Timeframe
5m
Direction
Long Only
Stoploss
-99.0%
Trailing Stop
No
ROI
0m: 1000.0%
Interface Version
2
Startup Candles
N/A
Indicators
23
freqtrade/freqtrade-strategies
Strategy 003 author@: Gerald Lonlas github@: https://github.com/freqtrade/freqtrade-strategies
# -*- coding: utf-8 -*-
import logging
import pathlib
import rapidjson
import freqtrade.vendor.qtpylib.indicators as qtpylib
import numpy as np
import talib.abstract as ta
from freqtrade.misc import json_load
from freqtrade.strategy.interface import IStrategy
from freqtrade.strategy import merge_informative_pair, timeframe_to_minutes
from freqtrade.strategy import DecimalParameter, IntParameter, CategoricalParameter
from freqtrade.exchange import timeframe_to_prev_date
from pandas import DataFrame, Series, concat
from functools import reduce
import math
from freqtrade.persistence import Trade
from datetime import datetime, timedelta
from technical.util import resample_to_interval, resampled_merge
from technical.indicators import zema, VIDYA, ichimoku
import pandas_ta as pta
log = logging.getLogger(__name__)
###########################################################################################################
## NostalgiaForInfinityV8 by iterativ ##
## ##
## 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, BUSDT 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_sell_signal must set to true (or not set at all). ##
## sell_profit_only must set to false (or not set at all). ##
## ignore_roi_if_buy_signal must set to true (or not set at all). ##
## ##
###########################################################################################################
## HOLD SUPPORT ##
## In case you want to have SOME of the trades to only be sold when on profit, add a file named ##
## "hold-trades.json" in the same directory as this strategy. ##
## ##
## The contents should be similar to: ##
## ##
## {"trade_ids": [1, 3, 7], "profit_ratio": 0.005} ##
## ##
## Or, for individual profit ratios(Notice the trade ID's as strings: ##
## ##
## {"trade_ids": {"1": 0.001, "3": -0.005, "7": 0.05}} ##
## ##
## NOTE: ##
## * `trade_ids` is a list of integers, the trade ID's, which you can get from the logs or from the ##
## output of the telegram status command. ##
## * Regardless of the defined profit ratio(s), the strategy MUST still produce a SELL signal for the ##
## HOLD support logic to run ##
## ##
###########################################################################################################
## DONATIONS ##
## ##
## Absolutely not required. However, will be accepted as a token of appreciation. ##
## ##
## BTC: bc1qvflsvddkmxh7eqhc4jyu5z5k6xcw3ay8jl49sk ##
## ETH (ERC20): 0x83D3cFb8001BDC5d2211cBeBB8cB3461E5f7Ec91 ##
## BEP20/BSC (ETH, BNB, ...): 0x86A0B21a20b39d16424B7c8003E4A7e12d78ABEe ##
## ##
###########################################################################################################
class NostalgiaForInfinityNext_ChangeToTower_V6(IStrategy):
INTERFACE_VERSION = 2
plot_config = {
'main_plot': {
},
'subplots': {
"buy tag": {
'buy_tag': {'color': 'green'}
},
}
}
# ROI table:
minimal_roi = {
"0": 10,
}
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'
res_timeframe = 'none'
info_timeframe = '1h'
