimize=False)
  entry_47_hl_pct_change_24_1h = DecimalParameter(00.50, 1.20, default=0.90, decimals=2, space="buy", optimize=False)
  entry_47_hl_pct_change_48_1h = DecimalParameter(00.60, 1.60, default=1.00, decimals=2, space="buy", optimize=False)
  entry_47_sup_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_47_res_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_47_sup_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_47_res_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_47_sup_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_47_res_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_47_ema_200_not_dec_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_47_ema_200_not_dec_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_47_ema_200_not_dec_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_47_not_downtrend_15m_enabled = CategoricalParameter([True, False], default=True, space="buy", optimize=False)
  entry_47_not_downtrend_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_47_not_downtrend_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_47_not_downtrend_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_47_rsi_3_min = DecimalParameter(00.0, 30.0, default=6.0, decimals=0, space="buy", optimize=False)
  entry_47_rsi_3_max = DecimalParameter(30.0, 60.0, default=60.0, decimals=0, space="buy", optimize=False)
  entry_47_rsi_3_15m_min = DecimalParameter(00.0, 30.0, default=16.0, decimals=0, space="buy", optimize=False)
  entry_47_rsi_3_1h_min = DecimalParameter(00.0, 30.0, default=20.0, decimals=0, space="buy", optimize=False)
  entry_47_rsi_3_4h_min = DecimalParameter(00.0, 30.0, default=20.0, decimals=0, space="buy", optimize=False)
  entry_47_rsi_3_1d_min = DecimalParameter(00.0, 30.0, default=20.0, decimals=0, space="buy", optimize=False)
  entry_47_cti_20_1h_max = DecimalParameter(0.0, 0.99, default=0.85, decimals=2, space="buy", optimize=False)
  entry_47_rsi_14_1h_max = DecimalParameter(50.0, 90.0, default=80.0, decimals=0, space="buy", optimize=False)
  entry_47_cti_20_4h_max = DecimalParameter(0.0, 0.99, default=0.85, decimals=2, space="buy", optimize=False)
  entry_47_rsi_14_4h_max = DecimalParameter(50.0, 90.0, default=80.0, decimals=0, space="buy", optimize=False)
  entry_47_cti_20_1d_max = DecimalParameter(0.0, 0.99, default=0.9, decimals=2, space="buy", optimize=False)
  entry_47_rsi_14_1d_max = DecimalParameter(50.0, 90.0, default=80.0, decimals=0, space="buy", optimize=False)
  entry_47_r_14_1h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_47_r_14_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_47_r_14_4h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_47_r_14_4h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_47_r_480_1h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_47_r_480_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_47_r_480_4h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_47_r_480_4h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_47_rsi_14_min = DecimalParameter(20.0, 40.0, default=24.0, decimals=0, space="buy", optimize=False)
  entry_47_rsi_14_max = DecimalParameter(26.0, 60.0, default=60.0, decimals=0, space="buy", optimize=False)
  entry_47_rsi_20_min = DecimalParameter(20.0, 40.0, default=24.0, decimals=0, space="buy", optimize=False)
  entry_47_rsi_20_max = DecimalParameter(26.0, 60.0, default=60.0, decimals=0, space="buy", optimize=False)
  entry_47_cti_20_max = DecimalParameter(-0.8, 0.8, default=-0.7, decimals=1, space="buy", optimize=False)
  entry_47_ema_offset = DecimalParameter(0.980, 0.999, default=0.992, decimals=3, space="buy", optimize=False)
  entry_47_high_max_12_1h_max = DecimalParameter(00.70, 0.95, default=0.88, decimals=2, space="buy", optimize=False)

  entry_48_close_max_12 = DecimalParameter(00.50, 0.95, default=0.80, decimals=2, space="buy", optimize=False)
  entry_48_close_max_24 = DecimalParameter(00.50, 0.95, default=0.75, decimals=2, space="buy", optimize=False)
  entry_48_close_max_48 = DecimalParameter(00.50, 0.95, default=0.70, decimals=2, space="buy", optimize=False)
  entry_48_high_max_24_1h = DecimalParameter(00.40, 0.95, default=0.60, decimals=2, space="buy", optimize=False)
  entry_48_high_max_24_4h = DecimalParameter(00.40, 0.95, default=0.50, decimals=2, space="buy", optimize=False)
  entry_48_high_max_6_1d = DecimalParameter(00.30, 0.95, default=0.45, decimals=2, space="buy", optimize=False)
  entry_48_hl_pct_change_6_1h = DecimalParameter(00.30, 0.90, default=0.5, decimals=2, space="buy", optimize=False)
  entry_48_hl_pct_change_12_1h = DecimalParameter(00.40, 1.00, default=0.75, decimals=2, space="buy", optimize=False)
  entry_48_hl_pct_change_24_1h = DecimalParameter(00.50, 1.20, default=0.90, decimals=2, space="buy", optimize=False)
  entry_48_hl_pct_change_48_1h = DecimalParameter(00.60, 1.60, default=1.00, decimals=2, space="buy", optimize=False)
  entry_48_sup_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_48_res_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_48_sup_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_48_res_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_48_sup_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_48_res_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_48_ema_200_not_dec_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_48_ema_200_not_dec_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_48_ema_200_not_dec_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_48_not_downtrend_15m_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_48_not_downtrend_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_48_not_downtrend_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_48_not_downtrend_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_48_ema_50_1h_over_ema_200_1h_enabled = CategoricalParameter(
    [True, False], default=True, space="buy", optimize=True
  )
  entry_48_rsi_3_min = DecimalParameter(00.0, 30.0, default=6.0, decimals=0, space="buy", optimize=False)
  entry_48_rsi_3_max = DecimalParameter(30.0, 60.0, default=60.0, decimals=0, space="buy", optimize=False)
  entry_48_rsi_3_15m_min = DecimalParameter(00.0, 30.0, default=6.0, decimals=0, space="buy", optimize=False)
  entry_48_rsi_3_1h_min = DecimalParameter(00.0, 30.0, default=10.0, decimals=0, space="buy", optimize=False)
  entry_48_rsi_3_4h_min = DecimalParameter(00.0, 30.0, default=10.0, decimals=0, space="buy", optimize=False)
  entry_48_rsi_3_1d_min = DecimalParameter(00.0, 30.0, default=10.0, decimals=0, space="buy", optimize=False)
  entry_48_cti_20_1h_max = DecimalParameter(0.0, 0.99, default=0.9, decimals=2, space="buy", optimize=False)
  entry_48_rsi_14_1h_max = DecimalParameter(50.0, 90.0, default=80.0, decimals=0, space="buy", optimize=False)
  entry_48_cti_20_4h_max = DecimalParameter(0.0, 0.99, default=0.9, decimals=2, space="buy", optimize=False)
  entry_48_rsi_14_4h_max = DecimalParameter(50.0, 90.0, default=80.0, decimals=0, space="buy", optimize=False)
  entry_48_cti_20_1d_max = DecimalParameter(0.0, 0.99, default=0.9, decimals=2, space="buy", optimize=False)
  entry_48_rsi_14_1d_max = DecimalParameter(50.0, 90.0, default=80.0, decimals=0, space="buy", optimize=False)
  entry_48_r_14_1h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_48_r_14_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_48_r_14_4h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_48_r_14_4h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_48_r_480_1h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_48_r_480_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_48_r_480_4h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_48_r_480_4h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_48_rsi_14_max = DecimalParameter(26.0, 50.0, default=38.0, decimals=0, space="buy", optimize=False)
  entry_48_cci_20_max = DecimalParameter(-180.0, -80.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_48_sma_offset = DecimalParameter(0.940, 0.978, default=0.962, decimals=3, space="buy", optimize=False)
  entry_48_inc_min = DecimalParameter(0.01, 0.04, default=0.022, decimals=3, space="buy", optimize=False)

  entry_49_close_max_12 = DecimalParameter(00.50, 0.95, default=0.88, decimals=2, space="buy", optimize=False)
  entry_49_close_max_24 = DecimalParameter(00.50, 0.95, default=0.86, decimals=2, space="buy", optimize=False)
  entry_49_close_max_48 = DecimalParameter(00.50, 0.95, default=0.70, decimals=2, space="buy", optimize=False)
  entry_49_high_max_24_1h = DecimalParameter(00.40, 0.95, default=0.60, decimals=2, space="buy", optimize=False)
  entry_49_high_max_24_4h = DecimalParameter(00.40, 0.95, default=0.50, decimals=2, space="buy", optimize=False)
  entry_49_high_max_6_1d = DecimalParameter(00.30, 0.95, default=0.45, decimals=2, space="buy", optimize=False)
  entry_49_hl_pct_change_6_1h = DecimalParameter(00.30, 0.90, default=0.5, decimals=2, space="buy", optimize=False)
  entry_49_hl_pct_change_12_1h = DecimalParameter(00.40, 1.00, default=0.75, decimals=2, space="buy", optimize=False)
  entry_49_hl_pct_change_24_1h = DecimalParameter(00.50, 1.20, default=0.90, decimals=2, space="buy", optimize=False)
  entry_49_hl_pct_change_48_1h = DecimalParameter(00.60, 1.60, default=1.00, decimals=2, space="buy", optimize=False)
  entry_49_sup_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_49_res_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_49_sup_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_49_res_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_49_sup_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_49_res_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_49_ema_200_not_dec_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_49_ema_200_not_dec_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_49_ema_200_not_dec_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_49_not_downtrend_15m_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_49_not_downtrend_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_49_not_downtrend_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_49_not_downtrend_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_49_ema_12_1h_over_ema_200_1h_enabled = CategoricalParameter(
    [True, False], default=True, space="buy", optimize=True
  )
  entry_49_rsi_3_min = DecimalParameter(00.0, 30.0, default=6.0, decimals=0, space="buy", optimize=False)
  entry_49_rsi_3_max = DecimalParameter(30.0, 60.0, default=60.0, decimals=0, space="buy", optimize=False)
  entry_49_rsi_3_15m_min = DecimalParameter(00.0, 30.0, default=6.0, decimals=0, space="buy", optimize=False)
  entry_49_rsi_3_1h_min = DecimalParameter(00.0, 30.0, default=10.0, decimals=0, space="buy", optimize=False)
  entry_49_rsi_3_4h_min = DecimalParameter(00.0, 30.0, default=10.0, decimals=0, space="buy", optimize=False)
  entry_49_rsi_3_1d_min = DecimalParameter(00.0, 30.0, default=10.0, decimals=0, space="buy", optimize=False)
  entry_49_cti_20_1h_max = DecimalParameter(0.0, 0.99, default=0.9, decimals=2, space="buy", optimize=False)
  entry_49_rsi_14_1h_max = DecimalParameter(50.0, 90.0, default=80.0, decimals=0, space="buy", optimize=False)
  entry_49_cti_20_4h_max = DecimalParameter(0.0, 0.99, default=0.9, decimals=2, space="buy", optimize=False)
  entry_49_rsi_14_4h_max = DecimalParameter(50.0, 90.0, default=80.0, decimals=0, space="buy", optimize=False)
  entry_49_cti_20_1d_max = DecimalParameter(0.0, 0.99, default=0.9, decimals=2, space="buy", optimize=False)
  entry_49_rsi_14_1d_max = DecimalParameter(50.0, 90.0, default=80.0, decimals=0, space="buy", optimize=False)
  entry_49_r_14_1h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_49_r_14_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_49_r_14_4h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_49_r_14_4h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_49_r_480_1h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_49_r_480_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_49_r_480_4h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_49_r_480_4h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_49_rsi_14_max = DecimalParameter(26.0, 50.0, default=36.0, decimals=0, space="buy", optimize=False)
  entry_49_r_14_max = DecimalParameter(-99.0, -70.0, default=-50.0, decimals=0, space="buy", optimize=False)
  entry_49_inc_min = DecimalParameter(0.01, 0.04, default=0.028, decimals=3, space="buy", optimize=False)

  entry_50_close_max_12 = DecimalParameter(00.50, 0.95, default=0.80, decimals=2, space="buy", optimize=False)
  entry_50_close_max_24 = DecimalParameter(00.50, 0.95, default=0.75, decimals=2, space="buy", optimize=False)
  entry_50_close_max_48 = DecimalParameter(00.50, 0.95, default=0.70, decimals=2, space="buy", optimize=False)
  entry_50_high_max_24_1h = DecimalParameter(00.40, 0.95, default=0.60, decimals=2, space="buy", optimize=False)
  entry_50_high_max_24_4h = DecimalParameter(00.40, 0.95, default=0.50, decimals=2, space="buy", optimize=False)
  entry_50_high_max_6_1d = DecimalParameter(00.30, 0.95, default=0.45, decimals=2, space="buy", optimize=False)
  entry_50_hl_pct_change_6_1h = DecimalParameter(00.30, 0.90, default=0.80, decimals=2, space="buy", optimize=False)
  entry_50_hl_pct_change_12_1h = DecimalParameter(00.40, 1.00, default=0.90, decimals=2, space="buy", optimize=False)
  entry_50_hl_pct_change_24_1h = DecimalParameter(00.50, 1.20, default=1.10, decimals=2, space="buy", optimize=False)
  entry_50_hl_pct_change_48_1h = DecimalParameter(00.60, 1.60, default=1.20, decimals=2, space="buy", optimize=False)
  entry_50_sup_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_50_res_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_50_sup_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_50_res_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_50_sup_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_50_res_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_50_ema_200_not_dec_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_50_ema_200_not_dec_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_50_ema_200_not_dec_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_50_not_downtrend_15m_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_50_not_downtrend_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_50_not_downtrend_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_50_not_downtrend_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_50_ema_12_1h_over_ema_200_1h_enabled = CategoricalParameter(
    [True, False], default=True, space="buy", optimize=False
  )
  entry_50_rsi_3_min = DecimalParameter(00.0, 30.0, default=0.0, decimals=0, space="buy", optimize=False)
  entry_50_rsi_3_max = DecimalParameter(30.0, 70.0, default=46.0, decimals=0, space="buy", optimize=False)
  entry_50_rsi_3_15m_min = DecimalParameter(00.0, 36.0, default=0.0, decimals=0, space="buy", optimize=False)
  entry_50_rsi_3_1h_min = DecimalParameter(00.0, 36.0, default=0.0, decimals=0, space="buy", optimize=False)
  entry_50_rsi_3_4h_min = DecimalParameter(00.0, 36.0, default=0.0, decimals=0, space="buy", optimize=False)
  entry_50_rsi_3_1d_min = DecimalParameter(00.0, 30.0, default=0.0, decimals=0, space="buy", optimize=False)
  entry_50_cti_20_1h_max = DecimalParameter(0.0, 0.99, default=0.80, decimals=2, space="buy", optimize=False)
  entry_50_rsi_14_1h_max = DecimalParameter(50.0, 90.0, default=80.0, decimals=0, space="buy", optimize=False)
  entry_50_cti_20_4h_max = DecimalParameter(0.0, 0.99, default=0.95, decimals=2, space="buy", optimize=False)
  entry_50_rsi_14_4h_max = DecimalParameter(50.0, 90.0, default=90.0, decimals=0, space="buy", optimize=False)
  entry_50_cti_20_1d_max = DecimalParameter(0.0, 0.99, default=0.95, decimals=2, space="buy", optimize=False)
  entry_50_rsi_14_1d_max = DecimalParameter(50.0, 90.0, default=90.0, decimals=0, space="buy", optimize=False)
  entry_50_r_14_1h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_50_r_14_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_50_r_14_4h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_50_r_14_4h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_50_r_480_1h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_50_r_480_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_50_r_480_4h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_50_r_480_4h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_50_bb_offset = DecimalParameter(0.970, 0.999, default=0.995, decimals=3, space="buy", optimize=False)
  entry_50_ema_open_offset = DecimalParameter(0.020, 0.040, default=0.020, decimals=3, space="buy", optimize=False)

  entry_102_close_max_12 = DecimalParameter(00.50, 0.95, default=0.92, decimals=2, space="buy", optimize=False)
  entry_102_close_max_24 = DecimalParameter(00.50, 0.95, default=0.75, decimals=2, space="buy", optimize=False)
  entry_102_close_max_48 = DecimalParameter(00.50, 0.95, default=0.70, decimals=2, space="buy", optimize=False)
  entry_102_high_max_24_1h = DecimalParameter(00.40, 0.95, default=0.65, decimals=2, space="buy", optimize=False)
  entry_102_high_max_24_4h = DecimalParameter(00.40, 0.95, default=0.60, decimals=2, space="buy", optimize=False)
  entry_102_high_max_6_1d = DecimalParameter(00.30, 0.95, default=0.55, decimals=2, space="buy", optimize=False)
  entry_102_hl_pct_change_6_1h = DecimalParameter(00.30, 0.90, default=0.5, decimals=2, space="buy", optimize=False)
  entry_102_hl_pct_change_12_1h = DecimalParameter(00.40, 1.00, default=0.75, decimals=2, space="buy", optimize=False)
  entry_102_hl_pct_change_24_1h = DecimalParameter(00.50, 1.20, default=0.90, decimals=2, space="buy", optimize=False)
  entry_102_hl_pct_change_48_1h = DecimalParameter(00.60, 1.60, default=1.00, decimals=2, space="buy", optimize=False)
  entry_102_sup_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_102_res_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_102_sup_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_102_res_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_102_sup_level_1d_enabled = CategoricalParameter([True, False], default=True, space="buy", optimize=False)
  entry_102_res_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_102_ema_200_not_dec_1h_enabled = CategoricalParameter(
    [True, False], default=False, space="buy", optimize=False
  )
  entry_102_ema_200_not_dec_4h_enabled = CategoricalParameter(
    [True, False], default=False, space="buy", optimize=False
  )
  entry_102_ema_200_not_dec_1d_enabled = CategoricalParameter(
    [True, False], default=False, space="buy", optimize=False
  )
  entry_102_not_downtrend_15m_enabled = CategoricalParameter([True, False], default=True, space="buy", optimize=False)
  entry_102_not_downtrend_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_102_not_downtrend_4h_enabled = CategoricalParameter([True, False], default=True, space="buy", optimize=False)
  entry_102_not_downtrend_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_102_rsi_3_min = DecimalParameter(00.0, 30.0, default=12.0, decimals=0, space="buy", optimize=False)
  entry_102_rsi_3_max = DecimalParameter(30.0, 70.0, default=30.0, decimals=0, space="buy", optimize=False)
  entry_102_rsi_3_15m_min = DecimalParameter(00.0, 30.0, default=16.0, decimals=0, space="buy", optimize=False)
  entry_102_rsi_3_1h_min = DecimalParameter(00.0, 30.0, default=12.0, decimals=0, space="buy", optimize=False)
  entry_102_rsi_3_4h_min = DecimalParameter(00.0, 30.0, default=12.0, decimals=0, space="buy", optimize=False)
  entry_102_rsi_3_1d_min = DecimalParameter(00.0, 30.0, default=6.0, decimals=0, space="buy", optimize=False)
  entry_102_cti_20_1h_max = DecimalParameter(0.0, 0.99, default=0.9, decimals=2, space="buy", optimize=False)
  entry_102_rsi_14_1h_max = DecimalParameter(50.0, 90.0, default=80.0, decimals=0, space="buy", optimize=False)
  entry_102_cti_20_4h_max = DecimalParameter(0.0, 0.99, default=0.9, decimals=2, space="buy", optimize=False)
  entry_102_rsi_14_4h_max = DecimalParameter(50.0, 90.0, default=80.0, decimals=0, space="buy", optimize=False)
  entry_102_cti_20_1d_max = DecimalParameter(0.0, 0.99, default=0.9, decimals=2, space="buy", optimize=False)
  entry_102_rsi_14_1d_max = DecimalParameter(50.0, 90.0, default=80.0, decimals=0, space="buy", optimize=False)
  entry_102_r_480_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_102_r_480_4h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_102_rsi_14_max = DecimalParameter(20.0, 60.0, default=46.0, decimals=0, space="buy", optimize=False)
  entry_102_ema_offset = DecimalParameter(0.940, 0.984, default=0.966, decimals=3, space="buy", optimize=False)
  entry_102_bb_offset = DecimalParameter(0.970, 1.010, default=0.999, decimals=3, space="buy", optimize=False)

  entry_103_close_max_12 = DecimalParameter(00.50, 0.95, default=0.80, decimals=2, space="buy", optimize=False)
  entry_103_close_max_24 = DecimalParameter(00.50, 0.95, default=0.75, decimals=2, space="buy", optimize=False)
  entry_103_close_max_48 = DecimalParameter(00.50, 0.95, default=0.70, decimals=2, space="buy", optimize=False)
  entry_103_high_max_24_1h = DecimalParameter(00.40, 0.95, default=0.60, decimals=2, space="buy", optimize=False)
  entry_103_high_max_24_4h = DecimalParameter(00.40, 0.95, default=0.50, decimals=2, space="buy", optimize=False)
  entry_103_high_max_6_1d = DecimalParameter(00.30, 0.95, default=0.45, decimals=2, space="buy", optimize=False)
  entry_103_hl_pct_change_6_1h = DecimalParameter(00.30, 0.90, default=0.80, decimals=2, space="buy", optimize=False)
  entry_103_hl_pct_change_12_1h = DecimalParameter(00.40, 1.00, default=0.90, decimals=2, space="buy", optimize=False)
  entry_103_hl_pct_change_24_1h = DecimalParameter(00.50, 1.20, default=0.95, decimals=2, space="buy", optimize=False)
  entry_103_hl_pct_change_48_1h = DecimalParameter(00.60, 1.60, default=1.00, decimals=2, space="buy", optimize=False)
  entry_103_sup_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_103_res_level_1h_enabled = CategoricalParameter([True, False], default=True, space="buy", optimize=False)
  entry_103_sup_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_103_res_level_4h_enabled = CategoricalParameter([True, False], default=True, space="buy", optimize=False)
  entry_103_sup_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_103_res_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_103_ema_200_not_dec_1h_enabled = CategoricalParameter(
    [True, False], default=False, space="buy", optimize=False
  )
  entry_103_ema_200_not_dec_4h_enabled = CategoricalParameter(
    [True, False], default=False, space="buy", optimize=False
  )
  entry_103_ema_200_not_dec_1d_enabled = CategoricalParameter(
    [True, False], default=False, space="buy", optimize=False
  )
  entry_103_not_downtrend_15m_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_103_not_downtrend_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_103_not_downtrend_4h_enabled = CategoricalParameter([True, False], default=True, space="buy", optimize=False)
  entry_103_not_downtrend_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_103_rsi_3_min = DecimalParameter(00.0, 30.0, default=10.0, decimals=0, space="buy", optimize=False)
  entry_103_rsi_3_max = DecimalParameter(30.0, 70.0, default=65.0, decimals=0, space="buy", optimize=False)
  entry_103_rsi_3_15m_min = DecimalParameter(00.0, 30.0, default=6.0, decimals=0, space="buy", optimize=False)
  entry_103_rsi_3_1h_min = DecimalParameter(00.0, 30.0, default=20.0, decimals=0, space="buy", optimize=False)
  entry_103_rsi_3_4h_min = DecimalParameter(00.0, 30.0, default=20.0, decimals=0, space="buy", optimize=False)
  entry_103_rsi_3_1d_min = DecimalParameter(00.0, 30.0, default=1.0, decimals=0, space="buy", optimize=False)
  entry_103_cti_20_1h_max = DecimalParameter(0.0, 0.99, default=0.85, decimals=2, space="buy", optimize=False)
  entry_103_rsi_14_1h_max = DecimalParameter(50.0, 90.0, default=85.0, decimals=0, space="buy", optimize=False)
  entry_103_cti_20_4h_max = DecimalParameter(0.0, 0.99, default=0.95, decimals=2, space="buy", optimize=False)
  entry_103_rsi_14_4h_max = DecimalParameter(50.0, 90.0, default=85.0, decimals=0, space="buy", optimize=False)
  entry_103_cti_20_1d_max = DecimalParameter(0.0, 0.99, default=0.95, decimals=2, space="buy", optimize=False)
  entry_103_rsi_14_1d_max = DecimalParameter(50.0, 90.0, default=85.0, decimals=0, space="buy", optimize=False)
  entry_103_r_14_1h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_103_r_14_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_103_r_14_4h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_103_r_14_4h_max = DecimalParameter(-40.0, -0.0, default=-5.0, decimals=0, space="buy", optimize=False)
  entry_103_r_480_1h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_103_r_480_1h_max = DecimalParameter(-40.0, -0.0, default=-25.0, decimals=0, space="buy", optimize=False)
  entry_103_r_480_4h_min = DecimalParameter(-100.0, -70.0, default=-90.0, decimals=0, space="buy", optimize=False)
  entry_103_r_480_4h_max = DecimalParameter(-40.0, -0.0, default=-25.0, decimals=0, space="buy", optimize=False)
  entry_103_rsi_14_min = DecimalParameter(20.0, 60.0, default=24.0, decimals=0, space="buy", optimize=False)
  entry_103_sma_offset = DecimalParameter(0.930, 0.972, default=0.958, decimals=3, space="buy", optimize=False)
  entry_103_bb_offset = DecimalParameter(0.940, 1.010, default=0.948, decimals=3, space="buy", optimize=False)

  entry_104_close_max_12 = DecimalParameter(00.50, 0.95, default=0.80, decimals=2, space="buy", optimize=False)
  entry_104_close_max_24 = DecimalParameter(00.50, 0.95, default=0.75, decimals=2, space="buy", optimize=False)
  entry_104_close_max_48 = DecimalParameter(00.50, 0.95, default=0.70, decimals=2, space="buy", optimize=False)
  entry_104_high_max_24_1h = DecimalParameter(00.40, 0.95, default=0.60, decimals=2, space="buy", optimize=False)
  entry_104_high_max_24_4h = DecimalParameter(00.40, 0.95, default=0.50, decimals=2, space="buy", optimize=False)
  entry_104_high_max_6_1d = DecimalParameter(00.30, 0.95, default=0.45, decimals=2, space="buy", optimize=False)
  entry_104_hl_pct_change_6_1h = DecimalParameter(00.30, 0.90, default=0.80, decimals=2, space="buy", optimize=False)
  entry_104_hl_pct_change_12_1h = DecimalParameter(00.40, 1.00, default=0.90, decimals=2, space="buy", optimize=False)
  entry_104_hl_pct_change_24_1h = DecimalParameter(00.50, 1.20, default=0.95, decimals=2, space="buy", optimize=False)
  entry_104_hl_pct_change_48_1h = DecimalParameter(00.60, 1.60, default=1.00, decimals=2, space="buy", optimize=False)
  entry_104_sup_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_104_res_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_104_sup_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_104_res_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_104_sup_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_104_res_level_1d_enabled = CategoricalParameter([True, False], default=True, space="buy", optimize=False)
  entry_104_ema_200_not_dec_1h_enabled = CategoricalParameter([True, False], default=True, space="buy", optimize=False)
  entry_104_ema_200_not_dec_4h_enabled = CategoricalParameter(
    [True, False], default=False, space="buy", optimize=False
  )
  entry_104_ema_200_not_dec_1d_enabled = CategoricalParameter(
    [True, False], default=False, space="buy", optimize=False
  )
  entry_104_not_downtrend_15m_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_104_not_downtrend_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_104_not_downtrend_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_104_not_downtrend_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_104_rsi_3_min = DecimalParameter(00.0, 30.0, default=6.0, decimals=0, space="buy", optimize=False)
  entry_104_rsi_3_max = DecimalParameter(30.0, 70.0, default=46.0, decimals=0, space="buy", optimize=False)
  entry_104_rsi_3_15m_min = DecimalParameter(00.0, 36.0, default=6.0, decimals=0, space="buy", optimize=False)
  entry_104_rsi_3_1h_min = DecimalParameter(00.0, 36.0, default=8.0, decimals=0, space="buy", optimize=False)
  entry_104_rsi_3_4h_min = DecimalParameter(00.0, 36.0, default=8.0, decimals=0, space="buy", optimize=False)
  entry_104_rsi_3_1d_min = DecimalParameter(00.0, 30.0, default=8.0, decimals=0, space="buy", optimize=False)
  entry_104_cti_20_1h_max = DecimalParameter(0.0, 0.99, default=0.80, decimals=2, space="buy", optimize=False)
  entry_104_rsi_14_1h_max = DecimalParameter(50.0, 90.0, default=70.0, decimals=0, space="buy", optimize=False)
  entry_104_cti_20_4h_max = DecimalParameter(0.0, 0.99, default=0.95, decimals=2, space="buy", optimize=False)
  entry_104_rsi_14_4h_max = DecimalParameter(50.0, 90.0, default=70.0, decimals=0, space="buy", optimize=False)
  entry_104_cti_20_1d_max = DecimalParameter(0.0, 0.99, default=0.95, decimals=2, space="buy", optimize=False)
  entry_104_rsi_14_1d_max = DecimalParameter(50.0, 90.0, default=70.0, decimals=0, space="buy", optimize=False)
  entry_104_r_14_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_104_r_14_4h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_104_r_480_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_104_r_480_4h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_104_rsi_14_min = DecimalParameter(20.0, 60.0, default=30.0, decimals=0, space="buy", optimize=False)
  entry_104_rsi_14_max = DecimalParameter(20.0, 60.0, default=46.0, decimals=0, space="buy", optimize=False)
  entry_104_sma_offset = DecimalParameter(0.940, 0.984, default=0.956, decimals=3, space="buy", optimize=False)

  entry_106_close_max_12 = DecimalParameter(00.50, 0.95, default=0.80, decimals=2, space="buy", optimize=False)
  entry_106_close_max_24 = DecimalParameter(00.50, 0.95, default=0.75, decimals=2, space="buy", optimize=False)
  entry_106_close_max_48 = DecimalParameter(00.50, 0.95, default=0.70, decimals=2, space="buy", optimize=False)
  entry_106_high_max_24_1h = DecimalParameter(00.40, 0.95, default=0.60, decimals=2, space="buy", optimize=False)
  entry_106_high_max_24_4h = DecimalParameter(00.40, 0.95, default=0.50, decimals=2, space="buy", optimize=False)
  entry_106_high_max_6_1d = DecimalParameter(00.30, 0.95, default=0.45, decimals=2, space="buy", optimize=False)
  entry_106_hl_pct_change_6_1h = DecimalParameter(00.30, 0.90, default=0.5, decimals=2, space="buy", optimize=False)
  entry_106_hl_pct_change_12_1h = DecimalParameter(00.40, 1.00, default=0.75, decimals=2, space="buy", optimize=False)
  entry_106_hl_pct_change_24_1h = DecimalParameter(00.50, 1.20, default=0.90, decimals=2, space="buy", optimize=False)
  entry_106_hl_pct_change_48_1h = DecimalParameter(00.60, 1.60, default=1.00, decimals=2, space="buy", optimize=False)
  entry_106_sup_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_106_res_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_106_sup_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_106_res_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_106_sup_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_106_res_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_106_ema_200_not_dec_1h_enabled = CategoricalParameter(
    [True, False], default=False, space="buy", optimize=False
  )
  entry_106_ema_200_not_dec_4h_enabled = CategoricalParameter(
    [True, False], default=False, space="buy", optimize=False
  )
  entry_106_ema_200_not_dec_1d_enabled = CategoricalParameter(
    [True, False], default=False, space="buy", optimize=False
  )
  entry_106_not_downtrend_15m_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_106_not_downtrend_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_106_not_downtrend_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_106_not_downtrend_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_106_rsi_3_min = DecimalParameter(00.0, 30.0, default=2.0, decimals=0, space="buy", optimize=False)
  entry_106_rsi_3_max = DecimalParameter(30.0, 60.0, default=60.0, decimals=0, space="buy", optimize=False)
  entry_106_rsi_3_15m_min = DecimalParameter(00.0, 30.0, default=2.0, decimals=0, space="buy", optimize=False)
  entry_106_rsi_3_1h_min = DecimalParameter(00.0, 30.0, default=6.0, decimals=0, space="buy", optimize=False)
  entry_106_rsi_3_4h_min = DecimalParameter(00.0, 30.0, default=6.0, decimals=0, space="buy", optimize=False)
  entry_106_rsi_3_1d_min = DecimalParameter(00.0, 30.0, default=6.0, decimals=0, space="buy", optimize=False)
  entry_106_cti_20_1h_max = DecimalParameter(0.0, 0.99, default=0.9, decimals=2, space="buy", optimize=False)
  entry_106_rsi_14_1h_max = DecimalParameter(50.0, 90.0, default=80.0, decimals=0, space="buy", optimize=False)
  entry_106_cti_20_4h_max = DecimalParameter(0.0, 0.99, default=0.9, decimals=2, space="buy", optimize=False)
  entry_106_rsi_14_4h_max = DecimalParameter(50.0, 90.0, default=80.0, decimals=0, space="buy", optimize=False)
  entry_106_cti_20_1d_max = DecimalParameter(0.0, 0.99, default=0.9, decimals=2, space="buy", optimize=False)
  entry_106_rsi_14_1d_max = DecimalParameter(50.0, 90.0, default=80.0, decimals=0, space="buy", optimize=False)
  entry_106_r_14_1h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_106_r_14_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_106_r_14_4h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_106_r_14_4h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_106_r_480_1h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_106_r_480_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_106_r_480_4h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_106_r_480_4h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_106_cti_20_max = DecimalParameter(-0.9, 0.0, default=-0.7, decimals=1, space="buy", optimize=False)
  entry_106_ewo_50_200_max = DecimalParameter(-10.0, -2.0, default=-8.0, decimals=1, space="buy", optimize=True)
  entry_106_sma_offset = DecimalParameter(0.980, 0.999, default=0.986, decimals=3, space="buy", optimize=True)

  entry_107_close_max_12 = DecimalParameter(00.50, 0.95, default=0.80, decimals=2, space="buy", optimize=False)
  entry_107_close_max_24 = DecimalParameter(00.50, 0.95, default=0.75, decimals=2, space="buy", optimize=False)
  entry_107_close_max_48 = DecimalParameter(00.50, 0.95, default=0.70, decimals=2, space="buy", optimize=False)
  entry_107_high_max_24_1h = DecimalParameter(00.40, 0.95, default=0.60, decimals=2, space="buy", optimize=False)
  entry_107_high_max_24_4h = DecimalParameter(00.40, 0.95, default=0.50, decimals=2, space="buy", optimize=False)
  entry_107_high_max_6_1d = DecimalParameter(00.30, 0.95, default=0.45, decimals=2, space="buy", optimize=False)
  entry_107_hl_pct_change_6_1h = DecimalParameter(00.30, 0.90, default=0.80, decimals=2, space="buy", optimize=False)
  entry_107_hl_pct_change_12_1h = DecimalParameter(00.40, 1.00, default=0.90, decimals=2, space="buy", optimize=False)
  entry_107_hl_pct_change_24_1h = DecimalParameter(00.50, 1.20, default=1.10, decimals=2, space="buy", optimize=False)
  entry_107_hl_pct_change_48_1h = DecimalParameter(00.60, 1.60, default=1.20, decimals=2, space="buy", optimize=False)
  entry_107_sup_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_107_res_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_107_sup_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_107_res_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_107_sup_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_107_res_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_107_ema_200_not_dec_1h_enabled = CategoricalParameter(
    [True, False], default=False, space="buy", optimize=False
  )
  entry_107_ema_200_not_dec_4h_enabled = CategoricalParameter(
    [True, False], default=False, space="buy", optimize=False
  )
  entry_107_ema_200_not_dec_1d_enabled = CategoricalParameter(
    [True, False], default=False, space="buy", optimize=False
  )
  entry_107_not_downtrend_15m_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_107_not_downtrend_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_107_not_downtrend_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_107_not_downtrend_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_107_rsi_3_min = DecimalParameter(00.0, 30.0, default=2.0, decimals=0, space="buy", optimize=False)
  entry_107_rsi_3_max = DecimalParameter(30.0, 70.0, default=46.0, decimals=0, space="buy", optimize=False)
  entry_107_rsi_3_15m_min = DecimalParameter(00.0, 36.0, default=2.0, decimals=0, space="buy", optimize=False)
  entry_107_rsi_3_1h_min = DecimalParameter(00.0, 36.0, default=8.0, decimals=0, space="buy", optimize=False)
  entry_107_rsi_3_4h_min = DecimalParameter(00.0, 36.0, default=8.0, decimals=0, space="buy", optimize=False)
  entry_107_rsi_3_1d_min = DecimalParameter(00.0, 30.0, default=8.0, decimals=0, space="buy", optimize=False)
  entry_107_cti_20_1h_min = DecimalParameter(-0.99, -0.50, default=-0.95, decimals=2, space="buy", optimize=False)
  entry_107_cti_20_1h_max = DecimalParameter(0.0, 0.99, default=0.80, decimals=2, space="buy", optimize=False)
  entry_107_rsi_14_1h_max = DecimalParameter(50.0, 90.0, default=80.0, decimals=0, space="buy", optimize=False)
  entry_107_cti_20_4h_max = DecimalParameter(0.0, 0.99, default=0.90, decimals=2, space="buy", optimize=False)
  entry_107_rsi_14_4h_max = DecimalParameter(50.0, 90.0, default=90.0, decimals=0, space="buy", optimize=False)
  entry_107_cti_20_1d_max = DecimalParameter(0.0, 0.99, default=0.95, decimals=2, space="buy", optimize=False)
  entry_107_rsi_14_1d_max = DecimalParameter(50.0, 90.0, default=90.0, decimals=0, space="buy", optimize=False)
  entry_107_r_14_1h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_107_r_14_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_107_r_14_4h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_107_r_14_4h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_107_r_480_1h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_107_r_480_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_107_r_480_4h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_107_r_480_4h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_107_bb40_bbdelta_close = DecimalParameter(0.030, 0.060, default=0.040, decimals=3, space="buy", optimize=False)
  entry_107_bb40_closedelta_close = DecimalParameter(
    0.010, 0.040, default=0.020, decimals=3, space="buy", optimize=False
  )
  entry_107_bb40_tail_bbdelta = DecimalParameter(0.10, 0.60, default=0.40, decimals=2, space="buy", optimize=False)
  entry_107_cti_20_max = DecimalParameter(-0.90, -0.50, default=-0.75, decimals=2, space="buy", optimize=False)
  entry_107_r_480_min = DecimalParameter(-100.0, -80.0, default=-94.0, decimals=0, space="buy", optimize=False)

  entry_108_close_max_12 = DecimalParameter(00.50, 0.95, default=0.80, decimals=2, space="buy", optimize=False)
  entry_108_close_max_24 = DecimalParameter(00.50, 0.95, default=0.75, decimals=2, space="buy", optimize=False)
  entry_108_close_max_48 = DecimalParameter(00.50, 0.95, default=0.70, decimals=2, space="buy", optimize=False)
  entry_108_high_max_24_1h = DecimalParameter(00.40, 0.95, default=0.60, decimals=2, space="buy", optimize=False)
  entry_108_high_max_24_4h = DecimalParameter(00.40, 0.95, default=0.50, decimals=2, space="buy", optimize=False)
  entry_108_high_max_6_1d = DecimalParameter(00.30, 0.95, default=0.45, decimals=2, space="buy", optimize=False)
  entry_108_hl_pct_change_6_1h = DecimalParameter(00.30, 0.90, default=0.80, decimals=2, space="buy", optimize=False)
  entry_108_hl_pct_change_12_1h = DecimalParameter(00.40, 1.00, default=0.90, decimals=2, space="buy", optimize=False)
  entry_108_hl_pct_change_24_1h = DecimalParameter(00.50, 1.20, default=1.10, decimals=2, space="buy", optimize=False)
  entry_108_hl_pct_change_48_1h = DecimalParameter(00.60, 1.60, default=1.20, decimals=2, space="buy", optimize=False)
  entry_108_sup_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_108_res_level_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_108_sup_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_108_res_level_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_108_sup_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_108_res_level_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_108_ema_200_not_dec_1h_enabled = CategoricalParameter(
    [True, False], default=False, space="buy", optimize=False
  )
  entry_108_ema_200_not_dec_4h_enabled = CategoricalParameter(
    [True, False], default=False, space="buy", optimize=False
  )
  entry_108_ema_200_not_dec_1d_enabled = CategoricalParameter(
    [True, False], default=False, space="buy", optimize=False
  )
  entry_108_not_downtrend_15m_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_108_not_downtrend_1h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_108_not_downtrend_4h_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_108_not_downtrend_1d_enabled = CategoricalParameter([True, False], default=False, space="buy", optimize=False)
  entry_108_rsi_3_min = DecimalParameter(00.0, 30.0, default=0.0, decimals=0, space="buy", optimize=False)
  entry_108_rsi_3_max = DecimalParameter(30.0, 70.0, default=46.0, decimals=0, space="buy", optimize=False)
  entry_108_rsi_3_15m_min = DecimalParameter(00.0, 36.0, default=2.0, decimals=0, space="buy", optimize=False)
  entry_108_rsi_3_1h_min = DecimalParameter(00.0, 36.0, default=8.0, decimals=0, space="buy", optimize=False)
  entry_108_rsi_3_4h_min = DecimalParameter(00.0, 36.0, default=8.0, decimals=0, space="buy", optimize=False)
  entry_108_rsi_3_1d_min = DecimalParameter(00.0, 30.0, default=8.0, decimals=0, space="buy", optimize=False)
  entry_108_cti_20_1h_min = DecimalParameter(-0.99, -0.50, default=-0.95, decimals=2, space="buy", optimize=False)
  entry_108_cti_20_1h_max = DecimalParameter(0.0, 0.99, default=0.90, decimals=2, space="buy", optimize=False)
  entry_108_rsi_14_1h_max = DecimalParameter(50.0, 90.0, default=90.0, decimals=0, space="buy", optimize=False)
  entry_108_cti_20_4h_max = DecimalParameter(0.0, 0.99, default=0.90, decimals=2, space="buy", optimize=False)
  entry_108_rsi_14_4h_max = DecimalParameter(50.0, 90.0, default=90.0, decimals=0, space="buy", optimize=False)
  entry_108_cti_20_1d_max = DecimalParameter(0.0, 0.99, default=0.95, decimals=2, space="buy", optimize=False)
  entry_108_rsi_14_1d_max = DecimalParameter(50.0, 90.0, default=90.0, decimals=0, space="buy", optimize=False)
  entry_108_r_14_1h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_108_r_14_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_108_r_14_4h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_108_r_14_4h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_108_r_480_1h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_108_r_480_1h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_108_r_480_4h_min = DecimalParameter(-100.0, -70.0, default=-100.0, decimals=0, space="buy", optimize=False)
  entry_108_r_480_4h_max = DecimalParameter(-40.0, -0.0, default=-0.0, decimals=0, space="buy", optimize=False)
  entry_108_rsi_14_min = DecimalParameter(10.0, 40.0, default=15.0, decimals=0, space="buy", optimize=False)
  entry_108_cti_20_max = DecimalParameter(-0.70, -0.40, default=-0.50, decimals=2, space="buy", optimize=False)
  entry_108_r_14_max = DecimalParameter(-100.0, 80.0, default=-90.0, decimals=0, space="buy", optimize=False)
  entry_108_bb_offset = DecimalParameter(0.970, 0.999, default=0.999, decimals=3, space="buy", optimize=False)
  entry_108_ema_open_offset = DecimalParameter(0.0100, 0.0400, default=0.0200, decimals=4, space="buy", optimize=False)

  #############################################################
  # CACHES

  hold_trades_cache = None
  target_profit_cache = None
  #############################################################
  #
  #
  #  $$$$$$\   $$$$$$\  $$\      $$\ $$\      $$\  $$$$$$\  $$\   $$\
  # $$  __$$\ $$  __$$\ $$$\    $$$ |$$$\    $$$ |$$  __$$\ $$$\  $$ |
  # $$ /  \__|$$ /  $$ |$$$$\  $$$$ |$$$$\  $$$$ |$$ /  $$ |$$$$\ $$ |
  # $$ |      $$ |  $$ |$$\$$\$$ $$ |$$\$$\$$ $$ |$$ |  $$ |$$ $$\$$ |
  # $$ |      $$ |  $$ |$$ \$$$  $$ |$$ \$$$  $$ |$$ |  $$ |$$ \$$$$ |
  # $$ |  $$\ $$ |  $$ |$$ |\$  /$$ |$$ |\$  /$$ |$$ |  $$ |$$ |\$$$ |
  # \$$$$$$  | $$$$$$  |$$ | \_/ $$ |$$ | \_/ $$ | $$$$$$  |$$ | \$$ |
  #  \______/  \______/ \__|     \__|\__|     \__| \______/ \__|  \__|
  #
  #
  #
  # $$$$$$$$\ $$\   $$\ $$\   $$\  $$$$$$\ $$$$$$$$\ $$$$$$\  $$$$$$\  $$\   $$\  $$$$$$\
  # $$  _____|$$ |  $$ |$$$\  $$ |$$  __$$\\__$$  __|\_$$  _|$$  __$$\ $$$\  $$ |$$  __$$\
  # $$ |      $$ |  $$ |$$$$\ $$ |$$ /  \__|  $$ |     $$ |  $$ /  $$ |$$$$\ $$ |$$ /  \__|
  # $$$$$\    $$ |  $$ |$$ $$\$$ |$$ |        $$ |     $$ |  $$ |  $$ |$$ $$\$$ |\$$$$$$\
  # $$  __|   $$ |  $$ |$$ \$$$$ |$$ |        $$ |     $$ |  $$ |  $$ |$$ \$$$$ | \____$$\
  # $$ |      $$ |  $$ |$$ |\$$$ |$$ |  $$\   $$ |     $$ |  $$ |  $$ |$$ |\$$$ |$$\   $$ |
  # $$ |      \$$$$$$  |$$ | \$$ |\$$$$$$  |  $$ |   $$$$$$\  $$$$$$  |$$ | \$$ |\$$$$$$  |
  # \__|       \______/ \__|  \__| \______/   \__|   \______| \______/ \__|  \__| \______/
  #
  #

  ###############################################################################################
  # COMMON FUNCTIONS FOR BOTH LONG AND SHORT SIDE STARTS HERE
  ###############################################################################################

  def __init__(self, config: dict) -> None:
    if "ccxt_config" not in config["exchange"]:
      config["exchange"]["ccxt_config"] = {}
    if "ccxt_async_config" not in config["exchange"]:
      config["exchange"]["ccxt_async_config"] = {}

    options = {
      "brokerId": None,
      "broker": {"spot": None, "margin": None, "future": None, "delivery": None},
      "partner": {
        "spot": {"id": None, "key": None},
        "future": {"id": None, "key": None},
        "id": None,
        "key": None,
      },
    }

    config["exchange"]["ccxt_config"]["options"] = options
    config["exchange"]["ccxt_async_config"]["options"] = options
    super().__init__(config)
    if ("exit_profit_only" in self.config and self.config["exit_profit_only"]) or (
      "sell_profit_only" in self.config and self.config["sell_profit_only"]
    ):
      self.exit_profit_only = True
    if "stop_threshold_spot" in self.config:
      self.stop_threshold = self.config["stop_threshold_spot"]
    if "stop_threshold_futures" in self.config:
      self.stop_threshold_futures = self.config["stop_threshold_futures"]
    if "regular_mode_stake_multiplier_spot" in self.config:
      self.regular_mode_stake_multiplier_spot = self.config["regular_mode_stake_multiplier_spot"]
    if "regular_mode_stake_multiplier_futures" in self.config:
      self.regular_mode_stake_multiplier_futures = self.config["regular_mode_stake_multiplier_futures"]
    if "regular_mode_derisk_1_spot" in self.config:
      self.regular_mode_derisk_1_spot = self.config["regular_mode_derisk_1_spot"]
    if "regular_mode_derisk_1_spot_old" in self.config:
      self.regular_mode_derisk_1_spot_old = self.config["regular_mode_derisk_1_spot_old"]
    if "regular_mode_derisk_spot" in self.config:
      self.regular_mode_derisk_spot = self.config["regular_mode_derisk_spot"]
    if "regular_mode_derisk_spot_old" in self.config:
      self.regular_mode_derisk_spot_old = self.config["regular_mode_derisk_spot_old"]
    if "regular_mode_derisk_1_futures" in self.config:
      self.regular_mode_derisk_1_futures = self.config["regular_mode_derisk_1_futures"]
    if "regular_mode_derisk_1_futures_old" in self.config:
      self.regular_mode_derisk_1_futures_old = self.config["regular_mode_derisk_1_futures_old"]
    if "regular_mode_derisk_futures" in self.config:
      self.regular_mode_derisk_futures = self.config["regular_mode_derisk_futures"]
    if "regular_mode_derisk_futures_old" in self.config:
      self.regular_mode_derisk_futures_old = self.config["regular_mode_derisk_futures_old"]

    if "custom_fee_open_rate" in self.config:
      self.custom_fee_open_rate = self.config["custom_fee_open_rate"]
    if "custom_fee_close_rate" in self.config:
      self.custom_fee_close_rate = self.config["custom_fee_close_rate"]

    if "futures_mode_leverage" in self.config:
      self.futures_mode_leverage = self.config["futures_mode_leverage"]
    if "futures_mode_leverage_rebuy_mode" in self.config:
      self.futures_mode_leverage_rebuy_mode = self.config["futures_mode_leverage_rebuy_mode"]
    if "futures_mode_leverage_grind_mode" in self.config:
      self.futures_mode_leverage_grind_mode = self.config["futures_mode_leverage_grind_mode"]

    if "grind_1_profit_threshold_spot" in self.config:
      self.grind_1_profit_threshold_spot = self.config["grind_1_profit_threshold_spot"]
    if "grind_1_profit_threshold_futures" in self.config:
      self.grind_1_profit_threshold_futures = self.config["grind_1_profit_threshold_futures"]
    if "grind_2_profit_threshold_spot" in self.config:
      self.grind_2_profit_threshold_spot = self.config["grind_2_profit_threshold_spot"]
    if "grind_2_profit_threshold_futures" in self.config:
      self.grind_2_profit_threshold_futures = self.config["grind_2_profit_threshold_futures"]
    if "grind_3_profit_threshold_spot" in self.config:
      self.grind_3_profit_threshold_spot = self.config["grind_3_profit_threshold_spot"]
    if "grind_3_profit_threshold_futures" in self.config:
      self.grind_3_profit_threshold_futures = self.config["grind_3_profit_threshold_futures"]
    if "grind_4_profit_threshold_spot" in self.config:
      self.grind_4_profit_threshold_spot = self.config["grind_4_profit_threshold_spot"]
    if "grind_4_profit_threshold_futures" in self.config:
      self.grind_4_profit_threshold_futures = self.config["grind_4_profit_threshold_futures"]
    if "grind_5_profit_threshold_spot" in self.config:
      self.grind_5_profit_threshold_spot = self.config["grind_5_profit_threshold_spot"]
    if "grind_5_profit_threshold_futures" in self.config:
      self.grind_5_profit_threshold_futures = self.config["grind_5_profit_threshold_futures"]
    if "grind_6_profit_threshold_spot" in self.config:
      self.grind_6_profit_threshold_spot = self.config["grind_6_profit_threshold_spot"]
    if "grind_6_profit_threshold_futures" in self.config:
      self.grind_6_profit_threshold_futures = self.config["grind_6_profit_threshold_futures"]
    if "grind_1_derisk_1_profit_threshold_spot" in self.config:
      self.grind_1_derisk_1_profit_threshold_spot = self.config["grind_1_derisk_1_profit_threshold_spot"]
    if "grind_1_derisk_1_profit_threshold_futures" in self.config:
      self.grind_1_derisk_1_profit_threshold_futures = self.config["grind_1_derisk_1_profit_threshold_futures"]
    if "grind_2_derisk_1_profit_threshold_spot" in self.config:
      self.grind_2_derisk_1_profit_threshold_spot = self.config["grind_2_derisk_1_profit_threshold_spot"]
    if "grind_2_derisk_1_profit_threshold_futures" in self.config:
      self.grind_2_derisk_1_profit_threshold_futures = self.config["grind_2_derisk_1_profit_threshold_futures"]
    if "regular_mode_grind_1_profit_threshold_spot" in self.config:
      self.regular_mode_grind_1_profit_threshold_spot = self.config["regular_mode_grind_1_profit_threshold_spot"]
    if "regular_mode_grind_1_profit_threshold_futures" in self.config:
      self.regular_mode_grind_1_profit_threshold_futures = self.config["regular_mode_grind_1_profit_threshold_futures"]
    if "regular_mode_grind_2_profit_threshold_spot" in self.config:
      self.regular_mode_grind_2_profit_threshold_spot = self.config["regular_mode_grind_2_profit_threshold_spot"]
    if "regular_mode_grind_2_profit_threshold_futures" in self.config:
      self.regular_mode_grind_2_profit_threshold_futures = self.config["regular_mode_grind_2_profit_threshold_futures"]
    if "regular_mode_grind_3_profit_threshold_spot" in self.config:
      self.regular_mode_grind_3_profit_threshold_spot = self.config["regular_mode_grind_3_profit_threshold_spot"]
    if "regular_mode_grind_3_profit_threshold_futures" in self.config:
      self.regular_mode_grind_3_profit_threshold_futures = self.config["regular_mode_grind_3_profit_threshold_futures"]
    if "regular_mode_grind_4_profit_threshold_spot" in self.config:
      self.regular_mode_grind_4_profit_threshold_spot = self.config["regular_mode_grind_4_profit_threshold_spot"]
    if "regular_mode_grind_4_profit_threshold_futures" in self.config:
      self.regular_mode_grind_4_profit_threshold_futures = self.config["regular_mode_grind_4_profit_threshold_futures"]
    if "regular_mode_grind_5_profit_threshold_spot" in self.config:
      self.regular_mode_grind_5_profit_threshold_spot = self.config["regular_mode_grind_5_profit_threshold_spot"]
    if "regular_mode_grind_5_profit_threshold_futures" in self.config:
      self.regular_mode_grind_5_profit_threshold_futures = self.config["regular_mode_grind_5_profit_threshold_futures"]

    if "grind_mode_max_slots" in self.config:
      self.grind_mode_max_slots = self.config["grind_mode_max_slots"]
    if "grind_mode_coins" in self.config:
      self.grind_mode_coins = self.config["grind_mode_coins"]
    if "max_slippage" in self.config:
      self.max_slippage = self.config["max_slippage"]
    if self.target_profit_cache is None:
      bot_name = ""
      if "bot_name" in self.config:
        bot_name = self.config["bot_name"] + "-"
      self.target_profit_cache = Cache(
        self.config["user_data_dir"]
        / (
          "nfix4-profit_max-"
          + bot_name
          + self.config["exchange"]["name"]
          + "-"
          + self.config["stake_currency"]
          + ("-(backtest)" if (self.config["runmode"].value == "backtest") else "")
          + ("-(hyperopt)" if (self.config["runmode"].value == "hyperopt") else "")
          + ".json"
        )
      )

    # OKX, Kraken provides a lower number of candle data per API call
    if self.config["exchange"]["name"] in ["okx", "okex"]:
      self.startup_candle_count = 480
    elif self.config["exchange"]["name"] in ["kraken"]:
      self.startup_candle_count = 710
    elif self.config["exchange"]["name"] in ["bybit"]:
      self.startup_candle_count = 199
    elif self.config["exchange"]["name"] in ["bitget"]:
      self.startup_candle_count = 499
    elif self.config["exchange"]["name"] in ["bingx"]:
      self.startup_candle_count = 499

    if ("trading_mode" in self.config) and (self.config["trading_mode"] in ["futures", "margin"]):
      self.is_futures_mode = True
      self.can_short = True

    # If the cached data hasn't changed, it's a no-op
    self.target_profit_cache.save()

  # Get Ticker Indicator
  # ---------------------------------------------------------------------------------------------
  def get_ticker_indicator(self):
    return int(self.timeframe[:-1])

  # Mark Profit Target
  # ---------------------------------------------------------------------------------------------
  def mark_profit_target(
    self,
    mode_name: str,
    pair: str,
    sell: bool,
    signal_name: str,
    trade: Trade,
    current_time: datetime,
    current_rate: float,
    current_profit: float,
    last_candle,
    previous_candle_1,
  ) -> tuple:
    if sell and (signal_name is not None):
      return pair, signal_name

    return None, None

  # Exit Profit Target
  # ---------------------------------------------------------------------------------------------
  def exit_profit_target(
    self,
    mode_name: str,
    pair: str,
    trade: Trade,
    current_time: datetime,
    current_rate: float,
    profit_stake: float,
    profit_ratio: float,
    profit_current_stake_ratio: float,
    profit_init_ratio: float,
    last_candle,
    previous_candle_1,
    previous_rate,
    previous_profit,
    previous_sell_reason,
    previous_time_profit_reached,
    enter_tags,
  ) -> tuple:
    if previous_sell_reason in [f"exit_{mode_name}_stoploss_doom", f"exit_{mode_name}_stoploss"]:
      if profit_ratio > 0.04:
        # profit is over the threshold, don't exit
        self._remove_profit_target(pair)
        return False, None
      if profit_ratio < -0.18:
        if profit_ratio < (previous_profit - 0.04):
          return True, previous_sell_reason
      elif profit_ratio < -0.1:
        if profit_ratio < (previous_profit - 0.04):
          return True, previous_sell_reason
      elif profit_ratio < -0.04:
        if profit_ratio < (previous_profit - 0.04):
          return True, previous_sell_reason
      else:
        if profit_ratio < (previous_profit - 0.04):
          return True, previous_sell_reason
    elif previous_sell_reason in [f"exit_{mode_name}_stoploss_u_e"]:
      if profit_current_stake_ratio > 0.04:
        # profit is over the threshold, don't exit
        self._remove_profit_target(pair)
        return False, None
      if profit_ratio < (previous_profit - (0.20 if trade.realized_profit == 0.0 else 0.26)):
        return True, previous_sell_reason
    elif previous_sell_reason in [f"exit_profit_{mode_name}_max"]:
      if profit_init_ratio < -0.08:
        # profit is under the threshold, cancel it
        self._remove_profit_target(pair)
        return False, None
      if self.is_futures_mode:
        if 0.01 <= profit_init_ratio < 0.02:
          if profit_init_ratio < (previous_profit * 0.5):
            return True, previous_sell_reason
        elif 0.02 <= profit_init_ratio < 0.03:
          if profit_init_ratio < (previous_profit * 0.6):
            return True, previous_sell_reason
        elif 0.03 <= profit_init_ratio < 0.04:
          if profit_init_ratio < (previous_profit * 0.7):
            return True, previous_sell_reason
        elif 0.04 <= profit_init_ratio < 0.08:
          if profit_init_ratio < (previous_profit * 0.8):
            return True, previous_sell_reason
        elif 0.08 <= profit_init_ratio < 0.16:
          if profit_init_ratio < (previous_profit * 0.9):
            return True, previous_sell_reason
        elif 0.16 <= profit_init_ratio:
          if profit_init_ratio < (previous_profit * 0.95):
            return True, previous_sell_reason
      else:
        if 0.01 <= profit_init_ratio < 0.03:
          if profit_init_ratio < (previous_profit * 0.6):
            return True, previous_sell_reason
        elif 0.03 <= profit_init_ratio < 0.08:
          if profit_init_ratio < (previous_profit * 0.65):
            return True, previous_sell_reason
        elif 0.08 <= profit_init_ratio < 0.16:
          if profit_init_ratio < (previous_profit * 0.7):
            return True, previous_sell_reason
        elif 0.16 <= profit_init_ratio:
          if profit_init_ratio < (previous_profit * 0.75):
            return True, previous_sell_reason
    else:
      return False, None

    return False, None

  # Calc Total Profit
  # ---------------------------------------------------------------------------------------------
  def calc_total_profit(
    self, trade: "Trade", filled_entries: "Orders", filled_exits: "Orders", exit_rate: float
  ) -> tuple:
    """
    Calculates the absolute profit for open trades.

    :param trade: trade object.
    :param filled_entries: Filled entries list.
    :param filled_exits: Filled exits list.
    :param exit_rate: The exit rate.
    :return tuple: The total profit in stake, ratio, ratio based on current stake, and ratio based on the first entry stake.
    """
    fee_open_rate = trade.fee_open if self.custom_fee_open_rate is None else self.custom_fee_open_rate
    fee_close_rate = trade.fee_close if self.custom_fee_close_rate is None else self.custom_fee_close_rate

    total_amount = 0.0
    total_stake = 0.0
    total_profit = 0.0
    current_stake = 0.0
    for entry_order in filled_entries:
      if trade.is_short:
        entry_stake = entry_order.safe_filled * entry_order.safe_price * (1 - fee_open_rate)
        total_amount += entry_order.safe_filled
        total_stake += entry_stake
        total_profit += entry_stake
      else:
        entry_stake = entry_order.safe_filled * entry_order.safe_price * (1 + fee_open_rate)
        total_amount += entry_order.safe_filled
        total_stake += entry_stake
        total_profit -= entry_stake
    for exit_order in filled_exits:
      if trade.is_short:
        exit_stake = exit_order.safe_filled * exit_order.safe_price * (1 + fee_close_rate)
        total_amount -= exit_order.safe_filled
        total_profit -= exit_stake
      else:
        exit_stake = exit_order.safe_filled * exit_order.safe_price * (1 - fee_close_rate)
        total_amount -= exit_order.safe_filled
        total_profit += exit_stake
    if trade.is_short:
      current_stake = total_amount * exit_rate * (1 + fee_close_rate)
      total_profit -= current_stake
    else:
      current_stake = total_amount * exit_rate * (1 - fee_close_rate)
      total_profit += current_stake
    if self.is_futures_mode:
      total_profit += trade.funding_fees
    total_profit_ratio = total_profit / total_stake
    current_profit_ratio = total_profit / current_stake
    init_profit_ratio = total_profit / filled_entries[0].cost
    return total_profit, total_profit_ratio, current_profit_ratio, init_profit_ratio

  # Custom Exit
  # ---------------------------------------------------------------------------------------------
  def custom_exit(
    self, pair: str, trade: "Trade", current_time: "datetime", current_rate: float, current_profit: float, **kwargs
  ):
    df, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
    last_candle = df.iloc[-1].squeeze()
    previous_candle_1 = df.iloc[-2].squeeze()
    previous_candle_2 = df.iloc[-3].squeeze()
    previous_candle_3 = df.iloc[-4].squeeze()
    previous_candle_4 = df.iloc[-5].squeeze()
    previous_candle_5 = df.iloc[-6].squeeze()

    enter_tag = "empty"
    if hasattr(trade, "enter_tag") and trade.enter_tag is not None:
      enter_tag = trade.enter_tag
    enter_tags = enter_tag.split()

    filled_entries = trade.select_filled_orders(trade.entry_side)
    filled_exits = trade.select_filled_orders(trade.exit_side)

    profit_stake = 0.0
    profit_ratio = 0.0
    profit_current_stake_ratio = 0.0
    profit_init_ratio = 0.0
    profit_stake, profit_ratio, profit_current_stake_ratio, profit_init_ratio = self.calc_total_profit(
      trade, filled_entries, filled_exits, current_rate
    )

    max_profit = (trade.max_rate - trade.open_rate) / trade.open_rate
    max_loss = (trade.open_rate - trade.min_rate) / trade.min_rate

    count_of_entries = len(filled_entries)
    if count_of_entries > 1:
      initial_entry = filled_entries[0]
      if initial_entry is not None and initial_entry.average is not None:
        max_profit = (trade.max_rate - initial_entry.average) / initial_entry.average
        max_loss = (initial_entry.average - trade.min_rate) / trade.min_rate

    # Long Normal mode
    if any(c in self.long_normal_mode_tags for c in enter_tags):
      sell, signal_name = self.long_exit_normal(
        pair,
        current_rate,
        profit_stake,
        profit_ratio,
        profit_current_stake_ratio,
        profit_init_ratio,
        max_profit,
        max_loss,
        filled_entries,
        filled_exits,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )
      if sell and (signal_name is not None):
        return f"{signal_name} ( {enter_tag})"

    # Long Pump mode
    if any(c in self.long_pump_mode_tags for c in enter_tags):
      sell, signal_name = self.long_exit_pump(
        pair,
        current_rate,
        profit_stake,
        profit_ratio,
        profit_current_stake_ratio,
        profit_init_ratio,
        max_profit,
        max_loss,
        filled_entries,
        filled_exits,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )
      if sell and (signal_name is not None):
        return f"{signal_name} ( {enter_tag})"

    # Long Quick mode
    if any(c in self.long_quick_mode_tags for c in enter_tags):
      sell, signal_name = self.long_exit_quick(
        pair,
        current_rate,
        profit_stake,
        profit_ratio,
        profit_current_stake_ratio,
        profit_init_ratio,
        max_profit,
        max_loss,
        filled_entries,
        filled_exits,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )
      if sell and (signal_name is not None):
        return f"{signal_name} ( {enter_tag})"

    # Long Rebuy mode
    if all(c in self.long_rebuy_mode_tags for c in enter_tags):
      sell, signal_name = self.long_exit_rebuy(
        pair,
        current_rate,
        profit_stake,
        profit_ratio,
        profit_current_stake_ratio,
        profit_init_ratio,
        max_profit,
        max_loss,
        filled_entries,
        filled_exits,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )
      if sell and (signal_name is not None):
        return f"{signal_name} ( {enter_tag})"

    # Long high profit mode
    if any(c in self.long_mode_tags for c in enter_tags):
      sell, signal_name = self.long_exit_high_profit(
        pair,
        current_rate,
        profit_stake,
        profit_ratio,
        profit_current_stake_ratio,
        profit_init_ratio,
        max_profit,
        max_loss,
        filled_entries,
        filled_exits,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )
      if sell and (signal_name is not None):
        return f"{signal_name} ( {enter_tag})"

    # Long rapid mode
    if any(c in self.long_rapid_mode_tags for c in enter_tags):
      sell, signal_name = self.long_exit_rapid(
        pair,
        current_rate,
        profit_stake,
        profit_ratio,
        profit_current_stake_ratio,
        profit_init_ratio,
        max_profit,
        max_loss,
        filled_entries,
        filled_exits,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )
      if sell and (signal_name is not None):
        return f"{signal_name} ( {enter_tag})"

    # Long grind mode
    if all(c in self.long_grind_mode_tags for c in enter_tags):
      sell, signal_name = self.long_exit_grind(
        pair,
        current_rate,
        profit_stake,
        profit_ratio,
        profit_current_stake_ratio,
        profit_init_ratio,
        max_profit,
        max_loss,
        filled_entries,
        filled_exits,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )
      if sell and (signal_name is not None):
        return f"{signal_name} ( {enter_tag})"

    # Short normal mode
    if any(c in self.short_normal_mode_tags for c in enter_tags):
      sell, signal_name = self.short_exit_normal(
        pair,
        current_rate,
        profit_stake,
        profit_ratio,
        profit_current_stake_ratio,
        profit_init_ratio,
        max_profit,
        max_loss,
        filled_entries,
        filled_exits,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )
      if sell and (signal_name is not None):
        return f"{signal_name} ( {enter_tag})"

    # Short Pump mode
    if any(c in self.short_pump_mode_tags for c in enter_tags):
      sell, signal_name = self.short_exit_pump(
        pair,
        current_rate,
        profit_stake,
        profit_ratio,
        profit_current_stake_ratio,
        profit_init_ratio,
        max_profit,
        max_loss,
        filled_entries,
        filled_exits,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )
      if sell and (signal_name is not None):
        return f"{signal_name} ( {enter_tag})"

    # Short Quick mode
    if any(c in self.short_quick_mode_tags for c in enter_tags):
      sell, signal_name = self.short_exit_quick(
        pair,
        current_rate,
        profit_stake,
        profit_ratio,
        profit_current_stake_ratio,
        profit_init_ratio,
        max_profit,
        max_loss,
        filled_entries,
        filled_exits,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )
      if sell and (signal_name is not None):
        return f"{signal_name} ( {enter_tag})"

    # Short Rebuy mode
    if all(c in self.short_rebuy_mode_tags for c in enter_tags):
      sell, signal_name = self.short_exit_rebuy(
        pair,
        current_rate,
        profit_stake,
        profit_ratio,
        profit_current_stake_ratio,
        profit_init_ratio,
        max_profit,
        max_loss,
        filled_entries,
        filled_exits,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )
      if sell and (signal_name is not None):
        return f"{signal_name} ( {enter_tag})"

    # Short high profit mode
    if any(c in self.short_mode_tags for c in enter_tags):
      sell, signal_name = self.short_exit_high_profit(
        pair,
        current_rate,
        profit_stake,
        profit_ratio,
        profit_current_stake_ratio,
        profit_init_ratio,
        max_profit,
        max_loss,
        filled_entries,
        filled_exits,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )
      if sell and (signal_name is not None):
        return f"{signal_name} ( {enter_tag})"

    # Short rapid mode
    if any(c in self.short_rapid_mode_tags for c in enter_tags):
      sell, signal_name = self.short_exit_rapid(
        pair,
        current_rate,
        profit_stake,
        profit_ratio,
        profit_current_stake_ratio,
        profit_init_ratio,
        max_profit,
        max_loss,
        filled_entries,
        filled_exits,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )
      if sell and (signal_name is not None):
        return f"{signal_name} ( {enter_tag})"

    # Trades not opened by X4
    if not trade.is_short and (
      not any(
        c
        in (
          self.long_normal_mode_tags
          + self.long_pump_mode_tags
          + self.long_quick_mode_tags
          + self.long_rebuy_mode_tags
          + self.long_mode_tags
          + self.long_rapid_mode_tags
          + self.long_grind_mode_tags
        )
        for c in enter_tags
      )
    ):
      # use normal mode for such trades
      sell, signal_name = self.long_exit_normal(
        pair,
        current_rate,
        profit_stake,
        profit_ratio,
        profit_current_stake_ratio,
        profit_init_ratio,
        max_profit,
        max_loss,
        filled_entries,
        filled_exits,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )
      if sell and (signal_name is not None):
        return f"{signal_name} ( {enter_tag})"

    # Trades not opened by X4
    if trade.is_short and (
      not any(
        c
        in (
          self.short_normal_mode_tags
          + self.short_pump_mode_tags
          + self.short_quick_mode_tags
          + self.short_rebuy_mode_tags
          + self.short_mode_tags
          + self.short_rapid_mode_tags
          + self.short_grind_mode_tags
        )
        for c in enter_tags
      )
    ):
      # use normal mode for such trades
      sell, signal_name = self.short_exit_normal(
        pair,
        current_rate,
        profit_stake,
        profit_ratio,
        profit_current_stake_ratio,
        profit_init_ratio,
        max_profit,
        max_loss,
        filled_entries,
        filled_exits,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )
      if sell and (signal_name is not None):
        return f"{signal_name} ( {enter_tag})"

    return None

  # Custom Stake Amount
  # ---------------------------------------------------------------------------------------------
  def custom_stake_amount(
    self,
    pair: str,
    current_time: datetime,
    current_rate: float,
    proposed_stake: float,
    min_stake: Optional[float],
    max_stake: float,
    leverage: float,
    entry_tag: Optional[str],
    side: str,
    **kwargs,
  ) -> float:
    enter_tags = entry_tag.split()
    if side == "long":
      # Rebuy mode
      if all(c in self.long_rebuy_mode_tags for c in enter_tags) or (
        any(c in self.long_rebuy_mode_tags for c in enter_tags)
        and all(c in (self.long_rebuy_mode_tags + self.long_grind_mode_tags) for c in enter_tags)
      ):
        stake_multiplier = self.rebuy_mode_stake_multiplier
        # Low stakes, on Binance mostly
        if (proposed_stake * self.rebuy_mode_stake_multiplier) < min_stake:
          stake_multiplier = self.rebuy_mode_stake_multiplier_alt
        return proposed_stake * stake_multiplier
      # Grind mode
      elif all(c in self.long_grind_mode_tags for c in enter_tags):
        for _, item in enumerate(
          self.grind_mode_stake_multiplier_futures if self.is_futures_mode else self.grind_mode_stake_multiplier_spot
        ):
          if (proposed_stake * item) > min_stake:
            stake_multiplier = item
            return proposed_stake * stake_multiplier
      else:
        stake_multiplier = (
          self.regular_mode_stake_multiplier_futures[0]
          if self.is_futures_mode
          else self.regular_mode_stake_multiplier_spot[0]
        )
        if (proposed_stake * stake_multiplier) > min_stake:
          return proposed_stake * stake_multiplier
        else:
          return min_stake
    else:
      # Rebuy mode
      if all(c in self.short_rebuy_mode_tags for c in enter_tags) or (
        any(c in self.short_rebuy_mode_tags for c in enter_tags)
        and all(c in (self.short_rebuy_mode_tags + self.short_grind_mode_tags) for c in enter_tags)
      ):
        stake_multiplier = self.rebuy_mode_stake_multiplier
        # Low stakes, on Binance mostly
        if (proposed_stake * self.rebuy_mode_stake_multiplier) < min_stake:
          stake_multiplier = self.rebuy_mode_stake_multiplier_alt
        return proposed_stake * stake_multiplier
      # Grind mode
      elif all(c in self.short_grind_mode_tags for c in enter_tags):
        for _, item in enumerate(
          self.grind_mode_stake_multiplier_futures if self.is_futures_mode else self.grind_mode_stake_multiplier_spot
        ):
          if (proposed_stake * item) > min_stake:
            stake_multiplier = item
            return proposed_stake * stake_multiplier
      else:
        stake_multiplier = (
          self.regular_mode_stake_multiplier_futures[0]
          if self.is_futures_mode
          else self.regular_mode_stake_multiplier_spot[0]
        )
        if (proposed_stake * stake_multiplier) > min_stake:
          return proposed_stake * stake_multiplier
        else:
          return min_stake

    return proposed_stake

  # Adjust Trade Position
  # ---------------------------------------------------------------------------------------------
  def adjust_trade_position(
    self,
    trade: Trade,
    current_time: datetime,
    current_rate: float,
    current_profit: float,
    min_stake: Optional[float],
    max_stake: float,
    current_entry_rate: float,
    current_exit_rate: float,
    current_entry_profit: float,
    current_exit_profit: float,
    **kwargs,
  ):
    if self.position_adjustment_enable == False:
      return None

    enter_tag = "empty"
    if hasattr(trade, "enter_tag") and trade.enter_tag is not None:
      enter_tag = trade.enter_tag
    enter_tags = enter_tag.split()

    # Rebuy mode
    if not trade.is_short and (
      all(c in self.long_rebuy_mode_tags for c in enter_tags)
      or (
        any(c in self.long_rebuy_mode_tags for c in enter_tags)
        and all(c in (self.long_rebuy_mode_tags + self.long_grind_mode_tags) for c in enter_tags)
      )
    ):
      return self.long_rebuy_adjust_trade_position(
        trade,
        enter_tags,
        current_time,
        current_rate,
        current_profit,
        min_stake,
        max_stake,
        current_entry_rate,
        current_exit_rate,
        current_entry_profit,
        current_exit_profit,
      )

    # Grinding
    elif not trade.is_short and (
      any(
        c
        in (
          self.long_normal_mode_tags
          + self.long_pump_mode_tags
          + self.long_quick_mode_tags
          + self.long_mode_tags
          + self.long_rapid_mode_tags
          + self.long_grind_mode_tags
        )
        for c in enter_tags
      )
      or not any(
        c
        in (
          self.long_normal_mode_tags
          + self.long_pump_mode_tags
          + self.long_quick_mode_tags
          + self.long_rebuy_mode_tags
          + self.long_mode_tags
          + self.long_rapid_mode_tags
          + self.long_grind_mode_tags
        )
        for c in enter_tags
      )
    ):
      return self.long_grind_adjust_trade_position(
        trade,
        enter_tags,
        current_time,
        current_rate,
        current_profit,
        min_stake,
        max_stake,
        current_entry_rate,
        current_exit_rate,
        current_entry_profit,
        current_exit_profit,
      )

    elif trade.is_short and (
      any(
        c
        in (
          self.short_normal_mode_tags
          + self.short_pump_mode_tags
          + self.short_quick_mode_tags
          + self.short_mode_tags
          + self.short_rapid_mode_tags
          + self.short_grind_mode_tags
        )
        for c in enter_tags
      )
      or not any(
        c
        in (
          self.short_normal_mode_tags
          + self.short_pump_mode_tags
          + self.short_quick_mode_tags
          + self.short_rebuy_mode_tags
          + self.short_mode_tags
          + self.short_rapid_mode_tags
          + self.short_grind_mode_tags
        )
        for c in enter_tags
      )
    ):
      return self.short_grind_adjust_trade_position(
        trade,
        enter_tags,
        current_time,
        current_rate,
        current_profit,
        min_stake,
        max_stake,
        current_entry_rate,
        current_exit_rate,
        current_entry_profit,
        current_exit_profit,
      )

    return None

  # Informative Pairs
  # ---------------------------------------------------------------------------------------------
  def informative_pairs(self):
    # get access to all pairs available in whitelist.
    pairs = self.dp.current_whitelist()
    # Assign tf to each pair so they can be downloaded and cached for strategy.
    informative_pairs = []
    for info_timeframe in self.info_timeframes:
      informative_pairs.extend([(pair, info_timeframe) for pair in pairs])

    if self.config["stake_currency"] in [
      "USDT",
      "BUSD",
      "USDC",
      "DAI",
      "TUSD",
      "FDUSD",
      "PAX",
      "USD",
      "EUR",
      "GBP",
      "TRY",
    ]:
      if ("trading_mode" in self.config) and (self.config["trading_mode"] in ["futures", "margin"]):
        btc_info_pair = f"BTC/{self.config['stake_currency']}:{self.config['stake_currency']}"
      else:
        btc_info_pair = f"BTC/{self.config['stake_currency']}"
    else:
      if ("trading_mode" in self.config) and (self.config["trading_mode"] in ["futures", "margin"]):
        btc_info_pair = "BTC/USDT:USDT"
      else:
        btc_info_pair = "BTC/USDT"

    informative_pairs.extend([(btc_info_pair, btc_info_timeframe) for btc_info_timeframe in self.btc_info_timeframes])

    return informative_pairs

  # Informative 1d Timeframe Indicators
  # ---------------------------------------------------------------------------------------------
  def informative_1d_indicators(self, metadata: dict, info_timeframe) -> DataFrame:
    tik = time.perf_counter()
    assert self.dp, "DataProvider is required for multiple timeframes."
    # Get the informative pair
    informative_1d = self.dp.get_pair_dataframe(pair=metadata["pair"], timeframe=info_timeframe)

    # Indicators
    # -----------------------------------------------------------------------------------------
    # RSI
    informative_1d["rsi_3"] = pta.rsi(informative_1d["close"], length=3, fillna=0.0)
    informative_1d["rsi_14"] = pta.rsi(informative_1d["close"], length=14, fillna=0.0)

    informative_1d["rsi_14_max_6"] = informative_1d["rsi_14"].rolling(6).max()

    # EMA
    informative_1d["ema_200"] = ta.EMA(informative_1d, timeperiod=200)

    informative_1d["ema_200_dec_4"] = (informative_1d["ema_200"].isnull()) | (
      informative_1d["ema_200"] <= informative_1d["ema_200"].shift(4)
    )

    # CTI
    informative_1d["cti_20"] = pta.cti(informative_1d["close"], length=20)

    informative_1d["cti_20_dec_3"] = informative_1d["cti_20"] < informative_1d["cti_20"].shift(3)

    # Pivots
    (
      informative_1d["pivot"],
      informative_1d["res1"],
      informative_1d["res2"],
      informative_1d["res3"],
      informative_1d["sup1"],
      informative_1d["sup2"],
      informative_1d["sup3"],
    ) = pivot_points(informative_1d, mode="fibonacci")

    # S/R
    res_series = (
      informative_1d["high"].rolling(window=5, center=True).apply(lambda row: is_resistance(row), raw=True).shift(2)
    )
    sup_series = (
      informative_1d["low"].rolling(window=5, center=True).apply(lambda row: is_support(row), raw=True).shift(2)
    )
    informative_1d["res_level"] = Series(
      np.where(
        res_series,
        np.where(informative_1d["close"] > informative_1d["open"], informative_1d["close"], informative_1d["open"]),
        float("NaN"),
      )
    ).ffill()
    informative_1d["res_hlevel"] = Series(np.where(res_series, informative_1d["high"], float("NaN"))).ffill()
    informative_1d["sup_level"] = Series(
      np.where(
        sup_series,
        np.where(informative_1d["close"] < informative_1d["open"], informative_1d["close"], informative_1d["open"]),
        float("NaN"),
      )
    ).ffill()

    # Downtrend checks
    informative_1d["not_downtrend"] = (informative_1d["close"] > informative_1d["close"].shift(2)) | (
      informative_1d["rsi_14"] > 50.0
    )

    informative_1d["is_downtrend_3"] = (
      (informative_1d["close"] < informative_1d["open"])
      & (informative_1d["close"].shift(1) < informative_1d["open"].shift(1))
      & (informative_1d["close"].shift(2) < informative_1d["open"].shift(2))
    )

    # Wicks
    informative_1d["top_wick_pct"] = (
      informative_1d["high"] - np.maximum(informative_1d["open"], informative_1d["close"])
    ) / np.maximum(informative_1d["open"], informative_1d["close"])
    informative_1d["bot_wick_pct"] = abs(
      (informative_1d["low"] - np.minimum(informative_1d["open"], informative_1d["close"]))
      / np.minimum(informative_1d["open"], informative_1d["close"])
    )

    # Candle change
    informative_1d["change_pct"] = (informative_1d["close"] - informative_1d["open"]) / informative_1d["open"]

    # Pump protections
    informative_1d["hl_pct_change_3"] = range_percent_change(self, informative_1d, "HL", 3)
    informative_1d["hl_pct_change_6"] = range_percent_change(self, informative_1d, "HL", 6)

    # Max highs
    informative_1d["high_max_6"] = informative_1d["high"].rolling(6).max()
    informative_1d["high_max_12"] = informative_1d["high"].rolling(12).max()

    # Max lows
    informative_1d["low_min_6"] = informative_1d["low"].rolling(6).min()
    informative_1d["low_min_12"] = informative_1d["low"].rolling(12).min()

    # Performance logging
    # -----------------------------------------------------------------------------------------
    tok = time.perf_counter()
    log.debug(f"[{metadata['pair']}] informative_1d_indicators took: {tok - tik:0.4f} seconds.")

    return informative_1d

  # Informative 4h Timeframe Indicators
  # ---------------------------------------------------------------------------------------------
  def informative_4h_indicators(self, metadata: dict, info_timeframe) -> DataFrame:
    tik = time.perf_counter()
    assert self.dp, "DataProvider is required for multiple timeframes."
    # Get the informative pair
    informative_4h = self.dp.get_pair_dataframe(pair=metadata["pair"], timeframe=info_timeframe)

    # Indicators
    # -----------------------------------------------------------------------------------------
    # RSI
    informative_4h["rsi_3"] = pta.rsi(informative_4h["close"], length=3, fillna=0.0)
    informative_4h["rsi_14"] = pta.rsi(informative_4h["close"], length=14, fillna=0.0)

    informative_4h["rsi_14_max_3"] = informative_4h["rsi_14"].rolling(3).max()
    informative_4h["rsi_14_max_6"] = informative_4h["rsi_14"].rolling(6).max()

    # EMA
    informative_4h["ema_12"] = ta.EMA(informative_4h, timeperiod=12)
    informative_4h["ema_26"] = ta.EMA(informative_4h, timeperiod=26)
    informative_4h["ema_50"] = ta.EMA(informative_4h, timeperiod=50)
    informative_4h["ema_200"] = ta.EMA(informative_4h, timeperiod=200)

    informative_4h["ema_200_dec_24"] = (informative_4h["ema_200"].isnull()) | (
      informative_4h["ema_200"] <= informative_4h["ema_200"].shift(24)
    )

    # SMA
    informative_4h["sma_50"] = pta.sma(informative_4h["close"], length=50, fillna=0.0)
    informative_4h["sma_200"] = pta.sma(informative_4h["close"], length=200, fillna=0.0)

    informative_4h["sma_200_dec_48"] = (
      (informative_4h["sma_200"].isnull())
      | (informative_4h["sma_200"].eq(0.0))
      | (informative_4h["sma_200"] <= informative_4h["sma_200"].shift(48))
    )

    # ZL MA
    informative_4h["zlma_50"] = pta.zlma(informative_4h["close"], length=50, mamode="ema", offset=0, fillna=0.0)

    informative_4h["zlma_50_dec"] = (
      (informative_4h["zlma_50"].isnull())
      | (informative_4h["zlma_50"].eq(0.0))
      | (informative_4h["zlma_50"] <= informative_4h["zlma_50"].shift(1))
    )

    # Williams %R
    informative_4h["r_14"] = pta.willr(
      informative_4h["high"], informative_4h["low"], informative_4h["close"], length=14
    )
    informative_4h["r_480"] = pta.willr(
      informative_4h["high"], informative_4h["low"], informative_4h["close"], length=480
    )

    # CTI
    informative_4h["cti_20"] = pta.cti(informative_4h["close"], length=20)

    # S/R
    res_series = (
      informative_4h["high"].rolling(window=5, center=True).apply(lambda row: is_resistance(row), raw=True).shift(2)
    )
    sup_series = (
      informative_4h["low"].rolling(window=5, center=True).apply(lambda row: is_support(row), raw=True).shift(2)
    )
    informative_4h["res_level"] = Series(
      np.where(
        res_series,
        np.where(informative_4h["close"] > informative_4h["open"], informative_4h["close"], informative_4h["open"]),
        float("NaN"),
      )
    ).ffill()
    informative_4h["res_hlevel"] = Series(np.where(res_series, informative_4h["high"], float("NaN"))).ffill()
    informative_4h["sup_level"] = Series(
      np.where(
        sup_series,
        np.where(informative_4h["close"] < informative_4h["open"], informative_4h["close"], informative_4h["open"]),
        float("NaN"),
      )
    ).ffill()

    # Downtrend checks
    informative_4h["not_downtrend"] = (informative_4h["close"] > informative_4h["close"].shift(2)) | (
      informative_4h["rsi_14"] > 50.0
    )

    informative_4h["is_downtrend_3"] = (
      (informative_4h["close"] < informative_4h["open"])
      & (informative_4h["close"].shift(1) < informative_4h["open"].shift(1))
      & (informative_4h["close"].shift(2) < informative_4h["open"].shift(2))
    )

    # Wicks
    informative_4h["top_wick_pct"] = (
      informative_4h["high"] - np.maximum(informative_4h["open"], informative_4h["close"])
    ) / np.maximum(informative_4h["open"], informative_4h["close"])
    informative_4h["bot_wick_pct"] = abs(
      (informative_4h["low"] - np.minimum(informative_4h["open"], informative_4h["close"]))
      / np.minimum(informative_4h["open"], informative_4h["close"])
    )

    # Candle change
    informative_4h["change_pct"] = (informative_4h["close"] - informative_4h["open"]) / informative_4h["open"]

    informative_4h["change_pct_min_3"] = informative_4h["change_pct"].rolling(3).min()

    informative_4h["change_pct_max_3"] = informative_4h["change_pct"].rolling(3).max()

    # Max highs
    informative_4h["high_max_3"] = informative_4h["high"].rolling(3).max()
    informative_4h["high_max_12"] = informative_4h["high"].rolling(12).max()
    informative_4h["high_max_24"] = informative_4h["high"].rolling(24).max()
    informative_4h["high_max_36"] = informative_4h["high"].rolling(36).max()
    informative_4h["high_max_48"] = informative_4h["high"].rolling(48).max()

    # Volume
    informative_4h["volume_mean_factor_6"] = informative_4h["volume"] / informative_4h["volume"].rolling(6).mean()

    # Performance logging
    # -----------------------------------------------------------------------------------------
    tok = time.perf_counter()
    log.debug(f"[{metadata['pair']}] informative_1d_indicators took: {tok - tik:0.4f} seconds.")

    return informative_4h

  # Informative 1h Timeframe Indicators
  # ---------------------------------------------------------------------------------------------
  def informative_1h_indicators(self, metadata: dict, info_timeframe) -> DataFrame:
    tik = time.perf_counter()
    assert self.dp, "DataProvider is required for multiple timeframes."
    # Get the informative pair
    informative_1h = self.dp.get_pair_dataframe(pair=metadata["pair"], timeframe=info_timeframe)

    # Indicators
    # -----------------------------------------------------------------------------------------
    # RSI
    informative_1h["rsi_3"] = pta.rsi(informative_1h["close"], length=3, fillna=0.0)
    informative_1h["rsi_14"] = pta.rsi(informative_1h["close"], length=14, fillna=0.0)

    informative_1h["rsi_14_max_3"] = informative_1h["rsi_14"].rolling(3).max()
    informative_1h["rsi_14_max_6"] = informative_1h["rsi_14"].rolling(6).max()

    # EMA
    informative_1h["ema_12"] = ta.EMA(informative_1h, timeperiod=12)
    informative_1h["ema_26"] = ta.EMA(informative_1h, timeperiod=26)
    informative_1h["ema_50"] = ta.EMA(informative_1h, timeperiod=50)
    informative_1h["ema_200"] = ta.EMA(informative_1h, timeperiod=200)

    informative_1h["ema_200_dec_48"] = (informative_1h["ema_200"].isnull()) | (
      informative_1h["ema_200"] <= informative_1h["ema_200"].shift(48)
    )

    # SMA
    informative_1h["sma_50"] = pta.sma(informative_1h["close"], length=50, fillna=0.0)
    informative_1h["sma_200"] = pta.sma(informative_1h["close"], length=200, fillna=0.0)

    informative_1h["sma_200_dec_48"] = (
      (informative_1h["sma_200"].isnull())
      | (informative_1h["sma_200"].eq(0.0))
      | (informative_1h["sma_200"] <= informative_1h["sma_200"].shift(48))
    )

    # ZL MA
    informative_1h["zlma_50"] = pta.zlma(informative_1h["close"], length=50, mamode="ema", offset=0, fillna=0.0)

    informative_1h["zlma_50_dec"] = (
      (informative_1h["zlma_50"].isnull())
      | (informative_1h["zlma_50"].eq(0.0))
      | (informative_1h["zlma_50"] <= informative_1h["zlma_50"].shift(1))
    )

    # BB
    bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(informative_1h), window=20, stds=2)
    informative_1h["bb20_2_low"] = bollinger["lower"]
    informative_1h["bb20_2_mid"] = bollinger["mid"]
    informative_1h["bb20_2_upp"] = bollinger["upper"]

    informative_1h["bb20_2_width"] = (informative_1h["bb20_2_upp"] - informative_1h["bb20_2_low"]) / informative_1h[
      "bb20_2_mid"
    ]

    # Williams %R
    informative_1h["r_14"] = pta.willr(
      informative_1h["high"], informative_1h["low"], informative_1h["close"], length=14
    )
    informative_1h["r_480"] = pta.willr(
      informative_1h["high"], informative_1h["low"], informative_1h["close"], length=480
    )

    # CTI
    informative_1h["cti_20"] = pta.cti(informative_1h["close"], length=20)
    informative_1h["cti_40"] = pta.cti(informative_1h["close"], length=40)

    informative_1h["cti_20_dec_3"] = informative_1h["cti_20"] < informative_1h["cti_20"].shift(3)

    # EWO
    informative_1h["ewo_50_200"] = ewo(informative_1h, 50, 200)

    # EverGet ChandelierExit
    high = informative_1h["high"]
    low = informative_1h["low"]
    close = informative_1h["close"]
    chandelier_atr = ta.ATR(high, low, close, 22) * 3.0
    long_stop = (high.rolling(22).max() if True else high.rolling(22).apply(lambda x: x[:-1].max())) - chandelier_atr
    long_stop_prev = long_stop.shift(1).fillna(long_stop)
    long_stop = close.shift(1).where(close.shift(1) > long_stop_prev, long_stop)
    short_stop = (low.rolling(22).min() if True else low.rolling(22).apply(lambda x: x[:-1].min())) + chandelier_atr
    short_stop_prev = short_stop.shift(1).fillna(short_stop)
    short_stop = close.shift(1).where(close.shift(1) < short_stop_prev, short_stop)
    informative_1h["chandelier_dir"] = 1
    informative_1h.loc[informative_1h["close"] <= long_stop_prev, "chandelier_dir"] = -1
    informative_1h.loc[informative_1h["close"] > short_stop_prev, "chandelier_dir"] = 1

    # S/R
    res_series = (
      informative_1h["high"].rolling(window=5, center=True).apply(lambda row: is_resistance(row), raw=True).shift(2)
    )
    sup_series = (
      informative_1h["low"].rolling(window=5, center=True).apply(lambda row: is_support(row), raw=True).shift(2)
    )
    informative_1h["res_level"] = Series(
      np.where(
        res_series,
        np.where(informative_1h["close"] > informative_1h["open"], informative_1h["close"], informative_1h["open"]),
        float("NaN"),
      )
    ).ffill()
    informative_1h["res_hlevel"] = Series(np.where(res_series, informative_1h["high"], float("NaN"))).ffill()
    informative_1h["sup_level"] = Series(
      np.where(
        sup_series,
        np.where(informative_1h["close"] < informative_1h["open"], informative_1h["close"], informative_1h["open"]),
        float("NaN"),
      )
    ).ffill()

    # Pump protections
    informative_1h["hl_pct_change_48"] = range_percent_change(self, informative_1h, "HL", 48)
    informative_1h["hl_pct_change_24"] = range_percent_change(self, informative_1h, "HL", 24)
    informative_1h["hl_pct_change_12"] = range_percent_change(self, informative_1h, "HL", 12)
    informative_1h["hl_pct_change_6"] = range_percent_change(self, informative_1h, "HL", 6)

    # Downtrend checks
    informative_1h["not_downtrend"] = (informative_1h["close"] > informative_1h["close"].shift(2)) | (
      informative_1h["rsi_14"] > 50.0
    )

    informative_1h["is_downtrend_3"] = (
      (informative_1h["close"] < informative_1h["open"])
      & (informative_1h["close"].shift(1) < informative_1h["open"].shift(1))
      & (informative_1h["close"].shift(2) < informative_1h["open"].shift(2))
    )

    # Wicks
    informative_1h["top_wick_pct"] = (
      informative_1h["high"] - np.maximum(informative_1h["open"], informative_1h["close"])
    ) / np.maximum(informative_1h["open"], informative_1h["close"])

    # Candle change
    informative_1h["change_pct"] = (informative_1h["close"] - informative_1h["open"]) / informative_1h["open"]

    # Max highs
    informative_1h["high_max_6"] = informative_1h["high"].rolling(6).max()
    informative_1h["high_max_12"] = informative_1h["high"].rolling(12).max()
    informative_1h["high_max_24"] = informative_1h["high"].rolling(24).max()
    informative_1h["high_max_48"] = informative_1h["high"].rolling(48).max()

    # Max lows
    informative_1h["low_min_12"] = informative_1h["low"].rolling(12).min()
    informative_1h["low_min_24"] = informative_1h["low"].rolling(24).min()
    informative_1h["low_min_48"] = informative_1h["low"].rolling(48).min()

    # Performance logging
    # -----------------------------------------------------------------------------------------
    tok = time.perf_counter()
    log.debug(f"[{metadata['pair']}] informative_1h_indicators took: {tok - tik:0.4f} seconds.")

    return informative_1h

  # Informative 15m Timeframe Indicators
  # ---------------------------------------------------------------------------------------------
  def informative_15m_indicators(self, metadata: dict, info_timeframe) -> DataFrame:
    tik = time.perf_counter()
    assert self.dp, "DataProvider is required for multiple timeframes."

    # Get the informative pair
    informative_15m = self.dp.get_pair_dataframe(pair=metadata["pair"], timeframe=info_timeframe)

    # Indicators
    # -----------------------------------------------------------------------------------------

    # RSI
    informative_15m["rsi_3"] = pta.rsi(informative_15m["close"], length=3)
    informative_15m["rsi_14"] = pta.rsi(informative_15m["close"], length=14)

    # EMA
    informative_15m["ema_12"] = ta.EMA(informative_15m, timeperiod=12)
    informative_15m["ema_26"] = ta.EMA(informative_15m, timeperiod=26)
    informative_15m["ema_200"] = ta.EMA(informative_15m, timeperiod=200)

    informative_15m["ema_200_dec_24"] = (informative_15m["ema_200"].isnull()) | (
      informative_15m["ema_200"] <= informative_15m["ema_200"].shift(24)
    )

    # SMA
    informative_15m["sma_200"] = ta.SMA(informative_15m, timeperiod=200)

    # ZL MA
    informative_15m["zlma_50"] = pta.zlma(informative_15m["close"], length=50, mamode="ema", offset=0)

    informative_15m["zlma_50_dec"] = (informative_15m["zlma_50"].isnull()) | (
      informative_15m["zlma_50"] <= informative_15m["zlma_50"].shift(1)
    )

    # BB - 20 STD2
    bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(informative_15m), window=20, stds=2)
    informative_15m["bb20_2_low"] = bollinger["lower"]
    informative_15m["bb20_2_mid"] = bollinger["mid"]
    informative_15m["bb20_2_upp"] = bollinger["upper"]

    # CTI
    informative_15m["cti_20"] = pta.cti(informative_15m["close"], length=20)

    # EWO
    informative_15m["ewo_50_200"] = ewo(informative_15m, 50, 200)

    # Downtrend check
    informative_15m["not_downtrend"] = (
      (informative_15m["close"] > informative_15m["open"])
      | (informative_15m["close"].shift(1) > informative_15m["open"].shift(1))
      | (informative_15m["close"].shift(2) > informative_15m["open"].shift(2))
      | (informative_15m["rsi_14"] > 50.0)
      | (informative_15m["rsi_3"] > 25.0)
    )

    # Performance logging
    # -----------------------------------------------------------------------------------------
    tok = time.perf_counter()
    log.debug(f"[{metadata['pair']}] informative_15m_indicators took: {tok - tik:0.4f} seconds.")

    return informative_15m

  # Coin Pair Base Timeframe Indicators
  # ---------------------------------------------------------------------------------------------
  def base_tf_5m_indicators(self, metadata: dict, df: DataFrame) -> DataFrame:
    tik = time.perf_counter()

    # Indicators
    # base_tf_5m_indicators_pandas_ta = pta.Strategy(
    # name="base_tf_5m_indicators_pandas_ta",
    # ta=[
    # # RSI
    # {"kind": "rsi", "length": 3},
    # {"kind": "rsi", "length": 14},
    # {"kind": "rsi", "length": 20},

    # # EMA
    # {"kind": "ema", "length": 12},
    # {"kind": "ema", "length": 16},
    # {"kind": "ema", "length": 20},
    # {"kind": "ema", "length": 26},
    # {"kind": "ema", "length": 50},
    # {"kind": "ema", "length": 100},
    # {"kind": "ema", "length": 200},

    # # SMA
    # {"kind": "sma", "length": 16},
    # {"kind": "sma", "length": 30},
    # {"kind": "sma", "length": 75},
    # {"kind": "sma", "length": 200},

    # # BB 20 - STD2
    # {"kind": "bbands", "length": 20}

    # # BB 40 - STD2
    # {"kind": "bbands", "length": 40}

    # # Williams %R
    # {"kind": "willr", "length": 14},
    # {"kind": "willr", "length": 480},

    # # CTI
    # {"kind": "cti", "length": 20},

    # # CCI
    # {"kind": "cci", "length": 20},

    # # Hull Moving Average
    # {"kind": "hma", "length": 55},
    # {"kind": "hma", "length": 70},

    # # ZL MA
    # {"kind": "zlma", "length": 50, "mamode":"linreg"},

    # # Heiken Ashi
    # {"kind": "ha"},
    #       ]
    # )

    # -----------------------------------------------------------------------------------------
    # RSI
    df["rsi_3"] = pta.rsi(df["close"], length=3)
    df["rsi_14"] = pta.rsi(df["close"], length=14)
    df["rsi_20"] = pta.rsi(df["close"], length=20)

    # EMA
    df["ema_12"] = ta.EMA(df, timeperiod=12)
    df["ema_16"] = ta.EMA(df, timeperiod=16)
    df["ema_20"] = ta.EMA(df, timeperiod=20)
    df["ema_26"] = ta.EMA(df, timeperiod=26)
    df["ema_50"] = ta.EMA(df, timeperiod=50)
    df["ema_100"] = ta.EMA(df, timeperiod=100)
    df["ema_200"] = ta.EMA(df, timeperiod=200)

    df["ema_200_dec_24"] = (df["ema_200"].isnull()) | (df["ema_200"] <= df["ema_200"].shift(24))

    df["ema_200_pct_change_144"] = (df["ema_200"] - df["ema_200"].shift(144)) / df["ema_200"].shift(144)
    df["ema_200_pct_change_288"] = (df["ema_200"] - df["ema_200"].shift(288)) / df["ema_200"].shift(288)

    # SMA
    df["sma_16"] = ta.SMA(df, timeperiod=16)
    df["sma_30"] = ta.SMA(df, timeperiod=30)
    df["sma_75"] = ta.SMA(df, timeperiod=75)
    df["sma_200"] = ta.SMA(df, timeperiod=200)

    # BB 20 - STD2
    bb_20_std2 = qtpylib.bollinger_bands(qtpylib.typical_price(df), window=20, stds=2)
    df["bb20_2_low"] = bb_20_std2["lower"]
    df["bb20_2_mid"] = bb_20_std2["mid"]
    df["bb20_2_upp"] = bb_20_std2["upper"]

    # BB 40 - STD2
    bb_40_std2 = qtpylib.bollinger_bands(df["close"], window=40, stds=2)
    df["bb40_2_low"] = bb_40_std2["lower"]
    df["bb40_2_mid"] = bb_40_std2["mid"]
    df["bb40_2_delta"] = (bb_40_std2["mid"] - df["bb40_2_low"]).abs()
    df["bb40_2_tail"] = (df["close"] - df["bb40_2_low"]).abs()

    # Williams %R
    df["r_14"] = pta.willr(df["high"], df["low"], df["close"], length=14)
    df["r_480"] = pta.willr(df["high"], df["low"], df["close"], length=480)

    # CTI
    df["cti_20"] = pta.cti(df["close"], length=20)

    # CCI
    df["cci_20"] = ta.CCI(df, source="hlc3", timeperiod=20)

    # EWO
    df["ewo_50_200"] = ewo(df, 50, 200)

    # Hull Moving Average
    df["hma_55"] = pta.hma(df["close"], length=55)
    df["hma_70"] = pta.hma(df["close"], length=70)

    df["hma_55_buy"] = (df["hma_55"] > df["hma_55"].shift(1)) & (df["hma_55"].shift(1) < df["hma_55"].shift(2))
    df["hma_70_buy"] = (df["hma_70"] > df["hma_70"].shift(1)) & (df["hma_70"].shift(1) < df["hma_70"].shift(2))

    # ZL MA
    df["zlma_50"] = pta.zlma(df["close"], length=50, mamode="ema", offset=0)

    # EverGet ChandelierExit
    high = df["high"]
    low = df["low"]
    close = df["close"]
    chandelier_atr = ta.ATR(high, low, close, 22) * 3.0
    long_stop = (high.rolling(22).max() if True else high.rolling(22).apply(lambda x: x[:-1].max())) - chandelier_atr
    long_stop_prev = long_stop.shift(1).fillna(long_stop)
    long_stop = close.shift(1).where(close.shift(1) > long_stop_prev, long_stop)
    short_stop = (low.rolling(22).min() if True else low.rolling(22).apply(lambda x: x[:-1].min())) + chandelier_atr
    short_stop_prev = short_stop.shift(1).fillna(short_stop)
    short_stop = close.shift(1).where(close.shift(1) < short_stop_prev, short_stop)
    df["chandelier_dir"] = 1
    df.loc[df["close"] <= long_stop_prev, "chandelier_dir"] = -1
    df.loc[df["close"] > short_stop_prev, "chandelier_dir"] = 1

    # Heiken Ashi
    heikinashi = qtpylib.heikinashi(df)
    df["ha_open"] = heikinashi["open"]
    df["ha_close"] = heikinashi["close"]
    df["ha_high"] = heikinashi["high"]
    df["ha_low"] = heikinashi["low"]

    # Dip protection
    df["tpct_change_0"] = top_percent_change(self, df, 0)
    df["tpct_change_2"] = top_percent_change(self, df, 2)

    # Candle change
    df["change_pct"] = (df["close"] - df["open"]) / df["open"]

    # Close max
    df["close_max_12"] = df["close"].rolling(12).max()
    df["close_max_24"] = df["close"].rolling(24).max()
    df["close_max_48"] = df["close"].rolling(48).max()

    # Open min
    df["open_min_6"] = df["open"].rolling(6).min()
    df["open_min_12"] = df["open"].rolling(12).min()

    # Close min
    df["close_min_12"] = df["close"].rolling(12).min()
    df["close_min_24"] = df["close"].rolling(24).min()
    df["close_min_48"] = df["close"].rolling(48).min()

    # Close delta
    df["close_delta"] = (df["close"] - df["close"].shift()).abs()

    # Number of empty candles in the last 288
    df["num_empty_288"] = (df["volume"] <= 0).rolling(window=288, min_periods=288).sum()

    # For sell checks
    df["crossed_below_ema_12_26"] = qtpylib.crossed_below(df["ema_12"], df["ema_26"])
    df["crossed_above_ema_12_26"] = qtpylib.crossed_above(df["ema_12"], df["ema_26"])

    # Global protections
    # -----------------------------------------------------------------------------------------
    if not self.config["runmode"].value in ("live", "dry_run"):
      # Backtest age filter
      df["bt_agefilter_ok"] = False
      df.loc[df.index > (12 * 24 * self.bt_min_age_days), "bt_agefilter_ok"] = True
    else:
      # Exchange downtime protection
      df["live_data_ok"] = df["volume"].rolling(window=72, min_periods=72).min() > 0

    # Performance logging
    # -----------------------------------------------------------------------------------------
    tok = time.perf_counter()
    log.debug(f"[{metadata['pair']}] base_tf_5m_indicators took: {tok - tik:0.4f} seconds.")

    return df

  # Coin Pair Indicator Switch Case
  # ---------------------------------------------------------------------------------------------
  def info_switcher(self, metadata: dict, info_timeframe) -> DataFrame:
    if info_timeframe == "1d":
      return self.informative_1d_indicators(metadata, info_timeframe)
    elif info_timeframe == "4h":
      return self.informative_4h_indicators(metadata, info_timeframe)
    elif info_timeframe == "1h":
      return self.informative_1h_indicators(metadata, info_timeframe)
    elif info_timeframe == "15m":
      return self.informative_15m_indicators(metadata, info_timeframe)
    else:
      raise RuntimeError(f"{info_timeframe} not supported as informative timeframe for BTC pair.")

  # BTC 1D Indicators
  # ---------------------------------------------------------------------------------------------
  def btc_info_1d_indicators(self, btc_info_pair, btc_info_timeframe, metadata: dict) -> DataFrame:
    tik = time.perf_counter()
    btc_info_1d = self.dp.get_pair_dataframe(btc_info_pair, btc_info_timeframe)
    # Indicators
    # -----------------------------------------------------------------------------------------
    btc_info_1d["rsi_14"] = pta.rsi(btc_info_1d["close"], length=14)
    # btc_info_1d['pivot'], btc_info_1d['res1'], btc_info_1d['res2'], btc_info_1d['res3'], btc_info_1d['sup1'], btc_info_1d['sup2'], btc_info_1d['sup3'] = pivot_points(btc_info_1d, mode='fibonacci')

    # Add prefix
    # -----------------------------------------------------------------------------------------
    ignore_columns = ["date"]
    btc_info_1d.rename(columns=lambda s: f"btc_{s}" if s not in ignore_columns else s, inplace=True)

    tok = time.perf_counter()
    log.debug(f"[{metadata['pair']}] btc_info_1d_indicators took: {tok - tik:0.4f} seconds.")

    return btc_info_1d

  # BTC 4h Indicators
  # ---------------------------------------------------------------------------------------------
  def btc_info_4h_indicators(self, btc_info_pair, btc_info_timeframe, metadata: dict) -> DataFrame:
    tik = time.perf_counter()
    btc_info_4h = self.dp.get_pair_dataframe(btc_info_pair, btc_info_timeframe)
    # Indicators
    # -----------------------------------------------------------------------------------------
    # RSI
    btc_info_4h["rsi_14"] = pta.rsi(btc_info_4h["close"], length=14)

    # SMA
    btc_info_4h["sma_200"] = ta.SMA(btc_info_4h, timeperiod=200)

    # Bull market or not
    btc_info_4h["is_bull"] = btc_info_4h["close"] > btc_info_4h["sma_200"]

    # Add prefix
    # -----------------------------------------------------------------------------------------
    ignore_columns = ["date"]
    btc_info_4h.rename(columns=lambda s: f"btc_{s}" if s not in ignore_columns else s, inplace=True)

    tok = time.perf_counter()
    log.debug(f"[{metadata['pair']}] btc_info_4h_indicators took: {tok - tik:0.4f} seconds.")

    return btc_info_4h

  # BTC 1h Indicators
  # ---------------------------------------------------------------------------------------------
  def btc_info_1h_indicators(self, btc_info_pair, btc_info_timeframe, metadata: dict) -> DataFrame:
    tik = time.perf_counter()
    btc_info_1h = self.dp.get_pair_dataframe(btc_info_pair, btc_info_timeframe)
    # Indicators
    # -----------------------------------------------------------------------------------------
    # RSI
    btc_info_1h["rsi_14"] = pta.rsi(btc_info_1h["close"], length=14)

    btc_info_1h["not_downtrend"] = (btc_info_1h["close"] > btc_info_1h["close"].shift(2)) | (
      btc_info_1h["rsi_14"] > 50.0
    )

    # Add prefix
    # -----------------------------------------------------------------------------------------
    ignore_columns = ["date"]
    btc_info_1h.rename(columns=lambda s: f"btc_{s}" if s not in ignore_columns else s, inplace=True)

    tok = time.perf_counter()
    log.debug(f"[{metadata['pair']}] btc_info_1h_indicators took: {tok - tik:0.4f} seconds.")

    return btc_info_1h

  # BTC 15m Indicators
  # ---------------------------------------------------------------------------------------------
  def btc_info_15m_indicators(self, btc_info_pair, btc_info_timeframe, metadata: dict) -> DataFrame:
    tik = time.perf_counter()
    btc_info_15m = self.dp.get_pair_dataframe(btc_info_pair, btc_info_timeframe)
    # Indicators
    # -----------------------------------------------------------------------------------------
    btc_info_15m["rsi_14"] = pta.rsi(btc_info_15m["close"], length=14)

    # Add prefix
    # -----------------------------------------------------------------------------------------
    ignore_columns = ["date"]
    btc_info_15m.rename(columns=lambda s: f"btc_{s}" if s not in ignore_columns else s, inplace=True)

    tok = time.perf_counter()
    log.debug(f"[{metadata['pair']}] btc_info_15m_indicators took: {tok - tik:0.4f} seconds.")

    return btc_info_15m

  # BTC 5m Indicators
  # ---------------------------------------------------------------------------------------------
  def btc_info_5m_indicators(self, btc_info_pair, btc_info_timeframe, metadata: dict) -> DataFrame:
    tik = time.perf_counter()
    btc_info_5m = self.dp.get_pair_dataframe(btc_info_pair, btc_info_timeframe)
    # Indicators
    # -----------------------------------------------------------------------------------------

    # RSI
    btc_info_5m["rsi_14"] = pta.rsi(btc_info_5m["close"], length=14)

    # Close max
    btc_info_5m["close_max_24"] = btc_info_5m["close"].rolling(24).max()
    btc_info_5m["close_max_72"] = btc_info_5m["close"].rolling(72).max()

    btc_info_5m["pct_close_max_24"] = (btc_info_5m["close_max_24"] - btc_info_5m["close"]) / btc_info_5m["close"]
    btc_info_5m["pct_close_max_72"] = (btc_info_5m["close_max_72"] - btc_info_5m["close"]) / btc_info_5m["close"]

    # Close min
    btc_info_5m["close_min_24"] = btc_info_5m["close"].rolling(24).min()
    btc_info_5m["close_min_72"] = btc_info_5m["close"].rolling(72).min()

    btc_info_5m["pct_close_min_24"] = (btc_info_5m["close_min_24"] - btc_info_5m["close"]) / btc_info_5m["close"]
    btc_info_5m["pct_close_min_72"] = (btc_info_5m["close_min_72"] - btc_info_5m["close"]) / btc_info_5m["close"]

    # Add prefix
    # -----------------------------------------------------------------------------------------
    ignore_columns = ["date"]
    btc_info_5m.rename(columns=lambda s: f"btc_{s}" if s not in ignore_columns else s, inplace=True)

    tok = time.perf_counter()
    log.debug(f"[{metadata['pair']}] btc_info_5m_indicators took: {tok - tik:0.4f} seconds.")

    return btc_info_5m

  # BTC Indicator Switch Case
  # ---------------------------------------------------------------------------------------------
  def btc_info_switcher(self, btc_info_pair, btc_info_timeframe, metadata: dict) -> DataFrame:
    if btc_info_timeframe == "1d":
      return self.btc_info_1d_indicators(btc_info_pair, btc_info_timeframe, metadata)
    elif btc_info_timeframe == "4h":
      return self.btc_info_4h_indicators(btc_info_pair, btc_info_timeframe, metadata)
    elif btc_info_timeframe == "1h":
      return self.btc_info_1h_indicators(btc_info_pair, btc_info_timeframe, metadata)
    elif btc_info_timeframe == "15m":
      return self.btc_info_15m_indicators(btc_info_pair, btc_info_timeframe, metadata)
    elif btc_info_timeframe == "5m":
      return self.btc_info_5m_indicators(btc_info_pair, btc_info_timeframe, metadata)
    else:
      raise RuntimeError(f"{btc_info_timeframe} not supported as informative timeframe for BTC pair.")

  # Populate Indicators
  # ---------------------------------------------------------------------------------------------
  def populate_indicators(self, df: DataFrame, metadata: dict) -> DataFrame:
    tik = time.perf_counter()
    """
        --> BTC informative indicators
        ___________________________________________________________________________________________
        """
    if self.config["stake_currency"] in [
      "USDT",
      "BUSD",
      "USDC",
      "DAI",
      "TUSD",
      "FDUSD",
      "PAX",
      "USD",
      "EUR",
      "GBP",
      "TRY",
    ]:
      if ("trading_mode" in self.config) and (self.config["trading_mode"] in ["futures", "margin"]):
        btc_info_pair = f"BTC/{self.config['stake_currency']}:{self.config['stake_currency']}"
      else:
        btc_info_pair = f"BTC/{self.config['stake_currency']}"
    else:
      if ("trading_mode" in self.config) and (self.config["trading_mode"] in ["futures", "margin"]):
        btc_info_pair = "BTC/USDT:USDT"
      else:
        btc_info_pair = "BTC/USDT"

    for btc_info_timeframe in self.btc_info_timeframes:
      btc_informative = self.btc_info_switcher(btc_info_pair, btc_info_timeframe, metadata)
      df = merge_informative_pair(df, btc_informative, self.timeframe, btc_info_timeframe, ffill=True)
      # Customize what we drop - in case we need to maintain some BTC informative ohlcv data
      # Default drop all
      drop_columns = {
        "1d": [f"btc_{s}_{btc_info_timeframe}" for s in ["date", "open", "high", "low", "close", "volume"]],
        "4h": [f"btc_{s}_{btc_info_timeframe}" for s in ["date", "open", "high", "low", "close", "volume"]],
        "1h": [f"btc_{s}_{btc_info_timeframe}" for s in ["date", "open", "high", "low", "close", "volume"]],
        "15m": [f"btc_{s}_{btc_info_timeframe}" for s in ["date", "open", "high", "low", "close", "volume"]],
        "5m": [f"btc_{s}_{btc_info_timeframe}" for s in ["date", "open", "high", "low", "close", "volume"]],
      }.get(
        btc_info_timeframe,
        [f"{s}_{btc_info_timeframe}" for s in ["date", "open", "high", "low", "close", "volume"]],
      )
      drop_columns.append(f"date_{btc_info_timeframe}")
      df.drop(columns=df.columns.intersection(drop_columns), inplace=True)

    """
        --> Indicators on informative timeframes
        ___________________________________________________________________________________________
        """
    for info_timeframe in self.info_timeframes:
      info_indicators = self.info_switcher(metadata, info_timeframe)
      df = merge_informative_pair(df, info_indicators, self.timeframe, info_timeframe, ffill=True)
      # Customize what we drop - in case we need to maintain some informative timeframe ohlcv data
      # Default drop all except base timeframe ohlcv data
      drop_columns = {
        "1d": [f"{s}_{info_timeframe}" for s in ["date", "open", "high", "low", "close", "volume"]],
        "4h": [f"{s}_{info_timeframe}" for s in ["date", "open", "high", "low", "close", "volume"]],
        "1h": [f"{s}_{info_timeframe}" for s in ["date", "open", "high", "low", "close", "volume"]],
        "15m": [f"{s}_{info_timeframe}" for s in ["date", "high", "low", "volume"]],
      }.get(info_timeframe, [f"{s}_{info_timeframe}" for s in ["date", "open", "high", "low", "close", "volume"]])
      df.drop(columns=df.columns.intersection(drop_columns), inplace=True)

    """
        --> The indicators for the base timeframe  (5m)
        ___________________________________________________________________________________________
        """
    df = self.base_tf_5m_indicators(metadata, df)

    df["zlma_50_1h"] = df["zlma_50_1h"].astype(np.float64).replace(to_replace=[np.nan, None], value=(0.0))
    df["zlma_50_4h"] = df["zlma_50_4h"].astype(np.float64).replace(to_replace=[np.nan, None], value=(0.0))
    df["cti_20_1d"] = df["cti_20_1d"].astype(np.float64).replace(to_replace=[np.nan, None], value=(0.0))
    df["r_480_1h"] = df["r_480_1h"].astype(np.float64).replace(to_replace=[np.nan, None], value=(-50.0))
    df["r_480_4h"] = df["r_480_4h"].astype(np.float64).replace(to_replace=[np.nan, None], value=(-50.0))
    df["rsi_14_1h"] = df["rsi_14_1h"].astype(np.float64).replace(to_replace=[np.nan, None], value=(50.0))
    df["rsi_14_4h"] = df["rsi_14_4h"].astype(np.float64).replace(to_replace=[np.nan, None], value=(50.0))
    df["rsi_14_1d"] = df["rsi_14_1d"].astype(np.float64).replace(to_replace=[np.nan, None], value=(50.0))