# BTC informative
has_BTC_base_tf = False
has_BTC_info_tf = True
# Backtest Age Filter emulation
has_bt_agefilter = False
bt_min_age_days = 3
# Exchange Downtime protection
has_downtime_protection = False
# 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_sell_signal = True
sell_profit_only = False
ignore_roi_if_buy_signal = True
# Number of candles the strategy requires before producing valid signals
startup_candle_count: int = 480
# Optional order type mapping.
order_types = {
'buy': 'limit',
'sell': 'limit',
'trailing_stop_loss': 'limit',
'stoploss': 'limit',
'stoploss_on_exchange': False
}
#############################################################
buy_params = {
#############
# Enable/Disable conditions
"buy_condition_1_enable": True,
"buy_condition_2_enable": True,
"buy_condition_3_enable": True,
"buy_condition_4_enable": True,
"buy_condition_5_enable": True,
"buy_condition_6_enable": True,
"buy_condition_7_enable": True,
"buy_condition_8_enable": True,
"buy_condition_9_enable": True,
"buy_condition_10_enable": True,
"buy_condition_11_enable": True,
"buy_condition_12_enable": True,
"buy_condition_13_enable": True,
"buy_condition_14_enable": True,
"buy_condition_15_enable": True,
"buy_condition_16_enable": True,
"buy_condition_17_enable": True,
"buy_condition_18_enable": True,
"buy_condition_19_enable": True,
"buy_condition_20_enable": True,
"buy_condition_21_enable": True,
"buy_condition_22_enable": True,
"buy_condition_23_enable": True,
"buy_condition_24_enable": True,
"buy_condition_25_enable": True,
"buy_condition_26_enable": True,
"buy_condition_27_enable": True,
"buy_condition_28_enable": True,
"buy_condition_29_enable": True,
"buy_condition_30_enable": True,
"buy_condition_31_enable": True,
"buy_condition_32_enable": True,
"buy_condition_33_enable": True,
"buy_condition_34_enable": True,
"buy_condition_35_enable": True,
"buy_condition_36_enable": True,
"buy_condition_37_enable": True,
"buy_condition_38_enable": True,
"buy_condition_39_enable": True,
"buy_condition_40_enable": True,
#############
}
sell_params = {
#############
# Enable/Disable conditions
"sell_condition_1_enable": True,
"sell_condition_2_enable": True,
"sell_condition_3_enable": True,
"sell_condition_4_enable": True,
"sell_condition_5_enable": True,
"sell_condition_6_enable": True,
"sell_condition_7_enable": True,
"sell_condition_8_enable": True,
#############
}
#############################################################
buy_protection_params = {
1: {
"ema_fast" : False,
"ema_fast_len" : "26",
"ema_slow" : True,
"ema_slow_len" : "100",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : True,
"sma200_rising_val" : "28",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : False,
"safe_dips_type" : "80",
"safe_pump" : False,
"safe_pump_type" : "70",
"safe_pump_period" : "24",
"btc_1h_not_downtrend" : False
},
2: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : True,
"ema_slow_len" : "20",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "50",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : True,
"safe_dips_type" : "50",
"safe_pump" : False,
"safe_pump_type" : "50",
"safe_pump_period" : "24",
"btc_1h_not_downtrend" : False
},
3: {
"ema_fast" : True,
"ema_fast_len" : "100",
"ema_slow" : True,
"ema_slow_len" : "100",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "50",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : True,
"safe_dips_type" : "70",
"safe_pump" : True,
"safe_pump_type" : "100",
"safe_pump_period" : "36",
"btc_1h_not_downtrend" : False
},
4: {
"ema_fast" : True,
"ema_fast_len" : "50",
"ema_slow" : True,
"ema_slow_len" : "50",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "50",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "20",
"safe_dips" : True,
"safe_dips_type" : "50",
"safe_pump" : False,
"safe_pump_type" : "110",
"safe_pump_period" : "48",
"btc_1h_not_downtrend" : False
},
5: {
"ema_fast" : True,
"ema_fast_len" : "100",
"ema_slow" : False,
"ema_slow_len" : "50",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "100",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "50",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : True,
"safe_dips_type" : "100",
"safe_pump" : True,
"safe_pump_type" : "30",
"safe_pump_period" : "36",
"btc_1h_not_downtrend" : False
},
6: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : True,
"ema_slow_len" : "100",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "50",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : True,
"safe_dips_type" : "50",
"safe_pump" : True,
"safe_pump_type" : "20",
"safe_pump_period" : "36",
"btc_1h_not_downtrend" : False
},
7: {
"ema_fast" : True,
"ema_fast_len" : "100",
"ema_slow" : True,
"ema_slow_len" : "12",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "50",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : True,
"safe_dips_type" : "130",
"safe_pump" : True,
"safe_pump_type" : "120",
"safe_pump_period" : "24",
"btc_1h_not_downtrend" : False
},
8: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : True,