    # Global protections
    df["protections_long_global"] = (
      # current 4h red with top wick, previous 4h red, 4h overbought
      (
        (df["change_pct_4h"] > -0.04)
        | (df["top_wick_pct_4h"] < 0.04)
        | (df["change_pct_4h"].shift(48) > -0.04)
        | (df["cti_20_4h"] < 0.8)
      )
      &
      # current 1h red, current 4h green, 4h overbought
      (
        (df["change_pct_1h"] > -0.04)
        | (df["change_pct_4h"] < 0.08)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 70.0)
      )
      &
      # current 4h red, previous 4h green, 4h overbought
      (
        (df["change_pct_4h"] > -0.04)
        | (df["change_pct_4h"].shift(48) < 0.04)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 70.0)
      )
      &
      # current 4h red, previous 4h red, 2nd previous 4h long green, 4h overbought
      (
        (df["change_pct_4h"] > -0.04)
        | (df["change_pct_4h"].shift(48) > -0.04)
        | (df["change_pct_4h"].shift(96) < 0.16)
        | (df["cti_20_4h"] < 0.5)
      )
      &
      # current 4h red, overbought 4h, sudden rise 4h (and now coming down)
      (
        (df["change_pct_4h"] > -0.01)
        | (df["rsi_14_max_6_4h"] < 80.0)
        | (df["cti_20_4h"] < 0.5)
        | (((df["ema_12_4h"] - df["ema_26_4h"]) / df["ema_26_4h"]) < 0.08)
      )
      # current 4h red, previous 4h green with top wick, 4h overbought
      & (
        (df["change_pct_4h"] > -0.01)
        | (df["change_pct_4h"].shift(48) < 0.08)
        | (df["top_wick_pct_4h"].shift(48) < 0.08)
        | (df["cti_20_4h"] < 0.5)
      )
      # current 4h long red, previous 4h red, 2nd previous 4h long green, 4h overbought
      & (
        (df["change_pct_4h"] > -0.08)
        | (df["change_pct_4h"].shift(48) > -0.01)
        | (df["change_pct_4h"].shift(96) < 0.08)
        | (df["cti_20_4h"] < 0.5)
      )
      # current 1h red, current 4h long green with top wick, 1h overbought
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["change_pct_4h"] < 0.08)
        | (df["top_wick_pct_4h"] < 0.04)
        | (df["cti_20_1h"] < 0.7)
      )
      # current 1h red, 1h overbought, 1d overbought, 1h descending
      & (
        (df["change_pct_1h"] > -0.04)
        | (df["cti_20_1h"] < 0.7)
        | (df["cti_20_1d"] < 0.8)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 1h overbought, 1d overbought, 1h descending
      & (
        (df["rsi_14_1h"] < 70.0)
        | (df["cti_20_1h"] < 0.7)
        | (df["cti_20_1d"] < 0.8)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 1d green, 4h overbought, 4h descending
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["rsi_14_4h"] < 70.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 4h red, previous 4h green, 1d overbought
      & (
        (df["change_pct_4h"] > -0.04)
        | (df["change_pct_4h"].shift(48) < 0.04)
        | (df["rsi_14_1d"] < 70.0)
        | (df["cti_20_1d"] < 0.5)
      )
      # 1h overbought, 4h overbought, 1d overbought
      & ((df["r_480_1h"] < -20.0) | (df["r_480_4h"] < -20.0) | (df["rsi_14_1d"] < 80.0) | (df["cti_20_1d"] < 0.85))
      # current 4h red, previous 4h red, 2nd previous 4h green with top wick, 4h overbought
      & (
        (df["change_pct_4h"] > -0.0)
        | (df["change_pct_4h"].shift(48) > -0.0)
        | (df["change_pct_4h"].shift(96) < 0.06)
        | (df["top_wick_pct_4h"].shift(96) < 0.06)
        | (df["cti_20_4h"] < 0.7)
      )
      # current 4h red, previous 4h red, 2nd previous 4h green, 4h overbought
      & (
        (df["change_pct_4h"] > -0.0)
        | (df["change_pct_4h"].shift(48) > -0.0)
        | (df["change_pct_4h"].shift(96) < 0.06)
        | (df["not_downtrend_1h"])
        | (df["cti_20_4h"] < 0.5)
      )
      # current 1d green with top wick, current & previous 4h red, 4h overbought
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["change_pct_4h"] > -0.0)
        | (df["change_pct_4h"].shift(48) > -0.0)
        | (df["cti_20_4h"] < 0.7)
      )
      # current 1h red, 1h downtrend, 15m move down, 1h move down, 1h downtrend, 4h downtrend
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_3_1h"] > 16.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 4h downtrend, 4h move down, 1d overbought
      & (
        (df["is_downtrend_3_4h"] == False)
        | (df["not_downtrend_4h"])
        | (df["rsi_3_4h"] > 16.0)
        | (df["cti_20_1d"] < 0.7)
      )
      # 4h red with top wick, 1h downtrend, 1d overbought
      & (
        (df["change_pct_4h"] > -0.04)
        | (df["top_wick_pct_4h"] < 0.04)
        | (df["is_downtrend_3_1h"] == False)
        | (df["rsi_14_1d"] < 70.0)
      )
      # current 1h red, previous 1h red, 4h overbought
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["change_pct_1h"].shift(12) > -0.01)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_max_6_4h"] < 70.0)
      )
      # current 1d long green, current 4h red, 1h high, 4h high, 1h downtrend, 4h downtrend
      & (
        (df["change_pct_1d"] < 0.16)
        | (df["change_pct_4h"] > -0.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 4h red, previous 4h red, 2nd previous 4h green with top wick, 4h overbought
      & (
        (df["change_pct_4h"] > -0.01)
        | (df["change_pct_4h"].shift(48) > -0.01)
        | (df["change_pct_4h"].shift(96) < 0.04)
        | (df["top_wick_pct_4h"].shift(96) < 0.04)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_max_6_4h"] < 70.0)
      )
      # 5m & 15m strond down move, 1h & 4h still high, 4h & 1d downtrend
      & (
        (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 10.0)
        | (df["cti_20_15m"] < -0.8)
        | (df["cti_20_1h"] < -0.0)
        | (df["cti_20_4h"] < -0.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 15m downtrend, 5m & 15m strong down move, 1h & 4h downtrend
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_3"] > 4.0)
        | (df["rsi_3_15m"] > 4.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 4h strong down move, 1h & 4h downtrend
      & ((df["rsi_3_4h"] > 4.0) | (df["ema_200_dec_48_1h"] == False) | (df["ema_200_dec_24_4h"] == False))
      # 1h downtrend, 1h strong down move, 1d overbought
      & ((df["not_downtrend_1h"]) | (df["rsi_3_1h"] > 10.0) | (df["rsi_14_1d"] < 70.0) | (df["cti_20_1d"] < 0.8))
      # 15m strong down move, 15m still dropping, 5m & 15m & 4h & 1d downtrend
      & (
        (df["rsi_3_15m"] > 8.0)
        | (df["cti_20_15m"] < -0.8)
        | (df["ema_200_dec_24"] == False)
        | (df["ema_200_dec_24_15m"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 4h downtrend, 15m still dropping, 1h & 4h down move, 5m & 15m & 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["cti_20_15m"] < -0.7)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_3_4h"] > 26.0)
        | (df["ema_200_dec_24"] == False)
        | (df["ema_200_dec_24_15m"] == False)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 15m & 1h & 4h downtrend, 5m & 15m strong down move, 1h & 4h still dropping, 5m & 15m & 1h downtrend
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_14_15m"] < 20.0)
        | (df["cti_20_1h"] < -0.8)
        | (df["cti_20_4h"] < -0.8)
        | (df["ema_200_dec_24"] == False)
        | (df["ema_200_dec_24_15m"] == False)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 4h long top wick, current 1h red, 15m down move, 1h & 4h still high
      & (
        (df["top_wick_pct_4h"] < 0.08)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_3_15m"] > 16.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["cti_20_4h"] < -0.0)
      )
      # 1h down move, 1h & 4h still high, 5m downtrend
      & (
        (df["rsi_3_1h"] > 16.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 70.0)
        | (df["ema_200_dec_24"] == False)
      )
      # current 4h red, 1h & 4h still high, 1d overbought, 4h overbought
      & (
        (df["change_pct_4h"] > -0.01)
        | (df["cti_20_1h"] < -0.5)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_1d"] < 70.0)
        | (df["rsi_14_max_3_4h"] < 70.0)
      )
      # current 1d long green, current 1h red, 1h still not low enough, 4h high
      & (
        (df["change_pct_1d"] < 0.16)
        | (df["change_pct_1h"] > -0.0)
        | (df["cti_20_1h"] < -0.8)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_max_3_4h"] < 70.0)
      )
      # current 1d red, 1h & 4h downtrend, 15m & 1h & 4h down move, 4h still dropping, 1d high
      & (
        (df["change_pct_1d"] > -0.06)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["cti_20_4h"] < -0.8)
        | (df["rsi_3_4h"] > 26.0)
        | (df["cti_20_1d"] < 0.5)
      )
      # current 4h long green, 1h downtrend, 15m down move, 1h still high
      & (
        (df["change_pct_4h"] < 0.08)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 16.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 15m & 1h downtrend, 15m & 1h strong down move, 15m & 1h downtrend
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 6.0)
        | (df["rsi_3_1h"] > 10.0)
        | (df["ema_200_dec_24_15m"] == False)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # currend 1d green, 4h & 1d overbought
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["cti_20_4h"] < 0.9)
        | (df["rsi_14_4h"] < 75.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 80.0)
      )
      # current 1d long red, previous 1d green, 1h & 4h downtrend, 5m & 15m & 1h downtrend
      & (
        (df["change_pct_1d"] > -0.16)
        | (df["change_pct_1d"].shift(288) < 0.08)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["ema_200_dec_24"] == False)
        | (df["ema_200_dec_24_15m"] == False)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 15m & 1h & 4h downtrend, 15m & 1h & 4h down move
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_15m"] > 6.0)
        | (df["rsi_14_15m"] > 10.0)
        | (df["rsi_3_1h"] > 10.0)
        | (df["rsi_3_4h"] > 20.0)
      )
      # current 5m strong down move, 1h & 1d high, 5m & 15m downtrend
      & (
        (df["rsi_3"] > 8.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["cti_20_1d"] < 0.9)
        | (df["ema_200_dec_24"] == False)
        | (df["ema_200_dec_24_15m"] == False)
      )
      # 15m & 1h downtrend, 4h high, 4h downtrend
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["cti_20_4h"] < 0.8)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 1h downtrend, 1h dropping, 4h still high, 5m & 15m downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["cti_20_1h"] < -0.8)
        | (df["rsi_3_1h"] > 10.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["ema_200_dec_24"] == False)
        | (df["ema_200_dec_24_15m"] == False)
      )
      # current 4h green with top wick, 15m still high, 4h overbought, 4h downtrend
      & (
        (df["change_pct_4h"] < 0.04)
        | (df["top_wick_pct_4h"] < 0.04)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 1d red, 1h downtrend, 15m down move, 4h down move & still high, 1d overbought
      & (
        (df["change_pct_1d"] > -0.06)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 10.0)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_3_4h"] > 26.0)
        | (df["cti_20_1d"] < 0.7)
      )
      # current 4h red, previous 4h green, 15m strong down move, 4h overbought
      & (
        (df["change_pct_4h"] > -0.01)
        | (df["change_pct_4h"].shift(48) < 0.01)
        | (df["rsi_3_15m"] > 6.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_max_3_4h"] < 70.0)
      )
      # current 1d green, 15m & 1h down move, 1d overbought
      & ((df["change_pct_1d"] < 0.08) | (df["rsi_3_15m"] > 6.0) | (df["rsi_3_1h"] > 20.0) | (df["cti_20_1d"] < 0.9))
      # 15m & 1h downtrend, 15m strong down move, 4h overbought
      & ((df["not_downtrend_15m"]) | (df["not_downtrend_1h"]) | (df["rsi_3_15m"] > 6.0) | (df["cti_20_4h"] < 0.8))
      # current 4h green with top wick, 15m down move, 4h overbought & high
      & (
        (df["change_pct_4h"] < 0.02)
        | (df["top_wick_pct_4h"] < 0.02)
        | (df["rsi_3_15m"] > 20.0)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_max_3_4h"] < 70.0)
      )
      # 15m & 1h & 4h downtrend, 15m strong down move
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_15m"] > 3.0)
        | (df["cti_20_1h"] < -0.7)
      )
      # 15m & 1h & 4h downtrend, 15m down move & still high, 1d overbought
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_15m"] < 26.0)
        | (df["cti_20_1d"] < 0.9)
      )
      # 15m downtrend, 5m & 15m downmove, 15m still high, 1d overbought
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_3"] > 4.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["cti_20_1d"] < 0.8)
      )
      # current 4h red, 1h downtrend, 4h overbought
      & (
        (df["change_pct_4h"] > -0.06)
        | (df["not_downtrend_1h"])
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_max_6_4h"] < 80.0)
      )
      # 15m & 1h downtrend, 15m & 1h downmove, 1d high, 1d downtrend
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 6.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 15m down move, 15m & 4h still high, 1d overbought, 5m & 15m downtrend, drop in last 48h
      & (
        (df["rsi_3_15m"] > 10.0)
        | (df["cti_20_15m"] < -0.5)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_1d"] < 65.0)
        | (df["ema_200_dec_24"] == False)
        | (df["ema_200_dec_24_15m"] == False)
        | (df["high_max_48_1h"] < (df["close"] * 1.24))
      )
      # 1h & 4h downtrend, 5m & 15m downmove
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 4.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 1d green with top wick, 15m downtrend, 1h & 1d still high
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["top_wick_pct_1d"] < 0.04)
        | (df["not_downtrend_15m"])
        | (df["rsi_3_15m"] > 16.0)
        | (df["cti_20_1h"] < 0.7)
        | (df["cti_20_1d"] < 0.7)
      )
      # current 1h long red, 1h downtrend, 4h still high, 4h & 1d downtrend
      & (
        (df["change_pct_1h"] > -0.08)
        | (df["not_downtrend_1h"])
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 40.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1d downtrend, 1h & 4h still low, 1d still high, drop in last 6 days
      & (
        (df["is_downtrend_3_1d"] == False)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["high_max_6_1d"] < (df["close"] * 1.5))
      )
      # 15m downtrend, 15m downmove, 1h & 4h & 1d still high
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
      )
      # current 4h red, previous 4h long green, 1h & 4h overbought
      & (
        (df["change_pct_4h"] > -0.01)
        | (df["change_pct_4h"].shift(48) < 0.08)
        | (df["cti_20_1h"] < 0.5)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_max_3_4h"] < 70.0)
      )
      # current 1d red, 1d & 4h downtrend, 15m & 1h & 4h downmove
      & (
        (df["change_pct_1d"] > -0.08)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_3_4h"] > 10.0)
      )
      # current 4h red with top wick, 1h downtrend, 15m & 1h downmove, 4h & 1d still high
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["top_wick_pct_4h"] < 0.02)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 6.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 50.0)
      )
      # current 1d green with top wick, 15m & 1h downtrend, 4h & 1d still high
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 60.0)
      )
      # current 15m & 1h downtrend, 4h overbought
      & ((df["not_downtrend_15m"]) | (df["not_downtrend_1h"]) | (df["cti_20_4h"] < 0.7) | (df["rsi_14_4h"] < 70.0))
      # current 1d red with top wick, previous 1d green with top wick, 1h & 4h & 1d still high, pump in last 6 days
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["top_wick_pct_1d"] < 0.04)
        | (df["change_pct_1d"].shift(288) < 0.04)
        | (df["top_wick_pct_1d"].shift(288) < 0.04)
        | (df["cti_20_1h"] < -0.0)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["hl_pct_change_6_1d"] < 0.5)
      )
      # 15m downtrend, 5m & 15m downmove, 1h & 4h downtrend, drop in last 6 days
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["cti_20_1h"] < -0.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["high_max_6_1d"] < (df["close"] * 1.5))
      )
      # 15m downtrend, 15m stil high, 1d overbought
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < -0.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 50.0)
      )
      # 15m downtrend, 15m stil high, 15m downmove, 1h & 4h overbought
      & (
        (df["not_downtrend_15m"])
        | (df["cti_20_15m"] < -0.5)
        | (df["rsi_3_15m"] > 6.0)
        | (df["cti_20_1h"] < 0.7)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
      )
      # current 1d red, 1h downtrend, 15m downmove, 1h & 4h downtrend
      & (
        (df["change_pct_1d"] > -0.12)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 16.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 1d green with top wick, current 4h red, 1h downtrend, 4h & 1d overbought
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["change_pct_4h"] > -0.0)
        | (df["not_downtrend_1h"])
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 50.0)
      )
      # current 1d green with top witck, current 4h red, 4h overbought
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["change_pct_4h"] > -0.01)
        | (df["rsi_14_max_3_4h"] < 70.0)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 1d green with top wick, 15m downtrend, 15m downmove, 4h overbought
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["not_downtrend_15m"])
        | (df["rsi_3_15m"] > 16.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 50.0)
      )
      # 1h & 4h downtrend, 15m downmove, 4h * 1d still high, 1h downtrend, drop in last 48 hours
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_15m"] > 20.0)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < -0.5)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["high_max_48_4h"] < (df["close"] * 1.4))
      )
      # current 1d long green, current 4h red, 1h downtrend, 4h & 1d overbought
      & (
        (df["change_pct_1d"] < 0.16)
        | (df["change_pct_4h"] > -0.04)
        | (df["not_downtrend_1h"])
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 70.0)
      )
      # current 1d green with top wick, current 4h green, 15m & 1h & 4h still high
      & (
        (df["change_pct_1d"] < 0.06)
        | (df["top_wick_pct_1d"] < 0.06)
        | (df["change_pct_4h"] < 0.04)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < -0.7)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_4h"] < 40.0)
      )
      # current 1d red, 1h downtrend, 15m downmove, 1h & 1d still high
      & (
        (df["change_pct_1d"] > -0.08)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 20.0)
        | (df["cti_20_1h"] < 0.25)
        | (df["cti_20_1d"] < -0.5)
        | (df["rsi_14_1d"] < 40.0)
      )
      # 1h downtrend, 15m & 1h downmove, 4h & 1d still high, 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_3_1h"] > 10.0)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < -0.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 4h downtrend, 5m & 15m & 1h & 4h downmove, 4h still high
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_3_4h"] > 20.0)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 30.0)
      )
      # 1h downtrend, 1h donwmove, 4h still high, 1d overbought
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 10.0)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 70.0)
      )
      # 1h downtrend, 1d still high, strong pump in last 6 days
      & ((df["not_downtrend_1h"]) | (df["cti_20_1d"] < 0.5) | (df["hl_pct_change_6_1d"] < 3.0))
      # current 5m red, 1h & 4h downtrend, 15m still high, 5m & 1h & 4h downmove, 1h downtrend
      & (
        (df["change_pct"] > -0.02)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_3_4h"] > 20.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 1d red, 1h downtrend, 15m & 1h & 4h still high
      & (
        (df["change_pct_1d"] > -0.08)
        | (df["not_downtrend_1h"])
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
      )
      # current 1d red with top wick, previous 1d red, 14m downmove, 1h & 1d still high, pump in last 6 days
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["top_wick_pct_1d"] < 0.04)
        | (df["change_pct_1d"].shift(288) > -0.04)
        | (df["rsi_3_15m"] > 20.0)
        | (df["cti_20_1h"] < -0.7)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["hl_pct_change_6_1d"] < 0.5)
      )
      # current 1d red, 1h & 4h downtrend, 5m downmove, 15m still high, 4h downmove
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 20.0)
        | (df["cti_20_15m"] < -0.8)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_3_4h"] > 20.0)
      )
      # current 4h red, 1h downtrend, 4m downmove, 15m & 1h & 4h * 1d still high, drop in last 6 days
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 30.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["high_max_6_1d"] < (df["close"] * 1.5))
      )
      # current 1d long red, 5m downmove, 1h & 4h downtrend, drops in last 6 days
      & (
        (df["change_pct_1d"] > -0.12)
        | (df["rsi_3"] > 20.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["high_max_6_1d"] < (df["close"] * 1.7))
      )
      # current 1d red, previous 1d long green, 4h overbought, 1d still high, pump in last 6 days
      & (
        (df["change_pct_1d"] > -0.01)
        | (df["change_pct_1d"].shift(288) < 0.12)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_max_3_4h"] < 70.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["hl_pct_change_6_1d"] < 0.5)
      )
      # current 1d red, 1h downtrend, 15m & 1d still high, 1h downtrend
      & (
        (df["change_pct_1d"] > -0.12)
        | (df["not_downtrend_1h"])
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 4h red, 1h & 4h downtrend, 15m & 1h & 4h downmove, 1d still high
      & (
        (df["change_pct_4h"] > -0.04)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_15m"] > 6.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_3_4h"] > 20.0)
        | (df["rsi_14_1d"] < 50.0)
      )
      # current 1d red, previous 1d long green with long top wick, 1h donwtremd, 4h & 1d still high
      & (
        (df["change_pct_1d"] > -0.01)
        | (df["change_pct_1d"].shift(288) < 0.16)
        | (df["top_wick_pct_1d"].shift(288) < 0.16)
        | (df["not_downtrend_1h"])
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 40.0)
      )
      # current 1d long green with long top wick, 15m downmove, 1h & 4h & 1d still high
      & (
        (df["change_pct_1d"] < 0.16)
        | (df["top_wick_pct_1d"] < 0.16)
        | (df["rsi_3_15m"] > 10.0)
        | (df["cti_20_1h"] < -0.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 60.0)
      )
      # 5m & 15m downmove, 15m & 1h & 4h still high, 1h downtrend, drop in last 6 days
      & (
        (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["high_max_6_1d"] < (df["close"] * 1.5))
      )
      # current 1d green with top wick, 1h downtrend, 15m & 1h donwmove, 4h & 1d still high, 4h downtrend
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["top_wick_pct_1d"] < 0.04)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 1h & 4h downtrend, 1h still high, 1h & 4h donwmove, 1d still high, 1h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["cti_20_1h"] < -0.7)
        | (df["rsi_3_1h"] > 10.0)
        | (df["rsi_3_4h"] > 26.0)
        | (df["cti_20_1d"] < -0.5)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 15m downtrend, 15m strong downmove, 1h & 4h high
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_3_15m"] > 6.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 60.0)
      )
      # current 1d long red, 1h & 4h downtrend, 1h & 4h downmove
      & (
        (df["change_pct_1d"] > -0.12)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_3_4h"] > 16.0)
      )
      # current 1d red, 1d & 1h & 4h donwtrend, 5m downmove, 15m & 1d still high, 1h downtrend
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["is_downtrend_3_1d"] == False)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 26.0)
        | (df["rsi_14_15m"] < 26.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 1d green with top wick, 1h & 4h & 1d still high, drop in last 6 days
      & (
        (df["change_pct_1d"] < 0.06)
        | (df["top_wick_pct_1d"] < 0.06)
        | (df["cti_20_1h"] < -0.5)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["high_max_6_1d"] < (df["close"] * 1.5))
      )
      # 15m & 1h & 4h downtrend, 15m & 1h & 4h downmove, 4h & 1d downtrend
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_3_1h"] > 10.0)
        | (df["rsi_3_4h"] > 20.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 15m downtrend, 15m downmove, 1h & 4h high
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_3_15m"] > 10.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
      )
      # current 5m red, 5m strong downmove
      & ((df["change_pct"] > -0.03) | (df["rsi_3"] > 4.0))
      # current 4h red, previous 4h green, 1h & 4h high, 4h downtrend
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["change_pct_4h"].shift(48) < 0.02)
        | (df["cti_20_1h"] < 0.5)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 1h red, 5m & 15 & 1h still high, 4h overbought, 4h downtrend
      & (
        (df["change_pct_1h"] > -0.0)
        | (df["rsi_14"] < 36.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < -0.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 65.0)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 1d long green with long top wick, 4h red, 1h & 4h downtrend, 4h still high
      & (
        (df["change_pct_1d"] < 0.16)
        | (df["top_wick_pct_1d"] < 0.16)
        | (df["change_pct_4h"] > -0.04)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["cti_20_4h"] < -0.0)
      )
      # current 4h red with top wick, 1h downtrend, 15m downmove, 1h & 4h still high
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["top_wick_pct_4h"] < 0.06)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 10.0)
        | (df["cti_20_1h"] < -0.0)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_4h"] < 40.0)
      )
      # 5m downmove, 15m & 1h & 4h still high, drop in last 24 hours
      & (
        (df["rsi_3"] > 6.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < -0.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["high_max_24_1h"] < (df["close"] * 1.26))
      )
      # 5m & 15m downmove, 15m & 1h & 4h & 1d high
      & (
        (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
      )
      # 1d very low, chance not finished drop, 1h & 4h & 1d downtrend
      & (
        (df["cti_20_1d"] > -0.95)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d green, previous 1d red with top wick, 1h & 4h & 1d still high
      & (
        (df["change_pct_1d"] < 0.06)
        | (df["change_pct_1d"].shift(288) > -0.04)
        | (df["top_wick_pct_1d"].shift(288) < 0.08)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
      )
      # 5m downmove, 4h & 1d overbought, pump in last 6 days
      & (
        (df["rsi_3"] > 10.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 60.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 70.0)
        | (df["hl_pct_change_6_1d"] < 0.5)
      )
      # current 4h red, current 1h red, 15m downmove, 1h & 4h & 1d still high:w
      & (
        (df["change_pct_4h"] > -0.03)
        | (df["change_pct_1h"] > -0.03)
        | (df["rsi_3_15m"] > 16.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
      )
      # current 1d long green, current 4h red, 1h downtrend, 15m downmove, 4h & 1d overbought
      & (
        (df["change_pct_1d"] < 0.16)
        | (df["change_pct_4h"] > -0.02)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 16.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
      )
      # 1h downtred, 5m strong downmove, 15m & 4h & 1d stil high
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 5.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 50.0)
      )
      # 4h & 1h downtrend, 15m downmove, 1d overbought
      & (
        (df["is_downtrend_3_4h"] == False)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 16.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 50.0)
      )
      # current 4h red, current 1h red, 15m downmove, 1h & 4h still high
      & (
        (df["change_pct_4h"] > -0.0)
        | (df["change_pct_1h"] > -0.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
      )
      # current 1d long top wick, current 4h red, current 1h red, 15m downmove, 1h & 4h still high, 1d overbought
      & (
        (df["top_wick_pct_1d"] < 0.16)
        | (df["change_pct_4h"] > -0.0)
        | (df["change_pct_1h"] > -0.0)
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 60.0)
      )
      # 15m downmove, 5m & 15m & 1h & 4h & 1d still high. 1h downtrend
      & (
        (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14"] < 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < -0.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 1d green with top wick, current 4h red, 3 previous 4h green, 1h & 4h & 1d still high
      & (
        (df["change_pct_1d"] < 0.06)
        | (df["top_wick_pct_1d"] < 0.06)
        | (df["change_pct_4h"] > -0.01)
        | (df["change_pct_4h"].shift(48) < 0.01)
        | (df["change_pct_4h"].shift(96) < 0.01)
        | (df["change_pct_4h"].shift(144) < 0.01)
        | (df["cti_20_1h"] < -0.5)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
      )
      # current 1d green with top wick, 1h downtrend, 15m & 1h downmove, 1h  4h still high, 4h & 1d downtrend
      & (
        (df["change_pct_1d"] < 0.06)
        | (df["top_wick_pct_1d"] < 0.06)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["cti_20_1h"] < -0.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 4h downtrend, 5m & 4h downmove, 1h & 4h downtrend
      & (
        (df["not_downtrend_4h"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_4h"] > 10.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 15m & 1h downtrend, 4h overbought
      & ((df["not_downtrend_15m"]) | (df["not_downtrend_1h"]) | (df["cti_20_4h"] < 0.8) | (df["rsi_14_4h"] < 50.0))
      # 1h downtrend, 15m downmove, 4h overbought
      & ((df["not_downtrend_1h"]) | (df["rsi_3_15m"] > 26.0) | (df["cti_20_4h"] < 0.8) | (df["rsi_14_4h"] < 50.0))
      # current 1d long green, 1h & 4h & 1d overbought
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["rsi_14_1h"] < 65.0)
        | (df["rsi_14_4h"] < 65.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
      )
      # current 4h long green with long top wick, 4h overbought, pump in last 24h
      & (
        (df["change_pct_4h"] < 0.1)
        | (df["top_wick_pct_4h"] < 0.1)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 60.0)
        | (df["hl_pct_change_24_1h"] < 0.7)
      )
      # 15m & 1h & 4h high, drop in last 2 hours
      & (
        (df["cti_20_15m"] < -0.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["close_max_24"] < (df["close"] * 1.08))
      )
      # current 4h red, 1h downtrend, 4h overbought
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["not_downtrend_1h"])
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
      )
      # 1h downtrend, 5m & 15m strong downmove, 4h & 1d still high
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 60.0)
      )
      # current 4h long red, 1h & 4h downtrend, 1h & 4h downmove, 4h downtrend
      & (
        (df["change_pct_4h"] > -0.08)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_3_4h"] > 26.0)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 1d green, 15m downmove, 1h & 4h still high, 1d overbought
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 60.0)
      )
      # 4h downtrend, 15m & 1h & 4h still high, 1h & 4h downtrend, drop in last 2 hours
      & (
        (df["not_downtrend_4h"])
        | (df["rsi_14_15m"] < 46.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["close_max_24"] < (df["close"] * 1.08))
      )
      # 15m & 4h downtrend, 4h strong down move, 4h very low, 1h & 4h downtrend
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_4h"] > 16.0)
        | (df["r_480_4h"] > -95.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 1d long green, current 4h red, previous 4h red, 1h downtrend, 4h still high, 4h downtrend
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["change_pct_4h"] > -0.02)
        | (df["change_pct_4h"].shift(48) > -0.02)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 10.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 1h downtrend, 15m & 1h downmove, 4h still high, 1d overbought
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 6.0)
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
      )
      # 5m & 15m downmove, 4h overbought, 1d still high
      & ((df["rsi_3"] > 20.0) | (df["rsi_3_15m"] > 6.0) | (df["rsi_14_4h"] < 65.0) | (df["rsi_14_1d"] < 50.0))
      # 1h downtrend, 15m & 1h downmove, 4h high
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 60.0)
      )
      # current 4h red, 1h downtrend, 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_1h"] > -0.04)
        | (df["not_downtrend_1h"])
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
      )
      # 15m & 1h & 4h downtrend, 5m & 4h strong downmove, 4h downtrend
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_4h"] > 16.0)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 4h red, 4h downtrend, 15m & 4h downmove, 1d overbought
      & (
        (df["change_pct_4h"] > -0.04)
        | (df["not_downtrend_4h"])
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_3_4h"] > 20.0)
        | (df["cti_20_1d"] < 0.7)
      )
      # current 5m long red or green 4h downtrend, 1h still high, 1h downtrend
      & (
        (abs(df["change_pct"]) < 0.05)
        | (df["not_downtrend_4h"])
        | (df["cti_20_1h"] < -0.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 1d long green, current 1h red, 1h still high, 1h downmove, 1h still high
      & (
        (df["change_pct_1d"] < 0.26)
        | (df["change_pct_1h"] > -0.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
      )
      # current 1d long greem, 1h downtrend, 1h downmove, 1d still high
      & ((df["change_pct_1d"] < 0.26) | (df["not_downtrend_1h"]) | (df["rsi_3_1h"] > 10.0) | (df["cti_20_1d"] < 0.5))
      # current 5m red, current 4h red, 1h downtrend, 5m downmove, 1h still high, 1h downtrend
      & (
        (df["change_pct_4h"] > -0.024)
        | (df["change_pct_4h"] > -0.0)
        | (df["is_downtrend_3_1h"] == False)
        | (df["rsi_3"] > 16.0)
        | (df["cti_20_1h"] < 0.8)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 1d red, 15m & 1h downtrend, 15m strong downmove, 1d still high, 1h downtrend
      & (
        (df["change_pct_1d"] > -0.08)
        | (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 6.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 4h green with long top wick, 1h still not low enough, 4h & 1d overbought
      & (
        (df["change_pct_4h"] < 0.01)
        | (df["top_wick_pct_4h"] < 0.08)
        | (df["cti_20_1h"] < -0.7)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_1d"] < 60.0)
      )
      # current 1d green with top wick, current 4h green with top wick, 15m & 1h downmove, 4h overbought
      & (
        (df["change_pct_1d"] < 0.06)
        | (df["top_wick_pct_1d"] < 0.06)
        | (df["change_pct_4h"] < 0.02)
        | (df["top_wick_pct_4h"] < 0.02)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
      )
      # 15m downmove, 4h & 1d overbought, 1d downtrend
      & (
        (df["rsi_3_15m"] > 20.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 70.0)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 4h red, current 1h red, 1h & 4h downtrend, 1h & 4h downmove, 1h & 4h still not low enough
      & (
        (df["change_pct_4h"] > -0.04)
        | (df["change_pct_1h"] > -0.04)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_1h"] > 10.0)
        | (df["rsi_3_4h"] > 26.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["rsi_14_4h"] < 36.0)
      )
      # current 1d red, 1h downtrend, 5m & 1h downmove, 4 h stil high, 1d overbought
      & (
        (df["change_pct_1d"] > -0.02)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 60.0)
      )
      # current 4h red, current 1h red, 1h & 4h downtrend, 1h & 4h strong downmove
      & (
        (df["change_pct_4h"] > -0.06)
        | (df["change_pct_1h"] > -0.03)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_1h"] > 6.0)
        | (df["rsi_3_4h"] > 10.0)
      )
      # current 1d long red, 1h & 4h downtrend, 15m still high, 1h & 4h downmove, 1d high
      & (
        (df["change_pct_1d"] > -0.12)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
      )
      # 1h & 4h downtrend, 15m downmove, 15m still higher, 1h downtrend, drop in last 6 days
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["high_max_6_1d"] < (df["close"] * 1.7))
      )
      # current 4h red with top wick, 1h & 4h downtrend, 5m downmove, 1h & 4h still high
      & (
        (df["change_pct_4h"] > -0.03)
        | (df["top_wick_pct_4h"] < 0.03)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 16.0)
        | (df["cti_20_1h"] < -0.8)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 40.0)
      )
      # 15m & 1h downtrend, 5m & 15m & 1h strong downmove
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 6.0)
        | (df["rsi_3_15m"] > 6.0)
        | (df["rsi_3_1h"] > 6.0)
      )
      # current 4h top wick, 15m & 1h still higher, 4h overbought
      & (
        (df["top_wick_pct_4h"] < 0.03)
        | (df["rsi_14_15m"] < 40.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < 0.9)
        | (df["rsi_14_4h"] < 70.0)
      )
      # current 1d long green, current 4h red, current 1h red, 1h downmove, 1h & 4h still high, 4h overbought
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["change_pct_4h"] > -0.03)
        | (df["change_pct_1h"] > -0.03)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
      )
      # 4h downtrend, 5m & 4h downmove, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_4h"])
        | (df["rsi_3_4h"] > 20.0)
        | (df["r_480_4h"] > -95.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 4h red, previous 4h green with top wick, 15m still high, 1h & 4h still high
      & (
        (df["change_pct_4h"] > -0.03)
        | (df["change_pct_4h"].shift(48) < 0.03)
        | (df["top_wick_pct_4h"].shift(48) < 0.03)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 50.0)
      )
      # current 1d green, 15m strong downmove, 1h & 4h still higher, 1d overbought
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 65.0)
      )
      # 1h downtrend, 5m & 15m & 1h downmove, 4h still high
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 6.0)
        | (df["rsi_3_15m"] > 6.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_14_4h"] < 46.0)
      )
      # current 1d red with top wick, 4h downtrend, 5m & 15m & 1h & 4h downmove, 15m & 1h & 4h still high
      & (
        (df["change_pct_1d"] > -0.03)
        | (df["top_wick_pct_1d"] < 0.03)
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_14_15m"] < 20.0)
        | (df["rsi_14_1h"] < 30.0)
        | (df["rsi_14_4h"] < 30.0)
      )
      # 5m downmove, 15m & 1h & 4h & 1d high
      & (
        (df["rsi_3"] > 16.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < 0.7)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 65.0)
        | (df["rsi_14_1d"] < 50.0)
      )
      # 1h downtrend, 5m & 15m & 1h downmove, 1d overbought
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["cti_20_1d"] < 0.85)
        | (df["rsi_14_1d"] < 60.0)
      )
      # current 1d green with top wick, 1h downmove, 1h still high, 4h & 1d overbought
      & (
        (df["change_pct_1d"] < 0.03)
        | (df["top_wick_pct_1d"] < 0.03)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 65.0)
        | (df["rsi_14_max_3_4h"] < 70.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 70.0)
      )
      # current 1d top wick, 4h downtrend, 15m downmove, 15m & 1h & 4h still high, 1d overbought
      & (
        (df["top_wick_pct_1d"] < 0.08)
        | (df["not_downtrend_4h"])
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_15m"] < 28.0)
        | (df["cti_20_1h"] < -0.7)
        | (df["cti_20_4h"] < -0.7)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 60.0)
      )
      # current 1d green, 15m downmove, 1h still high, 4h & 1d overbought, drop in last 2 hours
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < -0.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close_max_24"] < (df["close"] * 1.08))
      )
      # 1h downtrend, 5m & 15m & 1h strong downmove, 4h still high, 1h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 8.0)
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 1h downtrend, 5m downmove, 15m & 4h & 1d still high
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
      )
      # 15m downtrend, 14m & 1h downmove, 1h & 4h & 1d still high
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_3_15m"] > 6.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_1d"] < 60.0)
      )
      # current 1d bot & top wick, 15m downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["bot_wick_pct_1d"] < 0.04)
        | (df["top_wick_pct_1d"] < 0.04)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
      )
      # 1d downtrend, 5m & 15m downmove, 15m & 1h & 4h still high, 1h downtrend
      & (
        (df["is_downtrend_3_1d"] == False)
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 5m downmove, 15m & 1h & 4h & 1d stil high, drop in last 2 days, pump in last 6 days
      & (
        (df["rsi_3"] > 20.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < -0.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < -0.8)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 60.0)
        | (df["high_max_48_1h"] < (df["close"] * 1.26))
        | (df["hl_pct_change_6_1d"] < 0.7)
      )
      # current 1d top wick, 1h downtrend, 5m & 15m downmove, 1h & 4h still high, 4h downtrend
      & (
        (df["top_wick_pct_1d"] < 0.1)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_15m"] > 30.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 1d green with top wick, 5m & 15m downmove, 1h still high, 1h downtrend
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 50.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 1d downtrend, current 1d red, 5m & 15m & 4h downmove, 1h downtrend
      & (
        (df["is_downtrend_3_1d"] == False)
        | (df["change_pct_1d"] > -0.08)
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_4h"] > 12.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 4h green, current 1h red, 5m & 15m downmove, 15m  1h & 1d still high, 4h overbought
      & (
        (df["change_pct_4h"] < 0.01)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_3"] > 20.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 46.0)
      )
      # current 4h green, 1h downtrend, 5m & 15m & 1h strong downmove, 1h downtrend
      & (
        (df["change_pct_4h"] < 0.01)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_3_1h"] > 10.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 1d green, current 4h & 1h red, 1h downtrend, 5m & 15m downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["change_pct_4h"] > -0.01)
        | (df["change_pct_1h"] > -0.01)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 65.0)
      )
      # current 4h & 1h red, 1h downtrend, 5m downmove, 15m & 1h & 4h & 1d still high, 1h downtrend, drop in last 6 days
      & (
        (df["change_pct_4h"] > -0.01)
        | (df["change_pct_1h"] > -0.01)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 30.0)
        | (df["rsi_14"] > 36.0)
        | (df["rsi_14_15m"] < 26.0)
        | (df["cti_20_1h"] < -0.8)
        | (df["rsi_14_1h"] < 30.0)
        | (df["rsi_14_4h"] < 36.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["high_max_6_1d"] < (df["close"] * 1.4))
      )
      # current 4h green, current 1h red, 1h downtrend, 15m & 1h & 4h still high
      & (
        (df["change_pct_4h"] < 0.01)
        | (df["change_pct_1h"] > -0.01)
        | (df["not_downtrend_1h"])
        | (df["cti_20_15m"] < -0.7)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 46.0)
      )
      # current 4h top wick, 5m & 15m downmove, 1h & 4h still high, drop in last 6 days
      & (
        (df["top_wick_pct_4h"] < 0.04)
        | (df["rsi_3"] > 6.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["high_max_6_1d"] < (df["close"] * 1.7))
      )
      # current 4h green, current 1h red, 5m downmove, 15m & 1h & 4h still high
      & (
        (df["change_pct_4h"] < 0.03)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_3"] > 20.0)
        | (df["cti_20_15m"] < -0.5)
        | (df["rsi_14_15m"] < 40.0)
        | (df["cti_20_1h"] < -0.7)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
      )
      # current 4h long green, current 1h red, 15m & 1h & 4h still high
      & (
        (df["change_pct_4h"] < 0.08)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < -0.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 60.0)
      )
      # current 1h downtrend, 15m downmove, 15m & 1h & 4h still high, drop in last 2 hours
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < 0.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["close_max_24"] < (df["close"] * 1.08))
      )
      # 15m & 1h & 4h downtrend, 15m & 1h & 4h downmove, 1h downtrend, drop in last 6 days
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["high_max_6_1d"] < (df["close"] * 1.5))
      )
      # current 4h red, 15m downtrend, 15m & 1h downmove, 4h overbought
      & (
        (df["change_pct_4h"] > -0.03)
        | (df["not_downtrend_15m"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 16.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
      )
      # 5m & 15m downmove, 15m & 1h still high
      & (
        (df["rsi_3"] > 4.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 50.0)
      )
      # current 1d green with top wick, 5m downmove, 15m & 1h & 4h still high
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["rsi_3"] > 12.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
      )
      # current 4h red, current 1h red, 1h downtrend, 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_4h"] > -0.01)
        | (df["change_pct_1h"] > -0.01)
        | (df["not_downtrend_1h"])
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 60.0)
      )
      # 15m downtrend, 15m strong downmove, 1h & 4h stil high
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_3_15m"] > 8.0)
        | (df["cti_20_1h"] < -0.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 50.0)
      )
      # current 1h red, 15m & 1h overbought, drop in last 6 days
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["cti_20_15m"] < 0.7)
        | (df["rsi_14_15m"] < 50.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 60.0)
        | (df["rsi_14_1h"].shift(12) < 70.0)
        | (df["high_max_6_1d"] < (df["close"] * 1.5))
      )
      # 15m & 4h downtrend, 5m & 15m strong downmove, 4h still high, 4h downtrend, drop in the last 24 hours
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_15m"] > 12.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["high_max_24_1h"] < (df["close"] * 1.2))
      )
      # 5m strong downmove, 15m & 1h & 4h & 1d high
      & (
        (df["rsi_3"] > 12.0)
        | (df["rsi_14_15m"] < 50.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
      )
      # 1h & 4h downtrend, 5m & 1h & 4h downmove, drop in last 48 hours
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_3_4h"] > 26.0)
        | (df["high_max_48_1h"] < (df["close"] * 1.4))
      )
      # current 1h red, 5m & 15m downmove, 15m still high, 1h & 4h downtrend, drop in last 6 days
      & (
        (df["change_pct_1h"] > -0.03)
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["high_max_6_1d"] < (df["close"] * 1.4))
      )
      # current 4h green, current 1h red, 15m strong downmove, 1h & 4h still high
      & (
        (df["change_pct_4h"] < 0.03)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_3_15m"] > 6.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
      )
      # current 1h long red, 1h downtrend, 1h strong downmove, 1h & 4h downtrend
      & (
        (df["change_pct_1h"] > -0.08)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 10.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 1h long red, 1h downtrend, 4h overbought
      & ((df["change_pct_1h"] > -0.08) | (df["not_downtrend_1h"]) | (df["cti_20_4h"] < 0.7) | (df["rsi_14_4h"] < 60.0))
      # 5m & 15m downmove, 15m & 1h & 4h downtrend, drop in last 6 days
      & (
        (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 10.0)
        | (df["ema_200_dec_24_15m"] == False)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["high_max_6_1d"] < (df["close"] * 1.5))
      )
      # current 1h top wick, 5m downmove, 1h & 4h still high, 1h & 4h downtrend
      & (
        (df["top_wick_pct_1h"] < 0.04)
        | (df["rsi_3"] > 16.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 1d long green with long top wick, current 4h red, 15m downmove, 1h & 4h & 1d still high
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["top_wick_pct_1d"] < 0.12)
        | (df["change_pct_4h"] > -0.01)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
      )
      # current 4h green with top wick, 1h downtrend, 15m still high, 1h downmove, 1h & 4h still high
      & (
        (df["change_pct_4h"] < 0.03)
        | (df["top_wick_pct_4h"] < 0.03)
        | (df["not_downtrend_1h"])
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 50.0)
      )
      # current 1d red, 15m & 1h & 4h still high, pump in last 6 days, drop in last 6 days
      & (
        (df["change_pct_1d"] > -0.08)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["hl_pct_change_6_1d"] < 0.7)
        | (df["high_max_6_1d"] < (df["close"] * 1.5))
      )
      # 5m & 15m downmove, 15m still high, 1h overbought, 4h stil high
      & (
        (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 70.0)
        | (df["rsi_14_4h"] < 50.0)
      )
      # 5h downtrend, 4h strong downmove, pump in last 6 days, drop in last 6 days
      & (
        (df["not_downtrend_4h"])
        | (df["rsi_3_4h"] > 10.0)
        | (df["hl_pct_change_6_1d"] < 0.7)
        | (df["high_max_6_1d"] < (df["close"] * 1.5))
      )
      # 15m strong downmove, 1h & 4h high, 1h & 4h & 1d downtrend
      & (
        (df["rsi_3_15m"] > 12.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h downtrend, 15m & 1h downmove, 1h & 4h still high, 1d overbought
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 70.0)
      )
      # 15m downmove, 15m & 1h & 4h & 1d still high, 1h downtrend, pump in last 24 hours, drop in last 4 hours
      & (
        (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 65.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["hl_pct_change_12_1h"] < 0.24)
        | (df["close_max_48"] < (df["close"] * 1.08))
      )
      # current 1d long top wick, 5m & 15m strong downmove, 4h & 1d downtrend
      & (
        (df["top_wick_pct_1d"] < 0.16)
        | (df["rsi_3"] > 6.0)
        | (df["rsi_3_15m"] > 6.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 4h green with top wick, 1h downtrend, 5m & 15m downmove, 4h still high, 1d downtrend
      & (
        (df["change_pct_4h"] < 0.04)
        | (df["top_wick_pct_4h"] < 0.04)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 15m & 1h downtrend, 15m downmove, 15m & 4h still high, 1d overbought, drop in last 2 days
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 50.0)
        | (df["high_max_48_1h"] < (df["close"] * 1.24))
      )
      # 1h & 4h downtrend, 1h downmove, 1h & 4h still high, 1d overbought
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_14_1h"] < 30.0)
        | (df["rsi_14_4h"] < 30.0)
        | (df["cti_20_1d"] < 0.9)
        | (df["rsi_14_1d"] < 70.0)
      )
      # 1h downtrend, 15m & 1h strong downmove, 4h & 1d still high, 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_3_1h"] > 10.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 4h downtrend, 1h & 4h very down, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["r_480_1h"] > -90.0)
        | (df["r_480_4h"] > -95.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d red, previous 1d green with top wick, 15m downmove, 1h & 4h & 1d still high, drop in last 48 hours
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["change_pct_1d"].shift(288) < 0.04)
        | (df["top_wick_pct_1d"].shift(288) < 0.04)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["high_max_48_1h"] < (df["close"] * 1.2))
      )
      # 1h downtrend, 5m & 15m & 1h downmove, 1h & 4h & 1d still high, drop in last 48 hours
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["high_max_48_1h"] < (df["close"] * 1.3))
      )
      # current 4h long green, 5m & 15m downmove, 1h & 4h very down, 1h & 4h & 1d downtrend
      & (
        (df["change_pct_4h"] < 0.08)
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["r_480_1h"] > -85.0)
        | (df["r_480_4h"] > -95.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d green with top wick, 1h downtrend, 5m & 1h downmove, 1h very down, 4h stil high, 1h downtrend
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["top_wick_pct_1d"] < 0.12)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_1h"] > 12.0)
        | (df["r_480_1h"] > -85.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 1d green with top wick, current 4h red with top wick, 1h downtrend, 1h downmove, 4h still high, 1h downtrend
      & (
        (df["change_pct_1d"] < 0.06)
        | (df["top_wick_pct_1d"] < 0.06)
        | (df["change_pct_4h"] > -0.03)
        | (df["top_wick_pct_4h"] < 0.03)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 12.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 1d green with top wick, 1h & 4h downtrend, 5m & 15m & 1h downmove, 4h & 1d stil high
      & (
        (df["change_pct_1d"] < 0.03)
        | (df["top_wick_pct_1d"] < 0.03)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 50.0)
      )
      # 15m strond downmove, 1h & 4h & 1d high, 1h downtrend
      & (
        (df["rsi_3_15m"] > 12.0)
        | (df["cti_20_1h"] < 0.7)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 15m downmove, 15m & 1h & 4h & 1d high, drop in last 6 hours
      & (
        (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < 0.7)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["high_max_6_1h"] < (df["close"] * 1.2))
      )
      # current 4h red, previous 4h long green with long top wick, current 1h red, 10 downmove, 15m & 1h & 4h high
      & (
        (df["change_pct_4h"] > -0.0)
        | (df["change_pct_4h"].shift(48) < 0.12)
        | (df["top_wick_pct_4h"].shift(48) < 0.12)
        | (df["change_pct_1h"] > -0.0)
        | (df["rsi_3"] > 10.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 65.0)
      )
      # 1h downtrend, 1h strong downmove, 4h still high, 1d overbought
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 8.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.9)
        | (df["rsi_14_1d"] < 60.0)
      )
      # current 4h red, previous 4h top wick, 1h & 4h & 1d still high, 1h & 4h & 1d downtrend
      & (
        (df["change_pct_4h"] > -0.03)
        | (df["top_wick_pct_4h"].shift(48) < 0.04)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["rsi_14_max_3_4h"] < 70.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 4h red, 5m & 15m downmove, 4h high, 1d overbought
      & (
        (df["change_pct_4h"] > -0.03)
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 70.0)
      )
      # 1d & 1h downtrend, 5m & 15m downmove, 15m & 1h & 4h still high, 1d overbought, drop in last 6 days
      & (
        (df["is_downtrend_3_1d"] == False)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 60.0)
        | (df["high_max_6_1d"] < (df["close"] * 1.26))
      )
      # current 1d green, 15m strong downmove, 1h & 4h & 1d still high
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["rsi_3_15m"] > 4.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 60.0)
      )
      # current 1d green, current 4h red, 1h & 3h downmove, 1h & 4h & 1d still high
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["change_pct_4h"] > -0.03)
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_14_1h"] < 30.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 60.0)
      )
      # 15m & 1h downtrend, 5m & 15m & 1h downmove, 1h downtrend, drop in last 6 days
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_3_1h"] > 10.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["high_max_6_1d"] < (df["close"] * 1.5))
      )
      # 1h downtrend, 15m & 1h downmove, 15m still high, 1h & 4h very low, 1h & 4h & 1d downtrend, drop in last 6 days
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["r_480_1h"] > -80.0)
        | (df["r_480_4h"] > -90.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
        | (df["high_max_6_1d"] < (df["close"] * 1.5))
      )
      # 15m & 1h & 4h downtrend, 5m & 15m downmove, 1h & 4h very low, 4h & 1d downtrend
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 6.0)
        | (df["rsi_3_15m"] > 12.0)
        | (df["r_480_1h"] > -85.0)
        | (df["r_480_4h"] > -90.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 4h downtrend, 15m & 1h & 4h downmove, 1d high, drop in last 6 days
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_3_4h"] > 26.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["high_max_6_1d"] < (df["close"] * 1.5))
      )
      # current 1d long green, 1h downtrend, 1h downmove, 4h & 1d high
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 20.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
      )
      # 5m & 15m downmove, 15m & 1h & 4h still high, 1d downtrend, drop in last 6 days
      & (
        (df["rsi_3"] > 6.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["ema_200_dec_4_1d"] == False)
        | (df["high_max_6_1d"] < (df["close"] * 1.5))
      )
      # 1h downtrend, 5m downmove, 15m & 1h & 4h & 1d still high, 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 4h downtrend, 5m & 15m & 1h & 4h downmove, 1h downtrend, drop in last 6 days
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 26.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_14_15m"] > 36.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_3_4h"] > 16.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["high_max_6_1d"] < (df["close"] * 1.24))
      )
      # current 4h green with top wick, 5m downmove, 15m & 1h & 4h still high, 1h & 4h & 1d downtrend
      & (
        (df["change_pct_4h"] < 0.04)
        | (df["top_wick_pct_4h"] < 0.04)
        | (df["rsi_3"] > 20.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d long red, 5m & 15m downmove, 1h & 4h still high, drop in last 6 days
      & (
        (df["change_pct_1d"] > -0.08)
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["high_max_6_1d"] < (df["close"] * 1.24))
      )
      # 1h downtrend, 5m & 15m downmove, 15m & 1h & 4h & 1d high
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
      )
      # 15m downtrend, 5m & 15m strong downmove, 1h still high, 1h downtrend
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_3"] > 6.0)
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 1h downtrend, 1h downmove, 1h still high, 4h overbought, 4h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 65.0)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 5m & 15m strong downmove, 1h & 4h still high, 1d overbought
      & (
        (df["rsi_3"] > 6.0)
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 70.0)
      )
      # 4h downtrend, 5m downmove, 15m & 1h still high, 4h downmove, 1h downtrend
      & (
        (df["not_downtrend_4h"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_3_4h"] > 16.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 1d red, 1h & 4h downtrend, 15m & 1h & 4h downmove, 1h & 4h & 1d still high, drop in last 48 hours
      & (
        (df["change_pct_1d"] > -0.0)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 36.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["high_max_48_1h"] < (df["close"] * 1.26))
      )
      # 5m & 15m strong downmove, 1h & 4h downtrend
      & (
        (df["rsi_3"] > 4.0)
        | (df["rsi_3_15m"] > 4.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 15m downtrend, 5m & 15m strong downtrend, 1h & 4h still high
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_3"] > 6.0)
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
      )
      # 1h & 4h downtrend, 5m & 15m & 1h downmove, 1h & 4h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 10.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 15m downtrend, 5m downmove, 15m & 1h & 4h still high, 4h downtrend
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 1d long top wick, 1h & 4h still high, 1h & 4h very low, 1h & 4h & 1d downtrend
      & (
        (df["top_wick_pct_1d"] < 0.12)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["r_480_1h"] > -80.0)
        | (df["r_480_4h"] > -85.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 15m downtrend, 5m & 15m & 1h downmove, 1h & 4h & 1d still high, 1h & 4h downtrend
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 1d downtrend, 15, & 1h downmove, 1h & 4h & 1d still high
      & (
        (df["is_downtrend_3_1d"] == False)
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
      )
      # current 1d long green, 5m & 15m downmove, 1h & 4h & 1d still high, 1h downtrend
      & (
        (df["change_pct_1d"] < 0.16)
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 15m downtrend, 5m & 15m downmove, 1d still high, 1h downtrend, drop in last 6 days
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 10.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["high_max_6_1d"] < (df["close"] * 1.3))
      )
      # 1h downtrend, 15m & 1h downmove, 1h & 4h still high, 4h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 1h downtrend, 5m & 15m & 1h downmove, 1h downtrend, drop in last 6 days
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["high_max_6_1d"] < (df["close"] * 1.7))
      )
      # 1h downtrend, 5m & 15m & 1h downmove, 4h still high, 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h downtrend, 15m & 1h & 4h downmove, 1h & 4h & 1h downtrend, drop in last 6 days
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 10.0)
        | (df["rsi_3_4h"] > 26.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
        | (df["high_max_6_1d"] < (df["close"] * 1.5))
      )
      # 15m downtrend, 5m & 15m downmove, 1h & 4h still high, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 5m & 15m & 1h downmove, 1h & 4h & 1d high, 1d downtrend
      & (
        (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1d & 1h downtrend, 15m & 1h downmove, 1h & 4h & 1d still high
      & (
        (df["is_downtrend_3_1d"] == False)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 6.0)
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 50.0)
      )
      # 1h & 4h & 1d still high, 1d downtrend, big drop in last 12 days
      & (
        (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 65.0)
        | (df["ema_200_dec_4_1d"] == False)
        | (df["high_max_12_1d"] < (df["close"] * 2.5))
      )
      # 1h & 4h downtrend, 1d still high, big drop in last 12 days
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
        | (df["high_max_12_1d"] < (df["close"] * 5.0))
      )
      # current 1d red, 1h downtrend, 5m & 15h downmove, 1h & 4h & 1d still high
      & (
        (df["change_pct_1d"] > -0.08)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 8.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
      )
      # current 4h green with top wick, 5m & 15m downmove, 1h & 4h high, 1h downtrend
      & (
        (df["change_pct_4h"] < 0.04)
        | (df["top_wick_pct_4h"] < 0.08)
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["cti_20_1h"] < 0.7)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 1h downtrend, 5m & 15m strong downmove, 1h & 4h downtrend, drop in last 12 days
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 6.0)
        | (df["rsi_3_15m"] > 12.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["high_max_12_1d"] < (df["close"] * 1.9))
      )
      # 4h downtrend, 5m & 15m downmove, 1h & 4h very low, 1h & 4h & 1d downtrend, drop in last 12 days
      & (
        (df["not_downtrend_4h"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["r_480_1h"] > -80.0)
        | (df["r_480_4h"] > -85.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
        | (df["high_max_12_1d"] < (df["close"] * 1.5))
      )
      # current 4h top wick, 5m & 15m downmove, 1h & 4h high, 4h & 1d downtrend
      & (
        (df["top_wick_pct_4h"] < 0.06)
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 15m & 4h downtrend, 5m & 15m downmove, 4h low, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["r_480_4h"] > -80.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 4h downtreend, 1h & 4h downmove, 1h & 4h low, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_3_4h"] > 16.0)
        | (df["r_480_1h"] > -85.0)
        | (df["r_480_4h"] > -85.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d red, 1h & 4h downtrend, 15m downmove, 1h & 4h love, 1h & 4h & 1d downtrend
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["r_480_1h"] > -85.0)
        | (df["r_480_4h"] > -85.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 4h downtrend, 1h & 4h downmove, 1h & 4h low, 1h & 4h * 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_1h"] > 10.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["r_480_1h"] > -80.0)
        | (df["r_480_4h"] > -90.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d red, current 4h red, previous 4h green, 15m downtrend, 5m & 15m downmove, 1h & 4h & 1d still high, 1d downtrend
      & (
        (df["change_pct_1d"] > -0.01)
        | (df["change_pct_4h"] > -0.01)
        | (df["change_pct_4h"].shift(48) < 0.06)
        | (df["not_downtrend_15m"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 5m & 15m downmove, 1h & 4h still high, 4h low, 1h & 4h & 1d downtrend
      & (
        (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["r_480_4h"] > -90.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h downtrend, 1h downmove, 4h still high, 1h & 4h low, 1h & 4h & 1d downtrend, drop in last 12 days
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 10.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["r_480_1h"] > -80.0)
        | (df["r_480_4h"] > -95.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
        | (df["high_max_12_1d"] < (df["close"] * 1.7))
      )
      # current 4h green, 5m downmove, 1h & 4h still high, 4h low, 4h & 1d downtrend
      & (
        (df["change_pct_4h"] < 0.06)
        | (df["rsi_3"] > 12.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["r_480_4h"] > -90.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d green with top wick, 15m downtrend, 5m & 15m downmove, 1h & 4h stil high, 4h & 1d downtrend
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["not_downtrend_15m"])
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1d & 1hdowntrend, 5m & 15m & 1h downmove, 1h & 4h & 1d downtrend, drop in last 12 days
      & (
        (df["is_downtrend_3_1d"] == False)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
        | (df["high_max_12_1d"] < (df["close"] * 1.4))
      )
      # 4h downtrend, 5m & 4h downmove, 1h & 4h very low, 1h downtrend
      & (
        (df["not_downtrend_4h"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["r_480_1h"] > -97.0)
        | (df["r_480_4h"] > -97.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current & previous 4h red, 2nd previous 4h long green, 1h % 4h high, 1d downtrend
      & (
        (df["change_pct_4h"] > -0.01)
        | (df["change_pct_4h"].shift(48) > -0.01)
        | (df["change_pct_4h"].shift(96) < 0.16)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 4h red, previous 4h green, 5m & 15m downmove, 1d overbought
      & (
        (df["change_pct_4h"] > -0.04)
        | (df["change_pct_4h"].shift(48) < 0.04)
        | (df["rsi_3"] > 6.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 50.0)
      )
      # 1h downtrend, 5m & 15m & 1h downmove, 4h very low, 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["r_480_4h"] > -97.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 15m & 1h downtrend, 5m & 15m downmove, 5h still high, 1d overbought
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 70.0)
      )
      # current 4h long green, 5m strong downmove, 1h overbought, 4h still high
      & (
        (df["change_pct_4h"] < 0.08)
        | (df["rsi_3"] > 4.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 70.0)
        | (df["rsi_14_4h"] < 50.0)
      )
      # currend 1h red, current 4h top wick, current 1h red, 1h downtrend, 5m & 15m & 1h downmove, 4h & 1d still high
      & (
        (df["change_pct_1d"] > -0.03)
        | (df["top_wick_pct_4h"] < 0.03)
        | (df["change_pct_1h"] > -0.02)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 36.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
      )
      # current 1d green with top wick, current 4h red, 1h downtrend, 5m & 1h downmove, 4h stil high, 4h & 1d downmove
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["change_pct_4h"] > -0.03)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 40.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 4h downtrend, 5m & 15m downmove, 1h stil high, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_4h"])
        | (df["rsi_3"] > 6.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d green with top wick, current 4h red, previous 4h green with top wick, 1h downtrend, 4h overbought, 1d downtrend
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["change_pct_4h"] > -0.02)
        | (df["change_pct_4h"].shift(48) < 0.04)
        | (df["top_wick_pct_4h"].shift(48) < 0.04)
        | (df["not_downtrend_1h"])
        | (df["rsi_14_max_3_4h"] < 70.0)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 4h downtrend, 5m & 15m & 1h & 4h downmove, 1d stil high
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 6.0)
        | (df["rsi_3_1h"] > 12.0)
        | (df["rsi_3_4h"] > 26.0)
        | (df["rsi_14_1d"] < 46.0)
      )
      # current 4h red, 15m & 1h & 4h & 1d still high, big drop in last 6 days
      & (
        (df["change_pct_4h"] > -0.06)
        | (df["rsi_14_15m"] < 33.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["high_max_6_1d"] < (df["close"] * 4.0))
      )
      # current 1d red, previous 1d green with top wick, 5m & 15m downmove, 15m still high, 1d overbought
      & (
        (df["change_pct_1d"] > -0.08)
        | (df["change_pct_1d"].shift(288) < 0.03)
        | (df["top_wick_pct_1d"].shift(288) < 0.03)
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 33.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["rsi_14_1d"].shift(288) < 65.0)
        | (df["hl_pct_change_6_1d"] < 0.5)
      )
      # 5m & 15m downmove, 1h & 4h & 1d still high, 1d downtrend, pump in last 6 days
      & (
        (df["rsi_3"] > 12.0)
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 60.0)
        | (df["ema_200_dec_4_1d"] == False)
        | (df["hl_pct_change_6_1d"] < 0.7)
      )
      # current 1d long green, 5m strong downmove, 15m & 1h & 1d still high, 1d overbought, pump in last 12 days
      & (
        (df["change_pct_1d"] < 0.18)
        | (df["rsi_3"] > 12.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 60.0)
        | (df["high_max_12_1d"] < (df["close"] * 0.9))
      )
      # 1h downtrend, 5m downmove, 1h & 4h low, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 10.0)
        | (df["r_480_1h"] > -70.0)
        | (df["r_480_4h"] > -85.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h downtrend, 5m & 15m & 1h & 4h downmove, 4h very low, 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_3_4h"] > 36.0)
        | (df["r_480_4h"] > -95.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h downtrend, 5m & 1h downmove, 15m still high, 1h & 4h low, 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["r_480_1h"] > -75.0)
        | (df["r_480_4h"] > -90.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d red, 5m downmove, 15m still high, 1h & 4h & 1d downtrend
      & (
        (df["change_pct_1d"] > -0.08)
        | (df["rsi_3"] > 10.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 4h downtrend, 5m & 15m downmove, 15m & 1h & 4h & 1d still high, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_4h"])
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 33.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 4h downtrend, 1d downmove, 15m still high, 1h & 4h low, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_4h"])
        | (df["rsi_3_1d"] > 30.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["r_480_1h"] > -85.0)
        | (df["r_480_4h"] > -95.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 4h downtrend, 1h & 4h downmove, 15m stil high, 1h & 4h low, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_4h"])
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["r_480_1h"] > -70.0)
        | (df["r_480_4h"] > -80.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1d downtrend, 5m & 15m downmove, 15m & 1h & 4h still high, 4h & 1d downtrend
      & (
        (df["not_downtrend_1d"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 15m & 1h downtrend, 5m & 15m downmove, 15m & 4h & 1d still high, 1h downtrend
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 5m & 15m downmove, 15m & 1h & 4h still high, 1h & 4h & 1d downtrend
      & (
        (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 60.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 5m & 15m downmove, 15m & 1h & 4h & 1d stil high, 1d downtrend
      & (
        (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 5m & 15m downmove, 15m & 1h & 4h & 1d still high, 1d downtrend
      & (
        (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < -0.8)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < -0.8)
        | (df["rsi_14_1d"] < 50.0)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 4h green with top wick, 5m & 15m downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_4h"] < 0.04)
        | (df["top_wick_pct_4h"] < 0.04)
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 33.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
      )
      # current 4h red with top wick, 5m & 1h downmove, 1h & 4h still high, 1h & 4h & 1d downtrend
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["top_wick_pct_4h"] < 0.02)
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 4h downtrend, 5m & 15m & 1h downmove, 1h & 4h & 1d still high, 1h * 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_15m"] < 33.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["rsi_14_1h"] < 30.0)
        | (df["rsi_14_4h"] < 30.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d red, previous 1d green, 5m & 15m downmove, 15m & 1h & 4h & 1d still high, 1d downtrend
      & (
        (df["change_pct_1d"] > -0.03)
        | (df["change_pct_1d"].shift(288) < 0.03)
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h downtrend, 5m & 1h downmove, 15m & 1h & 4h & 1d still high, 1h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 4m & 15m downmove,15m & 1h & 4h & 1d still high
      & (
        (df["rsi_3"] > 26.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["cti_20_15m"] < -0.5)
        | (df["rsi_14_15m"] < 33.0)
        | (df["cti_20_1h"] < -0.8)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < -0.8)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
      )
      # 1h downtrend, 5m & 15m & 1h downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 16.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < -0.8)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
      )
      # 5m downmove, 15m  1h & 4h still high, 1h & 4h downtrend
      & (
        (df["rsi_3"] > 12.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["cti_20_1h"] < -0.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 1h downtrend, 5m & 15m & 1h downmove, 1h & 4h & 1d still high, 1h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_3_1h"] > 16.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < -0.8)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 1h downtrend, 5m & 15m & 1h & 4h downmove, 1h & 4h & 1d still high
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 10.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["sup_level_4h"])
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_3_4h"] > 36.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < -0.8)
        | (df["rsi_14_4h"] < 36.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
      )
      # 1d top wick, 1h downtrend, 5m & 15m & 1h downmove, 1h & 4h & 1d still high, 1h downtrend
      & (
        (df["top_wick_pct_1d"] < 0.03)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 16.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_14_1h"] < 30.0)
        | (df["rsi_14_4h"] < 30.0)
        | (df["rsi_14_1d"] < 30.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 5m & 1d downmove, 15m & 1h & 4h still high, 1h & 4h very low, 1h & 4h downtrend
      & (
        (df["rsi_3"] > 10.0)
        | (df["rsi_3_1d"] > 26.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 36.0)
        | (df["r_480_1h"] > -85.0)
        | (df["r_480_4h"] > -95.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 1h & 4h downtrend, 5m & 15m & 1h & 4h downmove, 4h & 1d still high, 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 20.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_3_4h"] > 36.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 4h downtrend, 5m & 4h downmove, 15m & 1h & 4h & 1d still high, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_4h"])
        | (df["rsi_3"] > 30.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 30.0)
        | (df["rsi_14_4h"] < 36.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d red, previous 1d green, 15m & 1h & 4h downtrend, 1d still high, 1h downtrend
      & (
        (df["change_pct_1d"] > -0.03)
        | (df["change_pct_1d"].shift(288) < 0.03)
        | (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 5m & 15m downmove, 15m & 1h & 4h & 1d still high, 4h & 1d downtrend
      & (
        (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 4h downtrend, 5m & 1h downmove, 15m & 1h & 1d stil high, 1h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 20.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["rsi_14_1h"] < 30.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 44.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h downtrend, 5m % 15m & 1h downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 12.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_15m"] < 33.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < -0.5)
        | (df["rsi_14_1d"] < 50.0)
      )
      # 1h & 4d downtrend, 5m & 15h & 1h downmove, 15m & 1h & 4h still high, 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 16.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 5m downtrend, 15m & 1h & 4h & 1d still high, 4h & 1d downtrend
      & (
        (df["rsi_3"] > 30.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 30.0)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d long green, 5m & 15m downmove, 15m & 1h & 4h & 1d still high, 1h & 4h & 1d downtrend
      & (
        (df["change_pct_1d"] < 0.16)
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 15m & 1h downtrend, 5m & 15m downmove, 15m & 1h & 4h * 1d still high
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 16.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
      )
      # 1h & 4h downtrend, 5m & 1h & 4h downmove, 15m still high, 1h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 1h & 1d downtrend, 5m & 1d downmove, 15m still high, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 12.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["rsi_3_1d"] > 12.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 5m & 15m downmove, 1h & 4h & 1d still high, 4h & 1d downtrend
      & (
        (df["rsi_3"] > 16.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < 0.6)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 4h green with top wick, 5m & 1d downmove, 15m & 1h still high, 1h & 4h & 1d downtrend
      & (
        (df["change_pct_4h"] < 0.04)
        | (df["top_wick_pct_4h"] < 0.04)
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_1d"] > 10.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h downtrend, 5m & 1h downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 12.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 60.0)
      )
      # 1h & 4h & 1d downtrend, 5, & 1h & 1d downmove, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_3_1d"] > 16.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 5m & 15m & 1h downmove, 1h & 4h still high, 1h & 4h downtrend
      & (
        (df["rsi_3"] > 10.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 1h downtrend, 5m downmove, 15m & 4h still high, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 5m & 15m downmove, 1h & 4h still high, 4h & 1d downtrend
      & (
        (df["rsi_3"] > 16.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d green with top wick, 5m downmove, 15m still high, 1h & 4h downtrend
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["top_wick_pct_1d"] < 0.04)
        | (df["rsi_3"] > 12.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["rsi_14_15m"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 1h & 4h downtrend, 5m & 15m & 4h downmove, 1h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 20.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_4h"] > 16.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 1h & 4h downtrend, 5m & 15m & 1h & 4h downmove
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 10.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_3_4h"] > 30.0)
      )
      # 5m & 15m downmove, 15m & 1h & 4h still high, 4h & 1d downtrend
      & (
        (df["rsi_3"] > 10.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h downtrend, 5m & 15m downmove, 15m & 1h & 4h still high, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 4h downtrend, 5m downmove, 15m & 1h & 4h & 1d still high, 4h & 1d downtrend
      & (
        (df["not_downtrend_4h"])
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["r_480_4h"] > -75.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 5m red, 5m & 15m downmove, 15m & 1d still high, 1h downtrend
      & (
        (df["change_pct"] > -0.018)
        | (df["rsi_3"] > 10.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["cti_20_1d"] < -0.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 4h red, 1h downtrend, 5m & 15m downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_4h"] > -0.03)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 12.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < -0.0)
        | (df["rsi_14_1d"] < 50.0)
      )
      # 1h & 1d downtrend, 5m & 15m downmove, 4h low, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 16.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["r_480_4h"] > -85.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 4h & 1d downtrend, 5m & 15m & 1d downmove, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1d"] > 20.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h downtrend, 5m & 1h downmove, 15m & 4h & 1d still high, 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 12.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h downtrend, 5m & 15m downmove, 15m & 1h & 4h & 1d still high, 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 26.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["sup_level_4h"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < -0.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 4h & 1d downtrend, 5m & 15m & 1d downmove, 15m still high, 1h & dh downtrend
      & (
        (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1d"] > 16.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 5m & 15m downmove, 15m & 1h & 4h still high, 4h & 1d downtrend
      & (
        (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d green, 5m & 1h downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_1d"] < 0.06)
        | (df["rsi_3"] > 10.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < -0.5)
        | (df["rsi_14_1d"] < 46.0)
      )
      # 1h & 4h & 1d downtrend, 15m & 4h & 1d downmove, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_3_1d"] > 30.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 1d downtrend, 5m & 15m downmove, 15m & 1h & 4h still high, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 30.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1d downtrend, 5m & 15m & 1d downmove, 15m sitll high, 1h & 4h low, 1h & 4h & 1d downtrend
      & (
        (df["is_downtrend_3_1d"] == False)
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 12.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1d"] > 26.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["r_480_1h"] > -80.0)
        | (df["r_480_4h"] > -90.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 5m & 15m downmove, 15m & 1h & 4h still high, 1h downtrend
      & (
        (df["rsi_3"] > 30.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["cti_20_1h"] < 0.7)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 4h & 1d downtrend, 15m & 1h & 4h still high, 5m low, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_14_15m"] < 46.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d green with top wick, 5m & 15m downmove, 15m & 1h & 4h & 1d still high, 1h & 4h & 1d downtrend
      & (
        (df["change_pct_1d"] < 0.02)
        | (df["top_wick_pct_1d"] < 0.02)
        | (df["rsi_3"] > 36.0)
        | (df["rsi_3_15m"] > 36.0)
        | (df["cti_20_15m"] < -0.5)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h downtrend, 15m downmove, 15m & 4h & 1d still high, pump in last 6 days
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 60.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["hl_pct_change_6_1d"] < 0.7)
      )
      # 5m & 15m downmove, 15m & 1h & 4h still high, 1h & 4h & 1d downtrend
      & (
        (df["rsi_3"] > 36.0)
        | (df["rsi_3_15m"] > 36.0)
        | (df["cti_20_15m"] < -0.5)
        | (df["rsi_14_15m"] < 46.0)
        | (df["cti_20_1h"] < 0.8)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 4h green with top wick, 5m & 15m downmove, 15m & 1h & 4h & 1d still high, 1h downtrend
      & (
        (df["change_pct_4h"] < 0.02)
        | (df["top_wick_pct_4h"] < 0.02)
        | (df["rsi_3"] > 36.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["cti_20_15m"] < -0.5)
        | (df["rsi_14_15m"] < 40.0)
        | (df["cti_20_1h"] < -0.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 15m downmove, 15m & 1h & 4h & 1d still high, 4h downtrend
      & (
        (df["rsi_3_15m"] > 26.0)
        | (df["cti_20_15m"] < -0.5)
        | (df["rsi_14_15m"] < 33.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 5m downmove, 15m & 1h & 4h & 1d still high, 1h downtrend
      & (
        (df["rsi_3"] > 30.0)
        | (df["cti_20_15m"] < 0.5)
        | (df["rsi_14_15m"] < 50.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 40.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 1d red with top wick, previous 1d green, 1h downtrend, 5m downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_1d"] > -0.01)
        | (df["top_wick_pct_1d"] < 0.02)
        | (df["change_pct_1d"].shift(288) < 0.08)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 20.0)
        | (df["cti_20_15m"] < -0.5)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["bb20_2_low_15m"])
      )
      # 5m downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["rsi_3"] > 26.0)
        | (df["cti_20_15m"] < -0.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["bb20_2_low_15m"])
      )
      # current 1d green, current 4h green, current 1h green, 5m downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["change_pct_4h"] < 0.04)
        | (df["change_pct_1h"] < 0.02)
        | (df["rsi_3"] > 30.0)
        | (df["cti_20_15m"] < -0.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
      )
      # current 1d green with top wick, current 4h red, 5m & 15m downmove, 1h & 4h & 1d high, 1d downtrend
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["change_pct_4h"] > -0.01)
        | (df["rsi_3"] > 26.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_max_3_4h"] < 70.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 4h red, 5m & 15m downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_4h"] > -0.01)
        | (df["rsi_3"] > 36.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["cti_20_15m"] < -0.5)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["bb20_2_low_15m"])
      )
      # current 1d green with top wick, 15m downmove, 15m & 1h & 4h & 1d still high, drop in last 12 days
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["top_wick_pct_1d"] < 0.04)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
        | (df["high_max_12_1d"] < (df["close"] * 0.9))
      )
      # 15m & 1d downtrend, 5m & 15m & 1d downmove, 15m & 1h & 4h still high
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1d"] > 20.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["close"] > df["bb20_2_low_15m"])
      )
      # current 1d red with top wick, previous 1d green, 1d downtrend, 5m downmove, 15m & 1h & 4h still high, 4h & 1d downtrend
      & (
        (df["change_pct_1d"] > -0.02)
        | (df["top_wick_pct_1d"] < 0.02)
        | (df["change_pct_1d"].shift(288) < 0.04)
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 30.0)
        | (df["cti_20_15m"] < -0.5)
        | (df["rsi_14_15m"] < 40.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 5m & 15m downmove, 15m & 1h & 4h still high, 1d downtrend
      & (
        (df["rsi_3"] > 36.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < 0.7)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] < df["res_hlevel_1h"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d red with top wick, previous 1d green, 4h downtrend, 5m downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_1d"] > -0.02)
        | (df["top_wick_pct_1d"] < 0.02)
        | (df["change_pct_1d"].shift(288) < 0.02)
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 26.0)
        | (df["cti_20_15m"] < -0.5)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < -0.7)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < -0.7)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
      )
      # 1d downtrend, 15m & 1h & 1d still high, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_1d"])
        | (df["cti_20_15m"] < 0.5)
        | (df["rsi_14_15m"] < 46.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 36.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d red with top wick, previous 1d green, 5m downmove, 15m & 1h & 4h & 1d stil high, 4h & 1d downtrend
      & (
        (df["change_pct_1d"] > -0.02)
        | (df["top_wick_pct_1d"] < 0.02)
        | (df["change_pct_1d"].shift(288) < 0.02)
        | (df["rsi_3"] > 36.0)
        | (df["cti_20_15m"] < -0.5)
        | (df["rsi_14_15m"] < 46.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < -0.5)
        | (df["rsi_14_1d"] < 40.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d green with top wick, 5m downmove, 15m & 1h & 4h still high, 1d overbought
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["top_wick_pct_1d"] < 0.04)
        | (df["rsi_3"] > 36.0)
        | (df["cti_20_15m"] < -0.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 50.0)
      )
      # current 4h red, previous 4h green, 15m downmove, 15m & 1h & 4h & 1d still high, 1d downtrend
      & (
        (df["change_pct_4h"] > -0.01)
        | (df["change_pct_4h"].shift(48) < 0.02)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 15m & 4h & 1d downtrend, 5m & 15m & 1d downmove, 1h & 1d downtrend
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1d"] > 26.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 4h red, 15m downmove, 15m & 1h & 4h & 1d still high, 4h downtrend
      & (
        (df["change_pct_4h"] > -0.01)
        | (df["rsi_3_15m"] > 30.0)
        | (df["cti_20_15m"] < -0.5)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < -0.5)
        | (df["rsi_14_1d"] < 40.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 1d downtrend, 5m & 15m downmove, 15m & 1h still high, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_1d"])
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 5m downmove, 15m & 1h & 4h & 1d still high, 4h & 1d downtrend
      & (
        (df["rsi_3"] > 36.0)
        | (df["cti_20_15m"] < -0.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["cti_20_1h"] < -0.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < -0.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 4h green with top wick, 1h & 4h & 1d high
      & (
        (df["change_pct_4h"] < 0.02)
        | (df["top_wick_pct_4h"] < 0.02)
        | (df["cti_20_1h"] < 0.7)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 60.0)
        | (df["close"] > df["bb20_2_low_15m"])
      )
      # 15m downtrend, 5m & 15m downmove, 15m & 1h & 4d & 1d still high
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["bb20_2_low_15m"])
      )
      # current 1d red, 15m & 1d downtrend, 1d downmove, 15m & 1h high, 1h downtrend
      & (
        (df["change_pct_1d"] > -0.02)
        | (df["not_downtrend_15m"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_1d"] > 20.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < 0.7)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 1d red, current 4h green, 15m downmove, 15m & 1h & 1d high
      & (
        (df["change_pct_1d"] > -0.02)
        | (df["change_pct_4h"] < 0.02)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["rsi_14_1h"] < 60.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 50.0)
      )
      # current 1d green, 1h & 4h downtrend, 4h downmove, 15m & 1d still high
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_4h"] > 20.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1d"] < 50.0)
      )
      # current 1d green, current 4h green, 15m & 1h & 4h & 1d still high, pump in last 3 days
      & (
        (df["change_pct_1d"] < 0.16)
        | (df["change_pct_4h"] < 0.08)
        | (df["rsi_14_15m"] < 40.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["hl_pct_change_3_1d"] < 0.7)
      )
      # current 4h green, 5m downmove, 15m & 1h & 4h & 1d still high, 4h & 1d downtrend
      & (
        (df["change_pct_4h"] < 0.02)
        | (df["rsi_3"] > 26.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1d downtrend, 15m & 1h & 4h & 1d still high, 4h & 1d downtrend
      & (
        (df["is_downtrend_3_1d"] == False)
        | (df["rsi_14_15m"] < 50.0)
        | (df["cti_20_1h"] < -0.0)
        | (df["rsi_14_1h"] < 60.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1h green, 15m downtrend, 5m & 15m downmove, 15m & 1h & 4h still high, 24h downtrend
      & (
        (df["change_pct_1h"] < 0.0)
        | (df["not_downtrend_15m"])
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # cuerrent 5m red, previous 5m green, 15m downmove, 15m & 1h & 4h still high, 1h downtrend
      & (
        (df["change_pct"] > -0.016)
        | (df["change_pct"].shift(1) < 0.016)
        | (df["rsi_3_15m"] > 36.0)
        | (df["cti_20_15m"] < 0.5)
        | (df["rsi_14_15m"] < 46.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 36.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 5m & 15m downmove, 15m & 1h & 4h & 1d still high, 4h downtrend
      & (
        (df["rsi_3"] > 30.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["cti_20_15m"] < 0.5)
        | (df["rsi_14_15m"] < 40.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 15m & 1h & 4h high, 1h & 4h & 1d downtrend
      & (
        (df["cti_20_15m"] < 0.5)
        | (df["rsi_14_15m"] < 46.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 46.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1d downtrend, 5m downmove, 15m & 1h & 4h & 1h still high, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_1d"])
        | (df["rsi_3"] > 30.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < -0.5)
        | (df["rsi_14_1d"] < 36.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1h green, 15m downmove, 15m & 1h & 4h & 1d high
      & (
        (df["change_pct_1h"] < 0.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["cti_20_1h"] < 0.8)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 50.0)
      )
      # current 1d top wick, 4h downtrend, 15m & 1h & 4h & 1d high, 4h downtrend, 1d downtrend
      & (
        (df["top_wick_pct_1d"] < 0.08)
        | (df["is_downtrend_3_4h"] == False)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1d downtrend, 5m & 15m downmove, 15m & 1h & 4h & 1d still high, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_1d"])
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 5m downmove, 15m & 1h & 4h high, 1h downtrend
      & (
        (df["rsi_3"] > 30.0)
        | (df["cti_20_15m"] < -0.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["cti_20_1h"] < 0.7)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 15m downtrend, 15m downmove, 15m & 1h & 4h high
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["cti_20_15m"] < -0.5)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 50.0)
      )
      # current 1d red, previous 1d green with top wick, current 4h green, current 1h green, 15m downmove, 15m & 1h & 4h & 1d syill high, 4h & 1d downtrend
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["change_pct_1d"].shift(288) < 0.02)
        | (df["top_wick_pct_1d"].shift(288) < 0.02)
        | (df["change_pct_4h"] < 0.01)
        | (df["change_pct_1h"] < 0.01)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 15m & 1h downtrend, 15m downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["cti_20_15m"] < -0.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < -0.5)
        | (df["rsi_14_1d"] < 40.0)
      )
      # 5m & 15m downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["cti_20_15m"] < -0.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 40.0)
      )
      # 4h & 1d downtrend, 5m & 4h & 1d downmove, 15m still high, 1h & 4h low, 1h & 4h & 1d
      & (
        (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_4h"] > 36.0)
        | (df["rsi_3_1d"] > 36.0)
        | (df["cti_20_15m"] < -0.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["r_480_1h"] > -75.0)
        | (df["r_480_4h"] > -75.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 4h & 1d downtrend, 5m & 4h & 1d downmove, 5m & 15m & 1d still high, 1h & 1d downtrend
      & (
        (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_3_1d"] > 30.0)
        | (df["cti_20"] < -0.5)
        | (df["rsi_14"] < 33.0)
        | (df["cti_20_15m"] < -0.5)
        | (df["rsi_14_15m"] < 33.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 4h red, 1d downtrend, 5m & 1d downmove, 15m & 4h still high, 1h & 4h & 1d downtrend
      & (
        (df["change_pct_4h"] > -0.04)
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_1d"] > 12.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 5m & 15m downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["cti_20_15m"] < -0.5)
        | (df["rsi_14_15m"] < 33.0)
        | (df["cti_20_1h"] < 0.7)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["bb20_2_low_15m"])
      )
      # current 1d green with top wick, 1h downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 50.0)
      )
      # current 4h red, previous 4h green, 5m & 15m downmove, 1h & 4h still high, 1h & 4h & 1d downtrend
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["change_pct_4h"].shift(48) < 0.02)
        | (df["rsi_14"] < 12.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 4h downtrendm 5m & 15m & 1h downmove, 15m & 1h & 4h & 1d still high, 5m & 15m downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["ema_200_dec_24"] == False)
        | (df["ema_200_dec_24_15m"] == False)
      )
      # 1d & 1h downtrend, 5m downmove, 15m & 1h & 1d still high, 5m & 15m downtrend
      & (
        (df["is_downtrend_3_1d"] == False)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 40.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["ema_200_dec_24"] == False)
        | (df["ema_200_dec_24_15m"] == False)
      )
      # current 4h top wick, 15m downmove, 15m & 1h & 4h & 1d still high, drop in last 12 days
      & (
        (df["top_wick_pct_4h"] < 0.02)
        | (df["rsi_3_15m"] > 50.0)
        | (df["cti_20_15m"] < -0.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["cti_20_1h"] < 0.7)
        | (df["rsi_14_1h"] < 60.0)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < -0.5)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["high_max_12_1d"] < (df["close"] * 0.9))
      )
      # 1h downtrend, 5m & 1h downmove, 15m & 1h & 4h still high, 4h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 1h downtrend, 5m & 15m & 1h downmove, 15m & 1h & 4h & 1d still high, 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 4h & 1d downtrend, 5m & 15m & 1h downmove, 15m & 4h & 1d still high, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_4h"] < 36.0)
        | (df["rsi_14_1d"] < 36.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 5m & 15m downmove, 15m & 1h & 4h & 1d high, pump in last 12 days
      & (
        (df["rsi_3"] > 30.0)
        | (df["rsi_3_15m"] > 36.0)
        | (df["cti_20_15m"] < 0.5)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.9)
        | (df["rsi_14_1d"] < 70.0)
      )
      # 5m downmove, 15m & 1h & 4h & 1d still high, 4h downtrend
      & (
        (df["rsi_3"] > 10.0)
        | (df["cti_20_15m"] < 0.5)
        | (df["rsi_14_15m"] < 46.0)
        | (df["cti_20_1h"] < -0.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 4h green with top wick, 1d downtrend, 5m downmove, 15m & 1h & 4h stil high, 1h & 4h & 1d downtrend
      & (
        (df["change_pct_4h"] < 0.02)
        | (df["top_wick_pct_4h"] < 0.02)
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 26.0)
        | (df["cti_20_15m"] < 0.5)
        | (df["rsi_14_15m"] < 46.0)
        | (df["rsi_14_1h"] < 60.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h downtrend, 15m downmove, 15m & 1h & 4h & 1d still high, 1h & 4h low, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["r_480_1h"] > -80.0)
        | (df["r_480_4h"] > -80.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 4h downtrend, 5m & 15h & 1d downmove, 15m & 1h still high, 1h & 4h low, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_4h"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1d"] > 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["r_480_1h"] > -85.0)
        | (df["r_480_4h"] > -75.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d red, 15m downmove, 1h & 1d high, 1h downtrend
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["rsi_14_15m"] < 40.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 70.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 4m red, 4h downtrend, 5m & 4h downmove, 1d stil high, 1h & 4h downtrend
      & (
        (df["change_pct"] > -0.018)
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_4h"] > 20.0)
        | (df["cti_20_1d"] < -0.5)
        | (df["rsi_14_1d"] < 40.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 4h red, previous 4h green, 5m downmove, 15m & 1h & 4h & 1d high
      & (
        (df["change_pct_4h"] > -0.01)
        | (df["change_pct_4h"].shift(48) < 0.02)
        | (df["rsi_3"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < 0.7)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["bb20_2_low_15m"])
      )
      # 1h & 4h & 1d downtrend, 5m & 15m & 1d downmove, 1d stil high, 1h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_3_1d"] > 20.0)
        | (df["cti_20_1d"] < -0.5)
        | (df["rsi_14_1d"] < 40.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 4h green with top wick, 15m downmove, 15m & 1h & 4h & 1d still high, 4h & 1d downtrend
      & (
        (df["change_pct_4h"] < 0.01)
        | (df["top_wick_pct_4h"] < 0.04)
        | (df["rsi_3_15m"] > 30.0)
        | (df["cti_20_15m"] < -0.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h downtrend, 15m downmove, 15m & 1h & 4h still high, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 4h & 1d downtrend, 5m & 4h downmove, 15m still high, 4h low, 4h & 1d downtrend
      & (
        (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_4h"] > 20.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["r_480_4h"] > -85.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d & 4h green with top wick, 5m downmove, 15m & 1h & 4h & 1d high
      & (
        (df["change_pct_1d"] < 0.02)
        | (df["top_wick_pct_1d"] < 0.02)
        | (df["change_pct_4h"] < 0.01)
        | (df["top_wick_pct_4h"] < 0.02)
        | (df["rsi_3"] > 30.0)
        | (df["cti_20_15m"] < -0.5)
        | (df["rsi_14_15m"] < 46.0)
        | (df["cti_20_1h"] < 0.7)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 46.0)
      )
      # current & previous 1d red, 5m downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_1d"] > -0.0)
        | (df["change_pct_1d"].shift(288) > -0.08)
        | (df["rsi_3"] > 12.0)
        | (df["cti_20_15m"] < 0.5)
        | (df["rsi_14_15m"] < 50.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < -0.5)
        | (df["rsi_14_1d"] < 40.0)
      )
      # current 4h top wick, 5m & 15m downmove, 15m & 1h & 4h & 1d still high, 1d downtrend
      & (
        (df["top_wick_pct_4h"] < 0.06)
        | (df["rsi_3"] > 36.0)
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 4h red with top wick, 15m & 1h & 4h & 1d still high, 1h & 4h & 1d downtrend
      & (
        (df["change_pct_4h"] > -0.01)
        | (df["top_wick_pct_4h"] < 0.02)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d green, 5m & 15m downmove, 15m & 1h & 4h & 1d still high, 1h downtrend, drop in last 12 days
      & (
        (df["change_pct_1d"] < 0.06)
        | (df["rsi_3"] > 36.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["close"] > (df["high_max_12_1d"] * 0.8))
      )
      # 1h downtrend, 5m & 1h downmove, 15m & 1h & 4h & 1d still high, 5m & 15m downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 30.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["ema_200_dec_24"] == False)
        | (df["ema_200_dec_24_15m"] == False)
      )
      # current 1d red, 15m & 1h & 4h downtrend, 5m & 15m & 4h downmove, 1d still high, 5m & 15m downtrend
      & (
        (df["change_pct_1d"] > -0.08)
        | (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_4h"] > 26.0)
        | (df["cti_20_1d"] < -0.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_24"] == False)
        | (df["ema_200_dec_24_15m"] == False)
      )
      # current 4h green, current 1h red, 15m downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_4h"] < 0.08)
        | (df["change_pct_1h"] > -0.04)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 50.0)
      )
      # current 4h & current 1h green, 15m downmove, 15m & 1h & 4h still high, 1h & 4h downtrend
      & (
        (df["change_pct_4h"] < 0.04)
        | (df["change_pct_1h"] < 0.01)
        | (df["rsi_3_15m"] > 20.0)
        | (df["cti_20_15m"] < 0.5)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 1h red, 5m downmove, 15m & 1h & 4h high
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["rsi_3"] > 16.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 60.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] < df["res_hlevel_1h"])
      )
      # current 4h red, 1h downtrend, 5m & 15m downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_4h"] > -0.01)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
      )
      # current 1d green, 1h downtrend, 5m & 15m downmove, 4h & 1d overbought
      & (
        (df["change_pct_1d"] < 0.06)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 70.0)
      )
      # 15m & 1h & 4h downtrend, 15m downmove, 15m still high, 1d overbought, 1h & 1d downtrend
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1d downtrend, 5m & 15m downmove, 15m & 1h & 4h still high, 1h & 4h downtrend
      & (
        (df["not_downtrend_1d"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 15m & 1h & 4h & 1d downtrend, 15m downmove, 15m & 1h & 4h & 1d still high, 1h & 1d downtrend
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 30.0)
        | (df["rsi_14_4h"] < 30.0)
        | (df["rsi_14_1d"] < 30.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d red, 1d downtrend, 5m downmove, 15m still high, 1h & 4h downtrend
      & (
        (df["change_pct_1d"] > -0.08)
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 15m & 4h & 1d downtrend, 5m & 15m & 4h & 1d downmove, 1d still high, 1h downtrend
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_4h"] > 20.0)
        | (df["rsi_3_1d"] > 20.0)
        | (df["cti_20_1d"] < -0.7)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 1d top wick, 5m & 15m downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["top_wick_pct_1d"] < 0.02)
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < -0.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
      )
      # 15m & 1h & 1d downtrend, 15m & 1h & 1d downmove, 1h downtrend
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["is_downtrend_3_1d"] == False)
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_3_1d"] > 26.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 1d red, 5m & 15m downmove, 1h & 4h & 1d still high, 1h downtrend
      & (
        (df["change_pct_1d"] > -0.02)
        | (df["rsi_3"] > 36.0)
        | (df["rsi_3_1d"] > 30.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 4h green, 5m & 15m downmove, 15m & 1h & 4h & 1d high, pump in last 6 days
      & (
        (df["change_pct_4h"] < 0.04)
        | (df["rsi_3"] > 36.0)
        | (df["rsi_3_15m"] > 36.0)
        | (df["cti_20_15m"] < 0.5)
        | (df["rsi_14_15m"] < 46.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 70.0)
        | (df["hl_pct_change_6_1d"] < 0.9)
      )
      # current 1d red with top wick, 1h downtrend, 5m & 1h downmove, 15m & 1h & 4h & 1d still high, 1d downtrend
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["top_wick_pct_1d"] < 0.04)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 30.0)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 4h & 1d downtrend, 5m downmove, 15m & 1h & 4h & 1d still high, 4h & 1d downtrend
      & (
        (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 36.0)
        | (df["cti_20_15m"] < -0.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < -0.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d red, 4h downtrend, 5m & 15m & 1d downmove, 1h & 1d high, 1h downtrend
      & (
        (df["change_pct_1d"] > -0.08)
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1d"] > 20.0)
        | (df["cti_20_1h"] < 0.7)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 5m downmove, 15m & 1h & 4h still high, 4h low, 1h & 1d downtrend
      & (
        (df["rsi_3"] > 20.0)
        | (df["rsi_14_15m"] < 33.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["r_480_4h"] > -80.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 1d downtrend, 5m downmove, 15m & 1h & 4h still high, 1h & 4h low, 1h & 4h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 16.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["r_480_1h"] > -80.0)
        | (df["r_480_4h"] > -85.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 1d green, 1h downtrend, 15m & 1h downmove, 1h & 4h & 1d stil high, 4h low
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
        | (df["r_480_4h"] > -75.0)
        | (df["close"] > df["bb20_2_low_15m"])
      )
      # 1h & 4h & 1d downtrend, 1d downmove, 15m & 1h & 1d still high, 1h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["is_downtrend_3_1d"] == False)
        | (df["rsi_3_1d"] > 30.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 4h & 1d downtrend, 5m & 15m downmove, 15m & 1h still high, 1h & 4d downtrend
      & (
        (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_4h"] > 16.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 1d red, 5m & 15m downmove, 15m & 1h & 4h high
      & (
        (df["change_pct_1d"] > -0.12)
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 36.0)
        | (df["cti_20_15m"] < 0.5)
        | (df["rsi_14_15m"] < 46.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 50.0)
      )
      # current 1d & 4h red, 4h & 1d downtrend, 5m & 1h & 4h & 1d downmove, 1h downtrend
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["change_pct_4h"] > -0.08)
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_3_4h"] > 26.0)
        | (df["rsi_3_1d"] > 16.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # previous 5m red, 1d downtrend, 5m & 15m & 4h & 1d downmove, 1h low, 1h & 4h downtrend
      & (
        (df["change_pct"].shift(1) > -0.02)
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_4h"] > 36.0)
        | (df["r_480_1h"] > -80.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 4h green, current 1h red, 15m & 1h & 4h still high, 1h & 4h & 1d downtrend
      & (
        (df["change_pct_4h"] < 0.04)
        | (df["change_pct_1h"] > -0.02)
        | (df["not_downtrend_1d"])
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < -0.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 1d downtrend, 15m downmove, 1d still high, 1h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["is_downtrend_3_1d"] == False)
        | (df["rsi_3_15m"] > 16.0)
        | (df["cti_20_1d"] < -0.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 4h green with top wick, current 1d top wick, 15m downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_4h"] < 0.02)
        | (df["top_wick_pct_4h"] < 0.02)
        | (df["top_wick_pct_1d"] < 0.06)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < -0.7)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < -0.5)
        | (df["rsi_14_1d"] < 40.0)
      )
      # current 4h top wick, 15m & 1d downmove, 15m & 1h & 4h still high, 1h & 4h * 1d downtrend
      & (
        (df["top_wick_pct_4h"] < 0.04)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_3_1d"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 5m red, 1h & 1d downtrend, 5m downmove, 15m & 1h & 4h & 1d stil high
      & (
        (df["change_pct"] > -0.02)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["is_downtrend_3_1d"] == False)
        | (df["rsi_3"] > 12.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 36.0)
        | (df["rsi_14_1d"] < 36.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
      )
      # 15m & 1h downtrend, 5m & 15m downmove, 15m & 1h & 4h & 1d still high, 1d downtrend
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 1d downtrend, 5m & 15m & 4h & 1d downmove, 1d high, 1h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_3_1d"] > 30.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 40.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 1h downtrend, 5m & 15m downmove, 1h & 4h & 1d still high, 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 4h green with top wick, 5m & 15m downmove, 15m & 1h & 4h high, 1h & 4h & 1d downtrend
      & (
        (df["change_pct_4h"] < 0.02)
        | (df["top_wick_pct_4h"] < 0.02)
        | (df["rsi_3"] > 36.0)
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["rsi_14_1h"] < 60.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 4h downtrend, 5m & 1h & 4h downmove, 15m & 1h & 4h still high, 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 30.0)
        | (df["rsi_14_4h"] < 36.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 4h downtrend, 5m & 15m downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 36.0)
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 36.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 50.0)
      )
      # current 1d green, 1h downtrend, 15m downmove, 1h & 4h & 1d high
      & (
        (df["change_pct_1d"] < 0.01)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 60.0)
        | (df["r_480_4h"] < -20.0)
        | (df["close"] > df["sup_level_1h"])
      )
      # current 1d green, 5m & 15m downmove, 1h & 4h & 1d high, 1h downtrend
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_14_15m"] < 50.0)
        | (df["rsi_14_1h"] < 60.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 1d green, 5m downmove, 5m & 1h & 4h & 1d high
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["rsi_3"] > 10.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
      )
      # 1h downtrend, 1h & 4h downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_3_4h"] > 26.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["sup_level_1h"])
      )
      # 1h & 4h & 1d downtrend, 5m & 1h dowmove, 15m stil high, 1h & 4h low, 1h & 4h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["r_480_1h"] > -75.0)
        | (df["r_480_4h"] > -90.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 5m & 15m downmove, 1d still high, 1d downtrend
      & (
        (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 4.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 1h downtrend, 15m & 1h downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      # 15m downtrend, 5m & 15m downmove, 15m & 1h & 4h still high, 4h downtrend
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_3"] > 36.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 1d red, previous 1d green, 1h downtrend, 15m & 1h & 4h still high, 4h downtrend
      & (
        (df["change_pct_1d"] > -0.06)
        | (df["change_pct_1d"].shift(288) < 0.12)
        | (df["not_downtrend_1h"])
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 40.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 1h downtrend, 15m & 1h & 4h downmove, 4h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 8.0)
        | (df["rsi_3_4h"] > 26.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 5m & 1h downmove, 1h & 4h & 1d high
      & (
        (df["rsi_3"] > 10.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["sup_level_1h"])
      )
      # 1d downtrend, 5m & 15m & 1d downmove, 15m still high, 1h & 4h downtrend
      & (
        (df["not_downtrend_1d"])
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1d"] > 20.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 1h red, previous 1h green, 15m downmove, 1h & 4h high, 1h downtrend
      & (
        (df["change_pct_1h"] > -0.06)
        | (df["change_pct_1h"].shift(12) < 0.06)
        | (df["rsi_3_15m"] > 26.0)
        | (df["cti_20_1h"] < 0.7)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 1d green with top wick, 5m downmove, 15m & 1h & 4h stil high, 4h low, 1h & 4h downtrend
      & (
        (df["change_pct_1d"] < 0.06)
        | (df["top_wick_pct_1d"] < 0.06)
        | (df["rsi_3"] > 30.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["r_480_4h"] > -75.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 1h & 4h & 1d downtrend, 5m & 1h downmove, 15m & 1h still high, 1h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_1d"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 1h & 4h red, 1h & 4h downtrend, 15m & 1h & 4h downmove, 1d stil high
      & (
        (df["change_pct_1h"] > -0.04)
        | (df["change_pct_4h"] > -0.04)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      # 4h downtrend, 5m & 15m & 1h & 4h downmove, 1d still high, 5m low, 5m & 15m downtrend, drop in last 12 hours
      & (
        (df["not_downtrend_4h"])
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_3_4h"] > 36.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480"] > -80.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_24"] == False)
        | (df["ema_200_dec_24_15m"] == False)
        | (df["close"] > (df["high_max_12_1h"] * 0.86))
      )
      # 1h & 1d downtrend, 5m & 15m & 1d downmove, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1d"] > 20.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d green, current 4h red, 1h downtrend, 1h downmove, 5m & 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["change_pct_4h"] > -0.04)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14"] < 36.0)
        | (df["rsi_14_15m"] < 33.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
      )
      # 1h downtrend, 5m & 15m downmove, 15m & 1h & 4h still high, 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 4h downtrend, 4h & 1d downmove, 15m & 1d still high, 1h downtrend, drop in last 6 days
      & (
        (df["not_downtrend_4h"])
        | (df["rsi_3_4h"] > 26.0)
        | (df["rsi_3_1d"] > 26.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["close"] > (df["high_max_6_1d"] * 0.6))
      )
      # current 4h red, 1h downtrend, 1h dowmove, 1h & 4h & 1d still high
      & (
        (df["change_pct_4h"] > -0.04)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 20.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < -0.5)
        | (df["rsi_14_1d"] < 46.0)
      )
      # current 4h green with top wick, 1h downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_4h"] < 0.02)
        | (df["top_wick_pct_4h"] < 0.08)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 70.0)
        | (df["cti_20_1d"] < -0.5)
        | (df["rsi_14_1d"] < 46.0)
      )
      # 1h & 4h downtrend, 1h & 4h downmove, 4h & 1d stil high
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 60.0)
        | (df["close"] > df["sup_level_1h"])
      )
      # current 1d green, current 1h  red, 15m & 1h & 4h & 1d still high, 4h high
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["change_pct_1h"] > -0.02)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 60.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 65.0)
        | (df["r_480_4h"] < -16.0)
      )
      # 1h & 4h & 1d downtrend, 15m & 1h & 4h & 1d downmove, 15m still high, 1h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_3_1d"] > 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 1h downtrend, 5m & 15m downmove, 1h & 4h & 1d still high, 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 4h & 1d downtrend, 15m downmove, 15m & 1h & 4h & 1d still high, 1h & 4h downtrend
      & (
        (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["cti_20_15m"] < -0.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < -0.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 15m & 1d downtrend, 15m & 1d downmove, 1h high, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1d"] > 10.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 50.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d long green, 1h downtrend, 15m & 1h downmove, 1h & 4h & 1d still high
      & (
        (df["change_pct_1d"] < 0.26)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 60.0)
        | (df["close"] > df["sup_level_1h"])
      )
      # current 1d red, 15m downtrend, 15m downmove, 1h & 4h & 1d still high
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["not_downtrend_15m"])
        | (df["rsi_3_15m"] > 8.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 60.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      # 1h & 4h & 1d downtrend, 1h & 1d downmove, 5m & 15m still high, 5h low, 1h & 4h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_3_1d"] > 30.0)
        | (df["rsi_14"] < 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["r_480_4h"] > -75.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 15m downmove, 15m & 1h & 4h & 1d high
      & (
        (df["rsi_3_15m"] > 26.0)
        | (df["cti_20_15m"] < -0.5)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 70.0)
      )
      # current 1d red, 1h & 4h downtrend, 1h & 4h downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_1d"] > -0.08)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 30.0)
        | (df["rsi_14_4h"] < 36.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
      )
      # 1h downtrend, 1h downmove, 5m & 15m & 1h & 4h & 1d still high, 4h high
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14"] < 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < -0.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_4h"] < -20.0)
      )
      # current 4h red, previous 4h green, 15m & 1h downtrend, 15m & 1h downmove, 4h high, 1h downtrend
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["change_pct_4h"].shift(48) < 0.04)
        | (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 12.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 5m & 15m downmove, 15m & 1h & 4h & 1d high
      & (
        (df["rsi_3"] > 36.0)
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      # 1h & 4h downtrend, 1h & 4h downmove, 1h & 4h & 1d stil high
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_1h"] > 10.0)
        | (df["rsi_3_4h"] > 36.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["rsi_14_1h"] < 30.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["sup_level_1h"])
      )
      # 5m & 15m downmove, 1h & 4h & 1d still high, 5m low, 1h downtrend
      & (
        (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 36.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
        | (df["r_480"] > -90.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 4h green, 1h downtrend, 15m & 1h downmove, 1h & 4h & 1d still high
      & (
        (df["change_pct_4h"] < 0.04)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["sup_level_1h"])
      )
      # 1h downtrend, 1h downmove, 5m & 15m & 1h & 4h & 1d still high
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14"] < 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
      )
      # current 1d green, 1h downtrend, 1h downmove, 1h & 4h still high, 4h & 1d downtrend
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 12.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 4h green, 15m downmove, 15m & 1h & 4h still high, 4h low, 1h & 4h & 1d downtrend
      & (
        (df["change_pct_4h"] < 0.02)
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["r_480_4h"] > -85.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d green with top wick, 1h downmove, 15m & 1h & 4h & 1d still high, drop in last 6 days
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > (df["high_max_6_1d"] * 0.8))
      )
      # 15m & 1h & 4h downtrend, 15m & 1h & 4h downmove, 1h downtrend
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_15m"] > 4.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 4h & 1d downtrend, 5m downmove, 15m & 1h & 4h & 1d still high, 4h downtrend
      & (
        (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 1h downtrend, 5m downmove, 15m & 1h & 4h still high, 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 4h downtrend, 15m & 1h downmove, 4h & 1d stil high, 5m low
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480"] > -80.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      # 1h downtrend 15m & 1h downmove, 4h & 1d still high, 4h low, 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 40.0)
        | (df["r_480_4h"] > -75.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d green, 15m & 1h downmove, 5m & 15m & 1h & 4h & 1d still high, 1d downtrend
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_14"] < 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 40.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 1d downtrend, 15m & 1h & 4h & 1d downmove, 1d still high, 5m & 15m & 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_3_4h"] > 36.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_24"] == False)
        | (df["ema_200_dec_24_15m"] == False)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 4h & 1d downtrend, 15m & 1h & 4h & 1d downmove, 1h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_3_1d"] > 10.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 4h & 1d downtrend, 15m & 1h & 4h & 1d downmove, 1d still high, 5m & 15m & 1h downtrend, drop in last 6 days
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_3_4h"] > 26.0)
        | (df["rsi_3_1d"] > 20.0)
        | (df["cti_20_1d"] < -0.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_24"] == False)
        | (df["ema_200_dec_24_15m"] == False)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["close"] > (df["high_max_6_1d"] * 0.6))
      )
      # current 4h red, previous 4h greem, 1h downtrend, 15m & 1h downmove, 1h & 4h & 1d still high, drop in last 6 days
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["change_pct_4h"].shift(48) < 0.01)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > (df["high_max_6_1d"] * 0.75))
      )
      # 1h downtrend, 15m & 1h & 4h downmove, 1h & 4h & 1d still high, 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 15m & 4h downtrend, 5m & 15m & 1h & 4h downmove, 4h & 1d still high
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_3_4h"] > 20.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 70.0)
        | (df["close"] > df["sup_level_1h"])
      )
      # current 1d green with top wick, 1h downtrend, 1h downmove, 5m & 15m & 1h & 4h & 1d still high, 5m downtrend
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.04)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14"] < 36.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["ema_200_dec_24"] == False)
      )
      # 1d downtrend, 5m & 15m & 1h & 4h & 1d still high, 4h low, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_1d"])
        | (df["rsi_14"] < 46.0)
        | (df["rsi_14_15m"] < 50.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 30.0)
        | (df["rsi_14_1d"] < 30.0)
        | (df["r_480_4h"] > -90.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d red, previous 1d green, 1h & 4h downmove, 15m & 4h &1d still high
      & (
        (df["change_pct_1d"] > -0.08)
        | (df["change_pct_1d"].shift(288) < 0.12)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["sup_level_1h"])
      )
      # 15m & 1h & 1d downtrend, 15m & 1h & 6h downmove
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_3_1d"] > 6.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      # 1h & 1d downtrend, 1d downmove, 15m stil high
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_1d"] > 6.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      # current 1d red with top wick, 1h & 4h downtrend, 15m & 1d downmove, 15m & 1h & 4h & 1d still high, 1h downtrend
      & (
        (df["change_pct_1d"] > -0.01)
        | (df["top_wick_pct_1d"] < 0.02)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1d"] > 36.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 30.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 1d red, current 4h red, previous 4h green, 5m & 15m & 1h & 4h downmove, 1h & 4h & 1d stil high
      & (
        (df["change_pct_1d"] > -0.01)
        | (df["change_pct_4h"] > -0.01)
        | (df["change_pct_4h"].shift(48) < 0.01)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 36.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["close"] > df["sup_level_1h"])
      )
      # 1h & 1d downtrend, 15m & 1h & 1d downmove, 4h low, 1h & 4h & 1d dowqntrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_3_1d"] > 16.0)
        | (df["r_480_4h"] > -90.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 1d downtrend, 5m & 15m downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 6.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 36.0)
        | (df["rsi_14_1d"] < 36.0)
        | (df["close"] > df["sup_level_4h"])
      )
      # current 1d green with top wick, current 4h red, 5m & 15m downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_1d"] < 0.02)
        | (df["top_wick_pct_1d"] < 0.02)
        | (df["change_pct_4h"] > -0.01)
        | (df["rsi_3"] > 16.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
      )
      # current 1d red, previous 1d green, 15m downmove, 5m & 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_1d"] > -0.12)
        | (df["change_pct_1d"].shift(288) < 0.12)
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_14"] < 30.0)
        | (df["cti_20_15m"] < -0.5)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["sup_level_1h"])
      )
      # 1h downtrend, 5m & 15m downmove, 15m & 1d high, 1h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 4.0)
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 4h green, current 1h red, 5m downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_4h"] < 0.01)
        | (df["change_pct_1h"] > -0.00)
        | (df["rsi_3"] > 26.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
      )
      # current 1d green, current 4h top wick, 5m & 15m downmove, 15m & 1h & 4h & 1d still high, pump in last 6 days, drop in last 6 days
      & (
        (df["change_pct_1d"] < 0.24)
        | (df["top_wick_pct_4h"] < 0.08)
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_14_15m"] < 33.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["hl_pct_change_6_1d"] < 0.9)
        | (df["close"] > (df["high_max_6_1d"] * 0.70))
      )
      # 1h & 4h & 1d downtrend, 5m & 15m downmove, 1h low, 1h & 4h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 30.0)
        | (df["rsi_14"] > 30.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["r_480_1h"] > -75.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 1d green with top wick, current 1h red, previous 1h greem, 15m & 1h & 4h & 1d stil high
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["change_pct_1h"] > -0.03)
        | (df["change_pct_1h"].shift(12) < 0.03)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 60.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
      )
      # current 1d green with top wick, previous 4h red, 1h downtrend, 5m & 15m downmove, 15m & 1h & 4h still high, 4h downtrend
      & (
        (df["change_pct_1d"] < 0.03)
        | (df["top_wick_pct_1d"] < 0.03)
        | (df["change_pct_4h"].shift(48) > -0.04)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 36.0)
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 50.0)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 1h downtrendm 5m & 1hm & 1h & 4h downmove, 1h & 4h & 1d still high
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_3_4h"] > 26.0)
        | (df["rsi_14_1h"] < 30.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      # 1h & 1d downtrendm 1h & 1d downmove, 5m & 15m & 1h & 4h satill high, 4h low, 1h & 4h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_3_1d"] > 26.0)
        | (df["rsi_14"] < 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["r_480_4h"] > -85.0)
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 15m downmove, 5m & 1h & 4h & 1d still high, 4h low, 4h & 1d downtrend
      & (
        (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14"] < 30.0)
        | (df["rsi_14_1h"] < 30.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < -0.5)
        | (df["rsi_14_1d"] < 40.0)
        | (df["r_480_4h"] > -75.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 4h & 1d downtrend, 1h & 4h & 1d downmove, 1h & 4h low, 1h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_3_1d"] > 16.0)
        | (df["r_480_1h"] > -75.0)
        | (df["r_480_4h"] > -80.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1d green, current 1h red, 15m & 1h downmove, 15m & 1h & 4h & 1d still high, 1d downtrend
      & (
        (df["change_pct_1d"] < 0.06)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_3_15m"] > 40.0)
        | (df["rsi_3_1h"] > 40.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 65.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 1d downtrend, 5m downmove, 15m & 1h still high, 1h & 4h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 5m downmove, 15m & 1h & 4h & 1d still high, 4h high
      & (
        (df["rsi_3"] > 30.0)
        | (df["cti_20_15m"] < -0.5)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 70.0)
        | (df["r_480_4h"] < -30.0)
        | (df["close"] > df["sup_level_1h"])
      )
      # current 1d red, 4h & 1d downtrend, 15m & 1d downmove, 5m & still high, 4h low, drop in last 6 days
      & (
        (df["change_pct_1d"] > -0.08)
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_1d"] > 36.0)
        | (df["rsi_14"] < 26.0)
        | (df["r_480_1h"] > -80.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > (df["high_max_6_1d"] * 0.75))
      )
      # current 1d red, previous 1d green, 15m downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_1d"] > -0.02)
        | (df["change_pct_1d"].shift(288) < 0.08)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 60.0)
        | (df["close"] > df["sup_level_1h"])
      )
      # current 1d red, previous 1d green, 1h downtrend, 5m & 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_1d"] > -0.01)
        | (df["change_pct_1d"].shift(288) < 0.06)
        | (df["not_downtrend_1h"])
        | (df["rsi_14"] < 33.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["sup_level_1h"])
      )
      # 1h downtrend, 1h downmove, 5m & 15m & 1h & 4h & 1d stil high, 4h high
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_14"] < 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 60.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_4h"] < -30.0)
        | (df["close"] > df["bb20_2_low_15m"])
      )
      # 15m & 1h downtrend, 15m & 1h downmove, 5m & 15m & 1h & 4h still high, 4h & 1d downtrend
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 10.0)
        | (df["rsi_14"] < 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 1d downtrend, 1d downmove, 5m & 15m & 1d still high, 1h low, drop in last 6 days
      & (
        (df["not_downtrend_1h"])
        | (df["is_downtrend_3_1d"] == False)
        | (df["rsi_3_1d"] > 30.0)
        | (df["rsi_14"] < 30.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["r_480_1h"] > -75.0)
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > (df["high_max_6_1d"] * 0.70))
      )
      # 1h & 1d downtrend, 15m & 1h & 1d downmove, 1h & 4h low, 1h & 4h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_3_1d"] > 10.0)
        | (df["r_480_1h"] > -90.0)
        | (df["r_480_4h"] > -90.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 5m downmove, 15m & 1h & 4h still high, 4h love, 1h downtrend
      & (
        (df["rsi_3"] > 4.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["r_480_1h"] > -85.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 1h downtrend, 1h downmove, 15m & 1h & 4h stil high, 4h low, 4h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 46.0)
        | (df["r_480_4h"] > -85.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 4h green with top wick, 1d downtrend, 15m & 1d downmove, 5m & 15m & 1h & 4h still high, 1h downtrend
      & (
        (df["change_pct_4h"] < 0.03)
        | (df["top_wick_pct_4h"] < 0.03)
        | (df["not_downtrend_1d"])
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_3_1d"] > 10.0)
        | (df["rsi_14"] < 36.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 1d downtrend, 5m & 15m & 1d downmove, 1h still high, 1h low, 1h downtrend, drop in last 6 days
      & (
        (df["not_downtrend_1d"])
        | (df["rsi_3"] > 6.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1d"] > 20.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["r_480_1h"] > -80.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["close"] > (df["high_max_6_1d"] * 0.75))
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_14"] < 30.0)
        | (df["cti_20_15m"] < -0.5)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 4h green, 1d downtrend, 15m & 1h & 4h still high, 1h & 4h downtrend
      & (
        (df["change_pct_4h"] < 0.03)
        | (df["not_downtrend_1d"])
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["r_14_1h"] < -20.0)
        | (df["r_14_4h"] < -20.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 15m downtrend, 15m downmove, 5m & 15m & 1h & 4h & 1d still high
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14"] < 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["sup_level_1h"])
      )
      # 5m downmove, 15m & 1h & 4h & 1d high
      & (
        (df["rsi_3"] > 10.0)
        | (df["cti_20_15m"] < -0.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["cti_20_1h"] < 0.8)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["bb20_2_low_15m"])
      )
      # current 4h red, previous 4h green, 5m & 1h downmove, 15m & 1h & 4h & 1d still high, drop in last 6 days
      & (
        (df["change_pct_4h"] > -0.01)
        | (df["change_pct_4h"].shift(48) < 0.01)
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > (df["high_max_6_1d"] * 0.80))
      )
      # current 1d top wick, 1h downtrend, 5m & 1h downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["top_wick_pct_1d"] < 0.08)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      # 5m & 15m downmove, 15m & 1h & 4h still high, 4h low, 1h downtrend
      & (
        (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["r_480_1h"] > -80.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 5m & 15m downmove, 1h & 4h & 1d still high, 1h high
      & (
        (df["rsi_3"] > 36.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
        | (df["r_480_1h"] < -30.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      # 1h downtrend, 5m downmove, 15m & 1h still high, 1h low, 1h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["r_480_1h"] > -85.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 1h & 4h downtrend, 5m & 15m & 4h downmove, 15m & 1h & 4h still high
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_4h"] > 26.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 30.0)
        | (df["rsi_14_4h"] < 30.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      # 1h downtrend, 5m & 15m downmove, 15m & 1h & 4h & 1d still high, 1h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 4h & 1d downtrend, 5m & 4h & 1d downmove, 1h downtrend
      & (
        (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_3_1d"] > 6.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # curent 1d red, previous 1d green, 1h downtrend, 15m & 1h & 4h downmove, 4h still high
      & (
        (df["change_pct_1d"] > -0.06)
        | (df["change_pct_1d"].shift(288) < 0.06)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["close"] > df["sup_level_1h"])
      )
      # 1h downtrend, 1h downmove, 15m & 1h & 4h & 1d still high, 1h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 12.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["sup_level_1h"])
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 1d downtrend, 15m & 1d downmove, 15m & 1h & 4h still high, 1h downtrend
      & (
        (df["not_downtrend_1d"])
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_3_1d"] > 36.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 36.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 1h red, previous 1h red, 5m & 15m & 1h & 4h still high, 1h & 4h downtrend
      & (
        (df["change_pct_1h"] > -0.04)
        | (df["change_pct_1h"].shift(12) < 0.01)
        | (df["not_downtrend_1h"])
        | (df["rsi_14"] < 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 1d red, previous 1d green, current 4h green, 1h downtrend, 5m downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_1d"] > -0.01)
        | (df["change_pct_1d"].shift(288) < 0.01)
        | (df["change_pct_4h"] < 0.02)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      # 4h downtrend, 15m & 4h & 1d downmove, 1h & 1d still high, 1h downtrend, drop in last 6 days
      & (
        (df["not_downtrend_4h"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_4h"] > 20.0)
        | (df["rsi_3_1d"] > 26.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["close"] > (df["high_max_6_1d"] * 0.70))
      )
      # 1d downtrend, 1d downmove, 15m & 1h & 4h still high, 4h low, 1h & 4h downtrend
      & (
        (df["not_downtrend_1d"])
        | (df["rsi_3_1d"] > 30.0)
        | (df["cti_20_15m"] < -0.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["r_480_4h"] > -80.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 4h red with top wick, 1h downtrend, 1h downmove, 15m & 1h & 4h & 1d stil high, 1d downtrend, drop in last 6 days
      & (
        (df["change_pct_4h"] > -0.03)
        | (df["top_wick_pct_4h"] < 0.03)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_4_1d"] == False)
        | (df["close"] > (df["high_max_6_1d"] * 0.70))
      )
      & (
        (df["not_downtrend_4h"])
        | (df["rsi_3"] > 36.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 36.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 40.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["close"] > (df["high_max_6_1d"] * 0.60))
      )
      # current 1d green, 15m & 1g downmove, 1h & 4h still high, 1h & 4h downtrend
      & (
        (df["change_pct_1d"] < 0.06)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 15m downmove, 1h & 4h & 1d high, 1h & 4h high
      & (
        (df["rsi_3_15m"] > 40.0)
        | (df["cti_20_1h"] < -0.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 70.0)
        | (df["r_480_1h"] < -25.0)
        | (df["r_480_4h"] < -20.0)
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["close"] > df["bb20_2_low_15m"])
      )
      # 4h downtrend, 5m downmove, 15m & 1h & 4h & 1d still high, 1h downtrend
      & (
        (df["not_downtrend_4h"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < -0.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 1h downtrend, 5m & 15m & 1h downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_14"] > 36.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["close"] > df["sup_level_1h"])
      )
      # 1h downtrend, 5m downmove, 5m & 15m & 1h still high, 1h low, 1h downtrend
      & (
        (df["not_downtrend_1d"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_14"] < 30.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["r_480_1h"] > -85.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 1h & 4h downtrend, 5m & h downmove, 15m & 1h & 4h & 1d stil high
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      # current 1d red, previous 1d green, 1h & 4h downtrend, 15m & 1h downmove, 15m & 1n & 4h & 1d still high
      & (
        (df["change_pct_1d"] > -0.02)
        | (df["change_pct_1d"].shift(288) < 0.02)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["sup_level_4h"])
      )
      # 1h downtrend, 1h downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 30.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      # 5m & 15m & 1h downmove, 5m & 1h & 4h & 1d still high, 1d downtrend
      & (
        (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h downtrend, 1h downmove, 1h & 4h & 1d still high, 1h & 4h high
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_1h"] < -20.0)
        | (df["r_480_4h"] < -20.0)
        | (df["close"] > df["bb20_2_low_1h"])
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["close"] > df["sup_level_1h"])
      )
      # 1h & 4h downtrend, 5m & 15m & 1h & 4h downmove, 1h & 4h & 1d still high
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_3_4h"] > 36.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      # 1h downtrend, 1h downmove, 5m & 15m & 1h & 4h & 1d still high
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 12.0)
        | (df["rsi_14"] < 40.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["close"] > df["sup_level_1h"])
      )
      # 1h & 1d downtrend, 15m & 1h downmove, 15m & 1h & 4h still high, 1h low, 1h & 4h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 30.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["r_480_1h"] > -85.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # current 4h green, 1h downtrend, 15m & 1h downmove, 15m & 1h & 4h still high
      & (
        (df["change_pct_4h"] < 0.02)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
      )
      # 1h & 1d downtrend, 15m & 1h downmove, 5m & 15m & 1h & 4h still high, 1h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14"] < 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 46.0)
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["ema_200_dec_48_1h"] == False)
      )
      # current 4h red, previous 4h green, 1h downtrend, 1h downmove, 5m & 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_4h"] > -0.03)
        | (df["change_pct_4h"].shift(48) < 0.03)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14"] < 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["rsi_14_1d"] < 46.0)
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
      )
      # 1h & 1d downtrend, 1h & 4h & 1d downmove, 15m still high, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_3_4h"] > 36.0)
        | (df["rsi_3_1d"] > 36.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 5m & 1h & 4h & 1d still high, drop in last 6 days
      & (
        (df["rsi_14"] < 30.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 60.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 70.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["close"] > df["sup_level_1h"])
        | (df["hl_pct_change_6_1d"] < 0.9)
      )
      # 1h & 1d downtrend, 5m & 1h downmove, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # current 1h red with top wick, 1h downtrend, 15m & 1h downmove, 5m & 15m & 1h & 4h still high, 1h downtrend
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["top_wick_pct_1h"] < 0.01)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_14"] < 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      # 4h downtrend, 4h downmove, 5m & 15m & 1h & 4h & 1d still high, 1h high
      & (
        (df["not_downtrend_4h"])
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_14"] < 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_1h"] < -30.0)
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      # 1h & qd downtrend, 5m & 15m & 1h downmove, 4h & 1d still high
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_14_4h"] < 36.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      # 5m & 15m & 1h downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 60.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["close"] > df["sup_level_1h"])
      )
      # current 1d red, current 4h green, 1d downtrend, 15m downmove, 15m & 1h still high, 1h downtrend, drop in last 6 days
      & (
        (df["change_pct_1d"] > -0.06)
        | (df["change_pct_4h"] < 0.06)
        | (df["not_downtrend_1d"])
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < 0.7)
        | (df["rsi_14_1h"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["close"] > (df["high_max_6_1d"] * 0.85))
      )
      # 5m downmove, 5m & 15m & 1h & 4h & 1d still high, pump in last 6 days
      & (
        (df["rsi_3"] > 26.0)
        | (df["rsi_14"] < 30.0)
        | (df["cti_20_15m"] < -0.5)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < -0.5)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["close"] > df["sup_level_1h"])
        | (df["hl_pct_change_6_1d"] < 0.5)
      )
      # 1h & 4h & 1d downtrend, 5m & 15m & 1h downmove, 4h low, 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["r_480_4h"] > -85.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h downtrend, 5m & 15m downmove, 15m & 1h & 4h & 1d still high, pump in last 6 days
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["hl_pct_change_6_1d"] < 0.8)
      )
      # 15m & 1h downmove, 5m & 15m & 1h & 4h & 1d still high, 1h & 4h high
      & (
        (df["rsi_3_15m"] > 40.0)
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_14"] < 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["r_480_1h"] < -30.0)
        | (df["r_480_4h"] < -15.0)
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["close"] > df["sup_level_1h"])
      )
      # current 4h red, previous 4h green, 5m & 1hm downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_4h"] > -0.00)
        | (df["change_pct_4h"].shift(48) < 0.00)
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      # current & previous 1h red, 5m & 15m downmove, 15m & 1h & 4h still high, 4h high
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["change_pct_1h"].shift(12) > -0.01)
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["cti_20_1h"] < 0.7)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["r_480_4h"] < -30.0)
      )
      # current 1h red, previous 1h green, 5m & 15m downmove, 5m & 15m still high, 1h pumped
      & (
        (df["change_pct_1h"] > -0.02)
        | (df["change_pct_1h"].shift(12) < 0.02)
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14"] < 30.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["cti_20_1h"] < 0.7)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_1h"].shift(12) < 70.0)
      )
      # current 4h green, current 1h red, 15m & 1h downmove, 4h & 1d still high, 4h high
      & (
        (df["change_pct_4h"] < 0.01)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 60.0)
        | (df["r_480_4h"] < -5.0)
      )
      # 1h downtrend, 1h downmove, 4h & 1d still high, 4h high
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 60.0)
        | (df["r_480_4h"] < -5.0)
      )
      # 1h downtrend, 1h downmove, 15m & 1h & 4h & 1d stil high, 4h high, pump in last 6 days
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 70.0)
        | (df["r_480_4h"] < -30.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["hl_pct_change_6_1d"] < 0.9)
      )
      # current 4h red, previous 4h green, current 1h red, 15m & 1h downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_4h"] > -0.04)
        | (df["change_pct_4h"].shift(48) < 0.04)
        | (df["change_pct_1h"] > -0.02)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 60.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["close"] > df["sup_level_4h"])
      )
      # current 1d red, current 1h red, previous 1h green, 5m & 15m downmove, 15m & 1h & 1d still high, 1d downtrend
      & (
        (df["change_pct_1d"] > -0.03)
        | (df["change_pct_1h"] > -0.02)
        | (df["change_pct_1h"].shift(12) < 0.02)
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_1d"] < 46.0)
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h & 4h & 1d downtrend, 1h & 1d downmove, 1h low, 1h & 4h downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_1h"] > 10.0)
        | (df["rsi_3_1d"] > 26.0)
        | (df["r_480_1h"] > -95.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 4h downtrend, 5m & 15m downtrend, 1h & 4h still high, 1h & 4h downtrend
      & (
        (df["not_downtrend_4h"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 40.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      # 1h downtrend, 15m & 1h downmove, 15m & 1h & 4h & 1d still high, 4h high
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 30.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_4h"] < -30.0)
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
    )

    df["global_protections_long_pump"] = (
      ((df["change_pct_4h"] < 0.12) | (df["top_wick_pct_4h"] < 0.12) | (df["rsi_14_1h"] < 70.0))
      & ((df["change_pct_1h"] > -0.04) | (df["change_pct_1h"].shift(12) < 0.04) | (df["cti_20_4h"] < 0.8))
      & ((df["change_pct_4h"] > -0.08) | (df["change_pct_4h"].shift(48) < 0.08) | (df["rsi_14_4h"].shift(48) < 70.0))
      & (
        (df["change_pct_1h"] > -0.04)
        | (df["change_pct_1h"].shift(12) < 0.01)
        | (df["cti_20_1h"] < 0.8)
        | (df["rsi_14_1h"].shift(12) < 70.0)
      )
      & (
        (df["change_pct_1h"].shift(12) > -0.04)
        | (df["change_pct_1h"].shift(24) < 0.02)
        | (df["rsi_14_1h"].shift(24) < 70.0)
      )
      & (
        (df["change_pct_1d"] > -0.02)
        | (df["change_pct_1d"].shift(288) > -0.02)
        | (df["not_downtrend_4h"])
        | (df["cti_20_1d"] < 0.8)
      )
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["change_pct_4h"].shift(48) < 0.02)
        | (df["cti_20_4h"].shift(48) < 0.8)
        | (df["rsi_14_4h"].shift(48) < 80.0)
      )
      & ((df["change_pct_1d"] > -0.04) | (df["change_pct_1d"].shift(288) < 0.12) | (df["rsi_14_1d"].shift(288) < 80.0))
      & (
        (df["change_pct_1h"] > -0.02)
        | (df["top_wick_pct_1h"] < 0.02)
        | (df["change_pct_1h"].shift(12) < 0.02)
        | (df["rsi_14_1h"].shift(12) < 80.0)
      )
      & (
        (df["change_pct_1h"] < 0.04)
        | (df["top_wick_pct_1h"] < 0.04)
        | (df["rsi_14_1h"] < 70.0)
        | (df["rsi_14_4h"] < 70.0)
      )
      & (
        (df["top_wick_pct_1d"] < 0.08)
        | (df["cti_20_1h"] < 0.7)
        | (df["cti_20_4h"] < 0.7)
        | (df["r_480_1h"] < -20.0)
        | (df["r_480_4h"] < -20.0)
      )
      & (
        (df["change_pct_1d"] < 0.18)
        | (df["top_wick_pct_1d"] < 0.18)
        | (df["top_wick_pct_4h"] < 0.08)
        | (df["cti_20_4h"] < 0.7)
      )
      & (
        (df["change_pct_4h"] > -0.12)
        | (df["change_pct_4h"].shift(48) < 0.02)
        | (df["cti_20_4h"].shift(48) < 0.5)
        | (df["rsi_14_4h"].shift(48) < 70.0)
      )
      & (
        (df["top_wick_pct_1d"] < 0.04)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 70.0)
        | (df["r_480_1h"] < -10.0)
        | (df["r_480_4h"] < -10.0)
      )
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["top_wick_pct_4h"] < 0.06)
        | (df["change_pct_4h"].shift(48) < 0.02)
        | (df["rsi_14_4h"].shift(48) < 80.0)
      )
      & (
        (df["change_pct_1d"] < 0.26)
        | (df["change_pct_4h"] > -0.10)
        | (df["rsi_14_4h"].shift(48) < 70.0)
        | (df["rsi_14_1d"] < 70.0)
      )
      & (
        (df["change_pct_1d"] < 0.26)
        | (df["top_wick_pct_1d"] < 0.12)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 70.0)
      )
      & (
        (df["change_pct_4h"] > -0.04)
        | (df["change_pct_4h"].shift(48) < 0.01)
        | (df["top_wick_pct_4h"].shift(48) < 0.06)
        | (df["change_pct_1h"] > -0.04)
        | (df["rsi_14_4h"].shift(48) < 60.0)
      )
      & (
        (df["change_pct_1d"] > -0.12)
        | (df["change_pct_1d"].shift(288) < 0.32)
        | (df["top_wick_pct_1d"].shift(288) < 0.22)
        | (df["rsi_14_1d"].shift(288) < 70.0)
      )
      & (
        (df["change_pct_4h"] < 0.12)
        | (df["top_wick_pct_4h"] < 0.08)
        | (df["change_pct_1h"] > -0.03)
        | (df["change_pct_1h"].shift(12) < 0.03)
        | (df["rsi_14_4h"] < 70.0)
      )
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["change_pct_4h"].shift(48) < 0.12)
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_14_1h"] < 70.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["r_480_4h"] < -30.0)
      )
      & (
        (df["change_pct_4h"] < 0.02)
        | (df["top_wick_pct_4h"] < 0.02)
        | (df["top_wick_pct_1h"] < 0.02)
        | (df["rsi_3"] > 20.0)
        | (df["rsi_14_1h"] < 60.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["r_480_1h"] < -20.0)
        | (df["r_480_4h"] < -20.0)
      )
      & (
        (df["change_pct_1d"] > -0.01)
        | (df["change_pct_1d"].shift(288) < 0.01)
        | (df["change_pct_1h"] > -0.01)
        | (df["change_pct_1h"].shift(12) < 0.00)
        | (df["rsi_14_1d"].shift(288) < 70.0)
        | (df["r_480_1h"] < -20.0)
        | (df["r_480_4h"] < -20.0)
      )
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["top_wick_pct_1d"] < 0.03)
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_1d"] < 60.0)
      )
      & ((df["change_pct_4h"] > -0.04) | (df["change_pct_4h"].shift(48) < 0.04) | (df["rsi_14_4h"].shift(48) < 80.0))
      & (
        (df["change_pct_1d"] < 0.30)
        | (df["top_wick_pct_4h"] < 0.06)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > (df["high_max_6_1d"] * 0.70))
      )
      & (
        (df["change_pct_4h"] < 0.08)
        | (df["change_pct_1h"] < 0.02)
        | (df["top_wick_pct_1h"] < 0.02)
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_4h"] < 60.0)
      )
      & (
        (df["change_pct_4h"] < 0.04)
        | (df["top_wick_pct_4h"] < 0.08)
        | (df["change_pct_4h"].shift(48) < 0.04)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_1h"] < 60.0)
        | (df["rsi_14_4h"] < 70.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["change_pct_4h"] > -0.02)
        | (df["change_pct_4h"].shift(48) < 0.04)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_4h"].shift(48) < 70.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_1d"] < 0.16)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["change_pct_4h"] < 0.06)
        | (df["top_wick_pct_4h"] < 0.06)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_3"] > 20.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 60.0)
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_1d"] > -0.01)
        | (df["change_pct_1d"].shift(288) > -0.04)
        | (df["top_wick_pct_1d"].shift(288) < 0.04)
        | (df["change_pct_1d"].shift(576) < 0.16)
        | (df["top_wick_pct_1d"].shift(576) < 0.08)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_1d"] > -0.00)
        | (df["top_wick_pct_1d"] < 0.16)
        | (df["change_pct_1d"].shift(288) < 0.32)
        | (df["change_pct_4h"] > -0.00)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 70.0)
      )
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["change_pct_1h"] > -0.02)
        | (df["not_downtrend_1h"])
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 70.0)
        | (df["r_480_4h"] < -20.0)
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 16.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 80.0)
        | (df["r_480_4h"] < -30.0)
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_1d"] > -0.06)
        | (df["change_pct_1d"].shift(288) < 0.24)
        | (df["top_wick_pct_1d"].shift(288) < 0.24)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
      )
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.04)
        | (df["change_pct_4h"] > -0.01)
        | (df["change_pct_1h"] > -0.01)
        | (df["change_pct_1h"].shift(12) < 0.01)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 65.0)
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_1d"] < 0.20)
        | (df["top_wick_pct_1d"] < 0.20)
        | (df["change_pct_4h"] > -0.01)
        | (df["change_pct_4h"].shift(48) < 0.01)
        | (df["cti_20_1h"] < 0.7)
        | (df["rsi_14_1h"] < 60.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_4h"].shift(48) < 70.0)
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.04)
        | (df["change_pct_4h"] > -0.04)
        | (df["change_pct_1h"] > -0.02)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_1d"] < 0.20)
        | (df["top_wick_pct_1d"] < 0.04)
        | (df["change_pct_4h"].shift(48) > -0.02)
        | (df["change_pct_4h"].shift(96) > -0.02)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_1d"] < 50.0)
      )
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["top_wick_pct_1d"] < 0.12)
        | (df["change_pct_1h"] > -0.02)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["close"] > (df["high_max_6_1d"] * 0.60))
        | (df["hl_pct_change_6_1d"] < 4.0)
      )
      & (
        (df["change_pct_1d"] < 0.32)
        | (df["top_wick_pct_1d"] < 0.12)
        | (df["change_pct_4h"] > -0.02)
        | (df["rsi_3_15m"] > 26.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_4h"] < 0.12)
        | (df["top_wick_pct_4h"] < 0.03)
        | (df["change_pct_1h"] > -0.01)
        | (df["change_pct_1h"].shift(12) > -0.01)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["r_480_4h"] < -20.0)
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_4h"] < 0.12)
        | (df["change_pct_1h"] > -0.03)
        | (df["cti_20_1h"] < 0.7)
        | (df["rsi_14_1h"] < 60.0)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 80.0)
        | (df["r_480_4h"] < -10.0)
      )
      & (
        (df["change_pct_1d"] < 0.24)
        | (df["change_pct_4h"] < 0.02)
        | (df["top_wick_pct_4h"] < 0.04)
        | (df["change_pct_1h"] > -0.02)
        | (df["rsi_14_4h"] < 75.0)
        | (df["rsi_14_1d"] < 70.0)
        | (df["r_480_4h"] < -20.0)
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_4h"] < 0.12)
        | (df["top_wick_pct_4h"] < 0.06)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_14_1h"] < 65.0)
        | (df["rsi_14_4h"] < 65.0)
        | (df["r_480_1h"] < -25.0)
        | (df["r_480_4h"] < -25.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_4h"] < 0.04)
        | (df["top_wick_pct_4h"] < 0.08)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_1h"] < 60.0)
        | (df["rsi_14_4h"] < 70.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["close"] > (df["high_max_6_1h"] * 0.88))
      )
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["top_wick_pct_1d"] < 0.04)
        | (df["change_pct_4h"] < 0.02)
        | (df["top_wick_pct_4h"] < 0.02)
        | (df["change_pct_1h"] > -0.02)
        | (df["rsi_14_4h"] < 65.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 70.0)
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_4h"] < 0.03)
        | (df["top_wick_pct_4h"] < 0.03)
        | (df["change_pct_1h"] > -0.08)
        | (df["change_pct_1h"].shift(12) < 0.02)
        | (df["rsi_14_4h"] < 65.0)
        | (df["r_480_4h"] < -15.0)
      )
      & (
        (df["change_pct_1h"] > -0.10)
        | (df["change_pct_1h"].shift(12) < 0.03)
        | (df["top_wick_pct_1h"].shift(12) < 0.03)
        | (df["rsi_14_1h"].shift(12) < 70.0)
        | (df["r_480_1h"].shift(12) < -25.0)
      )
      & (
        (df["is_downtrend_3_4h"] == False)
        | (df["change_pct_4h"] > -0.01)
        | (df["cti_20_dec_3_1h"] == False)
        | (df["cti_40_1h"] < 0.5)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_max_6_4h"] < 80.0)
        | (df["close"] > (df["high_max_12_1h"] * 0.80))
        | (df["hl_pct_change_24_1h"] < 0.5)
      )
      & (
        (df["change_pct_4h"] < 0.08)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_1d"] < 80.0)
        | (df["r_480_1h"] < -25.0)
        | (df["r_480_4h"] < -25.0)
        | (df["hl_pct_change_6_1d"] < 0.75)
      )
      & (
        (df["is_downtrend_3_4h"] == False)
        | (df["change_pct_4h"] > -0.01)
        | (df["not_downtrend_1h"])
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["close"] > (df["high_max_24_1h"] * 0.80))
        | (df["hl_pct_change_48_1h"] < 0.5)
      )
      & (
        (df["change_pct_1d"] < 0.24)
        | (df["top_wick_pct_1d"] < 0.24)
        | (df["change_pct_4h"] < 0.08)
        | (df["change_pct_1h"] > -0.01)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_4h"] < 65.0)
        | (df["rsi_14_1d"] < 65.0)
      )
      & (
        (df["top_wick_pct_4h"] < 0.08)
        | (df["change_pct_1h"] > -0.01)
        | (df["change_pct_1h"].shift(12) > -0.02)
        | (df["top_wick_pct_1h"].shift(24) < 0.08)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
      )
      & (
        (df["change_pct_4h"] > -0.06)
        | (df["change_pct_4h"].shift(48) < 0.02)
        | (df["top_wick_pct_4h"].shift(48) < 0.02)
        | (df["not_downtrend_1h"])
        | (df["rsi_14_4h"].shift(48) < 65.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 70.0)
      )
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["top_wick_pct_1d"] < 0.12)
        | (df["change_pct_4h"] < 0.06)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_3_1h"] > 26.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 75.0)
      )
      & (
        (df["change_pct_4h"] > -0.01)
        | (df["change_pct_4h"].shift(48) < 0.01)
        | (df["top_wick_pct_4h"].shift(48) < 0.02)
        | (df["cti_20_1h"] < 0.7)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"].shift(48) < 70.0)
        | (df["r_480_1h"] < -30.0)
        | (df["r_480_4h"] < -25.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["change_pct_1h"] > -0.02)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["r_480_4h"] < -30.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["close"] > (df["high_max_24_1h"] * 0.85))
        | (df["hl_pct_change_48_1h"] < 0.7)
      )
      & (
        (df["top_wick_pct_1d"] < 0.20)
        | (df["change_pct_4h"] < 0.08)
        | (df["top_wick_pct_4h"] < 0.04)
        | (df["change_pct_1h"] > -0.01)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 70.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct_4h"] > -0.01)
        | (df["change_pct_1h"] > -0.01)
        | (df["is_downtrend_3_4h"] == False)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 65.0)
        | (df["rsi_14_4h"].shift(48) < 70.0)
        | (df["rsi_14_max_6_4h"] < 80.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["close"] > (df["high_max_12_1h"] * 0.85))
        | (df["hl_pct_change_48_1h"] < 0.6)
      )
      & (
        (df["change_pct_4h"] < 0.02)
        | (df["top_wick_pct_4h"] < 0.02)
        | (df["rsi_3_15m"] > 20.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 75.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 75.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct_4h"] > -0.04)
        | (df["top_wick_pct_4h"] < 0.04)
        | (df["change_pct_4h"].shift(48) < 0.04)
        | (df["change_pct_1h"] > -0.02)
        | (df["cti_20_1h"] < 0.5)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_max_6_1d"] < 70.0)
        | (df["r_480_1h"] < -30.0)
        | (df["r_480_4h"] < -25.0)
      )
      & (
        (df["top_wick_pct_4h"] < 0.06)
        | (df["change_pct_1h"] > -0.01)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 70.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 60.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_4h"] < 0.16)
        | (df["top_wick_pct_4h"] < 0.08)
        | (df["change_pct_1h"] > -0.01)
        | (df["cti_20_1h"] < 0.7)
        | (df["rsi_14_1h"] < 60.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 70.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
      )
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["top_wick_pct_4h"] < 0.02)
        | (df["change_pct_4h"].shift(48) < 0.16)
        | (df["top_wick_pct_4h"].shift(48) < 0.08)
        | (df["change_pct_1h"] > -0.02)
        | (df["cti_20_1h"] < 0.7)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 65.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
      )
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["top_wick_pct_1d"] < 0.12)
        | (df["change_pct_1h"] > -0.01)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 70.0)
        | (df["r_480_4h"] < -25.0)
        | (df["close"] < df["res_hlevel_4h"])
      )
      & (
        (df["change_pct_1d"] < 0.16)
        | (df["top_wick_pct_1d"] < 0.12)
        | (df["change_pct_4h"] > -0.01)
        | (df["top_wick_pct_4h"] < 0.04)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 70.0)
        | (df["rsi_14_max_6_4h"] < 75.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 70.0)
        | (df["close"] < df["res_hlevel_4h"])
      )
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["change_pct_4h"].shift(48) > -0.04)
        | (df["change_pct_4h"].shift(96) < 0.04)
        | (df["rsi_14_1h"] < 60.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_max_6_4h"] < 75.0)
        | (df["r_480_1h"] < -15.0)
        | (df["r_480_4h"] < -25.0)
      )
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["top_wick_pct_1d"] < 0.12)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["r_480_1h"] < -35.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["ema_200_dec_4_1d"] == False)
        | (df["close"] > (df["high_max_12_1h"] * 0.88))
      )
      & (
        (df["not_downtrend_1h"])
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["hl_pct_change_6_1d"] < 1.2)
      )
      & (
        (df["top_wick_pct_1d"] < 0.08)
        | (df["not_downtrend_1h"])
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 60.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["close"] > (df["high_max_6_1d"] * 0.80))
        | (df["hl_pct_change_6_1d"] < 1.2)
      )
      & (
        (df["change_pct_4h"] < 0.16)
        | (df["rsi_3_15m"] > 16.0)
        | (df["cti_20_1h"] < 0.8)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 80.0)
        | (df["close"] < df["res_hlevel_4h"])
      )
      & (
        (df["change_pct_4h"] < 0.03)
        | (df["top_wick_pct_4h"] < 0.03)
        | (df["change_pct_1h"] > -0.03)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 75.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["hl_pct_change_6_1d"] < 0.5)
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_1d"] < 70.0)
        | (df["r_480_1h"] < -15.0)
        | (df["r_480_4h"] < -15.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["hl_pct_change_6_1d"] < 0.7)
      )
      & (
        (df["change_pct_4h"] < 0.03)
        | (df["top_wick_pct_4h"] < 0.03)
        | (df["change_pct_1h"] > -0.03)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 70.0)
        | (df["r_480_1h"] < -30.0)
        | (df["r_480_4h"] < -30.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_4h"] < 0.06)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_3_15m"] > 16.0)
        | (df["cti_20_1h"] < 0.8)
        | (df["rsi_14_1h"] < 70.0)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 70.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["hl_pct_change_48_1h"] < 0.7)
      )
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["top_wick_pct_1d"] < 0.12)
        | (df["change_pct_1h"] > -0.01)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 70.0)
        | (df["rsi_14_max_6_4h"] < 80.0)
        | (df["rsi_14_1d"] < 70.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_4h"] < 0.05)
        | (df["change_pct_1h"] > -0.05)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 70.0)
        | (df["r_480_1h"] < -30.0)
        | (df["r_480_4h"] < -10.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["hl_pct_change_6_1d"] < 0.7)
      )
      & (
        (df["change_pct_1h"] > -0.02)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 80.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["ema_200_dec_4_1d"] == False)
        | (df["hl_pct_change_48_1h"] < 0.7)
      )
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["change_pct_1d"].shift(288) < 0.12)
        | (df["not_downtrend_1h"])
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_4h"] < -30.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["change_pct_1d"] > -0.02)
        | (df["change_pct_1d"].shift(288) < 0.02)
        | (df["change_pct_4h"] < 0.02)
        | (df["top_wick_pct_4h"] < 0.16)
        | (df["change_pct_1h"] > -0.12)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_4h"] < -30.0)
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_4h"] < 0.18)
        | (df["change_pct_1h"] > -0.01)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 80.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["is_downtrend_3_4h"] == False)
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 70.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["hl_pct_change_6_1d"] < 1.0)
      )
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_max_6_4h"] < 80.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["r_480_1h"] < -35.0)
        | (df["r_480_4h"] < -25.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > (df["high_max_12_1h"] * 0.85))
      )
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["not_downtrend_1h"])
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 60.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 70.0)
        | (df["r_480_1h"] < -20.0)
        | (df["r_480_4h"] < -20.0)
        | (df["hl_pct_change_6_1d"] < 1.6)
      )
      & (
        (df["change_pct_4h"] < 0.16)
        | (df["change_pct_1h"] > -0.08)
        | (df["rsi_14_4h"] < 65.0)
        | (df["rsi_14_1d"] < 70.0)
        | (df["r_480_4h"] < -15.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["hl_pct_change_6_1d"] < 0.75)
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["change_pct_1h"].shift(12) < 0.01)
        | (df["rsi_3"] > 6.0)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_4h"] < 65.0)
        | (df["r_480_1h"] < -10.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] < df["res_hlevel_4h"])
      )
      & (
        (df["change_pct_4h"] > -0.04)
        | (df["change_pct_1h"] > -0.02)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 12.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_4h"].shift(48) < 70.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
      )
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 70.0)
        | (df["close"] < df["res_hlevel_4h"])
      )
      & (
        (df["change_pct_1h"] > -0.02)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 70.0)
        | (df["r_480_1h"] < -25.0)
        | (df["r_480_4h"] < -15.0)
      )
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["change_pct_1h"] > -0.01)
        | (df["not_downtrend_1h"])
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
      )
      & (
        (df["change_pct_1h"] > -0.02)
        | (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 60.0)
        | (df["r_480_1h"] < -25.0)
        | (df["r_480_4h"] < -10.0)
      )
      & (
        (df["change_pct_4h"] > -0.01)
        | (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 20.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 70.0)
        | (df["r_480_4h"] < -35.0)
        | (df["hl_pct_change_6_1d"] < 1.0)
      )
      & (
        (df["change_pct_1d"] < 0.02)
        | (df["top_wick_pct_1d"] < 0.06)
        | (df["change_pct_4h"] > -0.00)
        | (df["top_wick_pct_4h"] < 0.06)
        | (df["change_pct_4h"].shift(48) < 0.02)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 60.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 60.0)
        | (df["rsi_14_4h"].shift(48) < 70.0)
      )
      & (
        (df["change_pct_1d"] < 0.10)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 30.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 60.0)
        | (df["rsi_14_max_6_1d"] < 70.0)
        | (df["r_480_1h"] < -20.0)
        | (df["r_480_4h"] < -20.0)
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["change_pct_4h"].shift(48) < 0.02)
        | (df["top_wick_pct_4h"].shift(48) < 0.02)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_4h"].shift(48) < 70.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
      )
      & (
        (df["change_pct_1d"] < 0.06)
        | (df["top_wick_pct_1d"] < 0.06)
        | (df["change_pct_4h"] > -0.0)
        | (df["top_wick_pct_4h"] < 0.04)
        | (df["change_pct_4h"].shift(48) < 0.0)
        | (df["top_wick_pct_4h"].shift(48) < 0.04)
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 60.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_1d"] < 0.26)
        | (df["change_pct_4h"] < 0.04)
        | (df["top_wick_pct_4h"] < 0.04)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 12.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 60.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 70.0)
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_4h"] > -0.01)
        | (df["change_pct_4h"].shift(48) < 0.16)
        | (df["top_wick_pct_4h"].shift(48) < 0.08)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_1h"] < 60.0)
        | (df["rsi_14_4h"] < 70.0)
      )
      & (
        (df["change_pct_1d"] < 0.24)
        | (df["top_wick_pct_1d"] < 0.06)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 12.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 60.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_1d"] < 0.16)
        | (df["change_pct_4h"] > -0.02)
        | (df["change_pct_4h"].shift(48) < 0.06)
        | (df["top_wick_pct_4h"].shift(48) < 0.02)
        | (df["change_pct_1h"] > -0.02)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["close"] < df["res_hlevel_4h"])
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_3_1h"] > 12.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 70.0)
      )
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["change_pct_4h"].shift(48) < 0.08)
        | (df["not_downtrend_1h"])
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["rsi_14_max_6_1d"] < 80.0)
        | (df["close"] > (df["high_max_48_1h"] * 0.80))
        | (df["hl_pct_change_6_1d"] < 1.0)
      )
      & (
        (df["change_pct_1d"] < 0.24)
        | (df["top_wick_pct_1d"] < 0.06)
        | (df["change_pct_1h"] > -0.02)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 60.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] > (df["high_max_48_1h"] * 0.85))
      )
      & (
        (df["change_pct_1d"] < 0.16)
        | (df["top_wick_pct_1d"] < 0.16)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 20.0)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_1d"] < 70.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["ema_200_dec_4_1d"] == False)
        | (df["hl_pct_change_6_1d"] < 0.8)
      )
      & (
        (df["change_pct_1h"] < 0.06)
        | (df["not_downtrend_15m"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_1h"] < 70.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_1h"] < -10.0)
        | (df["r_480_4h"] < -15.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_1h"] > -0.06)
        | (df["change_pct_1h"].shift(12) < 0.06)
        | (df["not_downtrend_15m"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_1h"].shift(12) < 70.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_4h"] < -15.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_3"] > 10.0)
        | (df["cti_20_15m"] < 0.9)
        | (df["rsi_14_15m"] < 80.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 80.0)
        | (df["r_480_1h"] < -35.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["hl_pct_change_6_1d"] < 0.7)
      )
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 4.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_1h"] < -25.0)
        | (df["r_480_4h"] < -25.0)
        | (df["close"] > df["sup_level_1h"])
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_1d"] < 70.0)
        | (df["r_480_4h"] < -25.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > (df["high_max_6_1h"] * 0.75))
        | (df["hl_pct_change_6_1d"] < 1.0)
      )
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 8.0)
        | (df["rsi_3_15m"] > 8.0)
        | (df["rsi_14_4h"] < 70.0)
        | (df["r_480_4h"] < -25.0)
        | (df["close"] < df["res_hlevel_4h"])
      )
      & (
        (df["change_pct_1h"] > -0.02)
        | (df["not_downtrend_15m"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_max_3_1h"] < 75.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["r_480_4h"] < -35.0)
      )
      & (
        (df["top_wick_pct_1d"] < 0.06)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 30.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["rsi_14_1d"] < 65.0)
        | (df["close"] > df["sup_level_1h"])
      )
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_1d"] > -0.12)
        | (df["change_pct_1d"].shift(288) < 0.12)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 30.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 50.0)
        | (df["rsi_14_max_6_1d"] < 70.0)
        | (df["r_480_4h"] < -35.0)
        | (df["hl_pct_change_6_1d"] < 0.9)
      )
      & (
        (df["change_pct_4h"] > -0.04)
        | (df["change_pct_4h"].shift(48) < 0.04)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["rsi_14_max_6_1d"] < 70.0)
        | (df["hl_pct_change_6_1d"] < 0.9)
      )
      & (
        (df["change_pct_min_3_4h"] > -0.16)
        | (df["change_pct_max_3_4h"] < 0.36)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_max_6_4h"] < 80.0)
        | (df["close"] > (df["high_max_12_1h"] * 0.75))
        | (df["hl_pct_change_24_1h"] < 0.5)
      )
      & (
        (df["change_pct_1d"] < 0.16)
        | (df["top_wick_pct_1d"] < 0.16)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_max_6_4h"] < 80.0)
        | (df["close"] > (df["high_max_12_1h"] * 0.75))
        | (df["hl_pct_change_24_1h"] < 0.5)
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 50.0)
        | (df["r_480_1h"] < -35.0)
        | (df["r_480_4h"] < -25.0)
        | (df["close"] > df["sup_level_1h"])
      )
      & (
        (df["change_pct_1d"] < 0.01)
        | (df["change_pct_4h"] < 0.01)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 30.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 60.0)
        | (df["r_480_4h"] < -15.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
      )
      & (
        (df["change_pct_1d"] < 0.16)
        | (df["top_wick_pct_1d"] < 0.16)
        | (df["change_pct_4h"] > -0.04)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_max_3_4h"] < 75.0)
        | (df["rsi_14_1d"] < 75.0)
        | (df["r_480_1h"] < -35.0)
        | (df["r_480_4h"] < -35.0)
        | (df["hl_pct_change_6_1d"] < 1.0)
        | (((df["close"] - df["low_min_6_1d"]) / df["low_min_6_1d"]) < (df["hl_pct_change_6_1d"] * 0.38))
      )
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["rsi_14_15m"] > 40.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_max_3_4h"] < 80.0)
        | (df["r_480_1h"] < -35.0)
        | (df["r_480_4h"] < -25.0)
        | (df["hl_pct_change_6_1d"] < 0.9)
        | (((df["close"] - df["low_min_6_1d"]) / df["low_min_6_1d"]) < (df["hl_pct_change_6_1d"] * 0.38))
      )
      & (
        (df["change_pct_4h"] < 0.06)
        | (df["top_wick_pct_4h"] < 0.06)
        | (df["change_pct_1h"] > -0.02)
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_max_6_1h"] < 80.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1d"] < 0.16)
        | (df["top_wick_pct_1d"] < 0.04)
        | (df["change_pct_1h"] > -0.02)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["r_480_1h"] < -35.0)
        | (df["r_480_4h"] < -35.0)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1d"] < 0.26)
        | (df["change_pct_4h"] > -0.04)
        | (df["change_pct_4h"].shift(48) < 0.04)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_4h"].shift(48) < 70.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_4h"] < -25.0)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["r_480_1h"] < -35.0)
        | (df["r_480_4h"] < -25.0)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["cti_20_1h"] < 0.8)
        | (df["rsi_14_1h"] < 70.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1d"] > -0.08)
        | (df["change_pct_4h"] < 0.08)
        | (df["top_wick_pct_4h"] < 0.08)
        | (df["change_pct_1h"] > -0.02)
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["rsi_14_max_6_1d"] < 75.0)
        | (df["r_480_4h"] < -25.0)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_4h"] > -0.01)
        | (df["change_pct_4h"].shift(48) < 0.01)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_1h"] < -25.0)
        | (df["r_480_4h"] < -20.0)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1d"] < 0.16)
        | (df["top_wick_pct_1d"] < 0.04)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["r_480_1h"] < -25.0)
        | (df["r_480_4h"] < -20.0)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14"] < 40.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["rsi_14_1h"] < 65.0)
        | (df["rsi_14_max_3_1h"] < 70.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["ema_200_dec_4_1d"] == False)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_4h"] < 0.02)
        | (df["top_wick_pct_4h"] < 0.02)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 8.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1h"] > -0.02)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 70.0)
        | (df["r_480_1h"] < -40.0)
        | (df["r_480_4h"] < -25.0)
        | (df["ema_200_dec_4_1d"] == False)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 6.0)
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_14_max_6_1h"] < 70.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["close"] > df["sup_level_1h"])
      )
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 26.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 70.0)
        | (df["rsi_14_4h"] < 70.0)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1h"] > -0.02)
        | (df["change_pct_1h"].shift(12) < 0.02)
        | (df["not_downtrend_15m"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_1h"].shift(12) < 70.0)
        | (df["r_480_1h"] < -35.0)
        | (df["r_480_4h"] < -25.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_4h"] > -0.04)
        | (df["change_pct_4h"].shift(48) < 0.02)
        | (df["change_pct_1h"] > -0.01)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 16.0)
        | (df["r_480_4h"] < -25.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 8.0)
        | (df["rsi_14_1h"] < 60.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["r_480_1h"] < -35.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["change_pct_1d"].shift(288) < 0.04)
        | (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 8.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["rsi_14_max_6_1d"] < 70.0)
        | (df["r_480_4h"] < -25.0)
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_1h"] < 60.0)
        | (df["rsi_14_4h"] < 65.0)
        | (df["r_480_1h"] < -30.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_4h"] > -0.08)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["hl_pct_change_6_1d"] < 2.5)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_4h"] > -0.04)
        | (df["top_wick_pct_4h"] < 0.02)
        | (df["change_pct_4h"].shift(48) < 0.02)
        | (df["top_wick_pct_4h"].shift(48) < 0.02)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_14_4h"].shift(48) < 70.0)
        | (df["r_480_4h"] < -35.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["is_downtrend_3_1h"] == False)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_max_6_1h"] < 80.0)
        | (df["rsi_14_4h"] < 70.0)
        | (df["r_480_4h"] < -35.0)
        | (df["close"] < df["res_hlevel_4h"])
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["change_pct_1h"].shift(12) < 0.08)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 20.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["r_480_1h"] < -25.0)
        | (df["r_480_4h"] < -25.0)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 20.0)
        | (df["rsi_14"] > 30.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_15m"] < 32.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["r_480_1h"] < -40.0)
        | (df["r_480_4h"] < -30.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > (df["high_max_12_1d"] * 0.80))
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_4h"] < -35.0)
        | (df["close"] > df["sup_level_1h"])
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_4h"] > -0.01)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_max_6_1h"] < 70.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_1h"] < -30.0)
        | (df["r_480_4h"] < -30.0)
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14"] < 30.0)
        | (df["rsi_14_15m"] < 32.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["r_480_1h"] < -25.0)
        | (df["r_480_4h"] < -15.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (((df["close"] - df["low_min_6_1d"]) / df["low_min_6_1d"]) < (df["hl_pct_change_6_1d"] * 0.38))
      )
      & (
        (df["not_downtrend_1h"])
        | (df["is_downtrend_3_1d"] == False)
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["rsi_14_max_6_1d"] < 70.0)
        | (df["hl_pct_change_6_1d"] < 1.2)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_3"] > 12.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["rsi_14_max_6_1d"] < 70.0)
        | (df["r_480_4h"] < -35.0)
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 20.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 70.0)
        | (df["r_480_1h"] < -35.0)
        | (df["r_480_4h"] < -25.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["hl_pct_change_6_1d"] < 1.2)
      )
      & (
        (df["change_pct_4h"] < 0.02)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 20.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_1h"] < -25.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["change_pct_4h"] > -0.01)
        | (df["change_pct_4h"].shift(48) < 0.12)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_14"] < 36.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_max_6_1h"] < 70.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["close"] > (df["high_max_12_1d"] * 0.70))
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["change_pct_4h"] > -0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["r_480_1h"] < -25.0)
        | (df["r_480_4h"] < -25.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["change_pct_1h"] > -0.02)
        | (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > (df["high_max_48_1h"] * 0.80))
        | (df["hl_pct_change_6_1d"] < 1.2)
        | (((df["close"] - df["low_min_6_1d"]) / df["low_min_6_1d"]) < (df["hl_pct_change_6_1d"] * 0.38))
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 8.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["close"] > df["sup_level_4h"])
        | (df["hl_pct_change_6_1d"] < 1.2)
        | (((df["close"] - df["low_min_6_1d"]) / df["low_min_6_1d"]) < (df["hl_pct_change_6_1d"] * 0.38))
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 6.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["r_480_1h"] < -30.0)
        | (df["r_480_4h"] < -25.0)
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 4.0)
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["r_480_1h"] < -35.0)
        | (df["r_480_4h"] < -25.0)
        | (df["close"] > df["sup_level_1h"])
        | (((df["close"] - df["low_min_6_1d"]) / df["low_min_6_1d"]) < (df["hl_pct_change_6_1d"] * 0.38))
      )
      & (
        (df["change_pct_1d"] < 0.06)
        | (df["top_wick_pct_1d"] < 0.06)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_3"] > 20.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["r_480_4h"] < -35.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["ema_200_dec_4_1d"] == False)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_max_6_4h"] < 65.0)
        | (df["r_480_1h"] < -30.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_1d"] < 0.02)
        | (df["top_wick_pct_1d"] < 0.02)
        | (df["change_pct_1h"] > -0.00)
        | (df["change_pct_1h"].shift(12) < 0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_1h"] < -20.0)
        | (df["close"] < df["res_hlevel_1d"])
        | (((df["close"] - df["low_min_6_1d"]) / df["low_min_6_1d"]) < (df["hl_pct_change_6_1d"] * 0.38))
      )
      & (
        (df["change_pct_4h"] > -0.01)
        | (df["change_pct_4h"].shift(48) < 0.04)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 60.0)
        | (df["rsi_14_max_6_1h"] < 70.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["r_480_1h"] < -20.0)
        | (df["r_480_4h"] < -35.0)
        | (df["close"] > df["sup_level_4h"])
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_1d"] < 65.0)
        | (df["r_480_4h"] < -30.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1h"] > -0.03)
        | (df["not_downtrend_15m"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["r_480_1h"] < -30.0)
        | (df["close"] > df["sup_level_1h"])
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["change_pct_4h"] < 0.08)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 12.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["r_480_1h"] < -20.0)
        | (df["r_480_4h"] < -20.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["not_downtrend_15m"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["rsi_14_max_6_1d"] < 70.0)
        | (df["close"] < df["res_hlevel_1h"])
      )
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 8.0)
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["rsi_14_max_6_1d"] < 70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > (df["high_max_48_1h"] * 0.80))
        | (df["hl_pct_change_6_1d"] < 0.7)
      )
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 8.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_1h"] < 70.0)
        | (df["rsi_14_max_6_1h"] < 80.0)
        | (df["rsi_14_4h"] < 70.0)
        | (df["r_480_1h"] < -35.0)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1d"] > -0.01)
        | (df["top_wick_pct_1d"] < 0.16)
        | (df["change_pct_4h"] > -0.08)
        | (df["change_pct_1h"] > -0.04)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 16.0)
        | (df["close"] > df["sup_level_1h"])
        | (((df["close"] - df["low_min_6_1d"]) / df["low_min_6_1d"]) < (df["hl_pct_change_6_1d"] * 0.38))
      )
      & (
        (df["change_pct_1h"] > -0.04)
        | (df["not_downtrend_15m"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_max_6_1h"] < 70.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["rsi_14_max_6_1d"] < 70.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (((df["close"] - df["low_min_6_1d"]) / df["low_min_6_1d"]) < (df["hl_pct_change_6_1d"] * 0.38))
      )
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["change_pct_1h"] > -0.04)
        | (df["not_downtrend_1h"])
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 8.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["rsi_14_max_6_1d"] < 70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["change_pct_1h"] > -0.04)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 8.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["rsi_14_max_6_1d"] < 70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_1h"] < 70.0)
        | (df["rsi_14_4h"] < 70.0)
        | (df["r_480_1h"] < -3.0)
        | (df["r_480_4h"] < -3.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] > (df["close_max_12"] * 0.92))
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1d"] < 0.06)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 65.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["r_480_1h"] < -15.0)
        | (df["close"] > (df["close_max_24"] * 0.94))
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1d"] > -0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["r_480_1h"] < -30.0)
        | (df["rsi_14_max_6_1d"] < 70.0)
        | (df["hl_pct_change_6_1d"] < 0.9)
        | (((df["close"] - df["low_min_6_1d"]) / df["low_min_6_1d"]) < (df["hl_pct_change_6_1d"] * 0.38))
      )
      & (
        (df["change_pct_1h"] > -0.02)
        | (df["top_wick_pct_1h"] < 0.02)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_1h"] < -35.0)
        | (df["close"] < df["res_hlevel_1d"])
        | (df["hl_pct_change_6_1d"] < 0.7)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["change_pct_1h"] > -0.02)
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 70.0)
        | (df["r_480_1h"] < -35.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["change_pct_1h"] > -0.14)
        | (df["change_pct_1h"].shift(12) < 0.14)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14"] < 36.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_max_6_1h"] < 70.0)
        | (df["rsi_14_4h"] < 46.0)
      )
      & (
        (df["change_pct_1d"] > -0.02)
        | (df["change_pct_1d"].shift(288) < 0.02)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_3"] > 12.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_max_6_1h"] < 70.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["r_480_1h"] < -35.0)
        | (df["close"] > df["sup_level_1h"])
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["change_pct_1h"].shift(12) < 0.03)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 70.0)
        | (df["rsi_14_max_6_1h"] < 80.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_1h"] < -25.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_3"] > 12.0)
        | (df["rsi_14_15m"] < 50.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 80.0)
        | (df["r_480_1h"] < -20.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["hl_pct_change_6_1d"] < 1.0)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1h"] > -0.02)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 4.0)
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_max_6_1h"] < 70.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 6.0)
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 70.0)
        | (df["r_480_1h"] < -25.0)
        | (df["hl_pct_change_6_1d"] < 0.5)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1h"] < 0.03)
        | (df["not_downtrend_15m"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 36.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_15m"] < 33.0)
        | (df["rsi_14_1h"] < 60.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["r_480_1h"] < -16.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["change_pct_4h"] < 0.02)
        | (df["top_wick_pct_4h"] < 0.08)
        | (df["change_pct_1h"] > -0.04)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_max_6_1h"] < 80.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_1h"] < -35.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
      )
      & (
        (df["change_pct_1d"] < 0.18)
        | (df["change_pct_1h"] > -0.01)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_max_6_1h"] < 65.0)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["hl_pct_change_6_1d"] < 0.9)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_4h"] < 0.03)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_max_6_1h"] < 80.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["hl_pct_change_12_1h"] < 0.20)
      )
      & (
        (df["change_pct_1h"] > -0.03)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_max_6_1h"] < 70.0)
        | (df["rsi_14_4h"] < 70.0)
        | (df["r_480_1h"] < -30.0)
        | (df["r_480_1h"] < -25.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1d"] < 0.06)
        | (df["change_pct_4h"] > -0.02)
        | (df["change_pct_4h"].shift(48) < 0.01)
        | (df["rsi_3_1h"] > 40.0)
        | (df["rsi_3_4h"] > 40.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_dec_3_1h"] == False)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_4h"].shift(48) < 65.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["cti_20_dec_3_1d"] == False)
        | (df["r_480_4h"] < -25.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (((df["close"] - df["low_min_6_1d"]) / df["low_min_6_1d"]) < (df["hl_pct_change_6_1d"] * 0.38))
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["top_wick_pct_1h"] < 0.01)
        | (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_4h"] < -30.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (((df["close"] - df["low_min_6_1d"]) / df["low_min_6_1d"]) < (df["hl_pct_change_6_1d"] * 0.38))
      )
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["change_pct_1d"].shift(288) < 0.04)
        | (df["change_pct_1h"] > -0.01)
        | (df["not_downtrend_15m"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["r_480_4h"] < -35.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1h"] > -0.03)
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_max_6_1h"] < 70.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 70.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["close"] > (df["high_max_6_1d"] * 0.85))
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_max_6_1h"] < 70.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["r_480_1h"] < -30.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["top_wick_pct_1h"] < 0.01)
        | (df["change_pct_1h"].shift(12) < 0.06)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > (df["high_max_12_1d"] * 0.70))
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1d"] > -0.06)
        | (df["change_pct_1d"].shift(288) < 0.16)
        | (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["r_14_1h"] > -90.0)
        | (df["r_480_1h"] < -35.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["change_pct_1d"] > -0.03)
        | (df["change_pct_1d"].shift(288) < 0.03)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_4h"] < -20.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["sma_200_dec_48_1h"] == False)
      )
      & (
        (df["change_pct_4h"] > -0.01)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 70.0)
        | (df["r_480_1h"] < -35.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["hl_pct_change_6_1d"] < 0.9)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["not_downtrend_15m"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_1h"] < -25.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (((df["close"] - df["low_min_6_1d"]) / df["low_min_6_1d"]) < (df["hl_pct_change_6_1d"] * 0.38))
      )
      & (
        (df["change_pct_1d"] < 0.06)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_max_6_1h"] < 70.0)
        | (df["rsi_14_4h"] < 65.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_1h"] > 20.0)
        | (df["r_14"] < -80.0)
        | (df["rsi_14"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 70.0)
        | (df["r_14_4h"] < -35.0)
        | (df["r_480_1h"] < -35.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["hl_pct_change_6_1d"] < 1.2)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 4.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["hl_pct_change_6_1d"] < 1.2)
        | (df["close"] > (df["high_max_6_1d"] * 0.55))
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_max_6_1h"] < 70.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["r_480_1h"] < -20.0)
        | (df["r_480_4h"] < -20.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (((df["close"] - df["low_min_6_1d"]) / df["low_min_6_1d"]) < (df["hl_pct_change_6_1d"] * 0.38))
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_3_4h"] > 36.0)
        | (df["rsi_14_max_6_4h"] < 65.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_14_1h"] > -80.0)
        | (df["r_480_1h"] < -40.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["hl_pct_change_6_1d"] < 0.9)
        | (df["close"] > (df["high_max_24_1h"] * 0.86))
        | (((df["close"] - df["low_min_6_1d"]) / df["low_min_6_1d"]) < (df["hl_pct_change_6_1d"] * 0.38))
      )
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_1h"] < -30.0)
        | (df["r_480_4h"] < -20.0)
        | (df["close"] > df["sup_level_1h"])
      )
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 8.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_max_6_1h"] < 65.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_1h"] < 0.7)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["rsi_14_max_6_1d"] < 80.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["hl_pct_change_6_1d"] < 1.9)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["not_downtrend_4h"])
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_14"] < 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 30.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["rsi_14_max_6_1d"] < 70.0)
        | (df["r_480_4h"] < -35.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["hl_pct_change_6_1d"] < 0.7)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["r_480_4h"] < -30.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 45.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["r_480_1h"] < -40.0)
        | (df["r_480_4h"] < -20.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["hl_pct_change_6_1d"] < 0.7)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["change_pct_1h"] > -0.01)
        | (df["not_downtrend_15m"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["rsi_14_max_6_1d"] < 65.0)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["top_wick_pct_1d"] < 0.04)
        | (df["change_pct_1h"] > -0.01)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_14_1h"] < 20.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["r_480_4h"] < -25.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14"] < 25.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_1h"] < -20.0)
        | (df["r_480_4h"] < -10.0)
        | (df["close"] < df["res_hlevel_1h"])
      )
      & (
        (df["change_pct_1d"] > -0.03)
        | (df["change_pct_1d"].shift(288) > -0.03)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["rsi_14_max_6_1d"] < 70.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["hl_pct_change_6_1d"] < 0.9)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 15.0)
        | (df["rsi_3_4h"] > 15.0)
        | (df["rsi_14_4h"] < 30.0)
        | (df["rsi_14_max_6_4h"] < 65.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["rsi_14_max_6_1d"] < 65.0)
        | (df["r_14_1h"] > -90.0)
        | (df["r_14_4h"] > -90.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
    )