"ema_slow_len" : "12",
"close_above_ema_fast" : True,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "50",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : True,
"safe_dips_type" : "100",
"safe_pump" : True,
"safe_pump_type" : "120",
"safe_pump_period" : "24",
"btc_1h_not_downtrend" : False
},
9: {
"ema_fast" : True,
"ema_fast_len" : "100",
"ema_slow" : False,
"ema_slow_len" : "50",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "50",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : False,
"safe_dips_type" : "10",
"safe_pump" : False,
"safe_pump_type" : "50",
"safe_pump_period" : "24",
"btc_1h_not_downtrend" : False
},
10: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : True,
"ema_slow_len" : "50",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "50",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "24",
"safe_dips" : True,
"safe_dips_type" : "120",
"safe_pump" : False,
"safe_pump_type" : "50",
"safe_pump_period" : "24",
"btc_1h_not_downtrend" : False
},
11: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : False,
"ema_slow_len" : "50",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "50",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : False,
"safe_dips_type" : "100",
"safe_pump" : True,
"safe_pump_type" : "50",
"safe_pump_period" : "24",
"btc_1h_not_downtrend" : False
},
12: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : False,
"ema_slow_len" : "50",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "50",
"sma200_1h_rising" : True,
"sma200_1h_rising_val" : "24",
"safe_dips" : True,
"safe_dips_type" : "130",
"safe_pump" : True,
"safe_pump_type" : "40",
"safe_pump_period" : "24",
"btc_1h_not_downtrend" : False
},
13: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : False,
"ema_slow_len" : "50",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "50",
"sma200_1h_rising" : True,
"sma200_1h_rising_val" : "24",
"safe_dips" : True,
"safe_dips_type" : "20",
"safe_pump" : False,
"safe_pump_type" : "50",
"safe_pump_period" : "24",
"btc_1h_not_downtrend" : False
},
14: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : False,
"ema_slow_len" : "50",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : True,
"sma200_rising_val" : "30",
"sma200_1h_rising" : True,
"sma200_1h_rising_val" : "50",
"safe_dips" : True,
"safe_dips_type" : "120",
"safe_pump" : False,
"safe_pump_type" : "100",
"safe_pump_period" : "24",
"btc_1h_not_downtrend" : False
},
15: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : True,
"ema_slow_len" : "50",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "50",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : True,
"safe_dips_type" : "130",
"safe_pump" : True,
"safe_pump_type" : "20",
"safe_pump_period" : "36",
"btc_1h_not_downtrend" : False
},
16: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : True,
"ema_slow_len" : "50",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "50",
"sma200_rising" : False,
"sma200_rising_val" : "50",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : True,
"safe_dips_type" : "10",
"safe_pump" : True,
"safe_pump_type" : "10",
"safe_pump_period" : "24",
"btc_1h_not_downtrend" : False
},
17: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : False,
"ema_slow_len" : "50",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "50",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : True,
"safe_dips_type" : "120",
"safe_pump" : True,
"safe_pump_type" : "120",
"safe_pump_period" : "24",
"btc_1h_not_downtrend" : False
},
18: {
"ema_fast" : True,
"ema_fast_len" : "100",
"ema_slow" : True,
"ema_slow_len" : "50",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : True,
"close_above_ema_slow_len" : "200",
"sma200_rising" : True,
"sma200_rising_val" : "44",
"sma200_1h_rising" : True,
"sma200_1h_rising_val" : "72",
"safe_dips" : True,
"safe_dips_type" : "100",
"safe_pump" : True,
"safe_pump_type" : "120",
"safe_pump_period" : "24",
"btc_1h_not_downtrend" : False
},
19: {
"ema_fast" : True,
"ema_fast_len" : "50",
"ema_slow" : True,
"ema_slow_len" : "100",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "36",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : True,
"safe_dips_type" : "130",
"safe_pump" : False,
"safe_pump_type" : "50",
"safe_pump_period" : "24",
"btc_1h_not_downtrend" : False
},
20: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : True,
"ema_slow_len" : "50",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "50",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : False,
"safe_dips_type" : "10",
"safe_pump" : False,
"safe_pump_type" : "50",
"safe_pump_period" : "24",
"btc_1h_not_downtrend" : False
},
21: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : True,
"ema_slow_len" : "50",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "50",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : True,
"safe_dips_type" : "90",
"safe_pump" : False,
"safe_pump_type" : "50",
"safe_pump_period" : "24",
"btc_1h_not_downtrend" : False
},
22: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : False,