    df["global_protections_long_dump"] = (
      (
        (df["change_pct_4h"] > -0.02)
        | (df["change_pct_4h"].shift(48) < 0.02)
        | (df["not_downtrend_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["change_pct_4h"].shift(48) < 0.04)
        | (df["cti_20_4h"] < 0.7)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & ((df["change_pct_1d"] > -0.12) | (df["cti_20_1d"] < 0.7) | (df["ema_200_dec_48_1h"] == False))
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["r_480_1h"] > -90.0)
        | (df["r_480_4h"] > -90.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_1h"] > -0.04)
        | (df["change_pct_1h"].shift(12) < 0.04)
        | (df["r_480_1h"] > -90.0)
        | (df["r_480_4h"] > -90.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct_1d"] > -0.10)
        | (df["not_downtrend_1d"])
        | (df["r_480_1h"] > -80.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["not_downtrend_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["close"] > (df["high_max_6_1d"] * 0.55))
      )
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["r_480_4h"] > -80.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["top_wick_pct_1d"] < 0.12)
        | (df["change_pct_1h"] > -0.04)
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["change_pct_4h"].shift(48) < 0.06)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_14_4h"].shift(48) < 60.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["top_wick_pct_1d"] < 0.04)
        | (df["change_pct_1d"].shift(288) < 0.12)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_14_1d"].shift(288) < 60.0)
      )
      & (
        (df["change_pct_1h"] > -0.02)
        | (df["change_pct_1h"].shift(12) < 0.01)
        | (df["rsi_14_1h"].shift(12) < 70.0)
        | (df["r_480_4h"] > -90.0)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["rsi_3"] > 16.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["r_480_1h"] > -85.0)
        | (df["r_480_4h"] > -90.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 6.0)
        | (df["rsi_3_1d"] > 20.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["top_wick_pct_1d"] < 0.04)
        | (df["change_pct_4h"] < 0.04)
        | (df["rsi_3_15m"] > 26.0)
        | (df["r_480_4h"] < -15.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > (df["close_max_24"] * 0.94))
      )
      & (
        (df["change_pct_4h"] < 0.06)
        | (df["change_pct_1h"] > -0.04)
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_4h"] > 26.0)
        | (df["r_480_1h"] > -75.0)
        | (df["r_480_4h"] > -90.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct_1d"] > -0.02)
        | (df["change_pct_1h"] > -0.06)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 10.0)
        | (df["r_480_4h"] > -70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_1d"] > -0.06)
        | (df["top_wick_pct_1d"] < 0.06)
        | (df["change_pct_1d"].shift(288) < 0.32)
        | (df["change_pct_4h"] < 0.04)
        | (df["change_pct_4h"].shift(288) < 0.04)
        | (df["close"] > df["sup_level_1d"])
      )
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["r_480_1h"] > -90.0)
        | (df["r_480_4h"] > -70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["change_pct_4h"] > -0.06)
        | (df["change_pct_4h"].shift(48) < 0.02)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 16.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_3_1d"] > 6.0)
        | (df["r_480_1h"] > -90.0)
        | (df["r_480_4h"] > -90.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["not_downtrend_1d"])
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_3_1d"] > 16.0)
        | (df["r_480_1h"] > -90.0)
        | (df["r_480_4h"] > -95.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["not_downtrend_1d"])
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_3_1d"] > 30.0)
        | (df["r_480_1h"] > -70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["close"] > (df["high_max_6_1d"] * 0.75))
      )
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["change_pct_1d"].shift(288) < 0.12)
        | (df["top_wick_pct_1d"].shift(288) < 0.06)
        | (df["change_pct_4h"] > -0.02)
        | (df["change_pct_4h"].shift(48) < 0.02)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 20.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 50.0)
      )
      & (
        (df["change_pct_1d"] > -0.06)
        | (df["change_pct_1h"] > -0.02)
        | (df["change_pct_1h"].shift(12) < 0.04)
        | (df["not_downtrend_1d"])
        | (df["rsi_3_1d"] > 16.0)
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["top_wick_pct_1d"] < 0.12)
        | (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["close"] > (df["high_max_6_1d"] * 0.70))
      )
      & (
        (df["change_pct_1h"] > -0.02)
        | (df["not_downtrend_15m"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["cti_20_1h"] < 0.7)
        | (df["r_480_4h"] > -85.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct_4h"] > -0.03)
        | (df["change_pct_4h"].shift(48) < 0.12)
        | (df["change_pct_1h"] > -0.03)
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["r_14_4h"].shift(48) < -5.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["change_pct_4h"] > -0.01)
        | (df["change_pct_4h"].shift(48) < 0.04)
        | (df["not_downtrend_1d"])
        | (df["rsi_3_1d"] > 20.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      & (
        (df["change_pct_4h"] < 0.04)
        | (df["change_pct_1h"] > -0.04)
        | (df["cti_20_1h"] < 0.8)
        | (df["rsi_14_1h"].shift(12) < 70.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 65.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 35.0)
        | (df["rsi_14_15m"] > 35.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["close"] > (df["high_max_6_1h"] * 0.80))
      )
      & (
        (df["change_pct_1d"] > -0.08)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["close"] > (df["high_max_6_1d"] * 0.60))
      )
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["top_wick_pct_4h"] < 0.08)
        | (df["change_pct_4h"].shift(48) < 0.04)
        | (df["top_wick_pct_4h"].shift(48) < 0.04)
        | (df["change_pct_1h"] > -0.01)
        | (df["not_downtrend_1h"])
        | (df["is_downtrend_3_1h"] == False)
        | (df["rsi_3_1h"] > 30.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"].shift(48) < 65.0)
      )
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.04)
        | (df["change_pct_4h"] > -0.04)
        | (df["change_pct_4h"].shift(48) < 0.04)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["close"] > (df["high_max_6_1d"] * 0.80))
      )
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["r_480_1h"] > -80.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["top_wick_pct_4h"] < 0.08)
        | (df["not_downtrend_1h"])
        | (df["is_downtrend_3_1h"] == False)
        | (df["r_480_1h"] > -70.0)
        | (df["r_480_4h"] > -85.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["rsi_3_1d"] > 40.0)
        | (df["rsi_14_max_6_1d"].shift(288) < 70.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_12_4h"] > df["ema_26_4h"])
        | (df["close"] > (df["high_max_6_1d"] * 0.80))
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_1d"] > 40.0)
        | (df["r_480_1h"] > -80.0)
        | (df["r_480_4h"] > -90.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_1d"] > -0.02)
        | (df["not_downtrend_1h"])
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 50.0)
        | (df["rsi_14_max_6_1d"] < 65.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_12_1h"] > df["ema_26_1h"])
        | (df["ema_12_4h"] > df["ema_26_4h"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_4h"] > 40.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_1h"] < -35.0)
        | (df["r_480_4h"] > -80.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_12_1h"] > df["ema_26_1h"])
      )
      & (
        (df["top_wick_pct_1d"] < 0.10)
        | (df["change_pct_4h"] < 0.08)
        | (df["change_pct_1h"] > -0.01)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["close"] > (df["high_max_6_1d"] * 0.60))
      )
      & (
        (df["change_pct_4h"] < 0.04)
        | (df["top_wick_pct_4h"] < 0.04)
        | (df["change_pct_1h"] > -0.01)
        | (df["not_downtrend_1d"])
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct_4h"] < 0.08)
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 60.0)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 60.0)
        | (df["r_480_4h"] > -70.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_max_6_4h"] < 80.0)
        | (df["close"] < df["res_hlevel_1d"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
        | (df["hl_pct_change_24_1h"] < 0.5)
      )
      & (
        (df["change_pct_4h"] > -0.06)
        | (df["change_pct_1h"] > -0.01)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_3_4h"] > 26.0)
        | (df["rsi_14_max_6_4h"] < 65.0)
        | (df["r_480_4h"] > -85.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["hl_pct_change_6_1d"] < 0.5)
      )
      & (
        (df["change_pct_4h"] < 0.01)
        | (df["top_wick_pct_4h"] < 0.06)
        | (df["change_pct_1h"] > -0.00)
        | (df["not_downtrend_1d"])
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 70.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["change_pct_4h"].shift(48) < 0.02)
        | (df["top_wick_pct_4h"].shift(48) < 0.08)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 60.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_4h"] < 0.04)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_4h"] > -70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_4_1d"] == False)
        | (df["close"] > (df["high_max_24_1h"] * 0.90))
        | (df["hl_pct_change_6_1d"] < 0.8)
      )
      & (
        (df["change_pct_4h"] > -0.06)
        | (df["top_wick_pct_4h"] < 0.06)
        | (df["change_pct_4h"].shift(48) < 0.06)
        | (df["change_pct_1h"] > -0.01)
        | (df["cti_20_1d"] < 0.8)
      )
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["is_downtrend_3_4h"] == False)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 30.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["ema_200_dec_4_1d"] == False)
        | (df["close"] > (df["high_max_12_1h"] * 0.90))
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["r_480_1h"] > -75.0)
        | (df["r_480_4h"] > -80.0)
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_1h"] > 30.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["close"] > (df["high_max_6_1d"] * 0.80))
      )
      & (
        (df["change_pct_1h"] > -0.02)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["r_480_4h"] > -75.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_14_1h"] < 70.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_1d"] > -0.06)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 16.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["hl_pct_change_6_1d"] < 0.7)
      )
      & (
        (df["not_downtrend_1d"])
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["r_480_4h"] > -80.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_4h"] < 0.16)
        | (df["top_wick_pct_4h"] < 0.04)
        | (df["change_pct_1h"] > -0.06)
        | (df["rsi_14_4h"] < 70.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["ema_200_dec_4_1d"] == False)
        | (df["close"] > (df["high_max_12_1d"] * 0.75))
      )
      & (
        (df["not_downtrend_1h"])
        | (df["is_downtrend_3_1d"] == False)
        | (df["rsi_3_1h"] > 26.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["change_pct_4h"].shift(48) < 0.02)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["r_480_4h"] < -25.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["hl_pct_change_6_1d"] > 0.2)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_3_4h"] > 26.0)
        | (df["rsi_14_4h"].shift(48) < 65.0)
        | (df["close"] > df["sup_level_1h"])
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["close"] > (df["high_max_6_1d"] * 0.65))
      )
      & (
        (df["change_pct_4h"] < 0.16)
        | (df["top_wick_pct_4h"] < 0.04)
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_4h"] < 70.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
        | (df["close"] > (df["high_max_12_1d"] * 0.70))
      )
      & (
        (df["change_pct_1h"] > -0.02)
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_max_6_4h"] < 80.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["r_480_4h"] > -80.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_max_6_4h"] < 80.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
        | (df["hl_pct_change_48_1h"] < 0.50)
      )
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["change_pct_4h"] < 0.12)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 20.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 70.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_1h"] > -0.02)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_4h"] > -0.03)
        | (df["change_pct_4h"].shift(48) < 0.03)
        | (df["not_downtrend_1h"])
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["r_480_4h"] > -70.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_1d"] > -0.02)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_4h"] > -0.06)
        | (df["change_pct_4h"].shift(48) < 0.06)
        | (df["change_pct_1h"] > -0.02)
        | (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      & (
        (df["change_pct_4h"] < 0.02)
        | (df["top_wick_pct_4h"] < 0.02)
        | (df["change_pct_1h"] > -0.01)
        | (df["not_downtrend_1h"])
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["r_480_4h"] > -85.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 30.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["r_480_4h"] > -80.0)
        | (df["close"] > df["sup_level_1h"])
      )
      & (
        (df["change_pct_1d"] < 0.10)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 50.0)
        | (df["rsi_14_max_6_1d"] < 70.0)
        | (df["r_480_4h"] > -75.0)
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > (df["high_max_6_1d"] * 0.65))
      )
      & (
        (df["change_pct_4h"] < 0.03)
        | (df["top_wick_pct_4h"] < 0.03)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_1d"] > -0.02)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["rsi_14_max_6_1d"] < 70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > (df["high_max_6_1d"] * 0.65))
      )
      & (
        (df["change_pct_1h"] > -0.06)
        | (df["not_downtrend_1d"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 26.0)
        | (df["r_480_4h"] > -75.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["close"] > (df["high_max_6_1d"] * 0.75))
      )
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 12.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 60.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_3_1h"] > 12.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["r_480_4h"] > -65.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct_1d"] < 0.06)
        | (df["top_wick_pct_1d"] < 0.06)
        | (df["change_pct_4h"] < 0.06)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 4.0)
        | (df["rsi_3_15m"] > 6.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["change_pct_1h"] > -0.04)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 10.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      & (
        (df["change_pct_1d"] > -0.08)
        | (df["not_downtrend_15m"])
        | (df["is_downtrend_3_1d"] == False)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 20.0)
        | (df["close"] > df["sup_level_1d"])
        | (df["close"] > (df["high_max_6_1d"] * 0.65))
      )
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["top_wick_pct_1d"] < 0.04)
        | (df["not_downtrend_4h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 20.0)
        | (df["r_480_4h"] > -75.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["rsi_14_max_6_1d"] < 70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > (df["high_max_6_1d"] * 0.80))
      )
      & (
        (df["change_pct_4h"] > -0.12)
        | (df["change_pct_1h"] > -0.04)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["r_480_4h"] > -70.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
        | (df["close"] > (df["high_max_48_1h"] * 0.80))
      )
      & (
        (df["not_downtrend_4h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["r_480_4h"] > -70.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
        | (df["close"] > (df["high_max_48_1h"] * 0.80))
      )
      & (
        (df["not_downtrend_1d"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_4h"] < 65.0)
        | (df["r_480_4h"] > -70.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_3_4h"] > 20.0)
        | (df["rsi_3_1d"] > 20.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 10.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_4_1d"] == False)
        | (df["hl_pct_change_6_1d"] < 0.80)
      )
      & (
        (df["change_pct_1d"] < 0.06)
        | (df["top_wick_pct_1d"] < 0.06)
        | (df["change_pct_1h"] > -0.04)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_4h"] > -70.0)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_4h"] < 0.08)
        | (df["top_wick_pct_4h"] < 0.08)
        | (df["change_pct_1h"] > -0.03)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["change_pct_4h"].shift(48) < 0.06)
        | (df["top_wick_pct_4h"].shift(48) < 0.06)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["ema_200_dec_4_1d"] == False)
        | (df["hl_pct_change_6_1d"] < 0.9)
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_max_6_1h"] < 70.0)
        | (df["r_480_1h"] > -70.0)
        | (df["r_480_4h"] > -70.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct_1d"] > -0.03)
        | (df["change_pct_1d"].shift(288) < 0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_max_6_1h"] < 70.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 8.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_1h"] < -30.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
      )
      & (
        (df["change_pct_1d"] > -0.12)
        | (df["top_wick_pct_1d"] < 0.12)
        | (df["change_pct_1d"].shift(288) < 0.12)
        | (df["not_downtrend_1h"])
        | (df["rsi_14_1d"].shift(288) < 70.0)
        | (df["r_480_1h"] > -70.0)
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_4h"] < 0.8)
        | (df["rsi_14_4h"] < 60.0)
        | (df["r_480_4h"] > -70.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["hl_pct_change_6_1d"] < 1.0)
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 35.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["rsi_14_max_6_1d"] < 70.0)
        | (df["r_480_4h"] < -35.0)
        | (df["ema_200_dec_4_1d"] == False)
        | (df["hl_pct_change_6_1d"] < 0.7)
      )
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["top_wick_pct_4h"] < 0.10)
        | (df["change_pct_4h"].shift(48) < 0.04)
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_4h"] < -35.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_3"] > 8.0)
        | (df["rsi_3_1h"] > 10.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["change_pct_4h"] < 0.02)
        | (df["change_pct_1h"] > -0.01)
        | (df["top_wick_pct_1h"] < 0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_15m"] < 33.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["bb20_2_low_15m"])
        | (df["close"] > df["bb20_2_low_1h"])
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] < df["res_hlevel_4h"])
      )
      & (
        (df["change_pct_4h"] < 0.04)
        | (df["top_wick_pct_4h"] < 0.04)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 60.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] > (df["high_max_12_1d"] * 0.70))
      )
      & (
        (df["change_pct_4h"] < 0.08)
        | (df["change_pct_1h"] > -0.04)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["close"] > (df["high_max_6_1d"] * 0.75))
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_14_1d"] < 60.0)
        | (df["rsi_14_max_6_1d"] < 75.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 10.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["close"] > (df["high_max_12_1d"] * 0.60))
      )
      & (
        (df["change_pct_1d"] > -0.02)
        | (df["change_pct_4h"] > -0.02)
        | (df["change_pct_4h"].shift(48) < 0.06)
        | (df["is_downtrend_3_1d"] == False)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["rsi_14_max_6_1d"] < 80.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["close"] > (df["high_max_6_1d"] * 0.65))
      )
      & (
        (df["change_pct_4h"] < 0.03)
        | (df["top_wick_pct_4h"] < 0.03)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_3"] > 16.0)
        | (df["rsi_14_1h"] < 65.0)
        | (df["rsi_14_4h"] < 70.0)
        | (df["r_480_4h"] > -70.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 20.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["r_480_4h"] > -80.0)
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["change_pct_4h"] > -0.03)
        | (df["top_wick_pct_4h"] < 0.03)
        | (df["change_pct_4h"].shift(48) < 0.06)
        | (df["top_wick_pct_4h"].shift(48) < 0.06)
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14"] < 36.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 50.0)
      )
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_3_4h"] > 26.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["r_480_4h"] < -35.0)
        | (df["close"] > df["sup_level_1h"])
      )
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_3_4h"] > 20.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["not_downtrend_1d"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["close"] > (df["high_max_12_1d"] * 0.70))
      )
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["top_wick_pct_1d"] < 0.04)
        | (df["change_pct_1h"] > -0.02)
        | (df["not_downtrend_1h"])
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_1h"] > -0.02)
        | (df["not_downtrend_1d"])
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_1h"] > -0.02)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["r_480_4h"] > -80.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 12.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_1d"] < 0.26)
        | (df["top_wick_pct_1d"] < 0.16)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_4h"] < 60.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["top_wick_pct_1d"] < 0.12)
        | (df["change_pct_4h"] < 0.16)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_1h"] < 60.0)
        | (df["rsi_14_max_6_1h"] < 70.0)
        | (df["rsi_14_4h"] < 80.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["top_wick_pct_4h"] < 0.02)
        | (df["change_pct_4h"].shift(48) < 0.08)
        | (df["top_wick_pct_4h"].shift(48) < 0.08)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["r_480_4h"] > -80.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["change_pct_4h"].shift(48) < 0.02)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["r_480_4h"] > -80.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["not_downtrend_1d"])
        | (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["r_480_4h"] > -70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_4h"] < 0.03)
        | (df["top_wick_pct_4h"] < 0.03)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["ema_200_dec_4_1d"] == False)
        | (df["hl_pct_change_6_1d"] < 0.8)
      )
      & (
        (df["change_pct_4h"] > -0.04)
        | (df["top_wick_pct_4h"] < 0.04)
        | (df["change_pct_4h"].shift(48) < 0.04)
        | (df["not_downtrend_1h"])
        | (df["rsi_14_4h"] < 40.0)
        | (df["r_480_1h"] > -80.0)
        | (df["r_480_4h"] > -70.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_4h"] > 16.0)
        | (df["r_480_4h"] > -80.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_4h"] > 20.0)
        | (df["r_480_1h"] > -70.0)
        | (df["r_480_4h"] > -80.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_4h"] > 16.0)
        | (df["r_480_1h"] > -80.0)
        | (df["r_480_4h"] > -85.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["change_pct_1h"] > -0.02)
        | (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 65.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 16.0)
        | (df["r_480_1h"] < -40.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["change_pct_4h"] > -0.08)
        | (df["not_downtrend_4h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_1h"] > 30.0)
        | (df["rsi_3_4h"] > 16.0)
        | (df["rsi_14_4h"] > 30.0)
        | (df["r_480_1h"] > -70.0)
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      & (
        (df["change_pct_4h"] > -0.01)
        | (df["change_pct_4h"].shift(48) < 0.01)
        | (df["not_downtrend_1h"])
        | (df["rsi_3_1h"] > 12.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["r_480_1h"] > -65.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct_4h"] < 0.08)
        | (df["not_downtrend_1h"])
        | (df["rsi_14_max_6_1h"] < 70.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct_4h"] < 0.08)
        | (df["change_pct_1h"] > -0.04)
        | (df["change_pct_1h"].shift(12) < 0.04)
        | (df["rsi_14_1h"].shift(12) < 70.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct_4h"] > -0.08)
        | (df["change_pct_4h"].shift(48) < 0.08)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_14_max_6_1h"] < 70.0)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct_1d"] > -0.08)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["close"] > (df["high_max_12_1d"] * 0.70))
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["change_pct_1h"].shift(12) < 0.01)
        | (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 8.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["r_480_4h"] > -65.0)
        | (df["close"] > df["sup_level_1h"])
      )
      & (
        (df["change_pct_4h"] > -0.08)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_4h"] > 16.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["change_pct_1d"] > -0.06)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 50.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["close"] > (df["high_max_6_1d"] * 0.80))
      )
      & (
        (df["change_pct_1d"] < 0.16)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 12.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["close"] > (df["high_max_6_1d"] * 0.85))
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14"] < 36.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["r_480_1h"] > -65.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["r_480_4h"] < -35.0)
        | (df["close"] > df["sup_level_1h"])
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_max_6_1h"] < 70.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["close"] > (df["high_max_12_1d"] * 0.75))
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 20.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["close"] > (df["high_max_12_1d"] * 0.60))
      )
      & (
        (df["not_downtrend_1d"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (((df["close"] - df["low_min_6_1d"]) / df["low_min_6_1d"]) < (df["hl_pct_change_6_1d"] * 0.38))
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 60.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["r_480_4h"] > -70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14"] < 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["r_480_1h"] < -15.0)
        | (df["r_480_4h"] > -70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_15m"] < 32.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["ema_200_dec_4_1d"] == False)
        | (df["close"] > (df["high_max_6_1d"] * 0.85))
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["r_480_1h"] > -70.0)
        | (df["r_480_4h"] < -35.0)
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 26.0)
        | (df["r_480_1h"] > -65.0)
        | (df["r_480_4h"] > -70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["r_480_4h"] > -70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["change_pct_1h"].shift(12) < 0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 16.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["r_480_4h"] > -80.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["change_pct_4h"].shift(48) < 0.02)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_1h"] < -30.0)
        | (df["r_480_4h"] > -65.0)
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 6.0)
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 8.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_1d"] > -0.06)
        | (df["is_downtrend_3_1d"] == False)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_14"] < 32.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["close"] > (df["high_max_6_1d"] * 0.70))
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["close"] > df["sup_level_1h"])
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["r_480_4h"] > -70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 8.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["r_480_4h"] > -70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 6.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["r_480_4h"] > -65.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 6.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_max_6_4h"] < 70.0)
        | (df["r_480_4h"] > -70.0)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 20.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["rsi_14_max_6_1d"] < 65.0)
        | (df["r_480_1h"] > -65.0)
        | (df["r_480_4h"] > -75.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["close"] > (df["high_max_6_1d"] * 0.80))
      )
      & (
        (df["change_pct_4h"] < 0.04)
        | (df["top_wick_pct_4h"] < 0.02)
        | (df["not_downtrend_1d"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_15m"] < 30.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["r_480_4h"] > -80.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_4h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["r_480_4h"] > -70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["r_480_4h"] < -30.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["r_480_1h"] > -65.0)
        | (df["r_480_4h"] > -70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["change_pct_1h"].shift(12) < 0.03)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_14_1h"] < 60.0)
        | (df["rsi_14_max_6_1h"] < 70.0)
        | (df["r_480_1h"] > -65.0)
        | (df["r_480_4h"] > -70.0)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_1h"] < 0.04)
        | (df["not_downtrend_15m"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["r_480_1h"] < -25.0)
        | (df["r_480_4h"] > -70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["rsi_14_max_6_1d"] < 80.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > (df["high_max_6_1d"] * 0.65))
      )
      & (
        (df["change_pct_1d"] > -0.12)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > (df["high_max_6_1d"] * 0.70))
        | (df["hl_pct_change_6_1d"] < 1.2)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_4h"] > 20.0)
        | (df["r_480_1h"] > -90.0)
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["close"] > (df["high_max_12_1d"] * 0.50))
      )
      & (
        (df["change_pct_1d"] < 0.16)
        | (df["top_wick_pct_1d"] < 0.16)
        | (df["change_pct_4h"] > -0.02)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["r_480_4h"] > -70.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_1h"] < 60.0)
        | (df["rsi_14_max_6_1h"] < 70.0)
        | (df["r_480_4h"] > -70.0)
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (((df["close"] - df["low_min_6_1d"]) / df["low_min_6_1d"]) < (df["hl_pct_change_6_1d"] * 0.38))
      )
      & (
        (df["change_pct_1h"] > -0.02)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_max_6_1h"] < 65.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["r_480_1h"] > -80.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 10.0)
        | (df["rsi_14_15m"] < 50.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["r_480_1h"] < -35.0)
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_4h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_max_6_1h"] < 65.0)
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_max_6_1h"] < 65.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["r_480_4h"] > -70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_1h"] < 60.0)
        | (df["rsi_14_max_6_1h"] < 70.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["r_480_1h"] < -25.0)
        | (df["r_480_4h"] > -80.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 4.0)
        | (df["rsi_3_15m"] > 10.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["not_downtrend_4h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 6.0)
        | (df["rsi_3_15m"] > 10.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      & (
        (df["not_downtrend_1d"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_1d"] > 26.0)
        | (df["rsi_14_15m"] < 50.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["r_480_1h"] > -85.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_3_4h"] > 36.0)
        | (df["rsi_3_1d"] > 36.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["r_480_1h"] > -75.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
      )
      & (
        (df["change_pct_4h"] > -0.04)
        | (df["change_pct_4h"] > -0.04)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 2.0)
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["change_pct_1d"].shift(288) < 0.12)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["change_pct"].rolling(18).min() > -0.12)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_15m"] > 20.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["not_downtrend_4h"])
        | (df["is_downtrend_3_4h"] == False)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_3_4h"] > 16.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > (df["high_max_6_1d"] * 0.50))
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_3"] > 16.0)
        | (df["rsi_14_15m"] < 68.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      & (
        (df["change_pct_1d"] > -0.06)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 26.0)
        | (df["rsi_14_15m"] < 44.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 65.0)
        | (df["rsi_14_max_6_1d"] < 80.0)
        | (df["close"] > (df["high_max_6_1d"] * 0.70))
        | (df["hl_pct_change_6_1d"] < 1.2)
      )
      & (
        (df["not_downtrend_4h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_4h"] > 20.0)
        | (df["rsi_14_1d"] < 65.0)
        | (df["rsi_14_max_6_1d"] < 80.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["close"] > (df["high_max_6_1d"] * 0.70))
        | (df["hl_pct_change_6_1d"] < 0.7)
      )
      & (
        (df["change_pct_1d"] > -0.02)
        | (df["change_pct_4h"] < 0.03)
        | (df["change_pct_1h"] > -0.01)
        | (df["change_pct_1h"].shift(12) < 0.03)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_1d"] > -0.06)
        | (df["change_pct_1h"] > -0.04)
        | (df["change_pct_1h"].shift(12) < 0.04)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 36.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 65.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > (df["high_max_6_1d"] * 0.70))
        | (df["hl_pct_change_6_1d"] < 1.2)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["r_480_4h"] > -80.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_min_3_4h"] > -0.16)
        | (df["not_downtrend_1d"])
        | (df["rsi_3_4h"] > 20.0)
        | (df["rsi_14_1h"] > 30.0)
        | (df["rsi_14_4h"] > 30.0)
        | (df["r_480_1h"] > -80.0)
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
        | (df["close"] > (df["high_max_24_1h"] * 0.76))
      )
      & (
        (df["change_pct_1d"] > -0.16)
        | (df["change_pct_1d"].shift(288) < 0.16)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > (df["high_max_24_1h"] * 0.75))
        | (df["hl_pct_change_6_1d"] < 0.9)
      )
      & (
        (df["change_pct_4h"] < 0.01)
        | (df["change_pct_4h"].shift(48) < 0.04)
        | (df["change_pct_1h"] > -0.01)
        | (df["not_downtrend_1d"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_max_6_1h"] < 65.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["r_480_1h"] > -65.0)
        | (df["ema_200_dec_48_1h"] == False)
      )
      & (
        (df["change_pct_4h"] > -0.12)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_3_4h"] > 20.0)
        | (df["r_480_1h"] > -60.0)
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 6.0)
        | (df["rsi_3_4h"] > 26.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["r_480_4h"] > -70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_3_4h"] > 20.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | ((df["zlma_50_1h"].ne(0.0)) & (df["close"] > df["zlma_50_1h"]))
        | ((df["zlma_50_4h"].ne(0.0)) & (df["close"] > df["zlma_50_4h"]))
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_3_1d"] > 26.0)
        | (df["rsi_14_max_6_1d"] < 65.0)
        | (df["r_480_1h"] > -90.0)
        | (df["r_480_4h"] > -65.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > (df["high_max_6_1d"] * 0.40))
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_1h"] > 2.0)
        | (df["rsi_3_4h"] > 16.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_1h"] > 10.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_3_1d"] > 30.0)
        | (df["r_480_1h"] > -80.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct_4h"] < 0.02)
        | (df["top_wick_pct_4h"] < 0.02)
        | (df["change_pct_1h"] > -0.01)
        | (df["not_downtrend_1d"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_max_6_1h"] < 65.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 46.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["sma_200_dec_48_1h"] == False)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["not_downtrend_1h"])
        | (df["is_downtrend_3_1h"] == False)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["sma_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_14_1h"] > -99.0)
        | (df["close"] > df["sup_level_1h"])
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_max_6_1h"] < 70.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_4h"] > -60.0)
      )
      & (
        (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 16.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["r_480_1h"] > -70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["close"] > (df["high_max_12_1d"] * 0.80))
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_15m"] > 8.0)
        | (df["rsi_3_1h"] > 8.0)
        | (df["rsi_3_4h"] > 8.0)
        | (df["r_480_1h"] > -90.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["is_downtrend_3_4h"] == False)
        | (df["not_downtrend_1d"])
        | (df["rsi_3_15m"] > 12.0)
        | (df["rsi_3_1h"] > 12.0)
        | (df["rsi_3_4h"] > 16.0)
        | (df["r_480_1h"] > -80.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
      )
      & (
        (df["change_pct_1d"] > -0.01)
        | (df["top_wick_pct_1d"] < 0.08)
        | (df["change_pct_1d"].shift(288) < 0.20)
        | (df["change_pct_1h"] < 0.06)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_3"] > 26.0)
        | (df["rsi_14_15m"] < 50.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["r_480_1h"] > -60.0)
        | (df["r_480_4h"] > -60.0)
        | (((df["close"] - df["low_min_6_1d"]) / df["low_min_6_1d"]) < (df["hl_pct_change_6_1d"] * 0.38))
      )
      & (
        (df["change_pct_1d"] < 0.16)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["rsi_14_max_6_4h"] < 80.0)
        | (df["r_480_4h"] > -70.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
        | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
      )
      & (
        (df["change_pct_1d"] > -0.16)
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_4h"] > 16.0)
        | (df["r_480_1h"] > -90.0)
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > (df["high_max_48_1h"] * 0.70))
      )
      & (
        (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 36.0)
        | (df["r_14"] < -80.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["r_14_1h"] < -60.0)
        | (df["r_14_4h"] < -25.0)
        | (df["r_480_1h"] > -70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct"].rolling(6).min() > -0.04)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14"] < 20.0)
        | (df["rsi_14_15m"] < 20.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["r_14_1h"] < -35.0)
        | (df["r_14_4h"] < -35.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["change_pct_4h"].shift(48) < 0.02)
        | (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 8.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["r_14"] < -95.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["r_14_1h"] < -95.0)
        | (df["r_14_4h"] < -95.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_1h"] > 10.0)
        | (df["rsi_3_4h"] > 26.0)
        | (df["r_14_1h"] < -95.0)
        | (df["r_14_4h"] < -95.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
      )
      & (
        (df["change_pct_1d"] > -0.10)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_3_4h"] > 36.0)
        | (df["rsi_14"] < 25.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["r_14_1h"] < -95.0)
        | (df["r_14_4h"] < -95.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["change_pct_1d"] > -0.10)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["r_14_1h"] < -80.0)
        | (df["r_14_4h"] < -80.0)
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["change_pct_1h"].shift(12) < 0.04)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 16.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["r_14_1h"] < -80.0)
        | (df["r_14_4h"] < -80.0)
        | (df["r_480_1h"] > -70.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["change_pct_4h"] < 0.06)
        | (df["change_pct_1h"] > -0.01)
        | (df["change_pct_1h"].shift(12) < 0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_1h"].shift(12) < 70.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["not_downtrend_4h"])
        | (df["is_downtrend_3_4h"] == False)
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_4h"] > 10.0)
        | (df["r_14_1h"] > -80.0)
        | (df["r_14_4h"] > -80.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_12_1h"] > df["ema_26_1h"])
      )
      & (
        (df["change_pct_4h"] < 0.04)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_3"] > 6.0)
        | (df["rsi_14_15m"] < 50.0)
        | (df["rsi_14_1h"] < 60.0)
        | (df["rsi_14_1h"].shift(12) < 70.0)
        | (df["rsi_14_4h"] < 60.0)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct_1d"] < 0.20)
        | (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["top_wick_pct_1d"] < 0.04)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_15m"] > 30.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["cti_20_4h"] < 0.8)
        | (df["r_480_1h"] > -70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["sma_200_dec_48_1h"] == False)
      )
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 4.0)
        | (df["rsi_3_1h"] > 12.0)
        | (df["rsi_3_4h"] > 16.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["r_480_1h"] > -85.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["sma_200_dec_48_1h"] == False)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["not_downtrend_1d"])
        | (df["rsi_3"] > 16.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["r_480_1h"] > -70.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["sma_200_dec_48_1h"] == False)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
      )
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["sma_200_dec_48_1h"] == False)
        | (df["ema_200_dec_48_1h"] == False)
      )
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["top_wick_pct_1d"] < 0.04)
        | (df["change_pct_1d"].shift(288) < 0.24)
        | (df["not_downtrend_1h"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["r_480_1h"] > -65.0)
        | (df["sma_200_dec_48_1h"] == False)
        | (df["ema_200_dec_48_1h"] == False)
      )
      & (
        (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 12.0)
        | (df["rsi_3_4h"] > 30.0)
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["r_480_1h"] > -75.0)
        | (df["close"] > df["sup_level_4h"])
        | (df["sma_200_dec_48_1h"] == False)
        | (df["ema_200_dec_48_1h"] == False)
      )
      & (
        (df["change_pct_1d"] > -0.02)
        | (df["change_pct_1d"].shift(288) > -0.02)
        | (df["change_pct_1h"] > -0.01)
        | (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 16.0)
        | (df["rsi_3_1h"] > 26.0)
        | (df["rsi_14_1h"] < 30.0)
        | (df["rsi_14_4h"] < 30.0)
        | (df["rsi_14_1d"] < 30.0)
        | (df["r_480_1h"] > -75.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["sma_200_dec_48_1h"] == False)
        | (df["ema_200_dec_48_1h"] == False)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 26.0)
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_14_1h"] < 30.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["r_14_1h"] > -95.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
      )
      & (
        (df["change_pct_1d"] > -0.08)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_3_1d"] > 36.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["r_480_1h"] > -85.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
      )
      & (
        (df["change_pct_1d"] > -0.02)
        | (df["change_pct_1d"].shift(288) < 0.08)
        | (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["r_480_1h"] < -40.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_14"] < 30.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["r_480_1h"] > -65.0)
        | (df["r_480_4h"] > -75.0)
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["change_pct"].rolling(12).min() > -0.08)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_3_4h"] > 26.0)
        | (df["rsi_14_1h"] < 30.0)
        | (df["rsi_14_4h"] < 36.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
      )
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 16.0)
        | (df["rsi_14"] < 15.0)
        | (df["rsi_14_15m"] < 20.0)
        | (df["rsi_14_1h"] < 30.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_14_1h"] > -90.0)
        | (df["r_14_4h"] > -75.0)
        | (df["close"] > df["sup_level_1h"])
      )
      & (
        (df["change_pct_1d"] > -0.05)
        | (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1h"] > 25.0)
        | (df["r_14_1h"] > -90.0)
        | (df["r_14_4h"] > -75.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["change_pct_4h"] > -0.01)
        | (df["change_pct_4h"].shift(48) < 0.01)
        | (df["not_downtrend_1h"])
        | (df["rsi_14_4h"] < 40.0)
        | (df["rsi_14_1d"] < 50.0)
        | (df["r_480_1h"] < -35.0)
        | (df["close"] > df["sup_level_1h"])
      )
    )

    # Global protections
    df["protections_long_rebuy"] = (
      # 1h & 4h downtrend, 15m & 1h & 4h downmove
      (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_3_4h"] > 20.0)
      )
      # current 1d red, 5m & 15m downmove, 1h & 4h & 1d still high, pump in last 6 days
      & (
        (df["change_pct_1d"] > -0.01)
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 26.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["hl_pct_change_6_1d"] < 0.5)
      )
      # 1h & 1d downtrend, 5m & 1h & 1d downmove, 1h downtrend, drop in last 6 days
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 16.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_3_1d"] > 20.0)
        | (df["ema_200_dec_48_1h"] == False)
        | (df["close"] > (df["high_max_6_1d"] * 0.75))
      )
      # 5m & 15m downmove, 15m & 4h & 1d still high, 5m low, 1d downtrend
      & (
        (df["rsi_3"] > 12.0)
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_14_15m"] < 26.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 40.0)
        | (df["r_480"] > -90.0)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h downtrend, 5m & 15m & 1h downmove, 15m & 4h & 1d still high
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 36.0)
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.8)
        | (df["rsi_14_1d"] < 60.0)
      )
      # 15m downtrend, 5m & 15m & 1h downmove, 5m & 15m & 1h & 4h & 1d still high
      & (
        (df["not_downtrend_15m"])
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_14"] < 30.0)
        | (df["rsi_14_15m"] < 33.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["rsi_14_1d"] < 36.0)
        | (df["close"] > df["bb20_2_low_15m"])
      )
      # current 1d red, previous 1d green, 5m downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_1d"] > -0.03)
        | (df["change_pct_1d"].shift(288) < 0.03)
        | (df["rsi_3"] > 12.0)
        | (df["rsi_14_15m"] < 46.0)
        | (df["cti_20_1h"] < -0.0)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < -0.0)
        | (df["rsi_14_4h"] < 46.0)
        | (df["cti_20_1d"] < 0.7)
        | (df["rsi_14_1d"] < 50.0)
      )
      # current 1d green, current 1h red, 5m downmove, 15m & 1h & 4h & 1d high
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_3"] > 20.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["cti_20_1h"] < 0.5)
        | (df["rsi_14_1h"] < 50.0)
        | (df["cti_20_4h"] < 0.5)
        | (df["rsi_14_4h"] < 70.0)
        | (df["rsi_14_1d"] < 46.0)
      )
      # current 1d green with top wick, current 1h red, 5m & 1h downmove, 15m & 1h & 4h & 1d still high
      & (
        (df["change_pct_1d"] < 0.03)
        | (df["top_wick_pct_1d"] < 0.03)
        | (df["change_pct_1h"] > -0.01)
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["cti_20_4h"] < 0.7)
        | (df["rsi_14_4h"] < 50.0)
        | (df["rsi_14_1d"] < 60.0)
      )
      # 15m & 1h downtrend, 15m & 1h downmove, 1h & 4h & 1d still high
      & (
        (df["not_downtrend_15m"])
        | (df["not_downtrend_1h"])
        | (df["rsi_3_15m"] > 20.0)
        | (df["rsi_3_1h"] > 20.0)
        | (df["rsi_14_1h"] < 30.0)
        | (df["rsi_14_4h"] < 40.0)
        | (df["cti_20_1d"] < 0.5)
        | (df["rsi_14_1d"] < 50.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      # 1h & 4h downtrend, 5m & 1h downmove, 15m & 1h still high, 1h & 4h low, 1h & 4h & 1d downtrend
      & (
        (df["not_downtrend_1h"])
        | (df["not_downtrend_4h"])
        | (df["rsi_3"] > 30.0)
        | (df["rsi_3_1h"] > 36.0)
        | (df["rsi_14_15m"] < 36.0)
        | (df["rsi_14_1h"] < 36.0)
        | (df["r_480_1h"] > -75.0)
        | (df["r_480_4h"] > -80.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_48_1h"] == False)
        | (df["ema_200_dec_24_4h"] == False)
        | (df["ema_200_dec_4_1d"] == False)
      )
      # 1h downtrend, 5m & 15m downmove, 15m & 1h & 4h still high, 1h low
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_1h"] > 30.0)
        | (df["rsi_14_15m"] < 30.0)
        | (df["cti_20_1h"] < -0.0)
        | (df["rsi_14_1h"] < 40.0)
        | (df["cti_20_4h"] < -0.5)
        | (df["rsi_14_4h"] < 46.0)
        | (df["r_480_1h"] > -75.0)
        | (df["close"] > df["sup_level_1h"])
      )
      # 4h & 1d downtrend, 5m & 15m & 4h downmove, 1d downtrend
      & (
        (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] > 20.0)
        | (df["rsi_3_15m"] > 10.0)
        | (df["rsi_3_4h"] > 20.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["ema_200_dec_4_1d"] == False)
      )
      & (
        (df["not_downtrend_1h"])
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] > 10.0)
        | (df["rsi_3_15m"] > 30.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
      )
      & (
        (df["change_pct_1h"] > -0.01)
        | (df["rsi_14"] > df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
        | (df["rsi_14_15m"] < 40.0)
        | (df["rsi_14_1h"] < 46.0)
        | (df["rsi_14_4h"] < 50.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["ema_200_dec_24_4h"] == False)
      )
    )

    df["protections_short_global"] = True

    df["global_protections_short_pump"] = (
      (
        (df["change_pct_4h"] < 0.04)
        | (df["rsi_14"] < df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] < df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] < 96.0)
        | (df["rsi_3_15m"] < 90.0)
        | (df["r_480_1h"] < -20.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["ema_200_dec_48_1h"] == True)
        | (df["hl_pct_change_6_1d"] < 0.5)
      )
      & (
        (df["change_pct_1h"] < 0.02)
        | (df["rsi_14"] < df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] < df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] < 94.0)
        | (df["rsi_3_15m"] < 86.0)
        | (df["r_480_1h"] < -10.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["ema_200_dec_48_1h"] == True)
        | (df["hl_pct_change_6_1d"] < 1.2)
      )
      & (
        (df["change_pct_4h"] < 0.02)
        | (df["change_pct_1h"] < 0.04)
        | (df["rsi_14"] < df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] < df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] < 90.0)
        | (df["rsi_3_15m"] < 74.0)
        | (df["rsi_3_1h"] < 74.0)
        | (df["r_480_1h"] < -12.0)
        | (df["r_480_4h"] < -22.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_4h"] < 0.08)
        | (df["change_pct_1h"] < 0.06)
        | (df["rsi_14"] < df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] < df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] < 90.0)
        | (df["rsi_3_15m"] < 84.0)
        | (df["rsi_3_1h"] < 84.0)
        | (df["rsi_3_4h"] < 84.0)
        | (df["r_480_1h"] < -12.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_1h"] < 0.10)
        | (df["rsi_14"] < df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] < df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] < 90.0)
        | (df["rsi_3_15m"] < 78.0)
        | (df["rsi_3_1h"] < 90.0)
        | (df["r_480_1h"] < -16.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["hl_pct_change_6_1d"] < 0.7)
      )
      & (
        (df["change_pct_1h"] < 0.03)
        | (df["rsi_14"] < df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] < df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] < 94.0)
        | (df["rsi_3_15m"] < 84.0)
        | (df["cti_20_1h"] > 0.5)
        | (df["cti_20_4h"] > 0.5)
        | (df["rsi_14_4h"] > 70.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["hl_pct_change_6_1d"] < 0.9)
      )
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["rsi_14"] < df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] < df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] < 92.0)
        | (df["rsi_3_15m"] < 90.0)
        | (df["rsi_14_1h"] > 64.0)
        | (df["rsi_14_4h"] > 70.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["hl_pct_change_6_1d"] < 0.9)
      )
      & (
        (df["change_pct_1d"] < 0.30)
        | (df["rsi_14"] < df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] < df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] < 85.0)
        | (df["rsi_3_15m"] < 90.0)
        | (df["rsi_3_4h"] < 90.0)
        | (df["rsi_14_1h"] > 90.0)
        | (df["rsi_14_4h"] > 90.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
      )
      & (
        (df["change_pct_1d"] < 0.20)
        | (df["change_pct_4h"] < 0.08)
        | (df["change_pct_1h"] < 0.04)
        | (df["rsi_14"] < df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] < df["rsi_14_15m"].shift(12))
        | (df["rsi_3_1h"] < 90.0)
        | (df["rsi_3_4h"] < 90.0)
        | (df["rsi_3_1d"] < 90.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_4h"] < 0.04)
        | (df["change_pct_1h"] < 0.03)
        | (df["rsi_14"] < df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] < df["rsi_14_15m"].shift(12))
        | (df["rsi_14_15m"] > 70.0)
        | (df["rsi_3_1h"] < 70.0)
        | (df["rsi_3_4h"] < 70.0)
        | (df["r_480_1h"] > -65.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
      )
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["change_pct_4h"] < 0.01)
        | (df["change_pct_1h"] < 0.01)
        | (df["rsi_14"] < df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] < df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] < 90.0)
        | (df["rsi_3_1h"] < 85.0)
        | (df["rsi_3_4h"] < 70.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_4h"] < 0.02)
        | (df["change_pct_1h"] < 0.01)
        | (df["rsi_14"] < df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] < df["rsi_14_15m"].shift(12))
        | (df["rsi_3_15m"] < 80.0)
        | (df["rsi_3_1h"] < 70.0)
        | (df["rsi_14_1h"] > 55.0)
        | (df["rsi_14_4h"] > 50.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["hl_pct_change_6_1d"] < 1.9)
      )
      & (
        (df["change_pct_1d"] > -0.24)
        | (df["rsi_14_1h"] > 65.0)
        | (df["rsi_14_4h"] > 60.0)
        | (df["hl_pct_change_6_1d"] < 4.0)
      )
      & (
        (df["change_pct_1d"] < 0.16)
        | (df["change_pct_1h"] < 0.01)
        | (df["rsi_3"] < 80.0)
        | (df["rsi_3_15m"] < 75.0)
        | (df["rsi_3_1d"] < 80.0)
        | (df["rsi_14_1h"] > 70.0)
        | (df["rsi_14_4h"] > 80.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["r_480_1h"] < -25.0)
        | (df["r_480_4h"] < -20.0)
      )
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["change_pct_1h"] < 0.02)
        | (df["rsi_3"] < 70.0)
        | (df["rsi_3_1d"] < 75.0)
        | (df["rsi_14_1h"] > 75.0)
        | (df["rsi_14_4h"] > 70.0)
        | (df["rsi_14_1d"] > 65.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_1d"] < 0.30)
        | (df["rsi_3"] < 75.0)
        | (df["rsi_3_15m"] < 70.0)
        | (df["rsi_3_1h"] < 70.0)
        | (df["rsi_3_4h"] < 90.0)
        | (df["rsi_3_1d"] < 90.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_4h"] < 0.02)
        | (df["rsi_3"] < 90.0)
        | (df["rsi_3_15m"] < 80.0)
        | (df["rsi_3_1h"] < 70.0)
        | (df["rsi_14_1h"] > 60.0)
        | (df["rsi_14_4h"] > 60.0)
        | (df["rsi_14_1d"] > 65.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["change_pct_4h"] < 0.01)
        | (df["change_pct_1h"] < 0.01)
        | (df["rsi_3"] < 90.0)
        | (df["rsi_3_15m"] < 80.0)
        | (df["rsi_3_1d"] < 75.0)
        | (df["rsi_14_15m"] > 65.0)
        | (df["rsi_14_1h"] > 50.0)
        | (df["rsi_14_4h"] > 50.0)
        | (df["r_480_4h"] < -35.0)
      )
      & (
        (df["change_pct_1d"] < 0.20)
        | (df["rsi_14"] < df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] < df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] < 70.0)
        | (df["rsi_3_15m"] < 75.0)
        | (df["rsi_3_1d"] < 80.0)
        | (df["rsi_14_15m"] > 75.0)
        | (df["rsi_14_1h"] > 65.0)
        | (df["rsi_14_4h"] > 65.0)
        | (df["r_480_1h"] < -40.0)
        | (df["r_480_4h"] < -40.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["bot_wick_pct_1d"] < 0.20)
        | (df["rsi_14"] < df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] < df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] < 80.0)
        | (df["rsi_3_15m"] < 75.0)
        | (df["rsi_14_1h"] > 70.0)
        | (df["r_480_1h"] < -25.0)
        | (df["r_480_4h"] < -20.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["change_pct_4h"] > -0.04)
        | (df["change_pct_1h"] < 0.01)
        | (df["rsi_3"] < 80.0)
        | (df["rsi_3_15m"] < 80.0)
        | (df["rsi_14_15m"] > 60.0)
        | (df["rsi_14_1h"] > 45.0)
        | (df["rsi_14_4h"] > 45.0)
        | (df["rsi_14_1d"] > 65.0)
        | (df["ema_200_dec_48_1h"] == True)
        | (df["ema_200_dec_24_4h"] == True)
      )
      & (
        (df["change_pct_1d"] > -0.02)
        | (df["rsi_3"] < 90.0)
        | (df["rsi_3_15m"] < 65.0)
        | (df["rsi_3_1h"] < 65.0)
        | (df["rsi_3_4h"] < 65.0)
        | (df["rsi_14_15m"] > 70.0)
        | (df["rsi_14_1h"] > 70.0)
        | (df["rsi_14_4h"] > 70.0)
        | (df["r_480_1h"] < -10.0)
        | (df["r_480_4h"] < -15.0)
        | (df["ema_200_dec_48_1h"] == True)
        | (df["ema_200_dec_24_4h"] == True)
      )
      & (
        (df["change_pct_1d"] > -0.06)
        | (df["bot_wick_pct_1d"] < 0.08)
        | (df["rsi_3"] < 70.0)
        | (df["rsi_3_15m"] < 70.0)
        | (df["rsi_14_15m"] > 70.0)
        | (df["rsi_14_1h"] > 70.0)
        | (df["rsi_14_4h"] > 70.0)
        | (df["ema_200_dec_48_1h"] == True)
        | (df["ema_200_dec_24_4h"] == True)
      )
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["change_pct_4h"] > -0.04)
        | (df["change_pct_1h"] < 0.02)
        | (df["rsi_3"] < 75.0)
        | (df["rsi_3_15m"] < 65.0)
        | (df["rsi_14_15m"] > 65.0)
        | (df["rsi_14_1h"] > 55.0)
        | (df["rsi_14_4h"] > 55.0)
        | (df["r_480_1h"] < -40.0)
        | (df["r_480_4h"] < -35.0)
        | (df["ema_200_dec_48_1h"] == True)
        | (df["ema_200_dec_24_4h"] == True)
      )
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["rsi_3"] < 80.0)
        | (df["rsi_3_15m"] < 75.0)
        | (df["rsi_3_1h"] < 65.0)
        | (df["rsi_3_4h"] < 75.0)
        | (df["r_480_1h"] < -20.0)
        | (df["r_480_4h"] < -20.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["ema_200_dec_48_1h"] == True)
        | (df["ema_200_dec_24_4h"] == True)
      )
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["rsi_3"] < 85.0)
        | (df["rsi_3_15m"] < 75.0)
        | (df["rsi_14_15m"] > 60.0)
        | (df["rsi_14_1h"] > 50.0)
        | (df["rsi_14_4h"] > 65.0)
        | (df["r_480_4h"] < -30.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["ema_200_dec_48_1h"] == True)
        | (df["ema_200_dec_24_4h"] == True)
      )
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["change_pct_4h"] < 0.02)
        | (df["change_pct_1h"] < 0.02)
        | (df["rsi_3"] < 70.0)
        | (df["rsi_3_15m"] < 75.0)
        | (df["r_480_1h"] < -10.0)
        | (df["r_480_4h"] < -10.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["ema_200_dec_48_1h"] == True)
        | (df["ema_200_dec_24_4h"] == True)
      )
      & (
        (df["change_pct_4h"] < 0.02)
        | (df["change_pct_1h"] < 0.03)
        | (df["rsi_3"] < 70.0)
        | (df["rsi_3_15m"] < 70.0)
        | (df["rsi_3_1h"] < 75.0)
        | (df["r_480_1h"] < -20.0)
        | (df["r_480_4h"] < -25.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["ema_200_dec_48_1h"] == True)
        | (df["ema_200_dec_24_4h"] == True)
      )
      & (
        (df["change_pct_4h"] < 0.01)
        | (df["change_pct_1h"] < 0.02)
        | (df["rsi_3"] < 80.0)
        | (df["rsi_3_1h"] < 70.0)
        | (df["rsi_3_4h"] < 70.0)
        | (df["rsi_14_15m"] > 75.0)
        | (df["rsi_14_1h"] > 75.0)
        | (df["rsi_14_4h"] > 80.0)
        | (df["r_480_1h"] < -10.0)
        | (df["r_480_4h"] < -20.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["ema_200_dec_48_1h"] == True)
        | (df["ema_200_dec_24_4h"] == True)
      )
      & (
        (df["change_pct_1d"] < 0.16)
        | (df["change_pct_4h"] < 0.02)
        | (df["change_pct_1h"] < 0.02)
        | (df["rsi_3"] < 80.0)
        | (df["rsi_3_15m"] < 65.0)
        | (df["rsi_3_1h"] < 75.0)
        | (df["rsi_3_4h"] < 70.0)
        | (df["rsi_14_15m"] > 75.0)
        | (df["rsi_14_1h"] > 80.0)
        | (df["rsi_14_4h"] > 70.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["ema_200_dec_48_1h"] == True)
        | (df["ema_200_dec_24_4h"] == True)
      )
      & (
        (df["change_pct_1d"] < 0.06)
        | (df["change_pct_1h"] < 0.01)
        | (df["rsi_3"] < 80.0)
        | (df["rsi_3_15m"] < 70.0)
        | (df["rsi_14_15m"] > 75.0)
        | (df["rsi_14_1h"] > 70.0)
        | (df["r_480_1h"] < -15.0)
        | (df["r_480_4h"] < -15.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["ema_200_dec_48_1h"] == True)
        | (df["ema_200_dec_24_4h"] == True)
      )
      & (
        (df["change_pct_1h"] < 0.01)
        | (df["rsi_14"] < df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] < df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] < 90.0)
        | (df["rsi_3_15m"] < 90.0)
        | (df["rsi_14_1h"] > 65.0)
        | (df["rsi_14_4h"] > 50.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
      )
      & (
        (df["change_pct_4h"] < 0.02)
        | (df["change_pct_1h"] < 0.02)
        | (df["rsi_3"] < 90.0)
        | (df["rsi_3_15m"] < 65.0)
        | (df["rsi_3_1h"] < 75.0)
        | (df["rsi_14_15m"] > 65.0)
        | (df["rsi_14_1h"] > 55.0)
        | (df["rsi_14_4h"] > 70.0)
        | (df["r_480_1h"] < -30.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["ema_200_dec_48_1h"] == True)
        | (df["ema_200_dec_24_4h"] == True)
      )
      & (
        (df["change_pct_1d"] < 0.26)
        | (df["change_pct_4h"] < 0.02)
        | (df["change_pct_1h"] < 0.02)
        | (df["rsi_3"] < 85.0)
        | (df["rsi_3_15m"] < 85.0)
        | (df["rsi_14_15m"] > 70.0)
        | (df["rsi_14_1h"] > 60.0)
        | (df["rsi_14_4h"] > 70.0)
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["ema_200_dec_48_1h"] == True)
        | (df["ema_200_dec_24_4h"] == True)
      )
      & (
        (df["change_pct_1h"] < 0.01)
        | (df["rsi_14"] < df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] < df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] < 75.0)
        | (df["rsi_3_15m"] < 70.0)
        | (df["rsi_14_1h"] > 70.0)
        | (df["rsi_14_4h"] > 80.0)
        | (df["rsi_14_1d"] > 80.0)
        | (df["r_480_1h"] < -30.0)
        | (df["r_480_4h"] < -40.0)
        | (df["close"] < df["res_hlevel_1d"])
        | (df["ema_200_dec_48_1h"] == True)
        | (df["ema_200_dec_24_4h"] == True)
        | (df["ema_200_dec_4_1d"] == True)
      )
      & (
        (df["change_pct_1d"] < 0.02)
        | (df["change_pct_1d"].shift(288) > -0.08)
        | (df["change_pct_1h"] < 0.02)
        | (df["rsi_3"] < 80.0)
        | (df["rsi_3_15m"] < 70.0)
        | (df["rsi_14_15m"] > 75.0)
        | (df["rsi_14_1h"] > 65.0)
        | (df["rsi_14_4h"] > 60.0)
        | (df["rsi_14_1d"] > 70.0)
        | (df["r_480_1h"] < -35.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["ema_200_dec_48_1h"] == True)
        | (df["ema_200_dec_24_4h"] == True)
      )
      & (
        (df["change_pct_1d"] < 0.02)
        | (df["change_pct_4h"] < 0.02)
        | (df["rsi_3"] < 80.0)
        | (df["rsi_3_15m"] < 70.0)
        | (df["rsi_14_15m"] > 75.0)
        | (df["rsi_14_1h"] > 75.0)
        | (df["rsi_14_4h"] > 75.0)
        | (df["rsi_14_1d"] > 70.0)
        | (df["r_480_1h"] < -35.0)
        | (df["close"] < df["res_hlevel_1d"])
        | (df["ema_200_dec_48_1h"] == True)
        | (df["ema_200_dec_24_4h"] == True)
      )
      & (
        (df["change_pct_1d"] < 0.16)
        | (df["rsi_3"] < 80.0)
        | (df["rsi_3_15m"] < 75.0)
        | (df["rsi_3_1h"] < 65.0)
        | (df["rsi_14_15m"] > 75.0)
        | (df["rsi_14_1h"] > 65.0)
        | (df["rsi_14_4h"] > 70.0)
        | (df["rsi_14_1d"] > 70.0)
        | (df["r_480_1h"] < -20.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["ema_200_dec_48_1h"] == True)
        | (df["ema_200_dec_24_4h"] == True)
      )
      & (
        (df["change_pct_1d"] < 0.02)
        | (df["change_pct_4h"] > -0.01)
        | (df["change_pct_1h"] < 0.01)
        | (df["rsi_14_15m"] > 70.0)
        | (df["rsi_14_1h"] > 65.0)
        | (df["rsi_14_4h"] > 60.0)
        | (df["r_480_1h"] < -20.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["ema_200_dec_48_1h"] == True)
        | (df["ema_200_dec_24_4h"] == True)
      )
      & (
        (df["change_pct_1d"] > -0.12)
        | (df["change_pct_4h"] < 0.08)
        | (df["change_pct_1h"] < 0.02)
        | (df["rsi_3"] < 85.0)
        | (df["rsi_3_15m"] < 85.0)
        | (df["rsi_14_1d"] > 70.0)
        | (df["r_480_1h"] < -30.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["ema_200_dec_48_1h"] == True)
        | (df["ema_200_dec_24_4h"] == True)
      )
      & (
        (df["change_pct_1d"] < 0.16)
        | (df["change_pct_1h"] < 0.01)
        | (df["rsi_14_15m"] > 70.0)
        | (df["rsi_14_1h"] > 70.0)
        | (df["rsi_14_4h"] > 75.0)
        | (df["rsi_14_1d"] > 80.0)
        | (df["r_480_1h"] < -20.0)
        | (df["r_480_4h"] < -20.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["ema_200_dec_48_1h"] == True)
        | (df["ema_200_dec_24_4h"] == True)
      )
      & (
        (df["change_pct_4h"] < 0.04)
        | (df["rsi_3"] < 85.0)
        | (df["rsi_3_1h"] < 80.0)
        | (df["rsi_3_4h"] < 80.0)
        | (df["rsi_14_4h"] > 70.0)
        | (df["rsi_14_1d"] > 60.0)
        | (df["r_480_1h"] < -30.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["change_pct_4h"] < 0.04)
        | (df["rsi_14"] > 75.0)
        | (df["rsi_14_15m"] > 65.0)
        | (df["rsi_14_1h"] > 65.0)
        | (df["rsi_14_4h"] > 70.0)
        | (df["r_480_1h"] < -35.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["ema_200_dec_48_1h"] == True)
      )
      & (
        (df["change_pct_1d"] < 0.34)
        | (df["change_pct_1h"] < 0.02)
        | (df["rsi_14"] > 80.0)
        | (df["rsi_14_15m"] > 65.0)
        | (df["rsi_14_1h"] > 75.0)
        | (df["rsi_14_4h"] > 75.0)
        | (df["r_480_1h"] < -15.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["ema_200_dec_48_1h"] == True)
      )
      & (
        (df["change_pct_4h"] < 0.01)
        | (df["rsi_3"] < 85.0)
        | (df["rsi_14"] > 75.0)
        | (df["rsi_14_15m"] > 75.0)
        | (df["rsi_14_1h"] > 75.0)
        | (df["rsi_14_4h"] > 80.0)
        | (df["r_480_1h"] < -20.0)
        | (df["r_480_4h"] < -20.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["ema_200_dec_48_1h"] == True)
        | (df["ema_200_dec_24_4h"] == True)
      )
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["change_pct_1d"].shift(288) > -0.02)
        | (df["rsi_14"] > 90.0)
        | (df["rsi_14_15m"] > 80.0)
        | (df["rsi_14_1h"] > 65.0)
        | (df["rsi_14_4h"] > 70.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
        | (df["ema_200_dec_48_1h"] == True)
        | (df["ema_200_dec_24_4h"] == True)
      )
      & (
        (df["change_pct_1d"] > -0.01)
        | (df["change_pct_4h"] > -0.01)
        | (df["change_pct_1h"] < 0.01)
        | (df["rsi_14"] > 85.0)
        | (df["rsi_14_15m"] > 70.0)
        | (df["rsi_14_1h"] > 60.0)
        | (df["rsi_14_4h"] > 55.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["ema_200_dec_48_1h"] == True)
        | (df["ema_200_dec_24_4h"] == True)
      )
      & (
        (df["change_pct_1d"] < 0.08)
        | (df["change_pct_1h"] < 0.01)
        | (df["rsi_3"] < 90.0)
        | (df["rsi_3_15m"] < 90.0)
        | (df["rsi_3_1h"] < 90.0)
        | (df["rsi_14_1h"] > 80.0)
        | (df["rsi_14_4h"] > 70.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_4h"] < 0.08)
        | (df["rsi_3"] < 80.0)
        | (df["rsi_3_15m"] < 80.0)
        | (df["rsi_3_4h"] < 95.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_1d"] < 0.26)
        | (df["change_pct_1h"] < 0.02)
        | (df["rsi_3"] < 80.0)
        | (df["rsi_3_15m"] < 80.0)
        | (df["rsi_3_1h"] < 75.0)
        | (df["rsi_14"] > 80.0)
        | (df["rsi_14_15m"] > 70.0)
        | (df["rsi_14_1d"] > 80.0)
        | (df["rsi_14_1d"].shift(288) > 45.0)
        | (df["r_480_1h"] < -20.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
      & (
        (df["change_pct_1d"] < 0.10)
        | (df["rsi_3"] < 80.0)
        | (df["rsi_3_15m"] < 80.0)
        | (df["rsi_3_1h"] < 80.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
        | (df["close"] < df["res_hlevel_1d"])
      )
    )

    df["global_protections_short_dump"] = (
      (
        (df["change_pct_1d"] < 0.10)
        | (df["change_pct_1h"] < 0.02)
        | (df["rsi_14"] < df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] < df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] < 80.0)
        | (df["rsi_3_15m"] < 74.0)
        | (df["rsi_3_1h"] < 86.0)
        | (df["rsi_14_1h"] > 70.0)
        | (df["rsi_14_4h"] > 60.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
      )
      & (
        (df["change_pct_1d"] < 0.12)
        | (df["change_pct_1d"].shift(288) > -0.12)
        | (df["rsi_14_4h"] > 64.0)
        | (df["rsi_14_1d"] > 40.0)
        | (df["close"] < df["res_hlevel_1h"])
        | (df["close"] < df["res_hlevel_4h"])
      )
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["change_pct_4h"] < 0.01)
        | (df["change_pct_1h"] < 0.01)
        | (df["not_downtrend_1d"])
        | (df["rsi_14"] < df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] < df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] < 74.0)
        | (df["rsi_14_15m"] > 70.0)
        | (df["rsi_14_1h"] > 45.0)
        | (df["rsi_14_4h"] > 35.0)
        | (df["r_480_1h"] > -85.0)
        | (df["r_480_4h"] > -90.0)
      )
      & (
        (df["change_pct_1d"] > -0.24)
        | (df["change_pct_1h"] < 0.01)
        | (df["rsi_14"] < df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] < df["rsi_14_15m"].shift(12))
        | (df["rsi_3"] < 80.0)
        | (df["rsi_14_15m"] > 90.0)
        | (df["rsi_14_1h"] > 60.0)
        | (df["rsi_14_4h"] > 45.0)
        | (df["r_480_1h"] > -75.0)
        | (df["r_480_4h"] > -65.0)
      )
      & (
        (df["change_pct_1h"] < 0.16)
        | (df["not_downtrend_1d"])
        | (df["rsi_3_15m"] < 75.0)
        | (df["rsi_14_1h"] > 45.0)
        | (df["rsi_14_4h"] > 45.0)
      )
      & (
        (df["change_pct_1d"] > -0.03)
        | (df["change_pct_1h"] < 0.01)
        | (df["not_downtrend_1d"])
        | (df["rsi_14"] < df["rsi_14"].shift(12))
        | (df["rsi_14_15m"] < df["rsi_14_15m"].shift(12))
        | (df["rsi_14_15m"] > 70.0)
        | (df["rsi_14_1h"] > 55.0)
        | (df["rsi_14_4h"] > 35.0)
        | (df["r_480_1h"] > -80.0)
        | (df["r_480_4h"] > -75.0)
        | (df["close"] > (df["high_max_6_1d"] * 0.60))
      )
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["change_pct_4h"] < 0.08)
        | (df["change_pct_1h"] < 0.04)
        | (df["not_downtrend_1d"])
        | (df["rsi_3_15m"] < 90.0)
      )
      & (
        (df["change_pct_1d"] < 0.04)
        | (df["change_pct_1d"].shift(288) > -0.04)
        | (df["rsi_3"] < 75.0)
        | (df["rsi_3_15m"] < 70.0)
        | (df["rsi_14_15m"] > 60.0)
        | (df["rsi_14_1h"] > 60.0)
        | (df["rsi_14_4h"] > 50.0)
        | (df["rsi_14_1d"] > 45.0)
        | (df["r_480_1h"] > -75.0)
        | (df["close"] < df["res_hlevel_1h"])
      )
      & (
        (df["change_pct_1d"] > -0.24)
        | (df["bot_wick_pct_1d"] < 0.24)
        | (df["change_pct_4h"] < 0.02)
        | (df["change_pct_1h"] < 0.01)
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] < 85.0)
        | (df["rsi_3_15m"] < 65.0)
        | (df["rsi_14_15m"] > 60.0)
        | (df["rsi_14_1h"] > 50.0)
        | (df["rsi_14_4h"] > 35.0)
        | (df["close"] > (df["high_max_6_1d"] * 0.60))
      )
      & (
        (df["change_pct_1d"] > -0.02)
        | (df["change_pct_4h"] > -0.02)
        | (df["bot_wick_pct_4h"] < 0.04)
        | (df["change_pct_1h"] < 0.02)
        | (df["rsi_3"] < 80.0)
        | (df["rsi_3_15m"] < 75.0)
        | (df["rsi_14"] > 75.0)
        | (df["rsi_14_15m"] > 60.0)
        | (df["rsi_14_1h"] > 45.0)
        | (df["rsi_14_4h"] > 30.0)
        | (df["close"] > df["sup_level_1h"])
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
      )
      & (
        (df["change_pct_4h"] > -0.02)
        | (df["bot_wick_pct_4h"] < 0.04)
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] < 85.0)
        | (df["rsi_3_15m"] < 80.0)
        | (df["rsi_14"] > 80.0)
        | (df["rsi_14_15m"] > 65.0)
        | (df["rsi_14_1h"] > 50.0)
        | (df["rsi_14_4h"] > 45.0)
        | (df["rsi_14_1d"] > 35.0)
        | (df["r_480_1h"] > -85.0)
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
      )
      & (
        (df["change_pct_1d"] > -0.04)
        | (df["change_pct_4h"] < 0.01)
        | (df["change_pct_1h"] < 0.01)
        | (df["not_downtrend_1d"])
        | (df["rsi_3"] < 80.0)
        | (df["rsi_3_15m"] < 75.0)
        | (df["rsi_14_15m"] > 80.0)
        | (df["rsi_14_1h"] > 60.0)
        | (df["rsi_14_4h"] > 35.0)
        | (df["close"] > df["sup_level_1d"])
      )
      & (
        (df["change_pct_1h"] < 0.04)
        | (df["not_downtrend_1d"])
        | (df["rsi_14"] > 80.0)
        | (df["rsi_14_15m"] > 70.0)
        | (df["cti_20_15m"] > 0.9)
        | (df["rsi_14_1h"] > 50.0)
        | (df["rsi_14_4h"] > 35.0)
        | (df["r_480_1h"] > -80.0)
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
      )
      & (
        (df["change_pct_4h"] > -0.06)
        | (df["not_downtrend_4h"])
        | (df["not_downtrend_1d"])
        | (df["rsi_14"] > 85.0)
        | (df["rsi_14_15m"] > 65.0)
        | (df["cti_20_15m"] > 0.9)
        | (df["rsi_14_1h"] > 35.0)
        | (df["rsi_14_4h"] > 35.0)
        | (df["rsi_14_1d"] > 45.0)
        | (df["r_480_1h"] > -85.0)
        | (df["close"] > df["sup_level_4h"])
        | (df["close"] > df["sup_level_1d"])
        | (df["close"] > (df["high_max_6_1d"] * 0.55))
      )
      & (
        (df["change_pct_1d"] > -0.12)
        | (df["change_pct_4h"] < 0.08)
        | (df["change_pct_1h"] < 0.02)
        | (df["rsi_3"] < 80.0)
        | (df["rsi_3_15m"] < 80.0)
        | (df["rsi_14"] > 80.0)
        | (df["rsi_14_15m"] > 80.0)
        | (df["rsi_14_1h"] > 65.0)
        | (df["rsi_14_4h"] > 55.0)
        | (df["rsi_14_1d"] > 50.0)
      )
    )

    df["protections_short_rebuy"] = True

    tok = time.perf_counter()
    log.debug(f"[{metadata['pair']}] Populate indicators took a total of: {tok - tik:0.4f} seconds.")

    return df

  # Confirm Trade Entry
  # ---------------------------------------------------------------------------------------------
  def confirm_trade_entry(
    self,
    pair: str,
    order_type: str,
    amount: float,
    rate: float,
    time_in_force: str,
    current_time: datetime,
    entry_tag: Optional[str],
    side: str,
    **kwargs,
  ) -> bool:
    # allow force entries
    if entry_tag == "force_entry":
      return True

    df, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)

    if len(df) < 1:
      return False

    df = df.iloc[-1].squeeze()

    # Grind mode
    entry_tags = entry_tag.split()
    if all(c in self.long_grind_mode_tags for c in entry_tags):
      is_pair_grind_mode = pair.split("/")[0] in self.grind_mode_coins
      if is_pair_grind_mode:
        num_open_grind_mode = 0
        open_trades = Trade.get_trades_proxy(is_open=True)
        for open_trade in open_trades:
          enter_tag = open_trade.enter_tag
          enter_tags = enter_tag.split()
          if all(c in self.long_grind_mode_tags for c in enter_tags):
            num_open_grind_mode += 1
        if num_open_grind_mode >= self.grind_mode_max_slots:
          # Reached the limit of grind mode open trades
          return False
      else:
        # The pair is not in the list of grind mode allowed
        return False

    if ("side" == "long" and rate > df["close"]) or ("side" == "short" and rate < df["close"]):
      slippage = (rate / df["close"]) - 1.0

      if ("side" == "long" and slippage < self.max_slippage) or ("side" == "short" and slippage > -self.max_slippage):
        return True
      else:
        log.warning(f"Cancelling buy for {pair} due to slippage {(slippage * 100.0):.2f}%")
        return False

    return True

  # Confirm Trade Exit
  # ---------------------------------------------------------------------------------------------
  def confirm_trade_exit(
    self,
    pair: str,
    trade: Trade,
    order_type: str,
    amount: float,
    rate: float,
    time_in_force: str,
    exit_reason: str,
    current_time: datetime,
    **kwargs,
  ) -> bool:
    # Allow force exits
    if exit_reason != "force_exit":
      if self._should_hold_trade(trade, rate, exit_reason):
        return False
      if exit_reason == "stop_loss":
        return False
      if self.exit_profit_only:
        if self.exit_profit_only:
          profit = 0.0
          if trade.realized_profit != 0.0:
            profit = ((rate - trade.open_rate) / trade.open_rate) * trade.stake_amount * (1 - trade.fee_close)
            profit = profit + trade.realized_profit
            profit = profit / trade.stake_amount
          else:
            profit = trade.calc_profit_ratio(rate)
          if profit < self.exit_profit_offset:
            return False

    self._remove_profit_target(pair)
    return True

  # Bot Loop Start
  # ---------------------------------------------------------------------------------------------
  def bot_loop_start(self, current_time: datetime, **kwargs) -> None:
    if self.config["runmode"].value not in ("live", "dry_run"):
      return super().bot_loop_start(datetime, **kwargs)

    if self.hold_support_enabled:
      self.load_hold_trades_config()

    return super().bot_loop_start(current_time, **kwargs)

  # Leverage
  # ---------------------------------------------------------------------------------------------
  def leverage(
    self,
    pair: str,
    current_time: datetime,
    current_rate: float,
    proposed_leverage: float,
    max_leverage: float,
    entry_tag: Optional[str],
    side: str,
    **kwargs,
  ) -> float:
    enter_tags = entry_tag.split()
    if all(c in self.long_rebuy_mode_tags for c in enter_tags):
      return self.futures_mode_leverage_rebuy_mode
    elif all(c in self.long_grind_mode_tags for c in enter_tags):
      return self.futures_mode_leverage_grind_mode
    return self.futures_mode_leverage

  # Correct Min Stake
  # ---------------------------------------------------------------------------------------------
  def correct_min_stake(self, min_stake: float) -> float:
    if self.config["exchange"]["name"] in ["bybit"]:
      if self.is_futures_mode:
        if min_stake < 5.0:
          min_stake = 5.0
    return min_stake

  # Set Profit Target
  # ---------------------------------------------------------------------------------------------
  def _set_profit_target(
    self, pair: str, sell_reason: str, rate: float, current_profit: float, current_time: datetime
  ):
    self.target_profit_cache.data[pair] = {
      "rate": rate,
      "profit": current_profit,
      "sell_reason": sell_reason,
      "time_profit_reached": current_time.isoformat(),
    }
    self.target_profit_cache.save()

  # Remove Profit Target
  # ---------------------------------------------------------------------------------------------
  def _remove_profit_target(self, pair: str):
    if self.target_profit_cache is not None:
      self.target_profit_cache.data.pop(pair, None)
      self.target_profit_cache.save()

  # Get Hold Trades Config File
  # ---------------------------------------------------------------------------------------------
  def get_hold_trades_config_file(self):
    proper_holds_file_path = self.config["user_data_dir"].resolve() / "nfi-hold-trades.json"
    if proper_holds_file_path.is_file():
      return proper_holds_file_path

    strat_file_path = pathlib.Path(__file__)
    hold_trades_config_file_resolve = strat_file_path.resolve().parent / "hold-trades.json"
    if hold_trades_config_file_resolve.is_file():
      log.warning(
        "Please move %s to %s which is now the expected path for the holds file",
        hold_trades_config_file_resolve,
        proper_holds_file_path,
      )
      return hold_trades_config_file_resolve

    # The resolved path does not exist, is it a symlink?
    hold_trades_config_file_absolute = strat_file_path.absolute().parent / "hold-trades.json"
    if hold_trades_config_file_absolute.is_file():
      log.warning(
        "Please move %s to %s which is now the expected path for the holds file",
        hold_trades_config_file_absolute,
        proper_holds_file_path,
      )
      return hold_trades_config_file_absolute

  # Load Hold Trades Config
  # ---------------------------------------------------------------------------------------------
  def load_hold_trades_config(self):
    if self.hold_trades_cache is None:
      hold_trades_config_file = self.get_hold_trades_config_file()
      if hold_trades_config_file:
        log.warning("Loading hold support data from %s", hold_trades_config_file)
        self.hold_trades_cache = HoldsCache(hold_trades_config_file)

    if self.hold_trades_cache:
      self.hold_trades_cache.load()

  # Should Hold Trade
  # ---------------------------------------------------------------------------------------------
  def _should_hold_trade(self, trade: "Trade", rate: float, sell_reason: str) -> bool:
    if self.config["runmode"].value not in ("live", "dry_run"):
      return False

    if not self.hold_support_enabled:
      return False

    # Just to be sure our hold data is loaded, should be a no-op call after the first bot loop
    self.load_hold_trades_config()

    if not self.hold_trades_cache:
      # Cache hasn't been setup, likely because the corresponding file does not exist, sell
      return False

    if not self.hold_trades_cache.data:
      # We have no pairs we want to hold until profit, sell
      return False

    # By default, no hold should be done
    hold_trade = False

    trade_ids: dict = self.hold_trades_cache.data.get("trade_ids")
    if trade_ids and trade.id in trade_ids:
      trade_profit_ratio = trade_ids[trade.id]
      profit = 0.0
      if trade.realized_profit != 0.0:
        profit = ((rate - trade.open_rate) / trade.open_rate) * trade.stake_amount * (1 - trade.fee_close)
        profit = profit + trade.realized_profit
        profit = profit / trade.stake_amount
      else:
        profit = trade.calc_profit_ratio(rate)
      current_profit_ratio = profit
      if sell_reason == "force_sell":
        formatted_profit_ratio = f"{trade_profit_ratio * 100}%"
        formatted_current_profit_ratio = f"{current_profit_ratio * 100}%"
        log.warning(
          "Force selling %s even though the current profit of %s < %s",
          trade,
          formatted_current_profit_ratio,
          formatted_profit_ratio,
        )
        return False
      elif current_profit_ratio >= trade_profit_ratio:
        # This pair is on the list to hold, and we reached minimum profit, sell
        formatted_profit_ratio = f"{trade_profit_ratio * 100}%"
        formatted_current_profit_ratio = f"{current_profit_ratio * 100}%"
        log.warning(
          "Selling %s because the current profit of %s >= %s",
          trade,
          formatted_current_profit_ratio,
          formatted_profit_ratio,
        )
        return False

      # This pair is on the list to hold, and we haven't reached minimum profit, hold
      hold_trade = True

    trade_pairs: dict = self.hold_trades_cache.data.get("trade_pairs")
    if trade_pairs and trade.pair in trade_pairs:
      trade_profit_ratio = trade_pairs[trade.pair]
      profit = 0.0
      if trade.realized_profit != 0.0:
        profit = ((rate - trade.open_rate) / trade.open_rate) * trade.stake_amount * (1 - trade.fee_close)
        profit = profit + trade.realized_profit
        profit = profit / trade.stake_amount
      else:
        profit = trade.calc_profit_ratio(rate)
      current_profit_ratio = profit
      if sell_reason == "force_sell":
        formatted_profit_ratio = f"{trade_profit_ratio * 100}%"
        formatted_current_profit_ratio = f"{current_profit_ratio * 100}%"
        log.warning(
          "Force selling %s even though the current profit of %s < %s",
          trade,
          formatted_current_profit_ratio,
          formatted_profit_ratio,
        )
        return False
      elif current_profit_ratio >= trade_profit_ratio:
        # This pair is on the list to hold, and we reached minimum profit, sell
        formatted_profit_ratio = f"{trade_profit_ratio * 100}%"
        formatted_current_profit_ratio = f"{current_profit_ratio * 100}%"
        log.warning(
          "Selling %s because the current profit of %s >= %s",
          trade,
          formatted_current_profit_ratio,
          formatted_profit_ratio,
        )
        return False

      # This pair is on the list to hold, and we haven't reached minimum profit, hold
      hold_trade = True

    return hold_trade

  # Populate Exit Trend
  # ---------------------------------------------------------------------------------------------
  def populate_exit_trend(self, df: DataFrame, metadata: dict) -> DataFrame:
    df.loc[:, "exit_long"] = 0
    df.loc[:, "exit_short"] = 0

    return df

  #
  # $$$$$$$$\ $$\   $$\ $$$$$$$$\ $$$$$$$\ $$\     $$\
  # $$  _____|$$$\  $$ |\__$$  __|$$  __$$\\$$\   $$  |
  # $$ |      $$$$\ $$ |   $$ |   $$ |  $$ |\$$\ $$  /
  # $$$$$\    $$ $$\$$ |   $$ |   $$$$$$$  | \$$$$  /
  # $$  __|   $$ \$$$$ |   $$ |   $$  __$$<   \$$  /
  # $$ |      $$ |\$$$ |   $$ |   $$ |  $$ |   $$ |
  # $$$$$$$$\ $$ | \$$ |   $$ |   $$ |  $$ |   $$ |
  # \________|\__|  \__|   \__|   \__|  \__|   \__|
  #

  #
  #  $$$$$$\   $$$$$$\  $$\   $$\ $$$$$$$\  $$$$$$\ $$$$$$$$\ $$$$$$\  $$$$$$\  $$\   $$\  $$$$$$\
  # $$  __$$\ $$  __$$\ $$$\  $$ |$$  __$$\ \_$$  _|\__$$  __|\_$$  _|$$  __$$\ $$$\  $$ |$$  __$$\
  # $$ /  \__|$$ /  $$ |$$$$\ $$ |$$ |  $$ |  $$ |     $$ |     $$ |  $$ /  $$ |$$$$\ $$ |$$ /  \__|
  # $$ |      $$ |  $$ |$$ $$\$$ |$$ |  $$ |  $$ |     $$ |     $$ |  $$ |  $$ |$$ $$\$$ |\$$$$$$\
  # $$ |      $$ |  $$ |$$ \$$$$ |$$ |  $$ |  $$ |     $$ |     $$ |  $$ |  $$ |$$ \$$$$ | \____$$\
  # $$ |  $$\ $$ |  $$ |$$ |\$$$ |$$ |  $$ |  $$ |     $$ |     $$ |  $$ |  $$ |$$ |\$$$ |$$\   $$ |
  # \$$$$$$  | $$$$$$  |$$ | \$$ |$$$$$$$  |$$$$$$\    $$ |   $$$$$$\  $$$$$$  |$$ | \$$ |\$$$$$$  |
  #  \______/  \______/ \__|  \__|\_______/ \______|   \__|   \______| \______/ \__|  \__| \______/
  #

  # Populate Entry Trend
  # ---------------------------------------------------------------------------------------------
  def populate_entry_trend(self, df: DataFrame, metadata: dict) -> DataFrame:
    long_entry_conditions = []
    short_entry_conditions = []

    df.loc[:, "enter_tag"] = ""

    is_backtest = self.dp.runmode.value in ["backtest", "hyperopt", "plot"]
    # the number of free slots
    current_free_slots = self.config["max_open_trades"]
    if not is_backtest:
      current_free_slots = self.config["max_open_trades"] - Trade.get_open_trade_count()
    # Grind mode
    num_open_grind_mode = 0
    is_pair_grind_mode = metadata["pair"].split("/")[0] in self.grind_mode_coins
    if not is_backtest:
      open_trades = Trade.get_trades_proxy(is_open=True)
      for open_trade in open_trades:
        enter_tag = open_trade.enter_tag
        if enter_tag is not None:
          enter_tags = enter_tag.split()
          if all(c in self.long_grind_mode_tags for c in enter_tags):
            num_open_grind_mode += 1
    # if BTC/ETH stake
    is_btc_stake = self.config["stake_currency"] in self.btc_stakes
    allowed_empty_candles = 144 if is_btc_stake else 60

    #
    #  /$$       /$$$$$$ /$$   /$$ /$$$$$$        /$$$$$$$$/$$   /$$/$$$$$$$$/$$$$$$$$/$$$$$$$
    # | $$      /$$__  $| $$$ | $$/$$__  $$      | $$_____| $$$ | $|__  $$__| $$_____| $$__  $$
    # | $$     | $$  \ $| $$$$| $| $$  \__/      | $$     | $$$$| $$  | $$  | $$     | $$  \ $$
    # | $$     | $$  | $| $$ $$ $| $$ /$$$$      | $$$$$  | $$ $$ $$  | $$  | $$$$$  | $$$$$$$/
    # | $$     | $$  | $| $$  $$$| $$|_  $$      | $$__/  | $$  $$$$  | $$  | $$__/  | $$__  $$
    # | $$     | $$  | $| $$\  $$| $$  \ $$      | $$     | $$\  $$$  | $$  | $$     | $$  \ $$
    # | $$$$$$$|  $$$$$$| $$ \  $|  $$$$$$/      | $$$$$$$| $$ \  $$  | $$  | $$$$$$$| $$  | $$
    # |________/\______/|__/  \__/\______/       |________|__/  \__/  |__/  |________|__/  |__/
    #

    for enabled_long_entry_signal in self.long_entry_signal_params:
      index = int(enabled_long_entry_signal.split("_")[3])
      item_buy_protection_list = [True]
      if not self.config["runmode"].value in ("live", "dry_run"):
        if self.has_bt_agefilter:
          item_buy_protection_list.append(df["bt_agefilter_ok"])
      else:
        if self.has_downtime_protection:
          item_buy_protection_list.append(df["live_data_ok"])
      if self.long_entry_signal_params[f"{enabled_long_entry_signal}"]:
        # Long Entry Conditions Starts Here
        # -----------------------------------------------------------------------------------------
        long_entry_logic = []
        long_entry_logic.append(reduce(lambda x, y: x & y, item_buy_protection_list))

        # Condition #1 - Long mode bull. Uptrend.
        if index == 1:
          # Protections
          long_entry_logic.append(df["protections_long_global"] == True)
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close_max_12"] < (df["close"] * 1.2))
          long_entry_logic.append(df["close_max_24"] < (df["close"] * 1.24))
          long_entry_logic.append(df["close_max_48"] < (df["close"] * 1.3))
          long_entry_logic.append(df["high_max_24_1h"] < (df["close"] * 1.5))
          long_entry_logic.append(df["high_max_24_4h"] < (df["close"] * 1.75))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.4)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.5)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.75)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.9)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["cti_20_1h"] < 0.9)
          long_entry_logic.append(df["rsi_14_1h"] < 85.0)
          long_entry_logic.append(df["cti_20_4h"] < 0.9)
          long_entry_logic.append(df["rsi_14_4h"] < 85.0)
          long_entry_logic.append(df["cti_20_1d"] < 0.9)
          long_entry_logic.append(df["rsi_14_1d"] < 85.0)
          long_entry_logic.append(df["r_14_1h"] < -25.0)
          long_entry_logic.append(df["r_14_4h"] < -25.0)

          # Logic
          long_entry_logic.append(df["ema_26"] > df["ema_12"])
          long_entry_logic.append((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.02))
          long_entry_logic.append((df["ema_26"].shift() - df["ema_12"].shift()) > (df["open"] / 100))
          long_entry_logic.append(df["close"] < (df["bb20_2_low"] * 0.999))

        # Condition #2 - Normal mode bull.
        if index == 2:
          # Protections
          long_entry_logic.append(df["protections_long_global"] == True)
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close_max_12"] < (df["close"] * 1.16))
          long_entry_logic.append(df["close_max_24"] < (df["close"] * 1.24))
          long_entry_logic.append(df["close_max_48"] < (df["close"] * 1.3))
          long_entry_logic.append(df["high_max_24_1h"] < (df["close"] * 1.5))
          long_entry_logic.append(df["high_max_24_4h"] < (df["close"] * 1.75))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.4)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.5)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.75)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.9)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["cti_20_1h"] < 0.9)
          long_entry_logic.append(df["rsi_14_1h"] < 85.0)
          long_entry_logic.append(df["cti_20_4h"] < 0.9)
          long_entry_logic.append(df["rsi_14_4h"] < 85.0)
          long_entry_logic.append(df["cti_20_1d"] < 0.9)
          long_entry_logic.append(df["rsi_14_1d"] < 85.0)
          long_entry_logic.append(df["r_14_1h"] < -25.0)
          long_entry_logic.append(df["r_14_4h"] < -25.0)

          long_entry_logic.append(
            ((df["not_downtrend_1h"]) & (df["not_downtrend_4h"])) | (df["high_max_24_4h"] < (df["close"] * 1.5))
          )

          # Logic
          long_entry_logic.append(df["bb40_2_delta"].gt(df["close"] * 0.06))
          long_entry_logic.append(df["close_delta"].gt(df["close"] * 0.02))
          long_entry_logic.append(df["bb40_2_tail"].lt(df["bb40_2_delta"] * 0.2))
          long_entry_logic.append(df["close"].lt(df["bb40_2_low"].shift()))
          long_entry_logic.append(df["close"].le(df["close"].shift()))

        # Condition #3 - Normal mode bull.
        if index == 3:
          # Protections
          long_entry_logic.append(df["protections_long_global"] == True)
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close_max_12"] < (df["close"] * 1.2))
          long_entry_logic.append(df["close_max_24"] < (df["close"] * 1.24))
          long_entry_logic.append(df["close_max_48"] < (df["close"] * 1.26))
          long_entry_logic.append(df["high_max_24_1h"] < (df["close"] * 1.5))
          long_entry_logic.append(df["high_max_24_4h"] < (df["close"] * 1.75))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.4)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.5)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.75)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.9)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["ema_12_1h"] > df["ema_200_1h"])

          long_entry_logic.append(df["ema_12_4h"] > df["ema_200_4h"])

          long_entry_logic.append(df["rsi_3_15m"] > 16.0)
          long_entry_logic.append(df["rsi_3_1h"] > 6.0)
          long_entry_logic.append(df["rsi_3_4h"] > 6.0)
          long_entry_logic.append(df["rsi_14_4h"] < 70.0)
          long_entry_logic.append(df["rsi_14_1d"] < 85.0)

          long_entry_logic.append((df["change_pct_4h"] > -0.04) | (df["change_pct_4h"].shift(48) < 0.04))
          long_entry_logic.append((df["not_downtrend_1h"]) | (df["cti_20_1d"] < 0.85) | (df["r_480_4h"] < -30.0))

          # Logic
          long_entry_logic.append(df["rsi_14"] < 36.0)
          long_entry_logic.append(df["ha_close"] > df["ha_open"])
          long_entry_logic.append((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.020))

        # Condition #4 - Normal mode (Long).
        if index == 4:
          # Protections
          long_entry_logic.append(df["protections_long_global"] == True)
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * 0.82))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * 0.80))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * 0.72))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * 0.60))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * 0.50))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.4)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.5)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.75)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.9)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["cti_20_1h"] < 0.9)
          long_entry_logic.append(df["rsi_14_1h"] < 85.0)
          long_entry_logic.append(df["cti_20_4h"] < 0.9)
          long_entry_logic.append(df["rsi_14_4h"] < 85.0)
          long_entry_logic.append(df["cti_20_1d"] < 0.9)
          long_entry_logic.append(df["rsi_14_1d"] < 85.0)

          # Logic
          long_entry_logic.append(df["ema_26"] > df["ema_12"])
          long_entry_logic.append((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.018))
          long_entry_logic.append((df["ema_26"].shift() - df["ema_12"].shift()) > (df["open"] / 100))
          long_entry_logic.append(df["close"] < (df["bb20_2_low"] * 0.996))

        # Condition #5 - Normal mode (Long).
        if index == 5:
          # Protections
          long_entry_logic.append(df["protections_long_global"] == True)
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * 0.82))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * 0.80))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * 0.72))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * 0.60))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * 0.50))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.4)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.5)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.75)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.9)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          # Logic
          long_entry_logic.append(df["ema_26"] > df["ema_12"])
          long_entry_logic.append((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          long_entry_logic.append((df["ema_26"].shift() - df["ema_12"].shift()) > (df["open"] / 100))
          long_entry_logic.append(df["rsi_14"] < 36.0)

        # Condition #6 - Normal mode (Long).
        if index == 6:
          # Protections
          long_entry_logic.append(df["protections_long_global"] == True)
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * 0.82))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * 0.80))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * 0.72))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * 0.60))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * 0.50))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.4)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.5)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.75)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.9)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["cti_20_1h"] < 0.5)
          long_entry_logic.append(df["cti_20_4h"] < 0.75)
          long_entry_logic.append(df["rsi_14_4h"] < 85.0)

          # Logic
          long_entry_logic.append(df["close"] < (df["ema_26"] * 0.94))
          long_entry_logic.append(df["close"] < (df["bb20_2_low"] * 0.996))

        # Condition #7 Normal mode (long).
        if index == 7:
          # Protections
          long_entry_logic.append(df["protections_long_global"] == True)
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * 0.82))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * 0.80))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * 0.72))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * 0.60))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * 0.50))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.4)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.5)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.75)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.9)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["cti_20_1h"] < 0.8)
          long_entry_logic.append(df["rsi_14_1h"] < 80.0)
          long_entry_logic.append(df["cti_20_4h"] < 0.8)
          long_entry_logic.append(df["rsi_14_4h"] < 80.0)
          long_entry_logic.append(df["cti_20_1d"] < 0.8)
          long_entry_logic.append(df["rsi_14_1d"] < 80.0)

          # Logic
          long_entry_logic.append(df["close"] < (df["ema_16"] * 0.974))
          long_entry_logic.append(df["ewo_50_200"] > 2.0)
          long_entry_logic.append(df["rsi_14"] < 30.0)

        # Condition #8 Normal mode (Long).
        if index == 8:
          # Protections
          long_entry_logic.append(df["protections_long_global"] == True)
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * 0.82))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * 0.80))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * 0.72))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * 0.60))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * 0.50))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.4)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.5)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.75)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.9)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["cti_20_1h"] < 0.8)
          long_entry_logic.append(df["rsi_14_1h"] < 80.0)
          long_entry_logic.append(df["cti_20_4h"] < 0.8)
          long_entry_logic.append(df["rsi_14_4h"] < 80.0)
          long_entry_logic.append(df["cti_20_1d"] < 0.8)
          long_entry_logic.append(df["rsi_14_1d"] < 80.0)

          # Logic
          long_entry_logic.append(df["close"] < (df["ema_16"] * 0.944))
          long_entry_logic.append(df["ewo_50_200"] < -4.0)
          long_entry_logic.append(df["rsi_14"] < 30.0)

        # Condition #9 - Normal mode (Long).
        if index == 9:
          # Protections
          long_entry_logic.append(df["protections_long_global"] == True)
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * 0.82))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * 0.80))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * 0.72))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * 0.60))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * 0.50))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.4)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.5)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.75)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.9)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["cti_20_1h"] < 0.8)
          long_entry_logic.append(df["rsi_14_1h"] < 80.0)
          long_entry_logic.append(df["cti_20_4h"] < 0.8)
          long_entry_logic.append(df["rsi_14_4h"] < 80.0)
          long_entry_logic.append(df["cti_20_1d"] < 0.8)
          long_entry_logic.append(df["rsi_14_1d"] < 80.0)

          # Logic
          long_entry_logic.append(df["ema_26_15m"] > df["ema_12_15m"])
          long_entry_logic.append((df["ema_26_15m"] - df["ema_12_15m"]) > (df["open_15m"] * 0.020))
          long_entry_logic.append((df["ema_26_15m"].shift(3) - df["ema_12_15m"].shift(3)) > (df["open_15m"] / 100.0))
          long_entry_logic.append(df["close_15m"] < (df["bb20_2_low_15m"] * 0.99))

        # Condition #10 - Normal mode (Long)
        if index == 10:
          # Protections
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * 0.80))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * 0.75))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * 0.70))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * 0.60))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * 0.50))
          long_entry_logic.append(df["close"] > (df["high_max_6_1d"] * 0.45))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.80)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.90)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.95)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 1.00)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] >= 4.0)
          long_entry_logic.append(df["rsi_3"] <= 46.0)
          long_entry_logic.append(df["rsi_3_15m"] >= 6.0)
          long_entry_logic.append(df["rsi_3_1h"] >= 8.0)
          long_entry_logic.append(df["rsi_3_4h"] >= 8.0)
          long_entry_logic.append(df["rsi_3_1d"] >= 8.0)
          long_entry_logic.append(df["cti_20_1h"] <= 0.90)
          long_entry_logic.append(df["rsi_14_1h"] <= 80.0)
          long_entry_logic.append(df["cti_20_4h"] <= 0.90)
          long_entry_logic.append(df["rsi_14_4h"] <= 80.0)
          long_entry_logic.append(df["cti_20_1d"] <= 0.95)
          long_entry_logic.append(df["rsi_14_1d"] <= 80.0)
          long_entry_logic.append(df["r_14_1h"] <= -0.0)
          long_entry_logic.append(df["r_14_4h"] <= -0.0)
          long_entry_logic.append(df["r_480_1h"] <= -0.0)
          long_entry_logic.append(df["r_480_4h"] <= -0.0)

          # Logic
          long_entry_logic.append(df["rsi_14"] < 30.0)
          long_entry_logic.append(df["ema_26"] > df["ema_12"])
          long_entry_logic.append((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.0200))
          long_entry_logic.append((df["ema_26"].shift() - df["ema_12"].shift()) > (df["open"] / 100.0))
          long_entry_logic.append(df["close"] < (df["ema_20"] * 0.952))

        # Condition #11 - Normal mode (Long)
        if index == 11:
          # Protections
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * 0.80))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * 0.75))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * 0.70))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * 0.60))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * 0.50))
          long_entry_logic.append(df["close"] > (df["high_max_6_1d"] * 0.45))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.80)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.90)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.95)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 1.00)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] >= 2.0)
          long_entry_logic.append(df["rsi_3"] <= 46.0)
          long_entry_logic.append(df["rsi_3_15m"] >= 16.0)
          long_entry_logic.append(df["rsi_3_1h"] >= 8.0)
          long_entry_logic.append(df["rsi_3_4h"] >= 8.0)
          long_entry_logic.append(df["rsi_3_1d"] >= 8.0)
          long_entry_logic.append(df["cti_20_1h"] <= 0.95)
          long_entry_logic.append(df["rsi_14_1h"] <= 85.0)
          long_entry_logic.append(df["cti_20_4h"] <= 0.95)
          long_entry_logic.append(df["rsi_14_4h"] <= 85.0)
          long_entry_logic.append(df["cti_20_1d"] <= 0.95)
          long_entry_logic.append(df["rsi_14_1d"] <= 85.0)
          long_entry_logic.append(df["r_14_1h"] <= -0.0)
          long_entry_logic.append(df["r_14_4h"] <= -0.0)
          long_entry_logic.append(df["r_480_1h"] <= -0.0)
          long_entry_logic.append(df["r_480_4h"] <= -0.0)

          long_entry_logic.append(df["ema_100"] > df["ema_200"])
          long_entry_logic.append(df["ema_12_1h"] > df["ema_200_1h"])

          # Logic
          long_entry_logic.append(df["rsi_14"] < 45.0)
          long_entry_logic.append(df["cti_20"] < -0.50)
          long_entry_logic.append(df["ema_26"] > df["ema_12"])
          long_entry_logic.append((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.0260))
          long_entry_logic.append((df["ema_26"].shift() - df["ema_12"].shift()) > (df["open"] / 100.0))
          long_entry_logic.append(df["close"] < (df["sma_30"] * 0.978))

        # Condition #12 - Normal mode (Long)
        if index == 12:
          # Protections
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * 0.80))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * 0.75))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * 0.70))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * 0.60))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * 0.50))
          long_entry_logic.append(df["close"] > (df["high_max_6_1d"] * 0.45))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.80)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.90)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.95)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 1.00)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] >= 2.0)
          long_entry_logic.append(df["rsi_3"] <= 46.0)
          long_entry_logic.append(df["rsi_3_15m"] >= 12.0)
          long_entry_logic.append(df["rsi_3_1h"] >= 20.0)
          long_entry_logic.append(df["rsi_3_4h"] >= 20.0)
          long_entry_logic.append(df["rsi_3_1d"] >= 20.0)
          long_entry_logic.append(df["cti_20_1h"] <= 0.95)
          long_entry_logic.append(df["rsi_14_1h"] <= 90.0)
          long_entry_logic.append(df["cti_20_4h"] <= 0.95)
          long_entry_logic.append(df["rsi_14_4h"] <= 90.0)
          long_entry_logic.append(df["cti_20_1d"] <= 0.95)
          long_entry_logic.append(df["rsi_14_1d"] <= 90.0)
          long_entry_logic.append(df["r_14_1h"] >= -100.0)
          long_entry_logic.append(df["r_14_1h"] <= -0.0)
          long_entry_logic.append(df["r_14_4h"] >= -100.0)
          long_entry_logic.append(df["r_14_4h"] <= -0.0)
          long_entry_logic.append(df["r_480_1h"] >= -100.0)
          long_entry_logic.append(df["r_480_1h"] <= -0.0)
          long_entry_logic.append(df["r_480_4h"] >= -100.0)
          long_entry_logic.append(df["r_480_4h"] <= -0.0)

          long_entry_logic.append(df["ema_50_1h"] > df["ema_200_1h"])

          # Logic
          long_entry_logic.append(df["r_14"] < -88.0)
          long_entry_logic.append(df["close"] < (df["bb20_2_low"] * 0.984))
          long_entry_logic.append(df["close"] < (df["sma_30"] * 0.940))

        # Condition #13 - Normal mode (Long)
        if index == 13:
          # Protections
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.06)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.06)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * 0.84))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * 0.80))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * 0.75))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * 0.60))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.50)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.60)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.70)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.80)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] >= 6.0)
          long_entry_logic.append(df["rsi_3"] <= 50.0)
          long_entry_logic.append(df["rsi_3_15m"] >= 6.0)
          long_entry_logic.append(df["rsi_3_1h"] >= 6.0)
          long_entry_logic.append(df["rsi_3_4h"] >= 14.0)
          long_entry_logic.append(df["rsi_3_1d"] >= 14.0)
          long_entry_logic.append(df["cti_20_1h"] <= 0.90)
          long_entry_logic.append(df["rsi_14_1h"] <= 80.0)
          long_entry_logic.append(df["cti_20_4h"] <= 0.90)
          long_entry_logic.append(df["rsi_14_4h"] <= 80.0)
          long_entry_logic.append(df["cti_20_1d"] <= 0.90)
          long_entry_logic.append(df["rsi_14_1d"] <= 80.0)

          long_entry_logic.append(df["close"] > (df["sup_level_1h"] * 0.8))
          long_entry_logic.append(df["close"] < (df["res3_1d"] * 1.6))
          # long_entry_logic.append(df["sma_200_1h"] > df["sma_200_1h"].shift(48))

          long_entry_logic.append(
            (df["r_480_4h"] > -75.0) | (df["ema_200_dec_24_4h"] == False) | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append((df["not_downtrend_1h"]) | (df["rsi_14_4h"] < 70.0) | (df["r_480_4h"] < -30.0))
          long_entry_logic.append(
            (df["not_downtrend_15m"]) | (df["rsi_3"] > 16.0) | (df["rsi_3_15m"] > 20.0) | (df["rsi_3_1h"] > 20.0)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"]) | (df["rsi_3"] > 16.0) | (df["rsi_3_15m"] > 20.0) | (df["rsi_3_1h"] > 26.0)
          )
          long_entry_logic.append(
            (df["rsi_3"] > 12.0)
            | (df["rsi_3_15m"] > 26.0)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["hl_pct_change_6_1d"] < 0.9)
          )
          long_entry_logic.append(
            (df["not_downtrend_4h"]) | (df["rsi_3_15m"] > 30.0) | (df["rsi_3_4h"] > 30.0) | (df["r_480_4h"] < -30.0)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3"] > 26.0)
            | (df["ema_200_dec_48_1h"] == False)
          )
          long_entry_logic.append((df["not_downtrend_15m"]) | (df["rsi_3"] > 16.0) | (df["r_480_4h"] < -25.0))
          long_entry_logic.append(
            (df["not_downtrend_1d"])
            | (df["rsi_3"] > 16.0)
            | (df["rsi_3_15m"] > 26.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["close"] > (df["high_max_6_1d"] * 0.84))
          )
          long_entry_logic.append((df["not_downtrend_1h"]) | (df["rsi_3_15m"] > 16.0) | (df["rsi_14_1d"] < 70.0))
          long_entry_logic.append(
            (df["not_downtrend_1h"]) | (df["rsi_3"] > 16.0) | (df["rsi_3_15m"] > 30.0) | (df["rsi_14_1d"] < 70.0)
          )
          long_entry_logic.append(
            (df["sma_200_1h"] > df["sma_200_1h"].shift(48))
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["rsi_3"] > 12.0)
            | (df["rsi_3_15m"] > 12.0)
            | (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["close"] > (df["high_max_6_1d"] * 0.70))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3"] > 12.0)
            | (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["close"] > (df["high_max_24_1h"] * 0.75))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
            | (df["close"] > df["sup_level_1d"])
          )
          long_entry_logic.append(
            (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_3"] > 26.0)
            | (df["rsi_3_15m"] > 26.0)
            | (df["r_480_1h"] < -20.0)
            | (df["r_480_4h"] < -20.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
          )
          long_entry_logic.append(
            (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_3"] > 12.0)
            | (df["rsi_3_15m"] > 12.0)
            | (df["rsi_14_1h"] < 60.0)
            | (df["rsi_14_4h"] < 65.0)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_3"] > 26.0)
            | (df["rsi_3_15m"] > 26.0)
            | (df["close"] > (df["high_max_6_1d"] * 0.65))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_3"] > 12.0)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_3"] > 10.0)
            | (df["rsi_3_15m"] > 20.0)
            | (df["close"] > df["sup_level_1h"])
          )
          long_entry_logic.append(
            (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_4h"] < 70.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_1h"] > -0.03)
            | (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_14_4h"] < 60.0)
            | (df["close"] < df["res_hlevel_4h"])
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_14_1d"] < 70.0)
            | (df["close"] < df["res_hlevel_4h"])
            | (df["close"] < df["res_hlevel_1d"])
            | (df["ema_200_dec_4_1d"] == False)
            | (df["hl_pct_change_6_1d"] < 0.8)
          )
          long_entry_logic.append(
            (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_3"] > 26.0)
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_14_4h"] < 60.0)
            | (df["rsi_14_max_6_4h"] < 70.0)
            | (df["rsi_14_1d"] < 60.0)
            | (df["close"] < df["res_hlevel_4h"])
            | (df["close"] < df["res_hlevel_1d"])
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_1h"] > 10.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
          )
          long_entry_logic.append(
            (df["rsi_3_1h"] > 20.0)
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 50.0)
            | (df["rsi_14_4h"].shift(48) < 70.0)
            | (df["r_480_4h"] < -25.0)
            | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_3"] > 20.0)
            | (df["rsi_3_15m"] > 10.0)
            | (df["r_480_4h"] < -35.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_3"] > 26.0)
            | (df["rsi_3_15m"] > 12.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
          )
          long_entry_logic.append(
            (df["change_pct_4h"] > -0.02)
            | (df["change_pct_1h"] > -0.02)
            | (df["rsi_3_1h"] > 26.0)
            | (df["rsi_14_1h"] < 46.0)
            | (df["rsi_14_4h"] < 50.0)
            | (df["rsi_14_max_3_4h"] < 80.0)
            | (df["close"] < df["res_hlevel_4h"])
            | (df["close"] < df["res_hlevel_1d"])
            | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
          )
          long_entry_logic.append(
            (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_14_4h"] < 50.0)
            | (df["rsi_14_1d"] < 50.0)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["hl_pct_change_6_1d"] < 0.8)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_3"] > 26.0)
            | (df["rsi_3_15m"] > 12.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_3"] > 26.0)
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["close"] > df["sup_level_1h"])
          )
          long_entry_logic.append(
            (df["change_pct_1h"] > -0.01)
            | (df["not_downtrend_1h"])
            | (df["is_downtrend_3_1h"] == False)
            | (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_3_15m"] > 12.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
            | (df["close"] > df["sup_level_1d"])
            | (df["sma_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] > -0.01)
            | (df["change_pct_1h"] > -0.01)
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_3_15m"] > 36.0)
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 50.0)
            | (df["rsi_14_1d"] < 70.0)
            | (df["r_480_1h"] < -35.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] < df["res_hlevel_1d"])
            | (df["hl_pct_change_6_1d"] < 0.9)
            | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
          )
          long_entry_logic.append(
            (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_1h"] < 50.0)
            | (df["rsi_14_4h"] < 50.0)
            | (df["r_14_1h"] < -35.0)
            | (df["r_14_4h"] < -35.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
            | (df["close"] > df["sup_level_1d"])
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.08)
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_1d"])
            | (df["rsi_3_1h"] > 36.0)
            | (df["rsi_3_1d"] > 36.0)
            | (df["rsi_14_15m"] < 36.0)
            | (df["rsi_14_1d"] < 40.0)
            | (df["r_480_1h"] > -85.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
            | (df["close"] > df["sup_level_1d"])
          )

          # Logic
          long_entry_logic.append(df["ema_26"] > df["ema_12"])
          long_entry_logic.append((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.0150))
          long_entry_logic.append((df["ema_26"].shift() - df["ema_12"].shift()) > (df["open"] / 100))
          long_entry_logic.append(df["close"] < (df["bb20_2_low"] * 0.994))

        # Condition #14 - Normal mode (Long)
        if index == 14:
          # Protections
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] >= 2.0)
          long_entry_logic.append(df["rsi_3"] <= 46.0)
          long_entry_logic.append(df["rsi_3_15m"] >= 12.0)
          long_entry_logic.append(df["rsi_3_1h"] >= 12.0)
          long_entry_logic.append(df["rsi_3_4h"] >= 12.0)
          long_entry_logic.append(df["rsi_14_1d"] < 85.0)
          long_entry_logic.append(df["r_14_4h"] < -16.0)

          long_entry_logic.append(
            (df["rsi_14_4h"] < 75.0) | (df["rsi_14_1h"].shift(12) < 70.0) | (df["not_downtrend_1h"])
          )
          long_entry_logic.append(
            (df["change_pct_1h"] > -0.02)
            | (df["not_downtrend_1d"])
            | (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_3"] > 30.0)
            | (df["rsi_3_1d"] > 26.0)
            | (df["rsi_14_1h"] < 33.0)
            | (df["rsi_14_4h"] < 33.0)
            | (df["sma_200_dec_48_1h"] == False)
            | (df["ema_200_dec_48_1h"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.20)
            | (df["not_downtrend_1h"])
            | (df["rsi_3"] > 26.0)
            | (df["rsi_3_15m"] > 26.0)
            | (df["rsi_14_1h"] < 36.0)
            | (df["rsi_14_4h"] < 46.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.20)
            | (df["rsi_3"] > 12.0)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["rsi_14_1h"] < 46.0)
            | (df["rsi_14_max_6_1h"] < 65.0)
            | (df["rsi_14_4h"] < 50.0)
            | (df["r_480_1h"] < -30.0)
            | (df["r_480_4h"] < -30.0)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["rsi_3"] > 8.0)
            | (df["rsi_3_15m"] > 26.0)
            | (df["close"] < (df["bb20_2_low"] * 0.992))
            | (df["close"] < (df["ema_20"] * 0.954))
            | (df["close_15m"] < (df["ema_12_15m"] * 0.974))
          )
          long_entry_logic.append(
            (df["change_pct_1h"] > -0.04)
            | (df["not_downtrend_1h"])
            | (df["r_480_1h"] > -75.0)
            | (df["r_480_4h"] > -90.0)
            | (df["sma_200_dec_48_1h"] == False)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["rsi_3"] > 16.0)
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_14_1h"] < 60.0)
            | (df["rsi_14_4h"] < 65.0)
            | (df["rsi_14_1d"] < 65.0)
            | (df["r_480_1h"] < -35.0)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.24)
            | (df["change_pct_1h"] > -0.01)
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_3_1h"] > 36.0)
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_max_6_1h"] < 65.0)
            | (df["rsi_14_4h"] < 65.0)
            | (df["cti_20_4h"] < 0.8)
            | (df["close"] < (df["bb20_2_low"] * 0.998))
            | (df["close"] < (df["ema_20"] * 0.936))
            | (df["close_15m"] < (df["ema_12_15m"] * 0.936))
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.16)
            | (df["change_pct_1d"].shift(288) < 0.24)
            | (df["rsi_3"] > 8.0)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_1h"] < 36.0)
            | (df["rsi_14_4h"] < 46.0)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.12)
            | (df["top_wick_pct_4h"] < 0.12)
            | (df["change_pct_1h"] > -0.02)
            | (df["rsi_14_1h"] < 50.0)
            | (df["rsi_14_4h"] < 65.0)
            | (df["rsi_14_max_6_4h"] < 80.0)
            | (df["cti_20_4h"] < 0.8)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.12)
            | (df["change_pct_1d"].shift(288) < 0.24)
            | (df["sma_200_dec_48_1h"] == False)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_3_1h"] > 30.0)
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 60.0)
            | (df["r_480_1h"] > -70.0)
            | (df["r_480_4h"] > -80.0)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.16)
            | (df["change_pct_1h"] > -0.02)
            | (df["rsi_14_1h"] < 60.0)
            | (df["cti_20_1h"] < 0.9)
            | (df["rsi_14_4h"] < 80.0)
            | (df["r_480_1h"] < -35.0)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] > -0.06)
            | (df["change_pct_4h"].shift(48) < 0.06)
            | (df["change_pct_1h"] > -0.02)
            | (df["rsi_14_4h"] < 46.0)
            | (df["rsi_14_max_6_4h"] < 65.0)
            | (df["cti_20_4h"] < 0.7)
            | (df["r_480_1h"] > -70.0)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.06)
            | (df["top_wick_pct_4h"] < 0.06)
            | (df["change_pct_1h"] > -0.01)
            | (df["rsi_14_1h"] < 50.0)
            | (df["rsi_14_4h"] < 80.0)
            | (df["close"] > (df["high_max_6_1h"] * 0.70))
          )
          long_entry_logic.append(
            (df["change_pct_4h"] > -0.04)
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3"] > 10.0)
            | (df["rsi_3_1h"] > 30.0)
            | (df["rsi_3_4h"] > 36.0)
            | (df["rsi_14_max_6_1d"] < 80.0)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["rsi_3"] > 20.0)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 50.0)
            | (df["cti_20_4h"] < 0.8)
            | (df["rsi_14_1d"] < 50.0)
            | (df["r_480_1h"] < -30.0)
            | (df["r_480_4h"] < -20.0)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] > -0.01)
            | (df["change_pct_1h"] > -0.01)
            | (df["rsi_3"] > 16.0)
            | (df["rsi_14_15m"] < 36.0)
            | (df["rsi_14_1h"] < 46.0)
            | (df["rsi_14_4h"] < 50.0)
            | (df["rsi_14_1d"] < 70.0)
            | (df["r_480_1h"] < -25.0)
            | (df["close"] > df["sup_level_1h"])
            | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.01)
            | (df["rsi_3"] > 16.0)
            | (df["rsi_3_15m"] > 26.0)
            | (df["rsi_14_15m"] < 40.0)
            | (df["rsi_14_1h"] < 46.0)
            | (df["rsi_14_4h"] < 50.0)
            | (df["rsi_14_1d"] < 60.0)
            | (df["rsi_14_max_6_1d"] < 80.0)
            | (df["r_480_1h"] < -30.0)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] > -0.02)
            | (df["change_pct_1h"] > -0.02)
            | (df["rsi_3"] > 10.0)
            | (df["rsi_3_15m"] > 26.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["rsi_3_4h"] > 20.0)
            | (df["r_480_1h"] > -95.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
            | (df["sma_200_dec_48_1h"] == False)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1d"])
            | (df["rsi_3"] > 10.0)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 36.0)
            | (df["rsi_14_1h"] < 46.0)
            | (df["rsi_14_4h"] < 46.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["sma_200_dec_48_1h"] == False)
            | (df["ema_200_dec_48_1h"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3"] > 12.0)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_3_1h"] > 30.0)
            | (df["rsi_3_4h"] > 30.0)
            | (df["r_480_1h"] > -65.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
            | (df["sma_200_dec_48_1h"] == False)
            | (df["ema_200_dec_48_1h"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.04)
            | (df["top_wick_pct_1d"] < 0.04)
            | (df["change_pct_1d"].shift(288) < 0.24)
            | (df["not_downtrend_1h"])
            | (df["rsi_3"] > 20.0)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 36.0)
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["r_480_1h"] > -65.0)
            | (df["sma_200_dec_48_1h"] == False)
            | (df["ema_200_dec_48_1h"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.12)
            | (df["top_wick_pct_1d"] < 0.12)
            | (df["rsi_3"] > 8.0)
            | (df["rsi_14_15m"] < 36.0)
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 50.0)
            | (df["cti_20_4h"] < 0.7)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_3"] > 16.0)
            | (df["rsi_3_15m"] > 16.0)
            | (df["rsi_3_1h"] > 16.0)
            | (df["rsi_14"] < 20.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["rsi_14_1h"] < 30.0)
            | (df["rsi_14_4h"] < 45.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["rsi_14_1d"] < 50.0)
            | (df["close"] > df["sup_level_1h"])
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_3"] > 20.0)
            | (df["rsi_3_15m"] > 26.0)
            | (df["rsi_3_1h"] > 30.0)
            | (df["rsi_14_15m"] < 35.0)
            | (df["rsi_14_1h"] < 35.0)
            | (df["rsi_14_4h"] < 55.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["r_480_1h"] < -30.0)
            | (df["r_480_4h"] < -30.0)
            | (df["close"] > df["sup_level_1h"])
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.04)
            | (df["rsi_3"] > 16.0)
            | (df["rsi_3_15m"] > 26.0)
            | (df["rsi_14_15m"] < 36.0)
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 46.0)
            | (df["rsi_14_1d"] < 70.0)
            | (df["rsi_14_max_6_1d"] < 80.0)
            | (df["cti_20_1d"] < 0.8)
            | (df["close"] > df["sup_level_1h"])
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.04)
            | (df["not_downtrend_1h"])
            | (df["rsi_3"] > 16.0)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["rsi_14_1d"] < 50.0)
            | (df["rsi_14_max_6_1d"] < 70.0)
            | (df["cti_20_1d"] < 0.8)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.12)
            | (df["change_pct_1h"] > -0.02)
            | (df["rsi_3"] > 20.0)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 40.0)
            | (df["rsi_14_1h"] < 60.0)
            | (df["rsi_14_max_6_1h"] < 70.0)
            | (df["rsi_14_4h"] < 65.0)
            | (df["rsi_14_max_6_4h"] < 70.0)
            | (df["cti_20_4h"] < 0.7)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_1h"] < 30.0)
            | (df["rsi_14_max_6_1h"] < 70.0)
            | (df["rsi_14_4h"] < 65.0)
            | (df["cti_20_4h"] < 0.7)
            | (df["r_480_1h"] < -35.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.06)
            | (df["top_wick_pct_1d"] < 0.06)
            | (df["change_pct_1d"].shift(288) > -0.04)
            | (df["change_pct_1h"] > -0.02)
            | (df["change_pct_1h"].shift(12) < 0.02)
            | (df["rsi_3"] > 16.0)
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_14_15m"] < 36.0)
            | (df["rsi_14_1h"] < 46.0)
            | (df["rsi_14_4h"] < 60.0)
            | (df["r_480_1h"] < -30.0)
            | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.04)
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3"] > 8.0)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_3_1h"] > 36.0)
            | (df["rsi_3_4h"] > 36.0)
            | (df["rsi_14_1h"] < 36.0)
            | (df["rsi_14_4h"] < 36.0)
            | (df["rsi_14_1d"] < 46.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
            | (df["ema_200_dec_48_1h"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.04)
            | (df["top_wick_pct_1d"] < 0.04)
            | (df["change_pct_1d"].shift(288) < 0.12)
            | (df["top_wick_pct_1d"].shift(288) < 0.04)
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3"] > 30.0)
            | (df["rsi_3_15m"] > 36.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["rsi_3_4h"] > 36.0)
            | (df["rsi_14_1h"] < 30.0)
            | (df["rsi_14_4h"] < 36.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
            | (df["sma_200_dec_48_1h"] == False)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_1h"] > -0.02)
            | (df["rsi_3"] > 30.0)
            | (df["rsi_3_15m"] > 36.0)
            | (df["rsi_14_15m"] < 46.0)
            | (df["rsi_14_1h"] < 70.0)
            | (df["rsi_14_max_6_1h"] < 85.0)
            | (df["rsi_14_4h"] < 80.0)
            | (df["r_480_1h"] < -35.0)
            | (df["r_480_4h"] < -20.0)
            | (df["close"] < df["res_hlevel_4h"])
          )
          long_entry_logic.append(
            (df["change_pct_4h"] > -0.01)
            | (df["change_pct_1h"] > -0.01)
            | (df["not_downtrend_1h"])
            | (df["rsi_3"] > 16.0)
            | (df["rsi_3_15m"] > 26.0)
            | (df["rsi_3_1h"] > 26.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["rsi_14_1h"] < 36.0)
            | (df["rsi_14_4h"] < 46.0)
            | (df["rsi_14_1d"] < 46.0)
            | (df["cti_20_1d"] < 0.5)
            | (df["r_480_4h"] > -65.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.03)
            | (df["top_wick_pct_1d"] < 0.03)
            | (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 26.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["rsi_14_1h"] < 36.0)
            | (df["rsi_14_4h"] < 50.0)
            | (df["rsi_14_1d"] < 50.0)
            | (df["r_480_4h"] < -20.0)
            | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["rsi_3"] > 10.0)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_3_1h"] > 30.0)
            | (df["rsi_14_1h"] < 30.0)
            | (df["rsi_14_4h"] < 46.0)
            | (df["rsi_14_1d"] < 50.0)
            | (df["r_480_4h"] < -35.0)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.04)
            | (df["top_wick_pct_1d"] < 0.04)
            | (df["change_pct_1h"] > -0.01)
            | (df["not_downtrend_1h"])
            | (df["rsi_3"] > 10.0)
            | (df["rsi_3_15m"] > 26.0)
            | (df["rsi_3_1h"] > 30.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["rsi_14_1h"] < 36.0)
            | (df["rsi_14_4h"] < 50.0)
            | (df["rsi_14_1d"] < 50.0)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["not_downtrend_1d"])
            | (df["rsi_3"] > 20.0)
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_3_1h"] > 30.0)
            | (df["rsi_3_1h"] > 30.0)
            | (df["rsi_3_1d"] > 16.0)
            | (df["r_480_1h"] > -85.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
            | (df["close"] > df["sup_level_1d"])
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.03)
            | (df["top_wick_pct_1d"] < 0.03)
            | (df["rsi_3"] > 6.0)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14"] < 20.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["rsi_14_1h"] < 46.0)
            | (df["rsi_14_4h"] < 50.0)
            | (df["rsi_14_1d"] < 50.0)
            | (df["rsi_14_max_6_1d"] < 70.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.16)
            | (df["top_wick_pct_1d"] < 0.16)
            | (df["change_pct_4h"] < 0.02)
            | (df["change_pct_1h"] > -0.01)
            | (df["rsi_14_15m"] < 40.0)
            | (df["rsi_14_1h"] < 60.0)
            | (df["rsi_14_max_6_1h"] < 70.0)
            | (df["rsi_14_4h"] < 75.0)
            | (df["close"] < df["res_hlevel_1h"])
            | (df["close"] < df["res_hlevel_4h"])
            | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.03)
            | (df["change_pct_1d"].shift(288) > -0.03)
            | (df["rsi_14_15m"] < 40.0)
            | (df["rsi_14_1h"] < 50.0)
            | (df["rsi_14_4h"] < 50.0)
            | (df["rsi_14_1d"] < 50.0)
            | (df["rsi_14_max_6_1d"] < 70.0)
            | (df["cti_20_1d"] < 0.8)
            | (df["close"] < df["res_hlevel_4h"])
            | (df["close"] < df["res_hlevel_1d"])
            | (df["hl_pct_change_6_1d"] < 0.9)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.03)
            | (df["change_pct_1d"].shift(288) > -0.03)
            | (df["change_pct_4h"] > -0.06)
            | (df["top_wick_pct_4h"] < 0.06)
            | (df["not_downtrend_1h"])
            | (df["rsi_14_max_6_1d"] < 70.0)
            | (df["cti_20_1d"] < 0.8)
            | (df["hl_pct_change_6_1d"] < 0.9)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.24)
            | (df["change_pct_4h"] < 0.06)
            | (df["top_wick_pct_4h"] < 0.06)
            | (df["change_pct_1h"] > -0.02)
            | (df["rsi_14_15m"] < 40.0)
            | (df["rsi_14_1h"] < 50.0)
            | (df["rsi_14_4h"] < 80.0)
            | (df["r_480_1h"] < -35.0)
          )

          # Logic
          long_entry_logic.append(df["cti_20"] < -0.75)
          long_entry_logic.append(df["r_14"] < -90.0)
          long_entry_logic.append(df["close"] < (df["ema_20"] * 0.962))
          long_entry_logic.append(df["close_15m"] < (df["ema_12_15m"] * 0.982))

        # Condition #21 - Pump mode (Long).
        if index == 21:
          # Protections
          long_entry_logic.append(df["protections_long_global"] == True)
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * 0.84))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * 0.78))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * 0.72))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * 0.60))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * 0.50))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.4)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.5)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.75)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.9)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3_15m"] > 1.0)

          long_entry_logic.append(df["ema_200_dec_48_1h"] == False)
          long_entry_logic.append(df["ema_200_dec_24_4h"] == False)

          # Logic
          long_entry_logic.append(df["ema_26"] > df["ema_12"])
          long_entry_logic.append((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.020))
          long_entry_logic.append((df["ema_26"].shift() - df["ema_12"].shift()) > (df["open"] / 100))
          long_entry_logic.append(df["rsi_14"] < 36.0)

        # Condition #22 - Pump mode (Long).
        if index == 22:
          # Protections
          long_entry_logic.append(df["protections_long_global"] == True)
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * 0.82))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * 0.78))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * 0.72))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * 0.60))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * 0.50))

          long_entry_logic.append(df["rsi_14_1h"] < 85.0)
          long_entry_logic.append(df["cti_20_4h"] < 0.9)
          long_entry_logic.append(df["rsi_14_4h"] < 85.0)
          long_entry_logic.append(df["rsi_14_1d"] < 85.0)

          long_entry_logic.append(df["ema_200_1h"] > df["ema_200_1h"].shift(96))
          long_entry_logic.append(df["ema_200_dec_48_1h"] == False)
          long_entry_logic.append(df["sma_200_1h"] > df["sma_200_1h"].shift(24))

          # Logic
          long_entry_logic.append(df["close"] < (df["ema_16"] * 0.968))
          long_entry_logic.append(df["cti_20"] < -0.9)
          long_entry_logic.append(df["rsi_14"] < 50.0)

        # Condition #23 - Pump mode (Long).
        if index == 23:
          # Protections
          long_entry_logic.append(df["protections_long_global"] == True)
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * 0.82))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * 0.78))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * 0.72))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * 0.60))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * 0.50))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.5)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.6)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.75)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.8)
          long_entry_logic.append(df["hl_pct_change_6_1d"] < 1.5)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["cti_20_4h"] < 0.8)
          long_entry_logic.append(df["rsi_14_4h"] < 80.0)

          # Logic
          long_entry_logic.append(df["ewo_50_200_15m"] > 4.2)
          long_entry_logic.append(df["rsi_14_15m"].shift(1) < 30.0)
          long_entry_logic.append(df["rsi_14_15m"] < 30.0)
          long_entry_logic.append(df["rsi_14"] < 35.0)
          long_entry_logic.append(df["cti_20"] < -0.8)
          long_entry_logic.append(df["close"] < (df["ema_26_15m"] * 0.958))

        # Condition #24 - Pump mode (Long)
        if index == 24:
          # Protections
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * self.entry_24_close_max_12.value))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * self.entry_24_close_max_24.value))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * self.entry_24_close_max_48.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * self.entry_24_high_max_24_1h.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * self.entry_24_high_max_24_4h.value))
          long_entry_logic.append(df["close"] > (df["high_max_6_1d"] * self.entry_24_high_max_6_1d.value))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < self.entry_24_hl_pct_change_6_1h.value)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < self.entry_24_hl_pct_change_12_1h.value)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < self.entry_24_hl_pct_change_24_1h.value)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < self.entry_24_hl_pct_change_48_1h.value)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] >= self.entry_24_rsi_3_min.value)
          long_entry_logic.append(df["rsi_3"] <= self.entry_24_rsi_3_max.value)
          long_entry_logic.append(df["rsi_3_15m"] >= self.entry_24_rsi_3_15m_min.value)
          long_entry_logic.append(df["rsi_3_1h"] >= self.entry_24_rsi_3_1h_min.value)
          long_entry_logic.append(df["rsi_3_4h"] >= self.entry_24_rsi_3_4h_min.value)
          long_entry_logic.append(df["rsi_3_1d"] >= self.entry_24_rsi_3_1d_min.value)
          long_entry_logic.append(df["cti_20_1h"] <= self.entry_24_cti_20_1h_max.value)
          long_entry_logic.append(df["rsi_14_1h"] <= self.entry_24_rsi_14_1h_max.value)
          long_entry_logic.append(df["cti_20_4h"] <= self.entry_24_cti_20_4h_max.value)
          long_entry_logic.append(df["rsi_14_4h"] <= self.entry_24_rsi_14_4h_max.value)
          long_entry_logic.append(df["cti_20_1d"] <= self.entry_24_cti_20_1d_max.value)
          long_entry_logic.append(df["rsi_14_1d"] <= self.entry_24_rsi_14_1d_max.value)
          long_entry_logic.append(df["r_14_1h"] <= self.entry_24_r_14_1h_max.value)
          long_entry_logic.append(df["r_14_4h"] <= self.entry_24_r_14_1h_max.value)
          long_entry_logic.append(df["r_480_1h"] <= self.entry_24_r_480_1h_max.value)
          long_entry_logic.append(df["r_480_4h"] <= self.entry_24_r_480_1h_max.value)

          if self.entry_24_sup_level_1h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1h"])
          if self.entry_24_res_level_1h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_24_sup_level_4h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_4h"])
          if self.entry_24_res_level_4h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_4h"])
          if self.entry_24_sup_level_1d_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1d"])
          if self.entry_24_res_level_1d_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_24_ema_200_not_dec_1h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_48_1h"] == False)
          if self.entry_24_ema_200_not_dec_4h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_24_4h"] == False)
          if self.entry_24_ema_200_not_dec_1d_enabled.value:
            long_entry_logic.append(df["ema_200_dec_4_1d"] == False)
          if self.entry_24_not_downtrend_15m_enabled.value:
            long_entry_logic.append(df["not_downtrend_15m"])
          if self.entry_24_not_downtrend_1h_enabled.value:
            long_entry_logic.append(df["not_downtrend_1h"])
          if self.entry_24_not_downtrend_4h_enabled.value:
            long_entry_logic.append(df["not_downtrend_4h"])
          if self.entry_24_not_downtrend_1d_enabled.value:
            long_entry_logic.append(df["not_downtrend_1d"])
          if self.entry_24_ema_50_over_ema_200_enabled.value:
            long_entry_logic.append(df["ema_50"] > df["ema_200"])
          if self.entry_24_ema_12_1h_over_ema_200_1h_enabled.value:
            long_entry_logic.append(df["ema_12_1h"] > df["ema_200_1h"])

          # Logic
          long_entry_logic.append(df["rsi_14"] > self.entry_24_rsi_14_min.value)
          long_entry_logic.append(df["rsi_14"] < self.entry_24_rsi_14_max.value)
          long_entry_logic.append(df["cti_20"] < self.entry_24_cti_20_max.value)
          long_entry_logic.append(df["r_14"] < self.entry_24_r_14_max.value)
          long_entry_logic.append(df["ewo_50_200"] > self.entry_24_ewo_50_200_min.value)
          long_entry_logic.append(df["ewo_50_200"] < self.entry_24_ewo_50_200_max.value)
          long_entry_logic.append(df["close"] < (df["sma_75"] * self.entry_24_sma_offset.value))

        # Condition #25 - Pump mode (Long).
        if index == 25:
          # Protections
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * self.entry_25_close_max_12.value))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * self.entry_25_close_max_24.value))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * self.entry_25_close_max_48.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * self.entry_25_high_max_24_1h.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * self.entry_25_high_max_24_4h.value))
          long_entry_logic.append(df["close"] > (df["high_max_6_1d"] * self.entry_25_high_max_6_1d.value))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < self.entry_25_hl_pct_change_6_1h.value)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < self.entry_25_hl_pct_change_12_1h.value)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < self.entry_25_hl_pct_change_24_1h.value)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < self.entry_25_hl_pct_change_48_1h.value)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] > self.entry_25_rsi_3_min.value)
          long_entry_logic.append(df["rsi_3"] < self.entry_25_rsi_3_max.value)
          long_entry_logic.append(df["rsi_3_15m"] > self.entry_25_rsi_3_15m_min.value)
          long_entry_logic.append(df["rsi_3_1h"] > self.entry_25_rsi_3_1h_min.value)
          long_entry_logic.append(df["rsi_3_4h"] > self.entry_25_rsi_3_4h_min.value)
          long_entry_logic.append(df["rsi_3_1d"] > self.entry_25_rsi_3_1d_min.value)
          long_entry_logic.append(df["cti_20_1h"] < self.entry_25_cti_20_1h_max.value)
          long_entry_logic.append(df["rsi_14_1h"] < self.entry_25_rsi_14_1h_max.value)
          long_entry_logic.append(df["cti_20_4h"] < self.entry_25_cti_20_4h_max.value)
          long_entry_logic.append(df["rsi_14_4h"] < self.entry_25_rsi_14_4h_max.value)
          long_entry_logic.append(df["cti_20_1d"] < self.entry_25_cti_20_1d_max.value)
          long_entry_logic.append(df["rsi_14_1d"] < self.entry_25_rsi_14_1d_max.value)
          long_entry_logic.append(df["r_14_1h"] >= self.entry_25_r_14_1h_min.value)
          long_entry_logic.append(df["r_14_1h"] <= self.entry_25_r_14_1h_max.value)
          long_entry_logic.append(df["r_14_4h"] >= self.entry_25_r_14_4h_min.value)
          long_entry_logic.append(df["r_14_4h"] <= self.entry_25_r_14_4h_max.value)
          long_entry_logic.append(df["r_480_1h"] >= self.entry_25_r_480_1h_min.value)
          long_entry_logic.append(df["r_480_1h"] <= self.entry_25_r_480_1h_max.value)
          long_entry_logic.append(df["r_480_4h"] >= self.entry_25_r_480_4h_min.value)
          long_entry_logic.append(df["r_480_4h"] <= self.entry_25_r_480_4h_max.value)

          if self.entry_25_sup_level_1h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1h"])
          if self.entry_25_res_level_1h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_25_sup_level_4h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_4h"])
          if self.entry_25_res_level_4h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_4h"])
          if self.entry_25_sup_level_1d_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1d"])
          if self.entry_25_res_level_1d_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_25_ema_200_not_dec_1h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_48_1h"] == False)
          if self.entry_25_ema_200_not_dec_4h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_24_4h"] == False)
          if self.entry_25_ema_200_not_dec_1d_enabled.value:
            long_entry_logic.append(df["ema_200_dec_4_1d"] == False)
          if self.entry_25_not_downtrend_15m_enabled.value:
            long_entry_logic.append(df["not_downtrend_15m"])
          if self.entry_25_not_downtrend_1h_enabled.value:
            long_entry_logic.append(df["not_downtrend_1h"])
          if self.entry_25_not_downtrend_4h_enabled.value:
            long_entry_logic.append(df["not_downtrend_4h"])
          if self.entry_25_not_downtrend_1d_enabled.value:
            long_entry_logic.append(df["not_downtrend_1d"])

          long_entry_logic.append((df["r_480_4h"] > -70.0) | (df["ema_200_dec_24_4h"] == False))

          # Logic
          long_entry_logic.append(df["rsi_14"] < self.entry_25_rsi_14_max.value)
          long_entry_logic.append(df["cti_20"] < self.entry_25_cti_20_max.value)
          long_entry_logic.append(df["ewo_50_200"] > self.entry_25_ewo_50_200_min.value)
          long_entry_logic.append(df["close"] < (df["sma_30"] * self.entry_25_sma_offset.value))

        # Condition #26 - Pump mode (Long).
        if index == 26:
          # Protections
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * self.entry_26_close_max_12.value))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * self.entry_26_close_max_24.value))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * self.entry_26_close_max_48.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * self.entry_26_high_max_24_1h.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * self.entry_26_high_max_24_4h.value))
          long_entry_logic.append(df["close"] > (df["high_max_6_1d"] * self.entry_26_high_max_6_1d.value))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < self.entry_26_hl_pct_change_6_1h.value)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < self.entry_26_hl_pct_change_12_1h.value)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < self.entry_26_hl_pct_change_24_1h.value)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < self.entry_26_hl_pct_change_48_1h.value)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] > self.entry_26_rsi_3_min.value)
          long_entry_logic.append(df["rsi_3"] < self.entry_26_rsi_3_max.value)
          long_entry_logic.append(df["rsi_3_15m"] > self.entry_26_rsi_3_15m_min.value)
          long_entry_logic.append(df["rsi_3_1h"] > self.entry_26_rsi_3_1h_min.value)
          long_entry_logic.append(df["rsi_3_4h"] > self.entry_26_rsi_3_4h_min.value)
          long_entry_logic.append(df["rsi_3_1d"] > self.entry_26_rsi_3_1d_min.value)
          long_entry_logic.append(df["cti_20_1h"] < self.entry_26_cti_20_1h_max.value)
          long_entry_logic.append(df["rsi_14_1h"] < self.entry_26_rsi_14_1h_max.value)
          long_entry_logic.append(df["cti_20_4h"] < self.entry_26_cti_20_4h_max.value)
          long_entry_logic.append(df["rsi_14_4h"] < self.entry_26_rsi_14_4h_max.value)
          long_entry_logic.append(df["cti_20_1d"] < self.entry_26_cti_20_1d_max.value)
          long_entry_logic.append(df["rsi_14_1d"] < self.entry_26_rsi_14_1d_max.value)
          long_entry_logic.append(df["r_14_1h"] >= self.entry_26_r_14_1h_min.value)
          long_entry_logic.append(df["r_14_1h"] <= self.entry_26_r_14_1h_max.value)
          long_entry_logic.append(df["r_14_4h"] >= self.entry_26_r_14_4h_min.value)
          long_entry_logic.append(df["r_14_4h"] <= self.entry_26_r_14_4h_max.value)
          long_entry_logic.append(df["r_480_1h"] >= self.entry_26_r_480_1h_min.value)
          long_entry_logic.append(df["r_480_1h"] <= self.entry_26_r_480_1h_max.value)
          long_entry_logic.append(df["r_480_4h"] >= self.entry_26_r_480_4h_min.value)
          long_entry_logic.append(df["r_480_4h"] <= self.entry_26_r_480_4h_max.value)

          if self.entry_26_sup_level_1h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1h"])
          if self.entry_26_res_level_1h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_26_sup_level_4h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_4h"])
          if self.entry_26_res_level_4h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_4h"])
          if self.entry_26_sup_level_1d_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1d"])
          if self.entry_26_res_level_1d_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_26_ema_200_not_dec_1h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_48_1h"] == False)
          if self.entry_26_ema_200_not_dec_4h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_24_4h"] == False)
          if self.entry_26_ema_200_not_dec_1d_enabled.value:
            long_entry_logic.append(df["ema_200_dec_4_1d"] == False)
          if self.entry_26_not_downtrend_15m_enabled.value:
            long_entry_logic.append(df["not_downtrend_15m"])
          if self.entry_26_not_downtrend_1h_enabled.value:
            long_entry_logic.append(df["not_downtrend_1h"])
          if self.entry_26_not_downtrend_4h_enabled.value:
            long_entry_logic.append(df["not_downtrend_4h"])
          if self.entry_26_not_downtrend_1d_enabled.value:
            long_entry_logic.append(df["not_downtrend_1d"])
          long_entry_logic.append(df["ema_200_1h"] > df["ema_200_1h"].shift(12))
          long_entry_logic.append(df["ema_200_1h"].shift(12) > df["ema_200_1h"].shift(24))

          # Logic
          long_entry_logic.append(df["close"] < (df["bb20_2_low"] * self.entry_26_bb_offset.value))
          long_entry_logic.append(df["ewo_50_200_1h"] > self.entry_26_ewo_50_200_1h_min.value)
          long_entry_logic.append(df["ema_26"] > df["ema_12"])
          long_entry_logic.append((df["ema_26"] - df["ema_12"]) > (df["open"] * self.entry_26_ema_open_offset.value))
          long_entry_logic.append((df["ema_26"].shift() - df["ema_12"].shift()) > (df["open"] / 100.0))

        # Condition #41 - Quick mode bull.
        if index == 41:
          # Protections
          long_entry_logic.append(df["protections_long_global"] == True)
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close_max_12"] < (df["close"] * 1.2))
          long_entry_logic.append(df["close_max_24"] < (df["close"] * 1.24))
          long_entry_logic.append(df["close_max_48"] < (df["close"] * 1.3))
          long_entry_logic.append(df["high_max_24_1h"] < (df["close"] * 1.5))
          long_entry_logic.append(df["high_max_24_4h"] < (df["close"] * 1.75))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.4)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.5)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.75)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.9)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          # pump and now started dumping, still high
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.05)
            | (df["cti_20_1d"] < 0.5)
            | (df["rsi_14_1d"] < 70.0)
            | (df["hl_pct_change_48_1h"] < 0.4)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.16)
            | (df["top_wick_pct_1d"] < 0.1)
            | (df["cti_20_4h"] < 0.5)
            | (df["cti_20_1d"] < 0.5)
            | (df["rsi_14_1d"] < 70.0)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.06)
            | (df["top_wick_pct_4h"] < 0.06)
            | (df["cti_20_4h"] < 0.5)
            | (df["rsi_14_4h"] < 70.0)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.02)
            | (df["top_wick_pct_1d"] < 0.06)
            | (df["change_pct_1d"].shift(288) < 0.12)
            | (df["cti_20_4h"] < 0.5)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] > -0.06) | (df["change_pct_4h"].shift(48) < 0.06) | (df["cti_20_4h"] < 0.5)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] > -0.02)
            | (df["cti_20_4h"] < 0.85)
            | (df["cti_20_4h"].shift(48) < 0.85)
            | (df["rsi_14_4h"].shift(48) < 70.0)
          )
          long_entry_logic.append((df["cti_20_4h"] < 0.5) | (df["cti_20_1d"] < 0.9) | (df["rsi_14_1d"] < 75.0))
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_14_15m"] < 30.0)
            | (df["rsi_3_1h"] > 25.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < -0.0)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_15m"] > 10.0)
            | (df["rsi_3_1h"] > 10.0)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_1h"] > 10.0)
            | (df["cti_20_4h"] < -0.5)
            | (df["cti_20_1d"] < -0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < -0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.75)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["rsi_3_1h"] > 30.0)
            | (df["cti_20_4h"] < -0.8)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1d"] < -0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_14_15m"] < 30.0)
            | (df["rsi_3_1h"] > 10.0)
            | (df["cti_20_1d"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_4h"] < -0.8)
            | (df["cti_20_1d"] < -0.8)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["rsi_3_1h"] > 20.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < -0.0)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_14_15m"] < 30.0)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_1d"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_4h"] < -0.75)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.0)
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["cti_20_4h"] < -0.75)
            | (df["cti_20_1d"] < -0.8)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_14_15m"] < 30.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_4h"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.5)
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_4h"] < -0.0)
            | (df["cti_20_1d"] < -0.0)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_14_15m"] < 30.0)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < -0.8)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_3_1h"] > 10.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.75)
            | (df["rsi_3_15m"] > 10.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_4h"] < -0.8)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["rsi_3_1h"] > 30.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_14_15m"] < 20.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_1d"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["cti_20_1d"] < -0.8)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_14_15m"] < 20.0)
            | (df["rsi_3_1h"] > 30.0)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 10.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.5)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1d"] < 0.75)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1d"] < -0.8)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_14_15m"] < 20.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_4h"] < -0.8)
            | (df["cti_20_1d"] < -0.8)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.5)
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["cti_20_4h"] < -0.5)
            | (df["cti_20_1d"] < 0.75)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.5)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_1d"] < 0.5)
            | (df["ema_200_dec_48_1h"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.5)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 25.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_4h"] < -0.8)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.5)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < -0.5)
            | (df["cti_20_1d"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 20.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < -0.0)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < 0.5)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < 0.75)
            | (df["cti_20_1d"] < -0.75)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.75)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < -0.8)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.75)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < -0.5)
            | (df["cti_20_1d"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["cti_20_1d"] < -0.5)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_1d"] < -0.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.0)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < 0.5)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.75)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["cti_20_4h"] < -0.0)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.8)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["cti_20_1d"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 25.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < -0.0)
            | (df["cti_20_1d"] < -0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["cti_20_4h"] < -0.8)
            | (df["cti_20_1d"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.8)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["cti_20_4h"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < -0.0)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.5)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < -0.8)
            | (df["r_14_4h"] < -30.0)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.75)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["cti_20_1d"] < -0.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_4h"] < -0.5)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["rsi_3_1h"] > 30.0)
            | (df["cti_20_4h"] < -0.5)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_3_1h"] > 10.0)
            | (df["cti_20_4h"] < 0.5)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.75)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["cti_20_4h"] < -0.5)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < 0.5)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_4h"] < -0.8)
            | (df["cti_20_1d"] < -0.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.75)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < -0.0)
            | (df["cti_20_1d"] < -0.0)
          )
          long_entry_logic.append(
            (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < -0.8)
            | (df["cti_20_1d"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.5)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["cti_20_4h"] < 0.5)
            | (df["cti_20_1d"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.75)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_1d"] < -0.0)
            | (df["ema_200_dec_48_1h"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < -0.8)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.5)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < 0.5)
            | (df["rsi_14_4h"] < 70.0)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.9)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < 0.5)
            | (df["cti_20_1d"] < 0.5)
            | (df["hl_pct_change_48_1h"] < 0.5)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < -0.8)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_4h"] < -0.5)
            | (df["cti_20_1d"] < -0.8)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.75)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < -0.0)
            | (df["rsi_14_4h"] < 70.0)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < 0.5)
            | (df["rsi_14_4h"] < 70.0)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["rsi_3_1h"] > 30.0)
            | (df["cti_20_4h"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < -0.0)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["cti_20_15m"] < -0.5)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.5)
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["rsi_3_1h"] > 30.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["cti_20_1d"] < -0.0)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_15m"] > 20.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < -0.0)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_4h"] < -0.8)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.75)
            | (df["rsi_3_1h"] > 25.0)
            | (df["ema_200_dec_48_1h"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_4h"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_3_1h"] > 30.0)
            | (df["cti_20_4h"] < -0.5)
            | (df["cti_20_1d"] < -0.0)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.75)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["high_max_48_1h"] < (df["close"] * 1.3))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.75)
            | (df["cti_20_4h"] < -0.8)
            | (df["high_max_48_1h"] < (df["close"] * 1.3))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.75)
            | (df["cti_20_4h"] < -0.0)
            | (df["cti_20_1d"] < 0.75)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.9)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.75)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < -0.8)
          )
          long_entry_logic.append(
            (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.75)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["cti_20_1d"] < -0.5)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_15m"] > 10.0)
            | (df["rsi_3_1h"] > 10.0)
            | (df["cti_20_1d"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.5)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.8)
            | (df["cti_20_4h"] < -0.0)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < 0.5)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["cti_20_4h"] < 0.8)
            | (df["cti_20_1d"] < -0.0)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_1h"] < -0.75)
            | (df["rsi_3_1h"] > 10.0)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.75)
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < 0.8)
            | (df["cti_20_1d"] < 0.5)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1d"] < -0.8)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_1d"] < 0.5)
            | (df["ema_200_dec_48_1h"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.75)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_14_15m"] < 30.0)
            | (df["rsi_3_1h"] > 25.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_1h"] < -0.75)
            | (df["rsi_3_1h"] > 30.0)
            | (df["cti_20_1d"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.5)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < 0.5)
            | (df["cti_20_1d"] < -0.8)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["close_max_12"] < (df["close"] * 1.12))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_4h"] < -0.5)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.06)
            | (df["change_pct_1d"].shift(288) > -0.06)
            | (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_14_15m"] < 20.0)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < -0.8)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 10.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["cti_20_4h"] < -0.0)
            | (df["cti_20_1d"] < 0.75)
            | (df["close"] < (df["ema_200_4h"] * 1.1))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_15m"] > 20.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_1d"] < -0.75)
            | (df["ema_200_dec_48_1h"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["r_480_1h"] > -95.0)
            | (df["r_480_4h"] > -95.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["rsi_3_1h"] > 6.0)
            | (df["cti_20_1d"] < 0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["r_480_1h"] > -90.0)
            | (df["r_480_4h"] > -90.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["is_downtrend_3_1d"] == False) | (df["cti_20_1d"] < 0.5) | (df["high_max_6_1d"] < (df["close"] * 1.8))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["high_max_24_4h"] < (df["close"] * 1.5))
          )
          long_entry_logic.append(
            (df["is_downtrend_3_4h"] == False)
            | (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1d"] < 0.7)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_4h"] < 0.8) | (df["ema_200_dec_24_4h"] == False) | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_3_1h"] > 25.0)
            | (df["rsi_14_1h"] < 40.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.06)
            | (df["cti_20_15m"] < -0.5)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["cti_20_1d"] < 0.5)
            | (df["rsi_14_1d"] < 40.0)
          )
          long_entry_logic.append(
            (df["cti_20_1h"] < 0.5)
            | (df["rsi_14_1h"] < 40.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["rsi_14_4h"] < 40.0)
            | (df["cti_20_1d"] < 0.5)
            | (df["rsi_14_1d"] < 70.0)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14_15m"] < 30.0)
            | (df["rsi_3_1h"] > 25.0)
            | (df["rsi_14_1h"] < 40.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["rsi_14_4h"] < 40.0)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_3_1h"] > 30.0)
            | (df["rsi_14_1h"] < 40.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["rsi_14_4h"] < 40.0)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.01)
            | (df["cti_20_1d"] < 0.5)
            | (df["rsi_14_1d"] < 70.0)
            | (df["hl_pct_change_6_1d"] < 0.7)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["rsi_14_1h"] < 30.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_1h"] > 10.0)
            | (df["rsi_3_4h"] > 30.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.0)
            | (df["rsi_3"] > 20.0)
            | (df["rsi_14_1h"] < 40.0)
            | (df["cti_20_4h"] < -0.5)
            | (df["rsi_14_4h"] < 40.0)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append((df["change_pct_4h"] > -0.03) | (df["cti_20_1h"] < -0.5) | (df["cti_20_4h"] < 0.7))
          long_entry_logic.append(
            (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["high_max_24_4h"] < (df["close"] * 1.3))
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.0)
            | (df["rsi_14_1h"] < 40.0)
            | (df["cti_20_4h"] < -0.5)
            | (df["rsi_14_4h"] < 40.0)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )

          # Logic
          long_entry_logic.append(df["bb40_2_delta"].gt(df["close"] * 0.036))
          long_entry_logic.append(df["close_delta"].gt(df["close"] * 0.02))
          long_entry_logic.append(df["bb40_2_tail"].lt(df["bb40_2_delta"] * 0.4))
          long_entry_logic.append(df["close"].lt(df["bb40_2_low"].shift()))
          long_entry_logic.append(df["close"].le(df["close"].shift()))
          long_entry_logic.append(df["rsi_14"] < 36.0)

        # Condition #42 - Quick mode bull.
        if index == 42:
          # Protections
          long_entry_logic.append(df["protections_long_global"] == True)
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close_max_12"] < (df["close"] * 1.2))
          long_entry_logic.append(df["close_max_24"] < (df["close"] * 1.24))
          long_entry_logic.append(df["close_max_48"] < (df["close"] * 1.3))
          long_entry_logic.append(df["high_max_24_1h"] < (df["close"] * 1.5))
          long_entry_logic.append(df["high_max_24_4h"] < (df["close"] * 1.75))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.4)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.5)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.75)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.9)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["cti_20_1h"] < 0.8)
          long_entry_logic.append(df["rsi_14_1h"] < 80.0)
          long_entry_logic.append(df["cti_20_4h"] < 0.8)
          long_entry_logic.append(df["rsi_14_4h"] < 80.0)

          long_entry_logic.append(
            ((df["not_downtrend_1h"]) & (df["not_downtrend_4h"])) | (df["high_max_24_4h"] < (df["close"] * 1.5))
          )
          long_entry_logic.append(
            (df["top_wick_pct_4h"] < (abs(df["change_pct_4h"]) * 5.0))
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < 0.5)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["top_wick_pct_4h"] < (abs(df["change_pct_4h"]) * 5.0))
            | (df["cti_20_4h"] < 0.5)
            | (df["rsi_14_4h"] < 70.0)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.1)
            | (df["top_wick_pct_1d"] < 0.05)
            | (df["cti_20_1d"] < 0.5)
            | (df["rsi_14_1d"] < 80.0)
          )
          long_entry_logic.append(
            (df["change_pct_4h"].shift(48) < 0.1) | (df["change_pct_4h"] > -0.04) | (df["cti_20_4h"] < 0.5)
          )
          long_entry_logic.append(
            (df["top_wick_pct_1d"] < (abs(df["change_pct_1d"]) * 2.0))
            | (df["cti_20_1d"] < 0.5)
            | (df["rsi_14_1d"] < 80.0)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_3_1h"] > 30.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_3_1h"] > 10.0)
            | (df["ema_200_dec_48_1h"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_1d"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 20.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < -0.8)
            | (df["cti_20_1d"] < 0.5)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_1d"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.75)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.75)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["cti_20_4h"] < -0.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 20.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_15m"] > 10.0)
            | (df["rsi_3_1h"] > 25.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.04))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_15m"] > 10.0)
            | (df["rsi_3_1h"] > 10.0)
            | (df["cti_20_1d"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.75)
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_1h"] < -0.75)
            | (df["rsi_3_1h"] > 30.0)
            | (df["cti_20_1d"] < -0.0)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.75)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < -0.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.04))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < -0.5)
            | (df["cti_20_1d"] < 0.5)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.04))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["ema_200_dec_48_1h"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.04))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_3_1h"] > 10.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.05))
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.16)
            | (df["cti_20_15m"] < -0.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < -0.5)
            | (df["cti_20_1d"] < 0.5)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_1d"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.75)
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["rsi_3_1h"] > 25.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 20.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["rsi_3_1h"] > 10.0)
            | (df["cti_20_4h"] < -0.8)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.75)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["rsi_3_1h"] > 25.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.04))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.75)
            | (df["rsi_3_15m"] > 10.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.75)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["cti_20_15m"] < -0.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < -0.8)
            | (df["ema_200_dec_48_1h"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 20.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_3_1h"] > 10.0)
            | (df["cti_20_4h"] < -0.0)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.75)
            | (df["rsi_3_15m"] > 10.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.75)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.75)
            | (df["rsi_3_15m"] > 10.0)
            | (df["rsi_3_1h"] > 10.0)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["rsi_3_1h"] > 30.0)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 10.0)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["cti_20_4h"] < -0.0)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.75)
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_1h"] < -0.75)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.04))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["cti_20_15m"] < -0.75)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["cti_20_4h"] < -0.8)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_1d"] < -0.8)
            | (df["ema_200_dec_24_4h"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_3_1h"] > 25.0)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.04))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["cti_20_1d"] < -0.5)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.04))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_3_1h"] > 25.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["cti_20_4h"] < -0.0)
            | (df["cti_20_1d"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 10.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["ema_200_dec_48_1h"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.75)
            | (df["rsi_3_15m"] > 10.0)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < -0.0)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_4h"] < -0.5)
            | (df["cti_20_1d"] < 0.75)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 10.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["cti_20_4h"] < 0.5)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["cti_20_4h"] < -0.0)
            | (df["cti_20_1d"] < -0.5)
            | (df["ema_200_dec_24_4h"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.04))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_1d"] < 0.5)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_4h"] < -0.5)
            | (df["cti_20_1d"] < -0.8)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["close_max_24"] < (df["close"] * 1.1))
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append((df["rsi_3"] > 20.0) | (df["rsi_3_15m"] > 20.0) | (df["cti_20_1d"] < 0.8))
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 8.0)
            | (df["cti_20_4h"] < -0.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["top_wick_pct_1d"] < (abs(df["change_pct_1d"]) * 4.0))
            | (df["not_downtrend_1h"])
            | (df["cti_20_1h"] < -0.8)
            | (df["cti_20_4h"] < -0.0)
            | (df["ema_200_dec_4_1d"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.04))
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.04)
            | (df["top_wick_pct_4h"] < 0.04)
            | (df["ema_200_dec_48_1h"] == False)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.03))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"]) | (df["rsi_3_15m"] > 3.0) | (df["high_max_12_1d"] < (df["close"] * 1.5))
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.03)
            | (df["rsi_14_4h"] < 40.0)
            | (df["cti_20_1d"] < 0.5)
            | (df["rsi_14_1d"] < 70.0)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.06)
            | (df["top_wick_pct_1d"] < 0.06)
            | (df["cti_20_1h"] < 0.5)
            | (df["rsi_14_1h"] < 50.0)
            | (df["cti_20_1d"] < 0.5)
            | ((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.04))
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.01)
            | (df["cti_20_1d"] < 0.5)
            | (df["rsi_14_1d"] < 70.0)
            | (df["hl_pct_change_6_1d"] < 0.7)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.06)
            | (df["top_wick_pct_1d"] < 0.06)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_14_1h"] < 40.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["rsi_14_4h"] < 40.0)
            | (df["cti_20_1d"] < 0.5)
          )

          # Logic
          long_entry_logic.append(df["ema_26"] > df["ema_12"])
          long_entry_logic.append((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.018))
          long_entry_logic.append((df["ema_26"].shift() - df["ema_12"].shift()) > (df["open"] / 100))
          long_entry_logic.append(df["close"] < (df["bb20_2_low"] * 0.996))
          long_entry_logic.append(df["rsi_14"] < 40.0)

        # Condition #43 - Quick mode bull.
        if index == 43:
          # Protections
          long_entry_logic.append(df["protections_long_global"] == True)
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close_max_12"] < (df["close"] * 1.2))
          long_entry_logic.append(df["close_max_24"] < (df["close"] * 1.24))
          long_entry_logic.append(df["close_max_48"] < (df["close"] * 1.3))
          long_entry_logic.append(df["high_max_24_1h"] < (df["close"] * 1.5))
          long_entry_logic.append(df["high_max_24_4h"] < (df["close"] * 1.75))
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.5)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.75)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.9)

          long_entry_logic.append(df["cti_20_1h"] < 0.8)
          long_entry_logic.append(df["rsi_14_1h"] < 80.0)
          long_entry_logic.append(df["cti_20_4h"] < 0.8)
          long_entry_logic.append(df["rsi_14_4h"] < 80.0)

          long_entry_logic.append(
            ((df["not_downtrend_1h"]) & (df["not_downtrend_4h"])) | (df["high_max_24_4h"] < (df["close"] * 1.5))
          )
          long_entry_logic.append(
            (df["top_wick_pct_4h"] < (abs(df["change_pct_4h"]) * 5.0))
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < 0.5)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["top_wick_pct_4h"] < (abs(df["change_pct_4h"]) * 5.0))
            | (df["cti_20_4h"] < 0.5)
            | (df["rsi_14_4h"] < 70.0)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.1)
            | (df["top_wick_pct_4h"] < 0.05)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < 0.5)
            | (df["rsi_14_4h"] < 70.0)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.16) | (df["top_wick_pct_4h"] < 0.08) | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.06)
            | (df["change_pct_1d"].shift(288) < 0.1)
            | (df["top_wick_pct_1d"].shift(288) < 0.1)
            | (df["cti_20_1d"].shift(288) < 0.8)
            | (df["rsi_14_1d"].shift(288) < 70.0)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.1)
            | (df["top_wick_pct_1d"] < 0.05)
            | (df["cti_20_1d"] < 0.5)
            | (df["rsi_14_1d"] < 80.0)
          )
          long_entry_logic.append(
            (df["change_pct_4h"].shift(48) < 0.1) | (df["change_pct_4h"] > -0.04) | (df["cti_20_4h"] < 0.5)
          )
          long_entry_logic.append(
            (df["top_wick_pct_1d"] < (abs(df["change_pct_1d"]) * 2.0))
            | (df["cti_20_1d"] < 0.5)
            | (df["rsi_14_1d"] < 80.0)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.75)
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["rsi_3_1h"] > 30.0)
            | (df["cti_20_4h"] < -0.0)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["close"] < (df["ema_26"] * 0.93))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["cti_20_15m"] < -0.5)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["close"] < (df["ema_26"] * 0.93))
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["close"] < (df["ema_26"] * 0.92))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_1d"] < -0.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["close"] < (df["ema_26"] * 0.93))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < -0.0)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["close"] < (df["ema_26"] * 0.93))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.5)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["cti_20_4h"] < -0.8)
            | (df["close"] < (df["ema_26"] * 0.93))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 25.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["rsi_3_1h"] > 30.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["close"] < (df["ema_26"] * 0.93))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_15m"] > 10.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["close"] < (df["ema_26"] * 0.93))
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_1d"] < -0.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["close_max_24"] < (df["close"] * 1.12))
            | (df["close"] < (df["ema_26"] * 0.91))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["cti_20_4h"] < -0.5)
            | (df["cti_20_1d"] < -0.0)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["close"] < (df["ema_26"] * 0.93))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["rsi_3_1h"] > 10.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["cti_20_1d"] < -0.5)
            | (df["close"] < (df["ema_26"] * 0.9))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.75)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["close"] < (df["ema_26"] * 0.91))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["close"] < (df["ema_26"] * 0.92))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["rsi_3_1h"] > 25.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["close"] < (df["ema_26"] * 0.92))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_1h"] < -0.9)
            | (df["cti_20_1d"] < 0.5)
            | (df["close_max_12"] < (df["close"] * 1.1))
            | (df["close"] < (df["ema_26"] * 0.89))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 10.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_4h"] < -0.8)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["close"] < (df["ema_26"] * 0.92))
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.16)
            | (df["cti_20_15m"] < -0.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["cti_20_4h"] < -0.0)
            | (df["close"] < (df["ema_26"] * 0.92))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < -0.8)
            | (df["cti_20_1d"] < -0.5)
            | (df["close"] < (df["ema_26"] * 0.91))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["cti_20_15m"] < -0.75)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < 0.5)
            | (df["cti_20_1d"] < 0.5)
            | (df["close"] < (df["ema_26"] * 0.92))
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.1)
            | (df["not_downtrend_15m"])
            | (df["cti_20_15m"] < -0.5)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < 0.5)
            | (df["close"] < (df["ema_26"] * 0.92))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 20.0)
            | (df["cti_20_1h"] < -0.9)
            | (df["rsi_3_1h"] > 30.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["cti_20_1d"] < 0.5)
            | (df["close"] < (df["ema_26"] * 0.93))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["cti_20_15m"] < -0.5)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["close"] < (df["ema_26"] * 0.92))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 10.0)
            | (df["rsi_3_1h"] > 10.0)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["close"] < (df["ema_26"] * 0.91))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_3_1h"] > 20.0)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["close"] < (df["ema_26"] * 0.92))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_15m"] > 20.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["rsi_3_1h"] > 10.0)
            | (df["cti_20_4h"] < -0.8)
            | (df["cti_20_1d"] < 0.5)
            | (df["close"] < (df["ema_26"] * 0.92))
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_15m"] > 10.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["close"] < (df["ema_26"] * 0.88))
          )
          long_entry_logic.append((df["rsi_3"] > 20.0) | (df["rsi_3_15m"] > 20.0) | (df["cti_20_1d"] < 0.8))
          long_entry_logic.append(
            (df["rsi_3"] > 10.0)
            | (df["rsi_3_15m"] > 16.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["is_downtrend_3_1d"] == False)
            | (df["cti_20_1h"] < 0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3"] > 10.0)
            | (df["rsi_3_15m"] > 10.0)
            | (df["rsi_3_1h"] > 10.0)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["top_wick_pct_4h"] < (abs(df["change_pct_4h"]) * 4.0))
            | (df["change_pct_1h"] > -0.02)
            | (df["cti_20_1h"] < 0.5)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )

          # Logic
          long_entry_logic.append(df["close"] < (df["ema_26"] * 0.938))
          long_entry_logic.append(df["cti_20"] < -0.75)
          long_entry_logic.append(df["r_14"] < -94.0)

        # Condition #44 - Quick mode bull.
        if index == 44:
          # Protections
          long_entry_logic.append(df["protections_long_global"] == True)
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close_max_12"] < (df["close"] * 1.2))
          long_entry_logic.append(df["close_max_24"] < (df["close"] * 1.24))
          long_entry_logic.append(df["close_max_48"] < (df["close"] * 1.3))
          long_entry_logic.append(df["high_max_24_1h"] < (df["close"] * 1.5))
          long_entry_logic.append(df["high_max_24_4h"] < (df["close"] * 1.75))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.4)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.5)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.75)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.9)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["cti_20_1h"] < 0.8)
          long_entry_logic.append(df["rsi_14_1h"] < 80.0)
          long_entry_logic.append(df["cti_20_4h"] < 0.8)
          long_entry_logic.append(df["rsi_14_4h"] < 80.0)

          long_entry_logic.append(df["close_max_48"] > (df["close"] * 1.1))

          # pump and now started dumping, still high
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.05)
            | (df["cti_20_1d"] < 0.5)
            | (df["rsi_14_1d"] < 70.0)
            | (df["hl_pct_change_48_1h"] < 0.4)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.1)
            | (df["top_wick_pct_1d"] < 0.1)
            | (df["cti_20_4h"] < 0.5)
            | (df["cti_20_1d"] < 0.5)
            | (df["rsi_14_1d"] < 70.0)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.06)
            | (df["top_wick_pct_4h"] < 0.06)
            | (df["cti_20_4h"] < 0.5)
            | (df["rsi_14_4h"] < 70.0)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.02)
            | (df["top_wick_pct_1d"] < 0.06)
            | (df["change_pct_1d"].shift(288) < 0.12)
            | (df["cti_20_4h"] < 0.5)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] > -0.06) | (df["change_pct_4h"].shift(48) < 0.06) | (df["cti_20_4h"] < 0.5)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] > -0.02)
            | (df["cti_20_4h"] < 0.85)
            | (df["cti_20_4h"].shift(48) < 0.85)
            | (df["rsi_14_4h"].shift(48) < 70.0)
          )
          long_entry_logic.append(
            (df["top_wick_pct_4h"] < (abs(df["change_pct_4h"]) * 5.0))
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < 0.5)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["top_wick_pct_4h"] < (abs(df["change_pct_4h"]) * 5.0))
            | (df["cti_20_4h"] < 0.5)
            | (df["rsi_14_4h"] < 70.0)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.1)
            | (df["top_wick_pct_1d"] < 0.05)
            | (df["cti_20_1d"] < 0.5)
            | (df["rsi_14_1d"] < 80.0)
          )
          long_entry_logic.append(
            (df["change_pct_4h"].shift(48) < 0.1) | (df["change_pct_4h"] > -0.04) | (df["cti_20_4h"] < 0.5)
          )
          long_entry_logic.append(
            (df["top_wick_pct_1d"] < (abs(df["change_pct_1d"]) * 2.0))
            | (df["cti_20_1d"] < 0.5)
            | (df["rsi_14_1d"] < 80.0)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.16) | (df["top_wick_pct_4h"] < 0.08) | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.06)
            | (df["change_pct_1d"].shift(288) < 0.1)
            | (df["top_wick_pct_1d"].shift(288) < 0.1)
            | (df["cti_20_1d"].shift(288) < 0.8)
            | (df["rsi_14_1d"].shift(288) < 70.0)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.1)
            | (df["change_pct_1d"].shift(288) < 0.1)
            | (df["cti_20_1d"].shift(288) < 0.5)
            | (df["rsi_14_1d"].shift(288) < 70.0)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.1)
            | (df["top_wick_pct_1d"] < 0.05)
            | (df["cti_20_1d"] < 0.5)
            | (df["rsi_14_1d"] < 80.0)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.2)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < 0.5)
            | (df["rsi_14_4h"] < 70.0)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] > -0.06)
            | (df["top_wick_pct_4h"] < 0.06)
            | (df["change_pct_4h"].shift(48) < 0.01)
            | (df["cti_20_4h"] < 0.5)
            | (df["rsi_14_4h"].shift(48) < 70.0)
          )
          long_entry_logic.append(
            (df["top_wick_pct_1h"] < (abs(df["change_pct_1h"]) * 3.0))
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.04)
            | (df["top_wick_pct_4h"] < 0.06)
            | (df["cti_20_4h"] < 0.5)
            | (df["rsi_14_4h"] < 70.0)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["cti_20_15m"] < -0.0)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < -0.8)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 20.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < -0.0)
            | (df["cti_20_1d"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["rsi_3_1h"] > 25.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.06)
            | (df["top_wick_pct_4h"] < 0.06)
            | (df["cti_20_15m"] < -0.5)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 20.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < 0.5)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < -0.5)
            | (df["cti_20_1d"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.8)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_15m"] > 30.0)
            | (df["r_480_1h"] > -90.0)
            | (df["r_480_4h"] > -90.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.06)
            | (df["top_wick_pct_4h"] < 0.06)
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_1d"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_1h"] > -0.08)
            | (df["change_pct_1h"].shift(12) < 0.08)
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.06)
            | (df["top_wick_pct_4h"] < 0.06)
            | (df["cti_20_15m"] < -0.5)
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < 0.5)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.5)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_1d"] < 0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.5)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < -0.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.1)
            | (df["top_wick_pct_4h"] < 0.06)
            | (df["cti_20_15m"] < -0.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.04)
            | (df["top_wick_pct_4h"] < (abs(df["change_pct_4h"]) * 4.0))
            | (df["cti_20_4h"] < 0.5)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["rsi_3_1h"] > 30.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < -0.5)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.9)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.08)
            | (df["cti_20_15m"] < -0.5)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_1d"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.05)
            | (df["top_wick_pct_1d"] < 0.05)
            | (df["not_downtrend_15m"])
            | (df["cti_20_15m"] < -0.5)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < -0.5)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.5)
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < -0.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 10.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < -0.0)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["is_downtrend_3_4h"] == False)
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_3_1h"] > 25.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.5)
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_4h"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 10.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["cti_20_4h"] < -0.0)
            | (df["cti_20_1d"] < 0.75)
            | (df["close"] < (df["ema_200_4h"] * 1.1))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 10.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["rsi_3_1h"] > 25.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 10.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < 0.5)
            | (df["cti_20_1d"] < -0.0)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["is_downtrend_3_1h"] == False)
            | (df["cti_20_15m"] < -0.5)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < -0.5)
            | (df["cti_20_1d"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["cti_20_1d"] < -0.0)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["top_wick_pct_4h"] < (abs(df["change_pct_4h"]) * 2.0))
            | (df["cti_20_15m"] < -0.5)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["cti_20_4h"] < -0.5)
            | (df["cti_20_1d"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.1)
            | (df["top_wick_pct_4h"] < 0.03)
            | (df["cti_20_1h"] < 0.5)
            | (df["rsi_14_4h"] < 70.0)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.04)
            | (df["top_wick_pct_1d"] < 0.04)
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["rsi_14_1h"] < 50.0)
            | (df["cti_20_4h"] < -0.0)
            | (df["cti_20_1d"] < -0.8)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["rsi_3_1h"] > 30.0)
            | (df["cti_20_4h"] < -0.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.5)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < -0.5)
            | (df["cti_20_1d"] < 0.8)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_1d"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_1h"] > -0.03)
            | (df["change_pct_1h"].shift(12) < 0.03)
            | (df["cti_20_15m"] < -0.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < -0.8)
            | (df["cti_20_1d"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["rsi_3_1h"] > 30.0)
            | (df["cti_20_4h"] < -0.8)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.8)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < -0.5)
            | (df["cti_20_1d"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["top_wick_pct_4h"] < (abs(df["change_pct_4h"]) * 2.0))
            | (df["cti_20_1h"] < 0.5)
            | (df["rsi_3_1h"] > 30.0)
            | (df["cti_20_4h"] < -0.5)
            | (df["cti_20_1d"] < -0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append((df["cti_20_1h"] < 0.5) | (df["cti_20_4h"] < 0.5) | (df["rsi_14_4h"] < 70.0))
          long_entry_logic.append((df["change_pct_4h"] > -0.06) | (df["cti_20_1h"] < 0.5) | (df["cti_20_4h"] < 0.5))
          long_entry_logic.append(
            (df["change_pct_4h"].shift(48) < 0.04)
            | (df["top_wick_pct_4h"].shift(48) < 0.04)
            | (df["change_pct_4h"] > -0.02)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_4h"] < -0.0)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.06)
            | (df["change_pct_1d"].shift(288) < 0.06)
            | (df["cti_20_1d"].shift(288) < 0.8)
            | (df["rsi_14_1d"].shift(288) < 70.0)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 25.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["cti_20_4h"] < -0.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["cti_20_15m"] < -0.0)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < -0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.04)
            | (df["top_wick_pct_4h"] < 0.04)
            | (df["not_downtrend_1h"])
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["rsi_14_4h"] < 50.0)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.16)
            | (df["top_wick_pct_1d"] < 0.16)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.16)
            | (df["top_wick_pct_1d"] < 0.16)
            | (df["cti_20_15m"] < -0.5)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["cti_20_4h"] < -0.0)
            | (df["cti_20_1d"] < -0.5)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.16)
            | (df["top_wick_pct_1d"] < 0.16)
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_4h"] < 0.5)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.1)
            | (df["top_wick_pct_4h"] < 0.1)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < -0.5)
            | (df["rsi_14_4h"] < 70.0)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_4h"] < -0.9)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_14_15m"] < 20.0)
            | (df["rsi_3_1h"] > 10.0)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["top_wick_pct_1d"] < (abs(df["change_pct_1d"]) * 4.0))
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["cti_20_1d"] < 0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.08)
            | (df["top_wick_pct_4h"] < 0.04)
            | (df["rsi_3_15m"] > 20.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["cti_20_1d"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < -0.8)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["high_max_24_4h"] < (df["close"] * 1.5))
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < -0.0)
          )
          long_entry_logic.append(
            (df["change_pct_1h"] > -0.02)
            | (df["change_pct_1h"].shift(12) < 0.04)
            | (df["top_wick_pct_1h"].shift(12) < 0.04)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_1d"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["bb20_2_width_1h"] > 0.18)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_1h"] > 5.0)
            | (df["cti_20_1d"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.26)
            | (df["top_wick_pct_1d"] < 0.06)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < -0.5)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["is_downtrend_3_1d"] == False)
            | (df["not_downtrend_15m"])
            | (df["rsi_3_15m"] > 10.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["high_max_24_4h"] < (df["close"] * 1.5))
          )
          long_entry_logic.append(
            (df["change_pct_1h"] > -0.06)
            | (df["change_pct_1h"].shift(12) < 0.06)
            | (df["cti_20_15m"] < -0.5)
            | (df["rsi_14_15m"] < 30.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["top_wick_pct_1d"] < (abs(df["change_pct_1d"]) * 3.0))
            | (df["rsi_3_15m"] > 20.0)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["cti_20_15m"] < -0.5)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.5)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["cti_20_1d"] < 0.5)
            | (df["ema_200_dec_48_1h"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.8)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["cti_20_1d"] < 0.8)
            | (df["rsi_14_1d"] < 70.0)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.0)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.5)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["bb20_2_width_1h"] > 0.18)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.5)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["cti_20_1d"] < 0.5)
            | (df["bb20_2_width_1h"] > 0.2)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.2)
            | (df["top_wick_pct_1d"] < 0.05)
            | (df["cti_20_15m"] < -0.5)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1d"] < -0.5)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["bb20_2_width_1h"] > 0.17)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.25)
            | (df["top_wick_pct_1d"] < 0.2)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < -0.0)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["r_14"] < -96.0)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 30.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["rsi_3_1h"] > 25.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.9)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_1d"] < 0.5)
            | (df["bb20_2_width_1h"] > 0.16)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.05)
            | (df["top_wick_pct_4h"] < 0.05)
            | (df["cti_20_15m"] < -0.5)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["cti_20_1d"] < -0.0)
            | (df["bb20_2_width_1h"] > 0.22)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.1)
            | (df["top_wick_pct_1d"] < 0.06)
            | (df["cti_20_15m"] < -0.8)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["cti_20_4h"] < -0.0)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_1h"] < 0.5) | (df["cti_20_4h"] < -0.8) | (df["cti_20_1d"] < 0.8) | (df["rsi_14_1d"] < 70.0)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 10.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_1d"] < 0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["bb20_2_width_1h"] > 0.17)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["rsi_3_15m"] > 10.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["is_downtrend_3_1d"] == False)
            | (df["rsi_3_15m"] > 16.0)
            | (df["rsi_3_1h"] > 16.0)
            | (df["cti_20_1d"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["bb20_2_width_1h"] > 0.18)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14_15m"] < 20.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_1h"] < -0.8)
            | (df["cti_20_4h"] < -0.0)
            | (df["bb20_2_width_1h"] > 0.16)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["bb20_2_width_1h"] > 0.19)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.5)
            | (df["rsi_3_15m"] > 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_4h"].shift(48) < 0.06) | (df["change_pct_4h"] > -0.06) | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 20.0)
            | (df["cti_20_1h"] < -0.0)
            | (df["rsi_3_1h"] > 12.0)
            | (df["cti_20_1d"] < 0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["bb20_2_width_1h"] > 0.23)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_3_1h"] > 10.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_4h"])
            | (df["cti_20_15m"] < -0.9)
            | (df["rsi_14_15m"] < 20.0)
            | (df["r_480_1h"] > -90.0)
            | (df["r_480_4h"] > -90.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["rsi_3_15m"] > 20.0)
            | (df["r_480_4h"] > -90.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"]) | (df["not_downtrend_4h"]) | (df["rsi_3_1h"] > 20.0) | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_15m"] > 10.0)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["high_max_24_4h"] < (df["close"] * 1.5))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_15m"] > 20.0)
            | (df["rsi_3_1h"] > 10.0)
            | (df["r_480_1h"] > -90.0)
            | (df["r_480_4h"] > -90.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.5)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["r_480_4h"] > -90.0)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["bb20_2_width_1h"] > 0.22)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_15m"] < -0.5)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_4h"] < -0.5)
            | (df["r_480_4h"] > -90.0)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["bb20_2_width_1h"] > 0.22)
          )
          long_entry_logic.append(
            (df["change_pct_4h"].shift(48) < 0.16)
            | (df["top_wick_pct_4h"].shift(48) < 0.04)
            | (df["change_pct_4h"] > -0.02)
            | (df["top_wick_pct_4h"] < 0.04)
            | (df["cti_20_1h"] < 0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["is_downtrend_3_1d"] == False) | (df["cti_20_1d"] < 0.5) | (df["high_max_6_1d"] < (df["close"] * 1.8))
          )
          long_entry_logic.append(
            (df["top_wick_pct_4h"] < (abs(df["change_pct_4h"]) * 2.0))
            | (df["not_downtrend_1h"])
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_1h"] < 0.5)
            | (df["rsi_3_1h"] > 25.0)
            | (df["cti_20_4h"] < -0.8)
            | (df["cti_20_1d"] < -0.8)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["bb20_2_width_1h"] > 0.25)
          )
          long_entry_logic.append(
            (df["rsi_3"] > 10.0)
            | (df["rsi_3_15m"] > 16.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["top_wick_pct_1h"] < (abs(df["change_pct_1h"]) * 4.0))
            | (df["rsi_14_1h"] < 70.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["is_downtrend_3_1d"] == False)
            | (df["not_downtrend_1h"])
            | (df["rsi_3_1h"] > 30.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["high_max_48_1h"] < (df["close"] * 1.25))
          )
          long_entry_logic.append(
            (df["is_downtrend_3_1d"] == False)
            | (df["r_480_1h"] > -90.0)
            | (df["r_480_4h"] > -90.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.04)
            | (df["top_wick_pct_1d"] < 0.04)
            | (df["not_downtrend_1h"])
            | (df["rsi_3_1h"] > 20.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.8)
            | (df["rsi_3_15m"] > 25.0)
            | (df["rsi_14_15m"] < 20.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_3_1h"] > 25.0)
            | (df["rsi_14_1h"] < 40.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.0)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_14_1h"] < 40.0)
            | (df["cti_20_4h"] < -0.5)
            | (df["rsi_14_4h"] < 40.0)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["rsi_14_15m"] < 30.0)
            | (df["rsi_3_15m"] > 20.0)
            | (df["cti_20_1h"] < -0.5)
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_14_15m"] < 20.0)
            | (df["rsi_3_1h"] > 20.0)
            | (df["r_480_1h"] > -90.0)
            | (df["rsi_3_4h"] > 30.0)
            | (df["r_480_4h"] > -90.0)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] > -0.02)
            | (df["top_wick_pct_4h"] < 0.02)
            | (df["cti_20_4h"].shift(48) < 0.5)
            | (df["rsi_14_4h"].shift(48) < 70.0)
          )
          long_entry_logic.append(
            (df["cti_20_15m"] < -0.5)
            | (df["rsi_14_15m"] < 30.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["cti_20_1d"] < 0.5)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.06)
            | (df["top_wick_pct_4h"] < 0.06)
            | (df["cti_20_4h"] < 0.5)
            | (df["rsi_14_4h"] < 60.0)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["top_wick_pct_4h"] < (abs(df["change_pct_4h"]) * 2.0))
            | (df["cti_20_1h"] < 0.5)
            | (df["cti_20_4h"] < -0.0)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["top_wick_pct_4h"] < (abs(df["change_pct_4h"]) * 4.0))
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["rsi_14_1d"] < 40.0)
            | (df["cti_20_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.06)
            | (df["top_wick_pct_4h"] < 0.06)
            | (df["cti_20_1h"] < 0.5)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] > -0.02)
            | (df["top_wick_pct_4h"] < 0.02)
            | (df["cti_20_1h"] < 0.5)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] > 25.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["hl_pct_change_6_1d"] < 0.5)
          )
          long_entry_logic.append(
            (df["is_downtrend_3_4h"] == False)
            | (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_15m"] > 30.0)
            | (df["rsi_3_1h"] > 20.0)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_1h"] > 6.0)
            | (df["rsi_3_4h"] > 16.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["rsi_3"] > 12.0)
            | (df["cti_20_15m"] < -0.0)
            | (df["rsi_14_15m"] < 36.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["rsi_14_1h"] < 60.0)
            | (df["rsi_14_4h"] < 60.0)
          )

          # Logic
          long_entry_logic.append(df["bb20_2_width_1h"] > 0.132)
          long_entry_logic.append(df["cti_20"] < -0.8)
          long_entry_logic.append(df["r_14"] < -90.0)

        # Condition #45 - Quick mode (Long).
        if index == 45:
          # Protections
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * self.entry_45_close_max_12.value))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * self.entry_45_close_max_24.value))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * self.entry_45_close_max_48.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * self.entry_45_high_max_24_1h.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * self.entry_45_high_max_24_4h.value))
          long_entry_logic.append(df["close"] > (df["high_max_6_1d"] * self.entry_45_high_max_6_1d.value))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < self.entry_45_hl_pct_change_6_1h.value)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < self.entry_45_hl_pct_change_12_1h.value)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < self.entry_45_hl_pct_change_24_1h.value)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < self.entry_45_hl_pct_change_48_1h.value)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] > self.entry_45_rsi_3_min.value)
          long_entry_logic.append(df["rsi_3"] < self.entry_45_rsi_3_max.value)
          long_entry_logic.append(df["rsi_3_15m"] > self.entry_45_rsi_3_15m_min.value)
          long_entry_logic.append(df["rsi_3_1h"] > self.entry_45_rsi_3_1h_min.value)
          long_entry_logic.append(df["rsi_3_4h"] > self.entry_45_rsi_3_4h_min.value)
          long_entry_logic.append(df["rsi_3_1d"] > self.entry_45_rsi_3_1d_min.value)
          long_entry_logic.append(df["cti_20_1h"] < self.entry_45_cti_20_1h_max.value)
          long_entry_logic.append(df["rsi_14_1h"] < self.entry_45_rsi_14_1h_max.value)
          long_entry_logic.append(df["cti_20_4h"] < self.entry_45_cti_20_4h_max.value)
          long_entry_logic.append(df["rsi_14_4h"] < self.entry_45_rsi_14_4h_max.value)
          long_entry_logic.append(df["cti_20_1d"] < self.entry_45_cti_20_1d_max.value)
          long_entry_logic.append(df["rsi_14_1d"] < self.entry_45_rsi_14_1d_max.value)
          long_entry_logic.append(df["r_480_1h"] < self.entry_45_r_480_1h_max.value)
          long_entry_logic.append(df["r_480_4h"] < self.entry_45_r_480_1h_max.value)

          if self.entry_45_sup_level_1h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1h"])
          if self.entry_45_res_level_1h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_45_sup_level_4h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_4h"])
          if self.entry_45_res_level_4h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_4h"])
          if self.entry_45_sup_level_1d_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1d"])
          if self.entry_45_res_level_1d_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])

          # Logic
          long_entry_logic.append(df["rsi_14"] > self.entry_45_rsi_14_min.value)
          long_entry_logic.append(df["rsi_14"] < self.entry_45_rsi_14_max.value)
          long_entry_logic.append(df["rsi_20"] < df["rsi_20"].shift(1))
          long_entry_logic.append(df["cti_20"] < self.entry_45_cti_20_max.value)
          long_entry_logic.append(df["close"] < (df["sma_16"] * self.entry_45_sma_offset.value))

        # Condition #46 - Quick mode (Long).
        if index == 46:
          # Protections
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * self.entry_46_close_max_12.value))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * self.entry_46_close_max_24.value))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * self.entry_46_close_max_48.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * self.entry_46_high_max_24_1h.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * self.entry_46_high_max_24_4h.value))
          long_entry_logic.append(df["close"] > (df["high_max_6_1d"] * self.entry_46_high_max_6_1d.value))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < self.entry_46_hl_pct_change_6_1h.value)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < self.entry_46_hl_pct_change_12_1h.value)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < self.entry_46_hl_pct_change_24_1h.value)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < self.entry_46_hl_pct_change_48_1h.value)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] > self.entry_46_rsi_3_min.value)
          long_entry_logic.append(df["rsi_3"] < self.entry_46_rsi_3_max.value)
          long_entry_logic.append(df["rsi_3_15m"] > self.entry_46_rsi_3_15m_min.value)
          long_entry_logic.append(df["rsi_3_1h"] > self.entry_46_rsi_3_1h_min.value)
          long_entry_logic.append(df["rsi_3_4h"] > self.entry_46_rsi_3_4h_min.value)
          long_entry_logic.append(df["rsi_3_1d"] > self.entry_46_rsi_3_1d_min.value)
          long_entry_logic.append(df["cti_20_1h"] < self.entry_46_cti_20_1h_max.value)
          long_entry_logic.append(df["rsi_14_1h"] < self.entry_46_rsi_14_1h_max.value)
          long_entry_logic.append(df["cti_20_4h"] < self.entry_46_cti_20_4h_max.value)
          long_entry_logic.append(df["rsi_14_4h"] < self.entry_46_rsi_14_4h_max.value)
          long_entry_logic.append(df["cti_20_1d"] < self.entry_46_cti_20_1d_max.value)
          long_entry_logic.append(df["rsi_14_1d"] < self.entry_46_rsi_14_1d_max.value)
          long_entry_logic.append(df["r_14_1h"] >= self.entry_46_r_14_1h_min.value)
          long_entry_logic.append(df["r_14_1h"] <= self.entry_46_r_14_1h_max.value)
          long_entry_logic.append(df["r_14_4h"] >= self.entry_46_r_14_4h_min.value)
          long_entry_logic.append(df["r_14_4h"] <= self.entry_46_r_14_4h_max.value)
          long_entry_logic.append(df["r_480_1h"] >= self.entry_46_r_480_1h_min.value)
          long_entry_logic.append(df["r_480_1h"] <= self.entry_46_r_480_1h_max.value)
          long_entry_logic.append(df["r_480_4h"] >= self.entry_46_r_480_4h_min.value)
          long_entry_logic.append(df["r_480_4h"] <= self.entry_46_r_480_4h_max.value)

          if self.entry_46_sup_level_1h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1h"])
          if self.entry_46_res_level_1h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_46_sup_level_4h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_4h"])
          if self.entry_46_res_level_4h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_4h"])
          if self.entry_46_sup_level_1d_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1d"])
          if self.entry_46_res_level_1d_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_46_ema_200_not_dec_1h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_48_1h"] == False)
          if self.entry_46_ema_200_not_dec_4h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_24_4h"] == False)
          if self.entry_46_ema_200_not_dec_1d_enabled.value:
            long_entry_logic.append(df["ema_200_dec_4_1d"] == False)
          if self.entry_46_not_downtrend_15m_enabled.value:
            long_entry_logic.append(df["not_downtrend_15m"])
          if self.entry_46_not_downtrend_1h_enabled.value:
            long_entry_logic.append(df["not_downtrend_1h"])
          if self.entry_46_not_downtrend_4h_enabled.value:
            long_entry_logic.append(df["not_downtrend_4h"])
          if self.entry_46_not_downtrend_1d_enabled.value:
            long_entry_logic.append(df["not_downtrend_1d"])

          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["r_480_1h"] > -70.0)
            | (df["r_480_4h"] > -80.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
            | (df["close"] > df["sup_level_1d"])
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["cti_20_1d"] < 0.75)
            | (df["rsi_14_1d"] < 40.0)
            | (df["r_480_4h"] > -75.0)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["r_480_1h"] > -80.0)
            | (df["close"] > df["sup_level_4h"])
            | (df["close"] > df["sup_level_1d"])
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["cti_20_1d"] < 0.8)
            | (df["rsi_14_1d"] < 50.0)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["r_480_1h"] > -80.0)
            | (df["r_480_4h"] > -60.0)
            | (df["close"] > df["sup_level_4h"])
            | (df["close"] > df["sup_level_1d"])
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["r_480_1h"] > -70.0)
            | (df["r_480_4h"] > -70.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
            | (df["ema_200_dec_48_1h"] == False)
            | (df["close"] > (df["high_max_6_1d"] * 0.80))
          )
          long_entry_logic.append(
            (df["cti_20_4h"] < 0.75)
            | (df["rsi_14_4h"] < 60.0)
            | (df["close"] < df["res_hlevel_1h"])
            | (df["close"] < df["res_hlevel_4h"])
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14_1d"] < 40.0)
            | (df["r_480_1h"] > -70.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
            | (df["close"] > df["sup_level_1d"])
            | (df["ema_200_dec_48_1h"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.03)
            | (df["change_pct_1d"].shift(288) < 0.03)
            | (df["cti_20_1d"] < 0.7)
            | (df["rsi_14_1d"] < 50.0)
            | (df["r_480_4h"] > -70.0)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["r_480_4h"] < -25.0)
            | (df["cti_20_1d"] < 0.5)
            | (df["rsi_14_1d"] < 50.0)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["r_480_1h"] < -30.0)
            | (df["r_480_4h"] < -25.0)
            | (df["rsi_14_1d"] < 60.0)
            | (df["rsi_14_max_6_1d"] < 70.0)
            | (df["close"] > df["sup_level_4h"])
          )
          long_entry_logic.append(
            (df["r_480_1h"] < -35.0)
            | (df["r_480_4h"] < -25.0)
            | (df["rsi_14_1d"] < 50.0)
            | (df["rsi_14_max_6_1d"] < 70.0)
            | (df["close"] < df["res_hlevel_1h"])
            | (df["close"] < df["res_hlevel_4h"])
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
            | (df["close"] > df["sup_level_1d"])
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["ema_200_dec_24_4h"] == False) | (df["ema_200_dec_4_1d"] == False) | (df["hl_pct_change_6_1d"] > 0.12)
          )
          long_entry_logic.append(
            (df["rsi_14_4h"] < 40.0)
            | (df["r_480_4h"] > -65.0)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["hl_pct_change_6_1d"] > 0.20)
          )
          long_entry_logic.append(
            (df["not_downtrend_4h"])
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["hl_pct_change_6_1d"] > 0.25)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["rsi_14_4h"] < 40.0)
            | (df["cti_20_1d"] < 0.7)
            | (df["rsi_14_1d"] < 40.0)
            | (df["rsi_14_max_6_1d"] < 70.0)
            | (df["r_480_1h"] < -40.0)
            | (df["r_480_4h"] < -30.0)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14_4h"] < 40.0)
            | (df["cti_20_1d"] < 0.5)
            | (df["rsi_14_1d"] < 40.0)
            | (df["r_480_4h"] < -35.0)
            | (df["close"] > df["sup_level_4h"])
          )
          long_entry_logic.append(
            (df["change_pct_4h"] > -0.01)
            | (df["change_pct_4h"].shift(48) < 0.03)
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["rsi_14_1d"] < 40.0)
            | (df["r_480_1h"] > -75.0)
            | (df["r_480_4h"] > -75.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_4h"])
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["rsi_14_1d"] < 50.0)
            | (df["close"] > (df["high_max_12_1d"] * 0.60))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
          )
          long_entry_logic.append(
            (df["rsi_14_1h"] < 50.0)
            | (df["rsi_14_4h"] < 50.0)
            | (df["r_480_4h"] > -75.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["rsi_14_1d"] < 40.0)
            | (df["r_480_1h"] < -35.0)
            | (df["r_480_4h"] < -35.0)
            | (df["close"] > df["sup_level_1h"])
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["close"] > df["sup_level_4h"])
            | (df["close"] > df["sup_level_1d"])
            | (df["ema_200_dec_48_1h"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_14_max_6_1d"] < 70.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["r_480_4h"] > -70.0)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["rsi_14_1d"] < 40.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["hl_pct_change_6_1d"] > 0.20)
          )
          long_entry_logic.append(
            (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["rsi_14_1d"] < 40.0)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["hl_pct_change_6_1d"] > 0.20)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["rsi_14_1d"] < 40.0)
            | (df["r_480_4h"] < -35.0)
            | (df["close"] > df["sup_level_1h"])
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["rsi_14_1d"] < 50.0)
            | (df["close"] > (df["high_max_12_1d"] * 0.50))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_14_4h"] < 40.0)
            | (df["rsi_14_1d"] < 40.0)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["r_480_4h"] < -35.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
          )
          long_entry_logic.append(
            (df["cti_20_1h"] < 0.7)
            | (df["rsi_14_1h"] < 50.0)
            | (df["cti_20_4h"] < 0.7)
            | (df["rsi_14_4h"] < 70.0)
            | (df["r_480_1h"] < -35.0)
            | (df["r_480_4h"] < -35.0)
            | (df["close"] < df["res_hlevel_4h"])
            | (df["close"] < df["res_hlevel_1d"])
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["rsi_14_1d"] < 50.0)
            | (df["r_480_1h"] < -40.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["hl_pct_change_6_1d"] > 0.20)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["ema_200_dec_48_1h"] == False)
          )
          long_entry_logic.append(
            (df["rsi_14_1h"] < 50.0)
            | (df["rsi_14_max_3_1h"] < 70.0)
            | (df["rsi_14_4h"] < 50.0)
            | (df["close"] > df["sup_level_1d"])
            | (df["ema_200_dec_4_1d"] == False)
            | (df["hl_pct_change_6_1d"] > 0.20)
          )
          long_entry_logic.append(
            (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["rsi_14_1d"] < 40.0)
            | (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["r_480_4h"] > -75.0)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["close"] > df["sup_level_4h"])
            | (df["close"] > df["sup_level_1d"])
            | (df["ema_200_dec_48_1h"] == False)
            | (df["hl_pct_change_6_1d"] > 0.20)
          )
          long_entry_logic.append(
            (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["rsi_14_1d"] < 40.0)
            | (df["r_480_4h"] > -75.0)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.03)
            | (df["not_downtrend_1h"])
            | (df["rsi_14"] < 40.0)
            | (df["rsi_14_15m"] < 46.0)
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["rsi_14_1d"] < 40.0)
            | (df["r_480_4h"] < -40.0)
          )
          long_entry_logic.append(
            (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["rsi_14_1d"] < 40.0)
            | (df["r_480_1h"] > -70.0)
            | (df["close"] < df["res_hlevel_1h"])
            | (df["ema_200_dec_48_1h"] == False)
            | (df["hl_pct_change_6_1d"] > 0.20)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.02)
            | (df["change_pct_1d"].shift(288) < 0.02)
            | (df["not_downtrend_1h"])
            | (df["close"] > df["sup_level_1h"])
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_4h"] < 0.02)
            | (df["top_wick_pct_4h"] < 0.02)
            | (df["rsi_14_1h"] < 50.0)
            | (df["cti_20_4h"] < 0.8)
            | (df["rsi_14_4h"] < 60.0)
            | (df["close"] < df["res_hlevel_1h"])
            | (df["close"] < df["res_hlevel_4h"])
            | (df["close"] < df["res_hlevel_1d"])
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["rsi_14_1d"] < 40.0)
            | (df["close"] > df["sup_level_4h"])
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["rsi_14_1h"] < 50.0)
            | (df["rsi_14_4h"] < 50.0)
            | (df["rsi_14_max_6_1h"] < 70.0)
            | (df["rsi_14_1d"] < 50.0)
            | (df["r_480_1h"] < -35.0)
            | (df["r_480_4h"] < -35.0)
            | (df["close"] < df["res_hlevel_4h"])
            | (df["close"] < df["res_hlevel_1d"])
          )
          long_entry_logic.append(
            (df["rsi_14"] < 42.0)
            | (df["rsi_14_15m"] < 46.0)
            | (df["rsi_14_1h"] < 50.0)
            | (df["rsi_14_4h"] < 50.0)
            | (df["rsi_14_1d"] < 50.0)
            | (df["close"] < df["res_hlevel_4h"])
            | (df["close"] < df["res_hlevel_1d"])
          )
          long_entry_logic.append(
            (df["rsi_14"] < 46.0)
            | (df["rsi_14_15m"] < 46.0)
            | (df["rsi_14_1h"] < 50.0)
            | (df["rsi_14_4h"] < 50.0)
            | (df["rsi_14_1d"] < 50.0)
            | (df["close"] < df["res_hlevel_1h"])
            | (df["close"] < df["res_hlevel_4h"])
          )
          long_entry_logic.append(
            (df["rsi_14"] < 46.0)
            | (df["rsi_14_1h"] < 46.0)
            | (df["rsi_14_4h"] < 46.0)
            | (df["rsi_14_1d"] < 46.0)
            | (df["r_480_4h"] < -35.0)
            | (df["close"] < df["res_hlevel_4h"])
          )
          long_entry_logic.append(
            (df["rsi_14"] < 46.0)
            | (df["rsi_14_15m"] < 46.0)
            | (df["rsi_14_1h"] < 50.0)
            | (df["rsi_14_4h"] < 50.0)
            | (df["rsi_14_1d"] < 50.0)
            | (df["r_480_1h"] < -40.0)
            | (df["close"] < df["res_hlevel_1d"])
          )
          long_entry_logic.append(
            (df["rsi_14"] < 46.0)
            | (df["rsi_14_15m"] < 40.0)
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["rsi_14_1d"] < 50.0)
            | (df["close"] < df["res_hlevel_4h"])
            | (df["close"] < df["res_hlevel_1d"])
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_14_15m"] < 46.0)
            | (df["rsi_14_1h"] < 46.0)
            | (df["rsi_14_4h"] < 46.0)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["rsi_14"] < 40.0)
            | (df["rsi_14_15m"] < 40.0)
            | (df["rsi_14_1h"] < 46.0)
            | (df["rsi_14_4h"] < 50.0)
            | (df["rsi_14_1d"] < 50.0)
            | (df["r_480_4h"] > -65.0)
            | (df["close"] < df["res_hlevel_4h"])
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14"] < 46.0)
            | (df["rsi_14_15m"] < 46.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["rsi_14"] < 40.0)
            | (df["rsi_14_15m"] < 46.0)
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["r_480_1h"] > -65.0)
            | (df["r_480_4h"] > -65.0)
            | (df["ema_200_dec_4_1d"] == False)
            | (df["close"] > (df["high_max_6_1d"] * 0.60))
          )
          long_entry_logic.append(
            (df["change_pct_4h"] > -0.01)
            | (df["change_pct_4h"].shift(48) < 0.01)
            | (df["rsi_14"] < 40.0)
            | (df["rsi_14_15m"] < 40.0)
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 46.0)
            | (df["rsi_14_1d"] < 46.0)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14"] < 40.0)
            | (df["rsi_14_15m"] < 46.0)
            | (df["r_480_1h"] > -65.0)
            | (df["r_480_4h"] > -75.0)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["close"] > df["sup_level_1h"])
            | (df["ema_200_dec_48_1h"] == False)
            | (df["close"] > (df["high_max_12_1d"] * 0.75))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14"] < 40.0)
            | (df["rsi_14_15m"] < 40.0)
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["r_480_1h"] > -60.0)
            | (df["close"] > df["sup_level_4h"])
            | (df["ema_200_dec_48_1h"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_4h"])
            | (df["rsi_14"] < 46.0)
            | (df["rsi_14_15m"] < 40.0)
            | (df["rsi_14_1h"] < 40.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
            | (df["ema_200_dec_48_1h"] == False)
            | (df["close"] > (df["high_max_6_1d"] * 0.80))
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.04)
            | (df["change_pct_1d"].shift(288) < 0.04)
            | (df["not_downtrend_1h"])
            | (df["rsi_14"] < 36.0)
            | (df["rsi_14_15m"] < 40.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["close"] > df["sup_level_4h"])
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14_15m"] < 40.0)
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 46.0)
            | (df["rsi_14_1d"] < 50.0)
            | (df["rsi_14_max_6_1d"] < 70.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
          )
          long_entry_logic.append(
            (df["change_pct_1d"] < 0.06)
            | (df["top_wick_pct_1d"] < 0.06)
            | (df["rsi_14"] < 36.0)
            | (df["rsi_14_15m"] < 46.0)
            | (df["rsi_14_1h"] < 46.0)
            | (df["rsi_14_4h"] < 50.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_1h"].shift(12) > -0.02)
            | (df["rsi_14"] < 46.0)
            | (df["rsi_14_15m"] < 46.0)
            | (df["rsi_14_1h"] < 46.0)
            | (df["rsi_14_max_6_1h"] < 70.0)
            | (df["rsi_14_4h"] < 46.0)
            | (df["rsi_14_1d"] < 46.0)
            | (df["close"] < df["res_hlevel_4h"])
            | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_14"] < 40.0)
            | (df["rsi_14_15m"] < 40.0)
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["rsi_14_1d"] < 46.0)
            | (df["r_480_1h"] > -70.0)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_14"] < 40.0)
            | (df["rsi_14_15m"] < 40.0)
            | (df["rsi_14_1h"] < 40.0)
            | (df["rsi_14_4h"] < 40.0)
            | (df["rsi_14_1d"] < 46.0)
            | (df["r_480_1h"] < -35.0)
          )
          long_entry_logic.append(
            (df["rsi_14"] < 40.0)
            | (df["rsi_14_15m"] < 40.0)
            | (df["rsi_14_1h"] < 46.0)
            | (df["rsi_14_max_6_1h"] < 70.0)
            | (df["cti_20_1h"] < 0.5)
            | (df["rsi_14_4h"] < 46.0)
            | (df["rsi_14_1d"] < 46.0)
            | (df["close"] < df["res_hlevel_1h"])
          )
          long_entry_logic.append(
            (df["rsi_14"] < 40.0)
            | (df["rsi_14_15m"] < 40.0)
            | (df["rsi_14_1h"] < 46.0)
            | (df["rsi_14_4h"] < 46.0)
            | (df["rsi_14_1d"] < 46.0)
            | (df["r_480_1h"] < -35.0)
            | (df["r_480_4h"] > -60.0)
          )
          long_entry_logic.append(
            (df["rsi_14"] < 46.0)
            | (df["rsi_14_15m"] < 46.0)
            | (df["rsi_14_1h"] < 46.0)
            | (df["rsi_14_4h"] < 46.0)
            | (df["rsi_14_1d"] < 46.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["is_downtrend_3_1d"] == False)
            | (df["rsi_14"] < 40.0)
            | (df["rsi_14_15m"] < 40.0)
            | (df["rsi_14_1d"] < 50.0)
            | (df["cti_20_1d"] < 0.7)
            | (df["rsi_14_max_6_1d"] < 65.0)
            | (df["r_480_1h"] < -35.0)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.04)
            | (df["rsi_14"] < 40.0)
            | (df["rsi_14_15m"] < 40.0)
            | (df["rsi_14_1d"] < 50.0)
            | (df["cti_20_1d"] < 0.7)
            | (df["rsi_14_max_6_1d"] < 75.0)
          )
          long_entry_logic.append(
            (df["rsi_14"] < 40.0)
            | (df["rsi_14_15m"] < 46.0)
            | (df["rsi_14_1h"] < 46.0)
            | (df["rsi_14_4h"] < 46.0)
            | (df["rsi_14_1d"] < 46.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["hl_pct_change_6_1d"] > 0.25)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_14"] < 46.0)
            | (df["rsi_14_15m"] < 46.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["ema_200_dec_48_1h"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["is_downtrend_3_1d"] == False)
            | (df["rsi_14"] < 46.0)
            | (df["rsi_14_15m"] < 46.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["ema_200_dec_48_1h"] == False)
          )

          # Logic
          long_entry_logic.append(df["rsi_14"] < self.entry_46_rsi_14_max.value)
          long_entry_logic.append(df["chandelier_dir_1h"].shift(1) < -0)
          long_entry_logic.append(df["chandelier_dir_1h"] > 0)
          long_entry_logic.append(df["close"] > df["zlma_50_1h"])
          long_entry_logic.append(df["ema_12"] < df["ema_26"])

        # Condition #47 - Quick mode (Long).
        if index == 47:
          # Protections
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * self.entry_47_close_max_12.value))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * self.entry_47_close_max_24.value))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * self.entry_47_close_max_48.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * self.entry_47_high_max_24_1h.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * self.entry_47_high_max_24_4h.value))
          long_entry_logic.append(df["close"] > (df["high_max_6_1d"] * self.entry_47_high_max_6_1d.value))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < self.entry_47_hl_pct_change_6_1h.value)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < self.entry_47_hl_pct_change_12_1h.value)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < self.entry_47_hl_pct_change_24_1h.value)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < self.entry_47_hl_pct_change_48_1h.value)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] > self.entry_47_rsi_3_min.value)
          long_entry_logic.append(df["rsi_3"] < self.entry_47_rsi_3_max.value)
          long_entry_logic.append(df["rsi_3_15m"] > self.entry_47_rsi_3_15m_min.value)
          long_entry_logic.append(df["rsi_3_1h"] > self.entry_47_rsi_3_1h_min.value)
          long_entry_logic.append(df["rsi_3_4h"] > self.entry_47_rsi_3_4h_min.value)
          long_entry_logic.append(df["rsi_3_1d"] > self.entry_47_rsi_3_1d_min.value)
          long_entry_logic.append(df["cti_20_1h"] < self.entry_47_cti_20_1h_max.value)
          long_entry_logic.append(df["rsi_14_1h"] < self.entry_47_rsi_14_1h_max.value)
          long_entry_logic.append(df["cti_20_4h"] < self.entry_47_cti_20_4h_max.value)
          long_entry_logic.append(df["rsi_14_4h"] < self.entry_47_rsi_14_4h_max.value)
          long_entry_logic.append(df["cti_20_1d"] < self.entry_47_cti_20_1d_max.value)
          long_entry_logic.append(df["rsi_14_1d"] < self.entry_47_rsi_14_1d_max.value)
          long_entry_logic.append(df["r_14_1h"] >= self.entry_47_r_14_1h_min.value)
          long_entry_logic.append(df["r_14_1h"] <= self.entry_47_r_14_1h_max.value)
          long_entry_logic.append(df["r_14_4h"] >= self.entry_47_r_14_4h_min.value)
          long_entry_logic.append(df["r_14_4h"] <= self.entry_47_r_14_4h_max.value)
          long_entry_logic.append(df["r_480_1h"] >= self.entry_47_r_480_1h_min.value)
          long_entry_logic.append(df["r_480_1h"] <= self.entry_47_r_480_1h_max.value)
          long_entry_logic.append(df["r_480_4h"] >= self.entry_47_r_480_4h_min.value)
          long_entry_logic.append(df["r_480_4h"] <= self.entry_47_r_480_4h_max.value)

          if self.entry_47_sup_level_1h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1h"])
          if self.entry_47_res_level_1h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_47_sup_level_4h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_4h"])
          if self.entry_47_res_level_4h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_4h"])
          if self.entry_47_sup_level_1d_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1d"])
          if self.entry_47_res_level_1d_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_47_ema_200_not_dec_1h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_48_1h"] == False)
          if self.entry_47_ema_200_not_dec_4h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_24_4h"] == False)
          if self.entry_47_ema_200_not_dec_1d_enabled.value:
            long_entry_logic.append(df["ema_200_dec_4_1d"] == False)
          if self.entry_47_not_downtrend_15m_enabled.value:
            long_entry_logic.append(df["not_downtrend_15m"])
          if self.entry_47_not_downtrend_1h_enabled.value:
            long_entry_logic.append(df["not_downtrend_1h"])
          if self.entry_47_not_downtrend_4h_enabled.value:
            long_entry_logic.append(df["not_downtrend_4h"])
          if self.entry_47_not_downtrend_1d_enabled.value:
            long_entry_logic.append(df["not_downtrend_1d"])

          long_entry_logic.append(
            (df["not_downtrend_1d"])
            | (df["r_480_1h"] > -80.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["close"] > (df["high_max_6_1d"] * 0.75))
          )
          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["not_downtrend_4h"])
            | (df["rsi_3_1h"] > 30.0)
            | (df["rsi_3_4h"] > 36.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > (df["high_max_6_1d"] * 0.80))
          )
          long_entry_logic.append(
            (df["ema_200_dec_48_1h"] == False)
            | (df["close"] > (df["high_max_6_1d"] * 0.70))
            | (df["close"] > (df["high_max_12_1d"] * 0.60))
          )
          long_entry_logic.append(
            (df["cti_20_4h"] < 0.5)
            | (df["rsi_14_4h"] < 70.0)
            | (df["close"] < df["res_hlevel_4h"])
            | (df["close"] < df["res_hlevel_1d"])
          )
          long_entry_logic.append(
            (df["rsi_3_1h"] > 30.0)
            | (df["cti_20_4h"] < 0.5)
            | (df["rsi_14_4h"] < 50.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_24_4h"] == False)
          )

          # Logic
          long_entry_logic.append(df["rsi_14"] > self.entry_47_rsi_14_min.value)
          long_entry_logic.append(df["rsi_14"] < self.entry_47_rsi_14_max.value)
          long_entry_logic.append(df["rsi_20"] > self.entry_47_rsi_20_min.value)
          long_entry_logic.append(df["rsi_20"] < self.entry_47_rsi_20_max.value)
          long_entry_logic.append(df["cti_20"] < self.entry_47_cti_20_max.value)
          long_entry_logic.append(df["chandelier_dir"].shift(1) < -0)
          long_entry_logic.append(df["chandelier_dir"] > 0)
          long_entry_logic.append(df["ema_12"] < (df["ema_26"] * self.entry_47_ema_offset.value))
          long_entry_logic.append(df["close"] < (df["high_max_12_1h"] * self.entry_47_high_max_12_1h_max.value))

        # Condition #48 - Quick mode (Long).
        if index == 48:
          # Protections
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * self.entry_48_close_max_12.value))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * self.entry_48_close_max_24.value))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * self.entry_48_close_max_48.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * self.entry_48_high_max_24_1h.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * self.entry_48_high_max_24_4h.value))
          long_entry_logic.append(df["close"] > (df["high_max_6_1d"] * self.entry_48_high_max_6_1d.value))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < self.entry_48_hl_pct_change_6_1h.value)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < self.entry_48_hl_pct_change_12_1h.value)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < self.entry_48_hl_pct_change_24_1h.value)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < self.entry_48_hl_pct_change_48_1h.value)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] > self.entry_48_rsi_3_min.value)
          long_entry_logic.append(df["rsi_3"] < self.entry_48_rsi_3_max.value)
          long_entry_logic.append(df["rsi_3_15m"] > self.entry_48_rsi_3_15m_min.value)
          long_entry_logic.append(df["rsi_3_1h"] > self.entry_48_rsi_3_1h_min.value)
          long_entry_logic.append(df["rsi_3_4h"] > self.entry_48_rsi_3_4h_min.value)
          long_entry_logic.append(df["rsi_3_1d"] > self.entry_48_rsi_3_1d_min.value)
          long_entry_logic.append(df["cti_20_1h"] < self.entry_48_cti_20_1h_max.value)
          long_entry_logic.append(df["rsi_14_1h"] < self.entry_48_rsi_14_1h_max.value)
          long_entry_logic.append(df["cti_20_4h"] < self.entry_48_cti_20_4h_max.value)
          long_entry_logic.append(df["rsi_14_4h"] < self.entry_48_rsi_14_4h_max.value)
          long_entry_logic.append(df["cti_20_1d"] < self.entry_48_cti_20_1d_max.value)
          long_entry_logic.append(df["rsi_14_1d"] < self.entry_48_rsi_14_1d_max.value)
          long_entry_logic.append(df["r_14_1h"] >= self.entry_48_r_14_1h_min.value)
          long_entry_logic.append(df["r_14_1h"] <= self.entry_48_r_14_1h_max.value)
          long_entry_logic.append(df["r_14_4h"] >= self.entry_48_r_14_4h_min.value)
          long_entry_logic.append(df["r_14_4h"] <= self.entry_48_r_14_4h_max.value)
          long_entry_logic.append(df["r_480_1h"] >= self.entry_48_r_480_1h_min.value)
          long_entry_logic.append(df["r_480_1h"] <= self.entry_48_r_480_1h_max.value)
          long_entry_logic.append(df["r_480_4h"] >= self.entry_48_r_480_4h_min.value)
          long_entry_logic.append(df["r_480_4h"] <= self.entry_48_r_480_4h_max.value)

          if self.entry_48_sup_level_1h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1h"])
          if self.entry_48_res_level_1h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_48_sup_level_4h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_4h"])
          if self.entry_48_res_level_4h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_4h"])
          if self.entry_48_sup_level_1d_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1d"])
          if self.entry_48_res_level_1d_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_48_ema_200_not_dec_1h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_48_1h"] == False)
          if self.entry_48_ema_200_not_dec_4h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_24_4h"] == False)
          if self.entry_48_ema_200_not_dec_1d_enabled.value:
            long_entry_logic.append(df["ema_200_dec_4_1d"] == False)
          if self.entry_48_not_downtrend_15m_enabled.value:
            long_entry_logic.append(df["not_downtrend_15m"])
          if self.entry_48_not_downtrend_1h_enabled.value:
            long_entry_logic.append(df["not_downtrend_1h"])
          if self.entry_48_not_downtrend_4h_enabled.value:
            long_entry_logic.append(df["not_downtrend_4h"])
          if self.entry_48_not_downtrend_1d_enabled.value:
            long_entry_logic.append(df["not_downtrend_1d"])
          if self.entry_48_ema_50_1h_over_ema_200_1h_enabled.value:
            long_entry_logic.append(df["ema_50_1h"] > df["ema_200_1h"])

          # Logic
          long_entry_logic.append(df["rsi_14"] < self.entry_48_rsi_14_max.value)
          long_entry_logic.append(df["cci_20"] < self.entry_48_cci_20_max.value)
          long_entry_logic.append(df["close"] < (df["sma_30"] * self.entry_48_sma_offset.value))
          long_entry_logic.append(((df["close"] - df["open_min_6"]) / df["open_min_6"]) > self.entry_48_inc_min.value)

        # Condition #49 - Quick mode (Long).
        if index == 49:
          # Protections
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * self.entry_49_close_max_12.value))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * self.entry_49_close_max_24.value))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * self.entry_49_close_max_48.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * self.entry_49_high_max_24_1h.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * self.entry_49_high_max_24_4h.value))
          long_entry_logic.append(df["close"] > (df["high_max_6_1d"] * self.entry_49_high_max_6_1d.value))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < self.entry_49_hl_pct_change_6_1h.value)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < self.entry_49_hl_pct_change_12_1h.value)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < self.entry_49_hl_pct_change_24_1h.value)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < self.entry_49_hl_pct_change_48_1h.value)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] > self.entry_49_rsi_3_min.value)
          long_entry_logic.append(df["rsi_3"] < self.entry_49_rsi_3_max.value)
          long_entry_logic.append(df["rsi_3_15m"] > self.entry_49_rsi_3_15m_min.value)
          long_entry_logic.append(df["rsi_3_1h"] > self.entry_49_rsi_3_1h_min.value)
          long_entry_logic.append(df["rsi_3_4h"] > self.entry_49_rsi_3_4h_min.value)
          long_entry_logic.append(df["rsi_3_1d"] > self.entry_49_rsi_3_1d_min.value)
          long_entry_logic.append(df["cti_20_1h"] < self.entry_49_cti_20_1h_max.value)
          long_entry_logic.append(df["rsi_14_1h"] < self.entry_49_rsi_14_1h_max.value)
          long_entry_logic.append(df["cti_20_4h"] < self.entry_49_cti_20_4h_max.value)
          long_entry_logic.append(df["rsi_14_4h"] < self.entry_49_rsi_14_4h_max.value)
          long_entry_logic.append(df["cti_20_1d"] < self.entry_49_cti_20_1d_max.value)
          long_entry_logic.append(df["rsi_14_1d"] < self.entry_49_rsi_14_1d_max.value)
          long_entry_logic.append(df["r_14_1h"] >= self.entry_49_r_14_1h_min.value)
          long_entry_logic.append(df["r_14_1h"] <= self.entry_49_r_14_1h_max.value)
          long_entry_logic.append(df["r_14_4h"] >= self.entry_49_r_14_4h_min.value)
          long_entry_logic.append(df["r_14_4h"] <= self.entry_49_r_14_4h_max.value)
          long_entry_logic.append(df["r_480_1h"] >= self.entry_49_r_480_1h_min.value)
          long_entry_logic.append(df["r_480_1h"] <= self.entry_49_r_480_1h_max.value)
          long_entry_logic.append(df["r_480_4h"] >= self.entry_49_r_480_4h_min.value)
          long_entry_logic.append(df["r_480_4h"] <= self.entry_49_r_480_4h_max.value)

          if self.entry_49_sup_level_1h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1h"])
          if self.entry_49_res_level_1h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_49_sup_level_4h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_4h"])
          if self.entry_49_res_level_4h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_4h"])
          if self.entry_49_sup_level_1d_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1d"])
          if self.entry_49_res_level_1d_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_49_ema_200_not_dec_1h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_48_1h"] == False)
          if self.entry_49_ema_200_not_dec_4h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_24_4h"] == False)
          if self.entry_49_ema_200_not_dec_1d_enabled.value:
            long_entry_logic.append(df["ema_200_dec_4_1d"] == False)
          if self.entry_49_not_downtrend_15m_enabled.value:
            long_entry_logic.append(df["not_downtrend_15m"])
          if self.entry_49_not_downtrend_1h_enabled.value:
            long_entry_logic.append(df["not_downtrend_1h"])
          if self.entry_49_not_downtrend_4h_enabled.value:
            long_entry_logic.append(df["not_downtrend_4h"])
          if self.entry_49_not_downtrend_1d_enabled.value:
            long_entry_logic.append(df["not_downtrend_1d"])
          if self.entry_49_ema_12_1h_over_ema_200_1h_enabled.value:
            long_entry_logic.append(df["ema_12_1h"] > df["ema_200_1h"])

          # Logic
          long_entry_logic.append(df["rsi_14"] < self.entry_49_rsi_14_max.value)
          # long_entry_logic.append(df["r_14"] < self.entry_49_r_14_max.value)
          # long_entry_logic.append(df["cci_20"] < self.entry_49_cci_20_max.value)
          # long_entry_logic.append(df["close"] < (df["sma_30"] * self.entry_49_sma_offset.value))
          long_entry_logic.append(
            ((df["close"] - df["open_min_12"]) / df["open_min_12"]) > self.entry_49_inc_min.value
          )

        # Condition #50 - Quick mode (Long)
        if index == 50:
          # Protections
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * self.entry_50_close_max_12.value))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * self.entry_50_close_max_24.value))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * self.entry_50_close_max_48.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * self.entry_50_high_max_24_1h.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * self.entry_50_high_max_24_4h.value))
          long_entry_logic.append(df["close"] > (df["high_max_6_1d"] * self.entry_50_high_max_6_1d.value))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < self.entry_50_hl_pct_change_6_1h.value)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < self.entry_50_hl_pct_change_12_1h.value)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < self.entry_50_hl_pct_change_24_1h.value)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < self.entry_50_hl_pct_change_48_1h.value)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] >= self.entry_50_rsi_3_min.value)
          long_entry_logic.append(df["rsi_3"] <= self.entry_50_rsi_3_max.value)
          long_entry_logic.append(df["rsi_3_15m"] >= self.entry_50_rsi_3_15m_min.value)
          long_entry_logic.append(df["rsi_3_1h"] >= self.entry_50_rsi_3_1h_min.value)
          long_entry_logic.append(df["rsi_3_4h"] >= self.entry_50_rsi_3_4h_min.value)
          long_entry_logic.append(df["rsi_3_1d"] >= self.entry_50_rsi_3_1d_min.value)
          long_entry_logic.append(df["cti_20_1h"] <= self.entry_50_cti_20_1h_max.value)
          long_entry_logic.append(df["rsi_14_1h"] <= self.entry_50_rsi_14_1h_max.value)
          long_entry_logic.append(df["cti_20_4h"] <= self.entry_50_cti_20_4h_max.value)
          long_entry_logic.append(df["rsi_14_4h"] <= self.entry_50_rsi_14_4h_max.value)
          long_entry_logic.append(df["cti_20_1d"] <= self.entry_50_cti_20_1d_max.value)
          long_entry_logic.append(df["rsi_14_1d"] <= self.entry_50_rsi_14_1d_max.value)
          long_entry_logic.append(df["r_14_1h"] >= self.entry_50_r_14_1h_min.value)
          long_entry_logic.append(df["r_14_1h"] <= self.entry_50_r_14_1h_max.value)
          long_entry_logic.append(df["r_14_4h"] >= self.entry_50_r_14_4h_min.value)
          long_entry_logic.append(df["r_14_4h"] <= self.entry_50_r_14_4h_max.value)
          long_entry_logic.append(df["r_480_1h"] >= self.entry_50_r_480_1h_min.value)
          long_entry_logic.append(df["r_480_1h"] <= self.entry_50_r_480_1h_max.value)
          long_entry_logic.append(df["r_480_4h"] >= self.entry_50_r_480_4h_min.value)
          long_entry_logic.append(df["r_480_4h"] <= self.entry_50_r_480_4h_max.value)

          if self.entry_50_sup_level_1h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1h"])
          if self.entry_50_res_level_1h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_50_sup_level_4h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_4h"])
          if self.entry_50_res_level_4h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_4h"])
          if self.entry_50_sup_level_1d_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1d"])
          if self.entry_50_res_level_1d_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_50_ema_200_not_dec_1h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_48_1h"] == False)
          if self.entry_50_ema_200_not_dec_4h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_24_4h"] == False)
          if self.entry_50_ema_200_not_dec_1d_enabled.value:
            long_entry_logic.append(df["ema_200_dec_4_1d"] == False)
          if self.entry_50_not_downtrend_15m_enabled.value:
            long_entry_logic.append(df["not_downtrend_15m"])
          if self.entry_50_not_downtrend_1h_enabled.value:
            long_entry_logic.append(df["not_downtrend_1h"])
          if self.entry_50_not_downtrend_4h_enabled.value:
            long_entry_logic.append(df["not_downtrend_4h"])
          if self.entry_50_not_downtrend_1d_enabled.value:
            long_entry_logic.append(df["not_downtrend_1d"])
          if self.entry_50_ema_12_1h_over_ema_200_1h_enabled.value:
            long_entry_logic.append(df["ema_12_1h"] > df["ema_200_1h"])

          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_3"] > 12.0)
            | (df["rsi_3_15m"] > 4.0)
          )

          # Logic
          long_entry_logic.append(df["close"] < (df["bb20_2_low"] * self.entry_50_bb_offset.value))
          long_entry_logic.append(df["ema_26"] > df["ema_12"])
          long_entry_logic.append((df["ema_26"] - df["ema_12"]) > (df["open"] * self.entry_50_ema_open_offset.value))
          long_entry_logic.append((df["ema_26"].shift() - df["ema_12"].shift()) > (df["open"] / 100.0))

        # Condition #51 - Quick mode (Long).
        if index == 51:
          # Protections
          long_entry_logic.append(df["protections_long_global"] == True)
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * 0.94))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * 0.92))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * 0.90))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * 0.88))
          long_entry_logic.append(df["close"] > (df["high_max_48_1h"] * 0.86))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.60)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.70)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.80)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.90)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] >= 6.0)
          long_entry_logic.append(df["rsi_3"] <= 50.0)
          long_entry_logic.append(df["rsi_3_15m"] >= 10.0)
          long_entry_logic.append(df["rsi_3_1h"] >= 10.0)
          long_entry_logic.append(df["rsi_3_4h"] >= 10.0)
          # long_entry_logic.append(df["rsi_3_1d"] >= 10.0)
          long_entry_logic.append(df["cti_20_1h"] <= 0.90)
          long_entry_logic.append(df["rsi_14_1h"] <= 80.0)
          long_entry_logic.append(df["cti_20_4h"] <= 0.90)
          long_entry_logic.append(df["rsi_14_4h"] <= 80.0)
          long_entry_logic.append(df["cti_20_1d"] <= 0.90)
          long_entry_logic.append(df["rsi_14_1d"] <= 80.0)

          long_entry_logic.append(df["zlma_50_dec_1h"] == False)

          # Logic
          long_entry_logic.append(df["rsi_14"] < 32.0)
          long_entry_logic.append(df["close"] < (df["ema_26"] * 0.968))
          long_entry_logic.append(df["close"] < (df["bb20_2_low"] * 0.999))

        # Condition #52 - Quick mode (Long).
        if index == 52:
          # Protections
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.60)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.70)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.80)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.90)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3_15m"] >= 4.0)
          long_entry_logic.append(df["rsi_3_1h"] >= 4.0)
          long_entry_logic.append(df["rsi_14_1h"] <= 70.0)
          long_entry_logic.append(df["rsi_14_4h"] <= 70.0)
          long_entry_logic.append(df["rsi_14_1d"] <= 75.0)

          long_entry_logic.append(
            (df["not_downtrend_1h"])
            | (df["rsi_3"] > 4.0)
            | (df["rsi_3_15m"] > 6.0)
            | (df["r_480_1h"] > -80.0)
            | (df["ema_200_dec_24_4h"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_1d"] > -0.04)
            | (df["top_wick_pct_1d"] < 0.04)
            | (df["not_downtrend_4h"])
            | (df["rsi_3"] > 12.0)
            | (df["rsi_3_15m"] > 12.0)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["rsi_3"] > 20.0)
            | (df["rsi_3_15m"] >= 20.0)
            | (df["rsi_14_max_6_1h"] < 70.0)
            | (df["ema_200_dec_4_1d"] == False)
          )

          # Logic
          long_entry_logic.append(df["rsi_14"] < 36.0)
          long_entry_logic.append(df["close"] < (df["bb20_2_low"] * 0.988))
          long_entry_logic.append(df["ema_26"] > df["ema_12"])
          long_entry_logic.append((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.028))
          long_entry_logic.append((df["ema_26"].shift() - df["ema_12"].shift()) > (df["open"] / 100.0))

        # Condition #53 - Quick mode (Long).
        if index == 53:
          # Protections
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.60)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.70)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.80)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.90)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3_15m"] >= 4.0)
          long_entry_logic.append(df["rsi_3_1h"] >= 4.0)
          long_entry_logic.append(df["rsi_14_1h"] <= 70.0)
          long_entry_logic.append(df["rsi_14_4h"] <= 70.0)
          long_entry_logic.append(df["rsi_14_1d"] <= 75.0)
          long_entry_logic.append(df["r_480_1h"] <= -20.0)
          long_entry_logic.append(df["r_480_4h"] <= -20.0)

          long_entry_logic.append(
            (df["close"] > (df["high_max_6_1d"] * 0.70))
            | (df["hl_pct_change_6_1d"] < 1.2)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["close"] > df["sup_level_1h"])
            | (df["close"] > df["sup_level_4h"])
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["rsi_3"] >= 12.0)
            | (df["rsi_14_15m"] < 50.0)
            | (df["rsi_14_max_6_1h"] < 75.0)
            | (df["close"] < df["res_hlevel_1h"])
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1h"])
            | (df["rsi_3_15m"] >= 16.0)
            | (df["rsi_14_max_6_1h"] < 70.0)
            | (df["close"] > df["sup_level_1h"])
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["rsi_14_15m"] < 40.0)
            | (df["rsi_14_max_6_4h"] < 70.0)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["rsi_14_15m"] < 40.0)
            | (df["rsi_14_max_6_1h"] < 70.0)
            | (df["ema_200_dec_24_4h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["not_downtrend_1d"])
            | (df["rsi_3_15m"] >= 20.0)
            | (df["r_480_4h"] > -70.0)
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["rsi_3_15m"] >= 20.0)
            | (df["rsi_14_max_6_1h"] < 70.0)
            | (df["rsi_14_max_6_4h"] < 70.0)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["rsi_3_15m"] >= 20.0)
            | (df["rsi_14_max_6_4h"] < 75.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["hl_pct_change_48_1h"] < 0.5)
          )
          long_entry_logic.append(
            (df["not_downtrend_15m"])
            | (df["rsi_3_15m"] >= 20.0)
            | (df["rsi_14_max_6_1h"] < 70.0)
            | (df["close"] < df["res_hlevel_1h"])
            | (df["close"] < df["res_hlevel_4h"])
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["change_pct_1h"] > -0.08)
            | (df["change_pct_1h"].shift(12) < 0.08)
            | (df["rsi_14_1h"].shift(12) < 70.0)
            | (df["r_480_4h"] < -35.0)
          )

          # Logic
          long_entry_logic.append(df["rsi_3"] < 46.0)
          long_entry_logic.append(df["rsi_14"] > 35.0)
          long_entry_logic.append(df["rsi_20"] < df["rsi_20"].shift(1))
          long_entry_logic.append(df["cti_20"] < -0.60)
          long_entry_logic.append(df["close"] < (df["sma_16"] * 0.956))

        # Condition #61 - Rebuy mode (Long).
        if index == 61:
          # Protections
          long_entry_logic.append(df["protections_long_global"] == True)
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["protections_long_rebuy"] == True)
          long_entry_logic.append(current_free_slots >= self.rebuy_mode_min_free_slots)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close_max_12"] < (df["close"] * 1.2))
          long_entry_logic.append(df["close_max_24"] < (df["close"] * 1.24))
          long_entry_logic.append(df["close_max_48"] < (df["close"] * 1.3))
          long_entry_logic.append(df["high_max_24_1h"] < (df["close"] * 1.5))
          long_entry_logic.append(df["high_max_24_4h"] < (df["close"] * 1.75))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.4)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.5)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.75)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.9)

          long_entry_logic.append(df["rsi_3_15m"] > 6.0)
          long_entry_logic.append(df["rsi_3_1h"] > 6.0)
          long_entry_logic.append(df["rsi_3_4h"] > 6.0)
          long_entry_logic.append(df["cti_20_15m"] < 0.9)
          long_entry_logic.append(df["cti_20_1h"] < 0.9)
          long_entry_logic.append(df["cti_20_4h"] < 0.9)
          long_entry_logic.append(df["cti_20_1d"] < 0.9)

          long_entry_logic.append((df["change_pct_1h"] > -0.01) | (df["cti_20_1h"] < 0.7) | (df["rsi_14_1h"] < 50.0))
          long_entry_logic.append(
            (df["not_downtrend_1h"]) | (df["not_downtrend_4h"]) | (df["rsi_3"] > 16.0) | (df["r_480_4h"] < -30.0)
          )

          # Logic
          long_entry_logic.append(df["rsi_14"] < 40.0)
          long_entry_logic.append(df["bb40_2_delta"].gt(df["close"] * 0.03))
          long_entry_logic.append(df["close_delta"].gt(df["close"] * 0.018))
          long_entry_logic.append(df["bb40_2_tail"].lt(df["bb40_2_delta"] * 0.4))
          long_entry_logic.append(df["close"].lt(df["bb40_2_low"].shift()))
          long_entry_logic.append(df["close"].le(df["close"].shift()))

        # Condition #62 - Rebuy mode (Long).
        if index == 62:
          # Protections
          long_entry_logic.append(df["protections_long_global"] == True)
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["protections_long_rebuy"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * 0.94))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * 0.92))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * 0.90))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * 0.88))
          long_entry_logic.append(df["close"] > (df["high_max_48_1h"] * 0.86))
          long_entry_logic.append(df["close"] > (df["high_max_6_1d"] * 0.84))
          long_entry_logic.append(df["close"] > (df["high_max_12_1d"] * 0.82))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.60)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.70)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.80)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.90)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] >= 30.0)
          long_entry_logic.append(df["rsi_3"] <= 50.0)
          long_entry_logic.append(df["rsi_3_15m"] >= 30.0)
          long_entry_logic.append(df["rsi_3_1h"] >= 30.0)
          long_entry_logic.append(df["rsi_3_4h"] >= 30.0)
          long_entry_logic.append(df["rsi_3_1d"] >= 30.0)
          long_entry_logic.append(df["cti_20_1h"] <= 0.90)
          long_entry_logic.append(df["rsi_14_1h"] <= 80.0)
          long_entry_logic.append(df["cti_20_4h"] <= 0.90)
          long_entry_logic.append(df["rsi_14_4h"] <= 80.0)
          long_entry_logic.append(df["cti_20_1d"] <= 0.90)
          long_entry_logic.append(df["rsi_14_1d"] <= 80.0)
          long_entry_logic.append(df["r_480_1h"] <= -5.0)
          long_entry_logic.append(df["r_480_4h"] <= -5.0)

          long_entry_logic.append(df["close"] > df["ema_200_1h"])

          long_entry_logic.append(
            (df["change_pct_1h"] > -0.01) | (df["ema_200_dec_24_4h"] == False) | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["r_480_1h"] < -30.0)
            | (df["r_480_4h"] < -25.0)
            | (df["close"] < df["res_hlevel_4h"])
            | (df["close"] < df["res_hlevel_1d"])
            | (df["ema_200_dec_4_1d"] == False)
            | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
          )
          long_entry_logic.append(
            (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["r_480_1h"] < -25.0)
            | (df["r_480_4h"] < -30.0)
            | (df["close"] < df["res_hlevel_4h"])
            | (df["close"] < df["res_hlevel_1d"])
            | (((df["close"] - df["low_min_48_1h"]) / df["low_min_48_1h"]) < (df["hl_pct_change_48_1h"] * 0.38))
          )
          long_entry_logic.append(
            (df["not_downtrend_1d"])
            | (df["rsi_14_15m"] < 40.0)
            | (df["rsi_14_1h"] < 46.0)
            | (df["rsi_14_4h"] < 50.0)
            | (df["close"] > df["sup_level_1h"])
            | (df["ema_200_dec_48_1h"] == False)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_14_15m"] < 40.0)
            | (df["rsi_14_1h"] < 50.0)
            | (df["rsi_14_4h"] < 50.0)
            | (df["rsi_14_4h"] < 50.0)
            | (df["r_480_1h"] < -35.0)
            | (df["ema_200_dec_4_1d"] == False)
          )
          long_entry_logic.append(
            (df["rsi_14"] > df["rsi_14"].shift(12))
            | (df["rsi_14_15m"] > df["rsi_14_15m"].shift(12))
            | (df["rsi_14_15m"] < 40.0)
            | (df["rsi_14_1h"] < 60.0)
            | (df["rsi_14_4h"] < 60.0)
            | (df["r_14_1h"] < -25.0)
            | (df["r_14_4h"] < -25.0)
            | (df["ema_200_dec_24_4h"] == False)
          )

          # Logic
          long_entry_logic.append(df["rsi_14"] < 36.0)
          long_entry_logic.append(df["close"] < (df["ema_26"] * 0.988))

        # Condition #81 - High profit mode (log)
        if index == 81:
          # Protections
          long_entry_logic.append(df["protections_long_global"] == True)
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.06)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.06)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * 0.80))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * 0.78))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * 0.76))
          long_entry_logic.append(df["close"] > (df["high_max_12_1h"] * 0.74))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * 0.72))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.60)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.70)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.80)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.90)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] >= 6.0)
          long_entry_logic.append(df["rsi_3"] <= 50.0)
          long_entry_logic.append(df["rsi_3_15m"] >= 10.0)
          long_entry_logic.append(df["rsi_3_1h"] >= 10.0)
          long_entry_logic.append(df["rsi_3_4h"] >= 10.0)
          long_entry_logic.append(df["cti_20_1h"] <= 0.90)
          long_entry_logic.append(df["rsi_14_1h"] <= 80.0)
          long_entry_logic.append(df["cti_20_4h"] <= 0.90)
          long_entry_logic.append(df["rsi_14_4h"] <= 80.0)
          long_entry_logic.append(df["cti_20_1d"] <= 0.90)
          long_entry_logic.append(df["rsi_14_1d"] <= 80.0)

          long_entry_logic.append(df["ema_200_dec_48_1h"] == False)

          # Logic
          long_entry_logic.append(df["rsi_14"] < 32.0)
          long_entry_logic.append(df["bb40_2_delta"].gt(df["close"] * 0.036))
          long_entry_logic.append(df["close_delta"].gt(df["close"] * 0.012))
          long_entry_logic.append(df["bb40_2_tail"].lt(df["bb40_2_delta"] * 0.4))
          long_entry_logic.append(df["close"].lt(df["bb40_2_low"].shift()))
          long_entry_logic.append(df["close"].le(df["close"].shift()))

        # Condition #82 - High profit mode (Long).
        if index == 82:
          # Protections
          long_entry_logic.append(df["protections_long_global"] == True)
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.06)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.06)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * 0.80))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * 0.78))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * 0.76))
          long_entry_logic.append(df["close"] > (df["high_max_12_1h"] * 0.74))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * 0.72))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.60)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.70)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.80)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.90)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] >= 4.0)
          long_entry_logic.append(df["rsi_3"] <= 50.0)
          long_entry_logic.append(df["rsi_3_15m"] >= 4.0)
          long_entry_logic.append(df["rsi_3_1h"] >= 10.0)
          long_entry_logic.append(df["rsi_3_4h"] >= 10.0)
          long_entry_logic.append(df["cti_20_1h"] <= 0.90)
          long_entry_logic.append(df["rsi_14_1h"] <= 80.0)
          long_entry_logic.append(df["cti_20_4h"] <= 0.90)
          long_entry_logic.append(df["rsi_14_4h"] <= 80.0)
          long_entry_logic.append(df["cti_20_1d"] <= 0.90)
          long_entry_logic.append(df["rsi_14_1d"] <= 80.0)

          long_entry_logic.append(df["ema_200_dec_48_1h"] == False)
          long_entry_logic.append(df["ema_26_1h"] > df["ema_200_1h"])
          long_entry_logic.append(df["ema_50_1h"] > df["ema_200_1h"])

          # Logic
          long_entry_logic.append(df["ema_26"] > df["ema_12"])
          long_entry_logic.append((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.024))
          long_entry_logic.append((df["ema_26"].shift() - df["ema_12"].shift()) > (df["open"] / 100))

        # Condition #101 - Long mode rapid
        if index == 101:
          # Protections
          long_entry_logic.append(df["protections_long_global"] == True)
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close_max_12"] < (df["close"] * 1.18))
          long_entry_logic.append(df["close_max_24"] < (df["close"] * 1.2))
          long_entry_logic.append(df["close_max_48"] < (df["close"] * 1.22))
          long_entry_logic.append(df["high_max_24_1h"] < (df["close"] * 1.24))
          long_entry_logic.append(df["high_max_48_1h"] < (df["close"] * 1.26))
          long_entry_logic.append(df["high_max_24_4h"] < (df["close"] * 1.5))
          long_entry_logic.append(df["high_max_12_1d"] < (df["close"] * 1.6))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.4)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.5)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.75)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.8)
          long_entry_logic.append(df["hl_pct_change_6_1d"] < 0.9)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] > 4.0)
          long_entry_logic.append(df["rsi_3_15m"] > 6.0)
          long_entry_logic.append(df["cti_20_1h"] < 0.8)
          long_entry_logic.append(df["rsi_14_1h"] < 80.0)
          long_entry_logic.append(df["cti_20_4h"] < 0.8)
          long_entry_logic.append(df["rsi_14_4h"] < 80.0)
          long_entry_logic.append(df["cti_20_1d"] < 0.8)
          long_entry_logic.append(df["rsi_14_1d"] < 80.0)

          # Logic
          long_entry_logic.append(df["rsi_14"] < 36.0)
          long_entry_logic.append(df["rsi_14"] < df["rsi_14"].shift(1))
          long_entry_logic.append(df["close"] < (df["sma_16"] * 0.956))
          long_entry_logic.append(df["cti_20_15m"] < -0.5)

        # Condition #102 - Long mode rapid
        if index == 102:
          # Protections
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * self.entry_102_close_max_12.value))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * self.entry_102_close_max_24.value))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * self.entry_102_close_max_48.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * self.entry_102_high_max_24_1h.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * self.entry_102_high_max_24_4h.value))
          long_entry_logic.append(df["close"] > (df["high_max_6_1d"] * self.entry_102_high_max_6_1d.value))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < self.entry_102_hl_pct_change_6_1h.value)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < self.entry_102_hl_pct_change_12_1h.value)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < self.entry_102_hl_pct_change_24_1h.value)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < self.entry_102_hl_pct_change_48_1h.value)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] > self.entry_102_rsi_3_min.value)
          long_entry_logic.append(df["rsi_3"] < self.entry_102_rsi_3_max.value)
          long_entry_logic.append(df["rsi_3_15m"] > self.entry_102_rsi_3_15m_min.value)
          long_entry_logic.append(df["rsi_3_1h"] > self.entry_102_rsi_3_1h_min.value)
          long_entry_logic.append(df["rsi_3_4h"] > self.entry_102_rsi_3_4h_min.value)
          long_entry_logic.append(df["rsi_3_1d"] > self.entry_102_rsi_3_1d_min.value)
          long_entry_logic.append(df["cti_20_1h"] < self.entry_102_cti_20_1h_max.value)
          long_entry_logic.append(df["rsi_14_1h"] < self.entry_102_rsi_14_1h_max.value)
          long_entry_logic.append(df["cti_20_4h"] < self.entry_102_cti_20_4h_max.value)
          long_entry_logic.append(df["rsi_14_4h"] < self.entry_102_rsi_14_4h_max.value)
          long_entry_logic.append(df["cti_20_1d"] < self.entry_102_cti_20_1d_max.value)
          long_entry_logic.append(df["rsi_14_1d"] < self.entry_102_rsi_14_1d_max.value)
          long_entry_logic.append(df["r_480_1h"] < self.entry_102_r_480_1h_max.value)
          long_entry_logic.append(df["r_480_4h"] < self.entry_102_r_480_4h_max.value)

          if self.entry_102_sup_level_1h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1h"])
          if self.entry_102_res_level_1h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_102_sup_level_4h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_4h"])
          if self.entry_102_res_level_4h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_4h"])
          if self.entry_102_sup_level_1d_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1d"])
          if self.entry_102_res_level_1d_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_102_ema_200_not_dec_1h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_48_1h"] == False)
          if self.entry_102_ema_200_not_dec_4h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_24_4h"] == False)
          if self.entry_102_ema_200_not_dec_1d_enabled.value:
            long_entry_logic.append(df["ema_200_dec_4_1d"] == False)
          if self.entry_102_not_downtrend_15m_enabled.value:
            long_entry_logic.append(df["not_downtrend_15m"])
          if self.entry_102_not_downtrend_1h_enabled.value:
            long_entry_logic.append(df["not_downtrend_1h"])
          if self.entry_102_not_downtrend_4h_enabled.value:
            long_entry_logic.append(df["not_downtrend_4h"])
          if self.entry_102_not_downtrend_1d_enabled.value:
            long_entry_logic.append(df["not_downtrend_1d"])

          # Logic
          long_entry_logic.append(df["rsi_14"] < self.entry_102_rsi_14_max.value)
          long_entry_logic.append(df["close"] < (df["ema_16"] * self.entry_102_ema_offset.value))
          long_entry_logic.append(df["close"] < (df["bb20_2_low"] * self.entry_102_bb_offset.value))

        # Condition #103 - Long mode rapid
        if index == 103:
          # Protections
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * self.entry_103_close_max_12.value))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * self.entry_103_close_max_24.value))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * self.entry_103_close_max_48.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * self.entry_103_high_max_24_1h.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * self.entry_103_high_max_24_4h.value))
          long_entry_logic.append(df["close"] > (df["high_max_6_1d"] * self.entry_103_high_max_6_1d.value))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < self.entry_103_hl_pct_change_6_1h.value)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < self.entry_103_hl_pct_change_12_1h.value)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < self.entry_103_hl_pct_change_24_1h.value)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < self.entry_103_hl_pct_change_48_1h.value)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] > self.entry_103_rsi_3_min.value)
          long_entry_logic.append(df["rsi_3"] < self.entry_103_rsi_3_max.value)
          long_entry_logic.append(df["rsi_3_15m"] > self.entry_103_rsi_3_15m_min.value)
          long_entry_logic.append(df["rsi_3_1h"] > self.entry_103_rsi_3_1h_min.value)
          long_entry_logic.append(df["rsi_3_4h"] > self.entry_103_rsi_3_4h_min.value)
          long_entry_logic.append(df["rsi_3_1d"] > self.entry_103_rsi_3_1d_min.value)
          long_entry_logic.append(df["cti_20_1h"] < self.entry_103_cti_20_1h_max.value)
          long_entry_logic.append(df["rsi_14_1h"] < self.entry_103_rsi_14_1h_max.value)
          long_entry_logic.append(df["cti_20_4h"] < self.entry_103_cti_20_4h_max.value)
          long_entry_logic.append(df["rsi_14_4h"] < self.entry_103_rsi_14_4h_max.value)
          long_entry_logic.append(df["cti_20_1d"] < self.entry_103_cti_20_1d_max.value)
          long_entry_logic.append(df["rsi_14_1d"] < self.entry_103_rsi_14_1d_max.value)
          long_entry_logic.append(df["r_14_1h"] >= self.entry_103_r_14_1h_min.value)
          long_entry_logic.append(df["r_14_1h"] <= self.entry_103_r_14_1h_max.value)
          long_entry_logic.append(df["r_14_4h"] >= self.entry_103_r_14_4h_min.value)
          long_entry_logic.append(df["r_14_4h"] <= self.entry_103_r_14_4h_max.value)
          long_entry_logic.append(df["r_480_1h"] >= self.entry_103_r_480_1h_min.value)
          long_entry_logic.append(df["r_480_1h"] <= self.entry_103_r_480_1h_max.value)
          long_entry_logic.append(df["r_480_4h"] >= self.entry_103_r_480_4h_min.value)
          long_entry_logic.append(df["r_480_4h"] <= self.entry_103_r_480_4h_max.value)

          if self.entry_103_sup_level_1h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1h"])
          if self.entry_103_res_level_1h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_103_sup_level_4h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_4h"])
          if self.entry_103_res_level_4h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_4h"])
          if self.entry_103_sup_level_1d_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1d"])
          if self.entry_103_res_level_1d_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_103_ema_200_not_dec_1h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_48_1h"] == False)
          if self.entry_103_ema_200_not_dec_4h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_24_4h"] == False)
          if self.entry_103_ema_200_not_dec_1d_enabled.value:
            long_entry_logic.append(df["ema_200_dec_4_1d"] == False)
          if self.entry_103_not_downtrend_15m_enabled.value:
            long_entry_logic.append(df["not_downtrend_15m"])
          if self.entry_103_not_downtrend_1h_enabled.value:
            long_entry_logic.append(df["not_downtrend_1h"])
          if self.entry_103_not_downtrend_4h_enabled.value:
            long_entry_logic.append(df["not_downtrend_4h"])
          if self.entry_103_not_downtrend_1d_enabled.value:
            long_entry_logic.append(df["not_downtrend_1d"])

          # Logic
          long_entry_logic.append(df["rsi_14"] > self.entry_103_rsi_14_min.value)
          long_entry_logic.append(df["close"] < (df["sma_16"] * self.entry_103_sma_offset.value))
          long_entry_logic.append(df["close"] < (df["bb20_2_mid"] * self.entry_103_bb_offset.value))

        # Condition #104 - Long mode rapid
        if index == 104:
          # Protections
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * self.entry_104_close_max_12.value))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * self.entry_104_close_max_24.value))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * self.entry_104_close_max_48.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * self.entry_104_high_max_24_1h.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * self.entry_104_high_max_24_4h.value))
          long_entry_logic.append(df["close"] > (df["high_max_6_1d"] * self.entry_104_high_max_6_1d.value))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < self.entry_104_hl_pct_change_6_1h.value)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < self.entry_104_hl_pct_change_12_1h.value)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < self.entry_104_hl_pct_change_24_1h.value)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < self.entry_104_hl_pct_change_48_1h.value)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] > self.entry_104_rsi_3_min.value)
          long_entry_logic.append(df["rsi_3"] < self.entry_104_rsi_3_max.value)
          long_entry_logic.append(df["rsi_3_15m"] > self.entry_104_rsi_3_15m_min.value)
          long_entry_logic.append(df["rsi_3_1h"] > self.entry_104_rsi_3_1h_min.value)
          long_entry_logic.append(df["rsi_3_4h"] > self.entry_104_rsi_3_4h_min.value)
          long_entry_logic.append(df["rsi_3_1d"] > self.entry_104_rsi_3_1d_min.value)
          long_entry_logic.append(df["cti_20_1h"] < self.entry_104_cti_20_1h_max.value)
          long_entry_logic.append(df["rsi_14_1h"] < self.entry_104_rsi_14_1h_max.value)
          long_entry_logic.append(df["cti_20_4h"] < self.entry_104_cti_20_4h_max.value)
          long_entry_logic.append(df["rsi_14_4h"] < self.entry_104_rsi_14_4h_max.value)
          long_entry_logic.append(df["cti_20_1d"] < self.entry_104_cti_20_1d_max.value)
          long_entry_logic.append(df["rsi_14_1d"] < self.entry_104_rsi_14_1d_max.value)
          long_entry_logic.append(df["r_14_1h"] <= self.entry_104_r_14_1h_max.value)
          long_entry_logic.append(df["r_14_4h"] <= self.entry_104_r_14_4h_max.value)
          long_entry_logic.append(df["r_480_1h"] <= self.entry_104_r_480_1h_max.value)
          long_entry_logic.append(df["r_480_4h"] <= self.entry_104_r_480_4h_max.value)

          if self.entry_104_sup_level_1h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1h"])
          if self.entry_104_res_level_1h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_104_sup_level_4h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_4h"])
          if self.entry_104_res_level_4h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_4h"])
          if self.entry_104_sup_level_1d_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1d"])
          if self.entry_104_res_level_1d_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_104_ema_200_not_dec_1h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_48_1h"] == False)
          if self.entry_104_ema_200_not_dec_4h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_24_4h"] == False)
          if self.entry_104_ema_200_not_dec_1d_enabled.value:
            long_entry_logic.append(df["ema_200_dec_4_1d"] == False)
          if self.entry_104_not_downtrend_15m_enabled.value:
            long_entry_logic.append(df["not_downtrend_15m"])
          if self.entry_104_not_downtrend_1h_enabled.value:
            long_entry_logic.append(df["not_downtrend_1h"])
          if self.entry_104_not_downtrend_4h_enabled.value:
            long_entry_logic.append(df["not_downtrend_4h"])
          if self.entry_104_not_downtrend_1d_enabled.value:
            long_entry_logic.append(df["not_downtrend_1d"])

          # Logic
          long_entry_logic.append(df["rsi_14"] > self.entry_104_rsi_14_min.value)
          long_entry_logic.append(df["rsi_14"] < self.entry_104_rsi_14_max.value)
          long_entry_logic.append(df["close"] < (df["sma_16"] * self.entry_104_sma_offset.value))

        # Condition #105 - Long mode rapid
        if index == 105:
          # Protections
          long_entry_logic.append(df["protections_long_global"] == True)
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["high_max_12_1d"] < (df["close"] * 1.6))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.5)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.75)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.8)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.9)
          long_entry_logic.append(df["hl_pct_change_6_1d"] < 1.9)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] > 6.0)
          long_entry_logic.append(df["rsi_3_15m"] > 6.0)
          long_entry_logic.append(df["rsi_3_1h"] > 6.0)
          long_entry_logic.append(df["rsi_3_4h"] > 6.0)
          long_entry_logic.append(df["cti_20_1h"] < 0.8)
          long_entry_logic.append(df["rsi_14_1h"] < 80.0)
          long_entry_logic.append(df["cti_20_4h"] < 0.9)
          long_entry_logic.append(df["rsi_14_4h"] < 80.0)
          long_entry_logic.append(df["cti_20_1d"] < 0.8)
          long_entry_logic.append(df["rsi_14_1d"] < 80.0)
          long_entry_logic.append(df["close"] > df["sup_level_4h"])
          long_entry_logic.append(df["close"] > df["sup_level_1d"])

          # Logic
          long_entry_logic.append(df["rsi_3"] < 60.0)
          long_entry_logic.append(df["rsi_14"] < 46.0)
          long_entry_logic.append(df["ema_26"] > df["ema_12"])
          long_entry_logic.append((df["ema_26"] - df["ema_12"]) > (df["open"] * 0.018))
          long_entry_logic.append((df["ema_26"].shift() - df["ema_12"].shift()) > (df["open"] / 100))

        # Condition #106 - Rapid mode (Long).
        if index == 106:
          # Protections
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * self.entry_106_close_max_12.value))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * self.entry_106_close_max_24.value))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * self.entry_106_close_max_48.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * self.entry_106_high_max_24_1h.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * self.entry_106_high_max_24_4h.value))
          long_entry_logic.append(df["close"] > (df["high_max_6_1d"] * self.entry_106_high_max_6_1d.value))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < self.entry_106_hl_pct_change_6_1h.value)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < self.entry_106_hl_pct_change_12_1h.value)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < self.entry_106_hl_pct_change_24_1h.value)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < self.entry_106_hl_pct_change_48_1h.value)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] > self.entry_106_rsi_3_min.value)
          long_entry_logic.append(df["rsi_3"] < self.entry_106_rsi_3_max.value)
          long_entry_logic.append(df["rsi_3_15m"] > self.entry_106_rsi_3_15m_min.value)
          long_entry_logic.append(df["rsi_3_1h"] > self.entry_106_rsi_3_1h_min.value)
          long_entry_logic.append(df["rsi_3_4h"] > self.entry_106_rsi_3_4h_min.value)
          long_entry_logic.append(df["rsi_3_1d"] > self.entry_106_rsi_3_1d_min.value)
          long_entry_logic.append(df["cti_20_1h"] < self.entry_106_cti_20_1h_max.value)
          long_entry_logic.append(df["rsi_14_1h"] < self.entry_106_rsi_14_1h_max.value)
          long_entry_logic.append(df["cti_20_4h"] < self.entry_106_cti_20_4h_max.value)
          long_entry_logic.append(df["rsi_14_4h"] < self.entry_106_rsi_14_4h_max.value)
          long_entry_logic.append(df["cti_20_1d"] < self.entry_106_cti_20_1d_max.value)
          long_entry_logic.append(df["rsi_14_1d"] < self.entry_106_rsi_14_1d_max.value)
          long_entry_logic.append(df["r_14_1h"] >= self.entry_106_r_14_1h_min.value)
          long_entry_logic.append(df["r_14_1h"] <= self.entry_106_r_14_1h_max.value)
          long_entry_logic.append(df["r_14_4h"] >= self.entry_106_r_14_4h_min.value)
          long_entry_logic.append(df["r_14_4h"] <= self.entry_106_r_14_4h_max.value)
          long_entry_logic.append(df["r_480_1h"] >= self.entry_106_r_480_1h_min.value)
          long_entry_logic.append(df["r_480_1h"] <= self.entry_106_r_480_1h_max.value)
          long_entry_logic.append(df["r_480_4h"] >= self.entry_106_r_480_4h_min.value)
          long_entry_logic.append(df["r_480_4h"] <= self.entry_106_r_480_4h_max.value)

          if self.entry_106_sup_level_1h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1h"])
          if self.entry_106_res_level_1h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_106_sup_level_4h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_4h"])
          if self.entry_106_res_level_4h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_4h"])
          if self.entry_106_sup_level_1d_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1d"])
          if self.entry_106_res_level_1d_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_106_ema_200_not_dec_1h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_48_1h"] == False)
          if self.entry_106_ema_200_not_dec_4h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_24_4h"] == False)
          if self.entry_106_ema_200_not_dec_1d_enabled.value:
            long_entry_logic.append(df["ema_200_dec_4_1d"] == False)
          if self.entry_106_not_downtrend_15m_enabled.value:
            long_entry_logic.append(df["not_downtrend_15m"])
          if self.entry_106_not_downtrend_1h_enabled.value:
            long_entry_logic.append(df["not_downtrend_1h"])
          if self.entry_106_not_downtrend_4h_enabled.value:
            long_entry_logic.append(df["not_downtrend_4h"])
          if self.entry_106_not_downtrend_1d_enabled.value:
            long_entry_logic.append(df["not_downtrend_1d"])

          # Logic
          long_entry_logic.append(df["cti_20"] < self.entry_106_cti_20_max.value)
          long_entry_logic.append(df["ewo_50_200"] < self.entry_106_ewo_50_200_max.value)
          long_entry_logic.append(df["close"] < (df["sma_30"] * self.entry_106_sma_offset.value))

        # Condition #107 - Rapid mode (Long)
        if index == 107:
          # Protections
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * self.entry_107_close_max_12.value))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * self.entry_107_close_max_24.value))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * self.entry_107_close_max_48.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * self.entry_107_high_max_24_1h.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * self.entry_107_high_max_24_4h.value))
          long_entry_logic.append(df["close"] > (df["high_max_6_1d"] * self.entry_107_high_max_6_1d.value))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < self.entry_107_hl_pct_change_6_1h.value)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < self.entry_107_hl_pct_change_12_1h.value)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < self.entry_107_hl_pct_change_24_1h.value)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < self.entry_107_hl_pct_change_48_1h.value)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] >= self.entry_107_rsi_3_min.value)
          long_entry_logic.append(df["rsi_3"] <= self.entry_107_rsi_3_max.value)
          long_entry_logic.append(df["rsi_3_15m"] >= self.entry_107_rsi_3_15m_min.value)
          long_entry_logic.append(df["rsi_3_1h"] >= self.entry_107_rsi_3_1h_min.value)
          long_entry_logic.append(df["rsi_3_4h"] >= self.entry_107_rsi_3_4h_min.value)
          long_entry_logic.append(df["rsi_3_1d"] >= self.entry_107_rsi_3_1d_min.value)
          long_entry_logic.append(df["cti_20_1h"] >= self.entry_107_cti_20_1h_min.value)
          long_entry_logic.append(df["cti_20_1h"] <= self.entry_107_cti_20_1h_max.value)
          long_entry_logic.append(df["rsi_14_1h"] <= self.entry_107_rsi_14_1h_max.value)
          long_entry_logic.append(df["cti_20_4h"] <= self.entry_107_cti_20_4h_max.value)
          long_entry_logic.append(df["rsi_14_4h"] <= self.entry_107_rsi_14_4h_max.value)
          long_entry_logic.append(df["cti_20_1d"] <= self.entry_107_cti_20_1d_max.value)
          long_entry_logic.append(df["rsi_14_1d"] <= self.entry_107_rsi_14_1d_max.value)
          long_entry_logic.append(df["r_14_1h"] >= self.entry_107_r_14_1h_min.value)
          long_entry_logic.append(df["r_14_1h"] <= self.entry_107_r_14_1h_max.value)
          long_entry_logic.append(df["r_14_4h"] >= self.entry_107_r_14_4h_min.value)
          long_entry_logic.append(df["r_14_4h"] <= self.entry_107_r_14_4h_max.value)
          long_entry_logic.append(df["r_480_1h"] >= self.entry_107_r_480_1h_min.value)
          long_entry_logic.append(df["r_480_1h"] <= self.entry_107_r_480_1h_max.value)
          long_entry_logic.append(df["r_480_4h"] >= self.entry_107_r_480_4h_min.value)
          long_entry_logic.append(df["r_480_4h"] <= self.entry_107_r_480_4h_max.value)

          if self.entry_107_sup_level_1h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1h"])
          if self.entry_107_res_level_1h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_107_sup_level_4h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_4h"])
          if self.entry_107_res_level_4h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_4h"])
          if self.entry_107_sup_level_1d_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1d"])
          if self.entry_107_res_level_1d_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_107_ema_200_not_dec_1h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_48_1h"] == False)
          if self.entry_107_ema_200_not_dec_4h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_24_4h"] == False)
          if self.entry_107_ema_200_not_dec_1d_enabled.value:
            long_entry_logic.append(df["ema_200_dec_4_1d"] == False)
          if self.entry_107_not_downtrend_15m_enabled.value:
            long_entry_logic.append(df["not_downtrend_15m"])
          if self.entry_107_not_downtrend_1h_enabled.value:
            long_entry_logic.append(df["not_downtrend_1h"])
          if self.entry_107_not_downtrend_4h_enabled.value:
            long_entry_logic.append(df["not_downtrend_4h"])
          if self.entry_107_not_downtrend_1d_enabled.value:
            long_entry_logic.append(df["not_downtrend_1d"])
          long_entry_logic.append(df["ema_200_1h"] > df["ema_200_1h"].shift(12))
          long_entry_logic.append(df["ema_200_1h"].shift(12) > df["ema_200_1h"].shift(24))

          # Logic
          long_entry_logic.append(df["bb40_2_low"].shift().gt(0.0))
          long_entry_logic.append(df["bb40_2_delta"].gt(df["close"] * self.entry_107_bb40_bbdelta_close.value))
          long_entry_logic.append(df["close_delta"].gt(df["close"] * self.entry_107_bb40_closedelta_close.value))
          long_entry_logic.append(df["bb40_2_tail"].lt(df["bb40_2_delta"] * self.entry_107_bb40_tail_bbdelta.value))
          long_entry_logic.append(df["close"].lt(df["bb40_2_low"].shift()))
          long_entry_logic.append(df["close"].le(df["close"].shift()))
          long_entry_logic.append(df["cti_20"] < self.entry_107_cti_20_max.value)
          long_entry_logic.append(df["r_480"] > self.entry_107_r_480_min.value)

        # Condition #108 - Rapid mode (Long)
        if index == 108:
          # Protections
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * self.entry_108_close_max_12.value))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * self.entry_108_close_max_24.value))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * self.entry_108_close_max_48.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * self.entry_108_high_max_24_1h.value))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * self.entry_108_high_max_24_4h.value))
          long_entry_logic.append(df["close"] > (df["high_max_6_1d"] * self.entry_108_high_max_6_1d.value))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < self.entry_108_hl_pct_change_6_1h.value)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < self.entry_108_hl_pct_change_12_1h.value)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < self.entry_108_hl_pct_change_24_1h.value)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < self.entry_108_hl_pct_change_48_1h.value)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] >= self.entry_108_rsi_3_min.value)
          long_entry_logic.append(df["rsi_3"] <= self.entry_108_rsi_3_max.value)
          long_entry_logic.append(df["rsi_3_15m"] >= self.entry_108_rsi_3_15m_min.value)
          long_entry_logic.append(df["rsi_3_1h"] >= self.entry_108_rsi_3_1h_min.value)
          long_entry_logic.append(df["rsi_3_4h"] >= self.entry_108_rsi_3_4h_min.value)
          long_entry_logic.append(df["rsi_3_1d"] >= self.entry_108_rsi_3_1d_min.value)
          long_entry_logic.append(df["cti_20_1h"] >= self.entry_108_cti_20_1h_min.value)
          long_entry_logic.append(df["cti_20_1h"] <= self.entry_108_cti_20_1h_max.value)
          long_entry_logic.append(df["rsi_14_1h"] <= self.entry_108_rsi_14_1h_max.value)
          long_entry_logic.append(df["cti_20_4h"] <= self.entry_108_cti_20_4h_max.value)
          long_entry_logic.append(df["rsi_14_4h"] <= self.entry_108_rsi_14_4h_max.value)
          long_entry_logic.append(df["cti_20_1d"] <= self.entry_108_cti_20_1d_max.value)
          long_entry_logic.append(df["rsi_14_1d"] <= self.entry_108_rsi_14_1d_max.value)
          long_entry_logic.append(df["r_14_1h"] >= self.entry_108_r_14_1h_min.value)
          long_entry_logic.append(df["r_14_1h"] <= self.entry_108_r_14_1h_max.value)
          long_entry_logic.append(df["r_14_4h"] >= self.entry_108_r_14_4h_min.value)
          long_entry_logic.append(df["r_14_4h"] <= self.entry_108_r_14_4h_max.value)
          long_entry_logic.append(df["r_480_1h"] >= self.entry_108_r_480_1h_min.value)
          long_entry_logic.append(df["r_480_1h"] <= self.entry_108_r_480_1h_max.value)
          long_entry_logic.append(df["r_480_4h"] >= self.entry_108_r_480_4h_min.value)
          long_entry_logic.append(df["r_480_4h"] <= self.entry_108_r_480_4h_max.value)

          if self.entry_108_sup_level_1h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1h"])
          if self.entry_108_res_level_1h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_108_sup_level_4h_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_4h"])
          if self.entry_108_res_level_4h_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_4h"])
          if self.entry_108_sup_level_1d_enabled.value:
            long_entry_logic.append(df["close"] > df["sup_level_1d"])
          if self.entry_108_res_level_1d_enabled.value:
            long_entry_logic.append(df["close"] < df["res_level_1h"])
          if self.entry_108_ema_200_not_dec_1h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_48_1h"] == False)
          if self.entry_108_ema_200_not_dec_4h_enabled.value:
            long_entry_logic.append(df["ema_200_dec_24_4h"] == False)
          if self.entry_108_ema_200_not_dec_1d_enabled.value:
            long_entry_logic.append(df["ema_200_dec_4_1d"] == False)
          if self.entry_108_not_downtrend_15m_enabled.value:
            long_entry_logic.append(df["not_downtrend_15m"])
          if self.entry_108_not_downtrend_1h_enabled.value:
            long_entry_logic.append(df["not_downtrend_1h"])
          if self.entry_108_not_downtrend_4h_enabled.value:
            long_entry_logic.append(df["not_downtrend_4h"])
          if self.entry_108_not_downtrend_1d_enabled.value:
            long_entry_logic.append(df["not_downtrend_1d"])

          # Logic
          long_entry_logic.append(df["rsi_14"] > self.entry_108_rsi_14_min.value)
          long_entry_logic.append(df["cti_20"] < self.entry_108_cti_20_max.value)
          long_entry_logic.append(df["r_14"] < self.entry_108_r_14_max.value)
          long_entry_logic.append(df["r_14"].shift(1) < self.entry_108_r_14_max.value)
          long_entry_logic.append(df["close"] < (df["bb20_2_low"] * self.entry_108_bb_offset.value))
          long_entry_logic.append(df["ema_26"] > df["ema_12"])
          long_entry_logic.append((df["ema_26"] - df["ema_12"]) > (df["open"] * self.entry_108_ema_open_offset.value))
          long_entry_logic.append((df["ema_26"].shift() - df["ema_12"].shift()) > (df["open"] / 100.0))

        # Condition #109 - Rapid mode (Long)
        if index == 109:
          # Protections
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.04)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.04)
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.60)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.70)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.80)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.90)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] >= 0.0)
          long_entry_logic.append(df["rsi_3"] <= 46.0)
          long_entry_logic.append(df["rsi_3_15m"] >= 6.0)
          long_entry_logic.append(df["rsi_3_1h"] >= 10.0)
          long_entry_logic.append(df["rsi_3_4h"] >= 10.0)

          # Logic
          long_entry_logic.append(df["cti_20"] < -0.75)
          long_entry_logic.append(df["r_14"] < -90.0)
          long_entry_logic.append(df["close"] < (df["bb20_2_low"] * 0.999))
          long_entry_logic.append(df["close"] < (df["ema_20"] * 0.960))

        # Condition #110 - Rapid mode (Long).
        if index == 110:
          # Protections
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.03)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * 0.84))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * 0.80))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * 0.76))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * 0.70))
          long_entry_logic.append(df["close"] > (df["high_max_24_4h"] * 0.66))
          long_entry_logic.append(df["close"] > (df["high_max_6_1d"] * 0.60))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.60)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.70)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.80)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.90)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] > 2.0)
          long_entry_logic.append(df["rsi_3"] < 60.0)
          long_entry_logic.append(df["rsi_3_15m"] > 8.0)
          long_entry_logic.append(df["rsi_3_1h"] > 12.0)
          long_entry_logic.append(df["rsi_3_4h"] > 12.0)
          long_entry_logic.append(df["rsi_3_1d"] > 12.0)

          # Logic
          long_entry_logic.append(df["rsi_14"] < 36.0)
          long_entry_logic.append(df["cti_20"] < -0.75)
          long_entry_logic.append(df["ewo_50_200"] < -6.0)
          long_entry_logic.append(df["close"] < (df["ema_20"] * 0.988))

        # Condition #120 - Grind mode (Long).
        if index == 120:
          # Protections
          long_entry_logic.append(num_open_grind_mode < self.grind_mode_max_slots)
          long_entry_logic.append(is_pair_grind_mode)
          long_entry_logic.append(df["protections_long_global"] == True)
          long_entry_logic.append(df["global_protections_long_pump"] == True)
          long_entry_logic.append(df["global_protections_long_dump"] == True)
          long_entry_logic.append(df["protections_long_rebuy"] == True)
          long_entry_logic.append(df["btc_pct_close_max_24_5m"] < 0.03)
          long_entry_logic.append(df["btc_pct_close_max_72_5m"] < 0.06)
          long_entry_logic.append(df["close"] > (df["close_max_12"] * 0.94))
          long_entry_logic.append(df["close"] > (df["close_max_24"] * 0.92))
          long_entry_logic.append(df["close"] > (df["close_max_48"] * 0.90))
          long_entry_logic.append(df["close"] > (df["high_max_12_1h"] * 0.88))
          long_entry_logic.append(df["close"] > (df["high_max_24_1h"] * 0.86))
          long_entry_logic.append(df["close"] > (df["high_max_6_1d"] * 0.84))
          long_entry_logic.append(df["close"] > (df["high_max_12_1d"] * 0.80))
          long_entry_logic.append(df["hl_pct_change_6_1h"] < 0.30)
          long_entry_logic.append(df["hl_pct_change_12_1h"] < 0.40)
          long_entry_logic.append(df["hl_pct_change_24_1h"] < 0.50)
          long_entry_logic.append(df["hl_pct_change_48_1h"] < 0.60)
          long_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          long_entry_logic.append(df["rsi_3"] >= 30.0)
          long_entry_logic.append(df["rsi_3"] <= 60.0)
          long_entry_logic.append(df["rsi_3_15m"] >= 30.0)
          long_entry_logic.append(df["rsi_3_1h"] >= 30.0)
          long_entry_logic.append(df["rsi_3_4h"] >= 30.0)
          long_entry_logic.append(df["rsi_3_1d"] >= 30.0)
          long_entry_logic.append(df["cti_20_1h"] <= 0.70)
          long_entry_logic.append(df["rsi_14_1h"] <= 60.0)
          long_entry_logic.append(df["cti_20_4h"] <= 0.70)
          long_entry_logic.append(df["rsi_14_4h"] <= 60.0)
          long_entry_logic.append(df["cti_20_1d"] <= 0.70)
          long_entry_logic.append(df["rsi_14_1d"] <= 70.0)

          long_entry_logic.append(df["ema_200_dec_4_1d"] == False)

          # Logic
          long_entry_logic.append(df["rsi_14"] < 42.0)
          long_entry_logic.append(df["ema_12"] < df["ema_26"])
          long_entry_logic.append(df["ha_close"] > df["ha_open"])

        # Long Entry Conditions Ends Here

        long_entry_logic.append(df["volume"] > 0)
        item_long_entry = reduce(lambda x, y: x & y, long_entry_logic)
        df.loc[item_long_entry, "enter_tag"] += f"{index} "
        long_entry_conditions.append(item_long_entry)
        df.loc[:, "enter_long"] = item_long_entry

    if long_entry_conditions:
      df.loc[:, "enter_long"] = reduce(lambda x, y: x | y, long_entry_conditions)

    #   ______  __    __  ______  _______ ________        ________ __    __ ________ ________ _______
    #  /      \|  \  |  \/      \|       |        \      |        |  \  |  |        |        |       \
    # |  $$$$$$| $$  | $|  $$$$$$| $$$$$$$\$$$$$$$$      | $$$$$$$| $$\ | $$\$$$$$$$| $$$$$$$| $$$$$$$\
    # | $$___\$| $$__| $| $$  | $| $$__| $$ | $$         | $$__   | $$$\| $$  | $$  | $$__   | $$__| $$
    #  \$$    \| $$    $| $$  | $| $$    $$ | $$         | $$  \  | $$$$\ $$  | $$  | $$  \  | $$    $$
    #  _\$$$$$$| $$$$$$$| $$  | $| $$$$$$$\ | $$         | $$$$$  | $$\$$ $$  | $$  | $$$$$  | $$$$$$$\
    # |  \__| $| $$  | $| $$__/ $| $$  | $$ | $$         | $$_____| $$ \$$$$  | $$  | $$_____| $$  | $$
    #  \$$    $| $$  | $$\$$    $| $$  | $$ | $$         | $$     | $$  \$$$  | $$  | $$     | $$  | $$
    #   \$$$$$$ \$$   \$$ \$$$$$$ \$$   \$$  \$$          \$$$$$$$$\$$   \$$   \$$   \$$$$$$$$\$$   \$$
    #

    for enabled_short_entry_signal in self.short_entry_signal_params:
      short_index = int(enabled_short_entry_signal.split("_")[3])
      item_short_buy_protection_list = [True]
      if not self.config["runmode"].value in ("live", "dry_run"):
        if self.has_bt_agefilter:
          item_short_buy_protection_list.append(df["bt_agefilter_ok"])
      else:
        if self.has_downtime_protection:
          item_short_buy_protection_list.append(df["live_data_ok"])
      if self.short_entry_signal_params[f"{enabled_short_entry_signal}"]:
        # Short Entry Conditions Starts Here
        # -----------------------------------------------------------------------------------------
        short_entry_logic = []
        short_entry_logic.append(reduce(lambda x, y: x & y, item_short_buy_protection_list))

        # Condition #500 - Normal mode (Short).
        if short_index == 500:
          # Protections
          short_entry_logic.append(df["protections_short_global"] == True)
          short_entry_logic.append(df["global_protections_short_pump"] == True)
          short_entry_logic.append(df["global_protections_short_dump"] == True)
          short_entry_logic.append(df["hl_pct_change_6_1h"] < 0.90)
          short_entry_logic.append(df["hl_pct_change_12_1h"] < 1.00)
          short_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          short_entry_logic.append(df["rsi_3_15m"] <= 96.0)
          short_entry_logic.append(df["rsi_3_1h"] <= 96.0)

          # Logic
          short_entry_logic.append(df["ema_12"] > df["ema_26"])
          short_entry_logic.append((df["ema_12"] - df["ema_26"]) > (df["open"] * 0.028))
          short_entry_logic.append((df["ema_12"] - df["ema_26"]) > (df["open"] / 100.0))
          short_entry_logic.append(df["close"] > (df["bb20_2_upp"] * 1.012))
          short_entry_logic.append(df["rsi_14"] > 64.0)

        # Condition #501 - Normal mode (Short)
        if short_index == 501:
          # Protections
          short_entry_logic.append(df["protections_short_global"] == True)
          short_entry_logic.append(df["global_protections_short_pump"] == True)
          short_entry_logic.append(df["global_protections_short_dump"] == True)
          short_entry_logic.append(df["num_empty_288"] < allowed_empty_candles)

          short_entry_logic.append(df["rsi_3"] <= 98.0)
          short_entry_logic.append(df["rsi_3"] >= 54.0)
          short_entry_logic.append(df["rsi_3_15m"] <= 88.0)
          short_entry_logic.append(df["rsi_3_1h"] <= 88.0)
          short_entry_logic.append(df["rsi_3_4h"] <= 88.0)
          short_entry_logic.append(df["rsi_14_1d"] > 15.0)
          short_entry_logic.append(df["r_14_4h"] > -84.0)

          # Logic
          short_entry_logic.append(df["cti_20"] > 0.75)
          short_entry_logic.append(df["r_14"] > -10.0)
          short_entry_logic.append(df["close"] > (df["ema_20"] * 1.040))
          short_entry_logic.append(df["close_15m"] > (df["ema_12_15m"] * 1.020))

        # Short Entry Conditions Ends Here

        short_entry_logic.append(df["volume"] > 0)
        item_short_entry = reduce(lambda x, y: x & y, short_entry_logic)
        df.loc[item_short_entry, "enter_tag"] += f"{short_index} "
        short_entry_conditions.append(item_short_entry)
        df.loc[:, "enter_short"] = item_short_entry

    if short_entry_conditions:
      df.loc[:, "enter_short"] = reduce(lambda x, y: x | y, short_entry_conditions)

    return df

  ###############################################################################################

  # COMMON FUNCTIONS FOR BOTH LONG AND SHORT SIDE ENDS HERE

  ###############################################################################################

  #  /$$        /$$$$$$  /$$   /$$  /$$$$$$         /$$$$$$  /$$$$$$ /$$$$$$$  /$$$$$$$$
  # | $$       /$$__  $$| $$$ | $$ /$$__  $$       /$$__  $$|_  $$_/| $$__  $$| $$_____/
  # | $$      | $$  \ $$| $$$$| $$| $$  \__/      | $$  \__/  | $$  | $$  \ $$| $$
  # | $$      | $$  | $$| $$ $$ $$| $$ /$$$$      |  $$$$$$   | $$  | $$  | $$| $$$$$
  # | $$      | $$  | $$| $$  $$$$| $$|_  $$       \____  $$  | $$  | $$  | $$| $$__/
  # | $$      | $$  | $$| $$\  $$$| $$  \ $$       /$$  \ $$  | $$  | $$  | $$| $$
  # | $$$$$$$$|  $$$$$$/| $$ \  $$|  $$$$$$/      |  $$$$$$/ /$$$$$$| $$$$$$$/| $$$$$$$$
  # |________/ \______/ |__/  \__/ \______/        \______/ |______/|_______/ |________/

  # Long Side Functions for handling long orders
  # ---------------------------------------------------------------------------------------------

  #
  #  /$$        /$$$$$$  /$$   /$$  /$$$$$$        /$$$$$$$$ /$$   /$$ /$$$$$$ /$$$$$$$$
  # | $$       /$$__  $$| $$$ | $$ /$$__  $$      | $$_____/| $$  / $$|_  $$_/|__  $$__/
  # | $$      | $$  \ $$| $$$$| $$| $$  \__/      | $$      |  $$/ $$/  | $$     | $$
  # | $$      | $$  | $$| $$ $$ $$| $$ /$$$$      | $$$$$    \  $$$$/   | $$     | $$
  # | $$      | $$  | $$| $$  $$$$| $$|_  $$      | $$__/     >$$  $$   | $$     | $$
  # | $$      | $$  | $$| $$\  $$$| $$  \ $$      | $$       /$$/\  $$  | $$     | $$
  # | $$$$$$$$|  $$$$$$/| $$ \  $$|  $$$$$$/      | $$$$$$$$| $$  \ $$ /$$$$$$   | $$
  # |________/ \______/ |__/  \__/ \______/       |________/|__/  |__/|______/   |__/
  #

  ###############################################################################################

  # LONG EXIT FUNCTIONS STARTS HERE

  ###############################################################################################

  # Long Exit Normal
  # ---------------------------------------------------------------------------------------------
  def long_exit_normal(
    self,
    pair: str,
    current_rate: float,
    profit_stake: float,
    profit_ratio: float,
    profit_current_stake_ratio: float,
    profit_init_ratio: float,
    max_profit: float,
    max_loss: float,
    filled_entries,
    filled_exits,
    last_candle,
    previous_candle_1,
    previous_candle_2,
    previous_candle_3,
    previous_candle_4,
    previous_candle_5,
    trade: "Trade",
    current_time: "datetime",
    enter_tags,
  ) -> tuple:
    sell = False

    # Original sell signals
    sell, signal_name = self.long_exit_signals(
      self.long_normal_mode_name,
      profit_init_ratio,
      max_profit,
      max_loss,
      last_candle,
      previous_candle_1,
      previous_candle_2,
      previous_candle_3,
      previous_candle_4,
      previous_candle_5,
      trade,
      current_time,
      enter_tags,
    )

    # Main sell signals
    if not sell:
      sell, signal_name = self.long_exit_main(
        self.long_normal_mode_name,
        profit_init_ratio,
        max_profit,
        max_loss,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )

    # Williams %R based sells
    if not sell:
      sell, signal_name = self.long_exit_williams_r(
        self.long_normal_mode_name,
        profit_init_ratio,
        max_profit,
        max_loss,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )

    # Downtrend/descending based sells
    if not sell:
      sell, signal_name = self.long_exit_dec(
        self.long_normal_mode_name,
        profit_init_ratio,
        max_profit,
        max_loss,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )

    # Stoplosses
    if not sell:
      sell, signal_name = self.long_exit_stoploss(
        self.long_normal_mode_name,
        current_rate,
        profit_stake,
        profit_ratio,
        profit_current_stake_ratio,
        profit_init_ratio,
        max_profit,
        max_loss,
        filled_entries,
        filled_exits,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )

    # Profit Target Signal
    # Check if pair exist on target_profit_cache
    if self.target_profit_cache is not None and pair in self.target_profit_cache.data:
      previous_rate = self.target_profit_cache.data[pair]["rate"]
      previous_profit = self.target_profit_cache.data[pair]["profit"]
      previous_sell_reason = self.target_profit_cache.data[pair]["sell_reason"]
      previous_time_profit_reached = datetime.fromisoformat(self.target_profit_cache.data[pair]["time_profit_reached"])

      sell_max, signal_name_max = self.exit_profit_target(
        self.long_normal_mode_name,
        pair,
        trade,
        current_time,
        current_rate,
        profit_stake,
        profit_ratio,
        profit_current_stake_ratio,
        profit_init_ratio,
        last_candle,
        previous_candle_1,
        previous_rate,
        previous_profit,
        previous_sell_reason,
        previous_time_profit_reached,
        enter_tags,
      )
      if sell_max and signal_name_max is not None:
        return True, f"{signal_name_max}_m"
      if previous_sell_reason in [f"exit_{self.long_normal_mode_name}_stoploss_u_e"]:
        if profit_ratio > (previous_profit + 0.005):
          mark_pair, mark_signal = self.mark_profit_target(
            self.long_normal_mode_name,
            pair,
            True,
            previous_sell_reason,
            trade,
            current_time,
            current_rate,
            profit_ratio,
            last_candle,
            previous_candle_1,
          )
          if mark_pair:
            self._set_profit_target(pair, mark_signal, current_rate, profit_ratio, current_time)
      elif (profit_init_ratio > (previous_profit + 0.001)) and (
        previous_sell_reason not in [f"exit_{self.long_normal_mode_name}_stoploss_doom"]
      ):
        # Update the target, raise it.
        mark_pair, mark_signal = self.mark_profit_target(
          self.long_normal_mode_name,
          pair,
          True,
          previous_sell_reason,
          trade,
          current_time,
          current_rate,
          profit_init_ratio,
          last_candle,
          previous_candle_1,
        )
        if mark_pair:
          self._set_profit_target(pair, mark_signal, current_rate, profit_init_ratio, current_time)

    # Add the pair to the list, if a sell triggered and conditions met
    if sell and signal_name is not None:
      previous_profit = None
      if self.target_profit_cache is not None and pair in self.target_profit_cache.data:
        previous_profit = self.target_profit_cache.data[pair]["profit"]
      if signal_name in [
        f"exit_{self.long_normal_mode_name}_stoploss_doom",
        f"exit_{self.long_normal_mode_name}_stoploss_u_e",
      ]:
        mark_pair, mark_signal = self.mark_profit_target(
          self.long_normal_mode_name,
          pair,
          sell,
          signal_name,
          trade,
          current_time,
          current_rate,
          profit_ratio,
          last_candle,
          previous_candle_1,
        )
        if mark_pair:
          self._set_profit_target(pair, mark_signal, current_rate, profit_ratio, current_time)
        else:
          # Just sell it, without maximize
          return True, f"{signal_name}"
      elif (previous_profit is None) or (previous_profit < profit_init_ratio):
        mark_pair, mark_signal = self.mark_profit_target(
          self.long_normal_mode_name,
          pair,
          sell,
          signal_name,
          trade,
          current_time,
          current_rate,
          profit_init_ratio,
          last_candle,
          previous_candle_1,
        )
        if mark_pair:
          self._set_profit_target(pair, mark_signal, current_rate, profit_init_ratio, current_time)
        else:
          # Just sell it, without maximize
          return True, f"{signal_name}"
    else:
      if profit_init_ratio >= self.profit_max_thresholds[0]:
        previous_profit = None
        if self.target_profit_cache is not None and pair in self.target_profit_cache.data:
          previous_profit = self.target_profit_cache.data[pair]["profit"]
        if (previous_profit is None) or (previous_profit < profit_init_ratio):
          mark_signal = f"exit_profit_{self.long_normal_mode_name}_max"
          self._set_profit_target(pair, mark_signal, current_rate, profit_init_ratio, current_time)

    if signal_name not in [
      f"exit_profit_{self.long_normal_mode_name}_max",
      f"exit_{self.long_normal_mode_name}_stoploss_doom",
      f"exit_{self.long_normal_mode_name}_stoploss_u_e",
    ]:
      if sell and (signal_name is not None):
        return True, f"{signal_name}"

    return False, None

  # Long Exit Pump
  # ---------------------------------------------------------------------------------------------
  def long_exit_pump(
    self,
    pair: str,
    current_rate: float,
    profit_stake: float,
    profit_ratio: float,
    profit_current_stake_ratio: float,
    profit_init_ratio: float,
    max_profit: float,
    max_loss: float,
    filled_entries,
    filled_exits,
    last_candle,
    previous_candle_1,
    previous_candle_2,
    previous_candle_3,
    previous_candle_4,
    previous_candle_5,
    trade: "Trade",
    current_time: "datetime",
    enter_tags,
  ) -> tuple:
    sell = False

    # Original sell signals
    sell, signal_name = self.long_exit_signals(
      self.long_pump_mode_name,
      profit_init_ratio,
      max_profit,
      max_loss,
      last_candle,
      previous_candle_1,
      previous_candle_2,
      previous_candle_3,
      previous_candle_4,
      previous_candle_5,
      trade,
      current_time,
      enter_tags,
    )

    # Main sell signals
    if not sell:
      sell, signal_name = self.long_exit_main(
        self.long_pump_mode_name,
        profit_init_ratio,
        max_profit,
        max_loss,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )

    # Williams %R based sells
    if not sell:
      sell, signal_name = self.long_exit_williams_r(
        self.long_pump_mode_name,
        profit_init_ratio,
        max_profit,
        max_loss,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )

    # Downtrend/descending based sells
    if not sell:
      sell, signal_name = self.long_exit_dec(
        self.long_pump_mode_name,
        profit_init_ratio,
        max_profit,
        max_loss,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )

    # Stoplosses
    if not sell:
      sell, signal_name = self.long_exit_stoploss(
        self.long_pump_mode_name,
        current_rate,
        profit_stake,
        profit_ratio,
        profit_current_stake_ratio,
        profit_init_ratio,
        max_profit,
        max_loss,
        filled_entries,
        filled_exits,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )

    # Profit Target Signal
    # Check if pair exist on target_profit_cache
    if self.target_profit_cache is not None and pair in self.target_profit_cache.data:
      previous_rate = self.target_profit_cache.data[pair]["rate"]
      previous_profit = self.target_profit_cache.data[pair]["profit"]
      previous_sell_reason = self.target_profit_cache.data[pair]["sell_reason"]
      previous_time_profit_reached = datetime.fromisoformat(self.target_profit_cache.data[pair]["time_profit_reached"])

      sell_max, signal_name_max = self.exit_profit_target(
        self.long_pump_mode_name,
        pair,
        trade,
        current_time,
        current_rate,
        profit_stake,
        profit_ratio,
        profit_current_stake_ratio,
        profit_init_ratio,
        last_candle,
        previous_candle_1,
        previous_rate,
        previous_profit,
        previous_sell_reason,
        previous_time_profit_reached,
        enter_tags,
      )
      if sell_max and signal_name_max is not None:
        return True, f"{signal_name_max}_m"
      if previous_sell_reason in [f"exit_{self.long_pump_mode_name}_stoploss_u_e"]:
        if profit_ratio > (previous_profit + 0.005):
          mark_pair, mark_signal = self.mark_profit_target(
            self.long_pump_mode_name,
            pair,
            True,
            previous_sell_reason,
            trade,
            current_time,
            current_rate,
            profit_ratio,
            last_candle,
            previous_candle_1,
          )
          if mark_pair:
            self._set_profit_target(pair, mark_signal, current_rate, profit_ratio, current_time)
      elif (profit_init_ratio > (previous_profit + 0.001)) and (
        previous_sell_reason not in [f"exit_{self.long_pump_mode_name}_stoploss_doom"]
      ):
        # Update the target, raise it.
        mark_pair, mark_signal = self.mark_profit_target(
          self.long_pump_mode_name,
          pair,
          True,
          previous_sell_reason,
          trade,
          current_time,
          current_rate,
          profit_init_ratio,
          last_candle,
          previous_candle_1,
        )
        if mark_pair:
          self._set_profit_target(pair, mark_signal, current_rate, profit_init_ratio, current_time)

    # Add the pair to the list, if a sell triggered and conditions met
    if sell and signal_name is not None:
      previous_profit = None
      if self.target_profit_cache is not None and pair in self.target_profit_cache.data:
        previous_profit = self.target_profit_cache.data[pair]["profit"]
      if signal_name in [
        f"exit_{self.long_pump_mode_name}_stoploss_doom",
        f"exit_{self.long_pump_mode_name}_stoploss_u_e",
      ]:
        mark_pair, mark_signal = self.mark_profit_target(
          self.long_pump_mode_name,
          pair,
          sell,
          signal_name,
          trade,
          current_time,
          current_rate,
          profit_ratio,
          last_candle,
          previous_candle_1,
        )
        if mark_pair:
          self._set_profit_target(pair, mark_signal, current_rate, profit_ratio, current_time)
        else:
          # Just sell it, without maximize
          return True, f"{signal_name}"
      elif (previous_profit is None) or (previous_profit < profit_init_ratio):
        mark_pair, mark_signal = self.mark_profit_target(
          self.long_pump_mode_name,
          pair,
          sell,
          signal_name,
          trade,
          current_time,
          current_rate,
          profit_init_ratio,
          last_candle,
          previous_candle_1,
        )
        if mark_pair:
          self._set_profit_target(pair, mark_signal, current_rate, profit_init_ratio, current_time)
        else:
          # Just sell it, without maximize
          return True, f"{signal_name}"
    else:
      if profit_init_ratio >= self.profit_max_thresholds[2]:
        previous_profit = None
        if self.target_profit_cache is not None and pair in self.target_profit_cache.data:
          previous_profit = self.target_profit_cache.data[pair]["profit"]
        if (previous_profit is None) or (previous_profit < profit_init_ratio):
          mark_signal = f"exit_profit_{self.long_pump_mode_name}_max"
          self._set_profit_target(pair, mark_signal, current_rate, profit_init_ratio, current_time)

    if signal_name not in [
      f"exit_profit_{self.long_pump_mode_name}_max",
      f"exit_{self.long_pump_mode_name}_stoploss_doom",
      f"exit_{self.long_pump_mode_name}_stoploss_u_e",
    ]:
      if sell and (signal_name is not None):
        return True, f"{signal_name}"

    return False, None

  # Long Exit Signals
  # ---------------------------------------------------------------------------------------------
  def long_exit_quick(
    self,
    pair: str,
    current_rate: float,
    profit_stake: float,
    profit_ratio: float,
    profit_current_stake_ratio: float,
    profit_init_ratio: float,
    max_profit: float,
    max_loss: float,
    filled_entries,
    filled_exits,
    last_candle,
    previous_candle_1,
    previous_candle_2,
    previous_candle_3,
    previous_candle_4,
    previous_candle_5,
    trade: "Trade",
    current_time: "datetime",
    enter_tags,
  ) -> tuple:
    sell = False

    # Original sell signals
    sell, signal_name = self.long_exit_signals(
      self.long_quick_mode_name,
      profit_init_ratio,
      max_profit,
      max_loss,
      last_candle,
      previous_candle_1,
      previous_candle_2,
      previous_candle_3,
      previous_candle_4,
      previous_candle_5,
      trade,
      current_time,
      enter_tags,
    )

    # Main sell signals
    if not sell:
      sell, signal_name = self.long_exit_main(
        self.long_quick_mode_name,
        profit_init_ratio,
        max_profit,
        max_loss,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )

    # Williams %R based sells
    if not sell:
      sell, signal_name = self.long_exit_williams_r(
        self.long_quick_mode_name,
        profit_init_ratio,
        max_profit,
        max_loss,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )

    # Downtrend/descending based sells
    if not sell:
      sell, signal_name = self.long_exit_dec(
        self.long_quick_mode_name,
        profit_init_ratio,
        max_profit,
        max_loss,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )

    # Stoplosses
    if not sell:
      sell, signal_name = self.long_exit_stoploss(
        self.long_quick_mode_name,
        current_rate,
        profit_stake,
        profit_ratio,
        profit_current_stake_ratio,
        profit_init_ratio,
        max_profit,
        max_loss,
        filled_entries,
        filled_exits,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )

    # Extra sell logic
    if not sell:
      if (0.09 >= profit_init_ratio > 0.02) and (last_candle["rsi_14"] > 78.0):
        sell, signal_name = True, f"exit_{self.long_quick_mode_name}_q_1"

      if (0.09 >= profit_init_ratio > 0.02) and (last_candle["cti_20"] > 0.95):
        sell, signal_name = True, f"exit_{self.long_quick_mode_name}_q_2"

      if (0.09 >= profit_init_ratio > 0.02) and (last_candle["r_14"] >= -0.1):
        sell, signal_name = True, f"exit_{self.long_quick_mode_name}_q_3"

    # Profit Target Signal
    # Check if pair exist on target_profit_cache
    if self.target_profit_cache is not None and pair in self.target_profit_cache.data:
      previous_rate = self.target_profit_cache.data[pair]["rate"]
      previous_profit = self.target_profit_cache.data[pair]["profit"]
      previous_sell_reason = self.target_profit_cache.data[pair]["sell_reason"]
      previous_time_profit_reached = datetime.fromisoformat(self.target_profit_cache.data[pair]["time_profit_reached"])

      sell_max, signal_name_max = self.exit_profit_target(
        self.long_quick_mode_name,
        pair,
        trade,
        current_time,
        current_rate,
        profit_stake,
        profit_ratio,
        profit_current_stake_ratio,
        profit_init_ratio,
        last_candle,
        previous_candle_1,
        previous_rate,
        previous_profit,
        previous_sell_reason,
        previous_time_profit_reached,
        enter_tags,
      )
      if sell_max and signal_name_max is not None:
        return True, f"{signal_name_max}_m"
      if previous_sell_reason in [f"exit_{self.long_quick_mode_name}_stoploss_u_e"]:
        if profit_ratio > (previous_profit + 0.005):
          mark_pair, mark_signal = self.mark_profit_target(
            self.long_quick_mode_name,
            pair,
            True,
            previous_sell_reason,
            trade,
            current_time,
            current_rate,
            profit_ratio,
            last_candle,
            previous_candle_1,
          )
          if mark_pair:
            self._set_profit_target(pair, mark_signal, current_rate, profit_ratio, current_time)
      elif (profit_init_ratio > (previous_profit + 0.001)) and (
        previous_sell_reason not in [f"exit_{self.long_quick_mode_name}_stoploss_doom"]
      ):
        # Update the target, raise it.
        mark_pair, mark_signal = self.mark_profit_target(
          self.long_quick_mode_name,
          pair,
          True,
          previous_sell_reason,
          trade,
          current_time,
          current_rate,
          profit_init_ratio,
          last_candle,
          previous_candle_1,
        )
        if mark_pair:
          self._set_profit_target(pair, mark_signal, current_rate, profit_init_ratio, current_time)

    # Add the pair to the list, if a sell triggered and conditions met
    if sell and signal_name is not None:
      previous_profit = None
      if self.target_profit_cache is not None and pair in self.target_profit_cache.data:
        previous_profit = self.target_profit_cache.data[pair]["profit"]
      if signal_name in [
        f"exit_{self.long_quick_mode_name}_stoploss_doom",
        f"exit_{self.long_quick_mode_name}_stoploss_u_e",
      ]:
        mark_pair, mark_signal = self.mark_profit_target(
          self.long_quick_mode_name,
          pair,
          sell,
          signal_name,
          trade,
          current_time,
          current_rate,
          profit_ratio,
          last_candle,
          previous_candle_1,
        )
        if mark_pair:
          self._set_profit_target(pair, mark_signal, current_rate, profit_ratio, current_time)
        else:
          # Just sell it, without maximize
          return True, f"{signal_name}"
      elif (previous_profit is None) or (previous_profit < profit_init_ratio):
        mark_pair, mark_signal = self.mark_profit_target(
          self.long_quick_mode_name,
          pair,
          sell,
          signal_name,
          trade,
          current_time,
          current_rate,
          profit_init_ratio,
          last_candle,
          previous_candle_1,
        )
        if mark_pair:
          self._set_profit_target(pair, mark_signal, current_rate, profit_init_ratio, current_time)
        else:
          # Just sell it, without maximize
          return True, f"{signal_name}"
    else:
      if profit_init_ratio >= self.profit_max_thresholds[4]:
        previous_profit = None
        if self.target_profit_cache is not None and pair in self.target_profit_cache.data:
          previous_profit = self.target_profit_cache.data[pair]["profit"]
        if (previous_profit is None) or (previous_profit < profit_init_ratio):
          mark_signal = f"exit_profit_{self.long_quick_mode_name}_max"
          self._set_profit_target(pair, mark_signal, current_rate, profit_init_ratio, current_time)

    if signal_name not in [
      f"exit_profit_{self.long_quick_mode_name}_max",
      f"exit_{self.long_quick_mode_name}_stoploss_doom",
      f"exit_{self.long_quick_mode_name}_stoploss_u_e",
    ]:
      if sell and (signal_name is not None):
        return True, f"{signal_name}"

    return False, None

  # Long Exit Rebuy
  # ---------------------------------------------------------------------------------------------
  def long_exit_rebuy(
    self,
    pair: str,
    current_rate: float,
    profit_stake: float,
    profit_ratio: float,
    profit_current_stake_ratio: float,
    profit_init_ratio: float,
    max_profit: float,
    max_loss: float,
    filled_entries,
    filled_exits,
    last_candle,
    previous_candle_1,
    previous_candle_2,
    previous_candle_3,
    previous_candle_4,
    previous_candle_5,
    trade: "Trade",
    current_time: "datetime",
    enter_tags,
  ) -> tuple:
    sell = False

    # Original sell signals
    sell, signal_name = self.long_exit_signals(
      self.long_rebuy_mode_name,
      profit_init_ratio,
      max_profit,
      max_loss,
      last_candle,
      previous_candle_1,
      previous_candle_2,
      previous_candle_3,
      previous_candle_4,
      previous_candle_5,
      trade,
      current_time,
      enter_tags,
    )

    # Main sell signals
    if not sell:
      sell, signal_name = self.long_exit_main(
        self.long_rebuy_mode_name,
        profit_init_ratio,
        max_profit,
        max_loss,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )

    # Williams %R based sells
    if not sell:
      sell, signal_name = self.long_exit_williams_r(
        self.long_rebuy_mode_name,
        profit_init_ratio,
        max_profit,
        max_loss,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )

    # Downtrend/descending based sells
    if not sell:
      sell, signal_name = self.long_exit_dec(
        self.long_rebuy_mode_name,
        profit_init_ratio,
        max_profit,
        max_loss,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )

    # Stoplosses
    if not sell:
      if profit_stake < -(
        filled_entries[0].cost
        * (self.stop_threshold_futures_rebuy if self.is_futures_mode else self.stop_threshold_spot_rebuy)
        / (trade.leverage if self.is_futures_mode else 1.0)
      ):
        sell, signal_name = True, f"exit_{self.long_rebuy_mode_name}_stoploss_doom"

    # Profit Target Signal
    # Check if pair exist on target_profit_cache
    if self.target_profit_cache is not None and pair in self.target_profit_cache.data:
      previous_rate = self.target_profit_cache.data[pair]["rate"]
      previous_profit = self.target_profit_cache.data[pair]["profit"]
      previous_sell_reason = self.target_profit_cache.data[pair]["sell_reason"]
      previous_time_profit_reached = datetime.fromisoformat(self.target_profit_cache.data[pair]["time_profit_reached"])

      sell_max, signal_name_max = self.exit_profit_target(
        self.long_rebuy_mode_name,
        pair,
        trade,
        current_time,
        current_rate,
        profit_stake,
        profit_ratio,
        profit_current_stake_ratio,
        profit_init_ratio,
        last_candle,
        previous_candle_1,
        previous_rate,
        previous_profit,
        previous_sell_reason,
        previous_time_profit_reached,
        enter_tags,
      )
      if sell_max and signal_name_max is not None:
        return True, f"{signal_name_max}_m"
      if previous_sell_reason in [f"exit_{self.long_rebuy_mode_name}_stoploss_u_e"]:
        if profit_ratio > (previous_profit + 0.005):
          mark_pair, mark_signal = self.mark_profit_target(
            self.long_rebuy_mode_name,
            pair,
            True,
            previous_sell_reason,
            trade,
            current_time,
            current_rate,
            profit_ratio,
            last_candle,
            previous_candle_1,
          )
          if mark_pair:
            self._set_profit_target(pair, mark_signal, current_rate, profit_ratio, current_time)
      elif (profit_init_ratio > (previous_profit + 0.001)) and (
        previous_sell_reason not in [f"exit_{self.long_rebuy_mode_name}_stoploss_doom"]
      ):
        # Update the target, raise it.
        mark_pair, mark_signal = self.mark_profit_target(
          self.long_rebuy_mode_name,
          pair,
          True,
          previous_sell_reason,
          trade,
          current_time,
          current_rate,
          profit_init_ratio,
          last_candle,
          previous_candle_1,
        )
        if mark_pair:
          self._set_profit_target(pair, mark_signal, current_rate, profit_init_ratio, current_time)

    # Add the pair to the list, if a sell triggered and conditions met
    if sell and signal_name is not None:
      previous_profit = None
      if self.target_profit_cache is not None and pair in self.target_profit_cache.data:
        previous_profit = self.target_profit_cache.data[pair]["profit"]
      if signal_name in [
        f"exit_{self.long_rebuy_mode_name}_stoploss_doom",
        f"exit_{self.long_rebuy_mode_name}_stoploss_u_e",
      ]:
        mark_pair, mark_signal = self.mark_profit_target(
          self.long_rebuy_mode_name,
          pair,
          sell,
          signal_name,
          trade,
          current_time,
          current_rate,
          profit_ratio,
          last_candle,
          previous_candle_1,
        )
        if mark_pair:
          self._set_profit_target(pair, mark_signal, current_rate, profit_ratio, current_time)
        else:
          # Just sell it, without maximize
          return True, f"{signal_name}"
      elif (previous_profit is None) or (previous_profit < profit_init_ratio):
        mark_pair, mark_signal = self.mark_profit_target(
          self.long_rebuy_mode_name,
          pair,
          sell,
          signal_name,
          trade,
          current_time,
          current_rate,
          profit_init_ratio,
          last_candle,
          previous_candle_1,
        )
        if mark_pair:
          self._set_profit_target(pair, mark_signal, current_rate, profit_init_ratio, current_time)
        else:
          # Just sell it, without maximize
          return True, f"{signal_name}"
    else:
      if profit_init_ratio >= self.profit_max_thresholds[6]:
        previous_profit = None
        if self.target_profit_cache is not None and pair in self.target_profit_cache.data:
          previous_profit = self.target_profit_cache.data[pair]["profit"]
        if (previous_profit is None) or (previous_profit < profit_init_ratio):
          mark_signal = f"exit_profit_{self.long_rebuy_mode_name}_max"
          self._set_profit_target(pair, mark_signal, current_rate, profit_init_ratio, current_time)

    if signal_name not in [f"exit_profit_{self.long_rebuy_mode_name}_max"]:
      if sell and (signal_name is not None):
        return True, f"{signal_name}"

    return False, None

  # Long Exit High Profit
  # ---------------------------------------------------------------------------------------------
  def long_exit_high_profit(
    self,
    pair: str,
    current_rate: float,
    profit_stake: float,
    profit_ratio: float,
    profit_current_stake_ratio: float,
    profit_init_ratio: float,
    max_profit: float,
    max_loss: float,
    filled_entries,
    filled_exits,
    last_candle,
    previous_candle_1,
    previous_candle_2,
    previous_candle_3,
    previous_candle_4,
    previous_candle_5,
    trade: "Trade",
    current_time: "datetime",
    enter_tags,
  ) -> tuple:
    sell = False

    # Original sell signals
    sell, signal_name = self.long_exit_signals(
      self.long_high_profit_mode_name,
      profit_init_ratio,
      max_profit,
      max_loss,
      last_candle,
      previous_candle_1,
      previous_candle_2,
      previous_candle_3,
      previous_candle_4,
      previous_candle_5,
      trade,
      current_time,
      enter_tags,
    )

    # Main sell signals
    if not sell:
      sell, signal_name = self.long_exit_main(
        self.long_high_profit_mode_name,
        profit_init_ratio,
        max_profit,
        max_loss,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )

    # Williams %R based sells
    if not sell:
      sell, signal_name = self.long_exit_williams_r(
        self.long_high_profit_mode_name,
        profit_init_ratio,
        max_profit,
        max_loss,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )

    # Stoplosses
    if not sell:
      sell, signal_name = self.long_exit_stoploss(
        self.long_high_profit_mode_name,
        current_rate,
        profit_stake,
        profit_ratio,
        profit_current_stake_ratio,
        profit_init_ratio,
        max_profit,
        max_loss,
        filled_entries,
        filled_exits,
        last_candle,
        previous_candle_1,
        previous_candle_2,
        previous_candle_3,
        previous_candle_4,
        previous_candle_5,
        trade,
        current_time,
        enter_tags,
      )
    # Profit Target Signal
    # Check if pair exist on target_profit_cache
    if self.target_profit_cache is not None and pair in self.target_profit_cache.data:
      previous_rate = self.target_profit_cache.data[pair]["rate"]
      previous_profit = self.target_profit_cache.data[pair]["profit"]
      previous_sell_reason = self.target_profit_cache.data[pair]["sell_reason"]
      previous_time_profit_reached = datetime.fromisoformat(self.target_profit_cache.data[pair]["time_profit_reached"])

      sell_max, signal_name_max = self.exit_profit_target(
        self.long_high_profit_mode_name,
        pair,
        trade,
        current_time,
        current_rate,
        profit_stake,
        profit_ratio,
        profit_current_stake_ratio,
        profit_init_ratio,
        last_candle,
        previous_candle_1,
        previous_rate,
        previous_profit,
        previous_sell_reason,
        previous_time_profit_reached,
        enter_tags,
      )
      if sell_max and signal_name_max is not None:
        return True, f"{signal_name_max}_m"
      if previous_sell_reason in [f"exit_{self.long_high_profit_mode_name}_stoploss_u_e"]:
        if profit_ratio > (previous_profit + 0.005):
          mark_pair, mark_signal = self.mark_profit_target(
            self.long_high_profit_mode_name,
            pair,
            True,
            previous_sell_reason,
            trade,
            current_time,
            current_rate,
            profit_ratio,
            last_candle,
            previous_candle_1,
          )
          if mark_pair:
            self._set_profit_target(pair, mark_signal, current_rate, profit_ratio, current_time)
      elif (profit_init_ratio > (previous_profit + 0.001)) and (
        previous_sell_reason not in [f"exit_{self.long_high_profit_mode_name}_stoploss_doom"]
      ):
        # Update the target, raise it.
        mark_pair, mark_signal = self.mark_profit_target(
          self.long_high_profit_mode_name,
          pair,
          True,
          previous_sell_reason,
          trade,
          current_time,
          current_rate,
          profit_init_ratio,
          last_candle,
          previous_candle_1,
        )
        if mark_pair:
          self._set_profit_target(pair, mark_signal, current_rate, profit_init_ratio, current_time)

    # Add the pair to the list, if a sell triggered and conditions met
    if sell and signal_name is not None:
      previous_profit = None
      if self.target_profit_cache is not