"ema_slow_len" : "50",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "50",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : True,
"safe_dips_type" : "130",
"safe_pump" : True,
"safe_pump_type" : "110",
"safe_pump_period" : "24",
"btc_1h_not_downtrend" : False
},
23: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : False,
"ema_slow_len" : "50",
"close_above_ema_fast" : True,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : True,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "50",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : True,
"safe_dips_type" : "50",
"safe_pump" : False,
"safe_pump_type" : "50",
"safe_pump_period" : "24",
"btc_1h_not_downtrend" : False
},
24: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : False,
"ema_slow_len" : "50",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "30",
"sma200_1h_rising" : True,
"sma200_1h_rising_val" : "36",
"safe_dips" : True,
"safe_dips_type" : "20",
"safe_pump" : False,
"safe_pump_type" : "50",
"safe_pump_period" : "24",
"btc_1h_not_downtrend" : False
},
25: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : False,
"ema_slow_len" : "100",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "50",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : True,
"sma200_rising_val" : "20",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : False,
"safe_dips_type" : "10",
"safe_pump" : True,
"safe_pump_type" : "20",
"safe_pump_period" : "24",
"btc_1h_not_downtrend" : False
},
26: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : True,
"ema_slow_len" : "100",
"close_above_ema_fast" : True,
"close_above_ema_fast_len" : "50",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "30",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : True,
"safe_dips_type" : "60",
"safe_pump" : True,
"safe_pump_type" : "100",
"safe_pump_period" : "48",
"btc_1h_not_downtrend" : False
},
27: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : False,
"ema_slow_len" : "100",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "50",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "30",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : True,
"safe_dips_type" : "130",
"safe_pump" : False,
"safe_pump_type" : "50",
"safe_pump_period" : "36",
"btc_1h_not_downtrend" : True
},
28: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : False,
"ema_slow_len" : "100",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "50",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "30",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : False,
"safe_dips_type" : "50",
"safe_pump" : True,
"safe_pump_type" : "110",
"safe_pump_period" : "36",
"btc_1h_not_downtrend" : True
},
29: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : False,
"ema_slow_len" : "100",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "50",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "30",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : False,
"safe_dips_type" : "50",
"safe_pump" : False,
"safe_pump_type" : "110",
"safe_pump_period" : "36",
"btc_1h_not_downtrend" : False
},
30: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : True,
"ema_slow_len" : "100",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "50",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "30",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : False,
"safe_dips_type" : "50",
"safe_pump" : False,
"safe_pump_type" : "110",
"safe_pump_period" : "36",
"btc_1h_not_downtrend" : False
},
31: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : False,
"ema_slow_len" : "100",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "50",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "100",
"sma200_rising" : False,
"sma200_rising_val" : "30",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : False,
"safe_dips_type" : "110",
"safe_pump" : False,
"safe_pump_type" : "10",
"safe_pump_period" : "48",
"btc_1h_not_downtrend" : False
},
32: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : False,
"ema_slow_len" : "100",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "50",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "100",
"sma200_rising" : False,
"sma200_rising_val" : "30",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : True,
"safe_dips_type" : "120",
"safe_pump" : True,
"safe_pump_type" : "120",
"safe_pump_period" : "48",
"btc_1h_not_downtrend" : False
},
33: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : True,
"ema_slow_len" : "50",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "50",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "100",
"sma200_rising" : False,
"sma200_rising_val" : "30",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : True,
"safe_dips_type" : "100",
"safe_pump" : True,
"safe_pump_type" : "10",
"safe_pump_period" : "24",
"btc_1h_not_downtrend" : False
},
34: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : False,
"ema_slow_len" : "100",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "50",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "100",
"sma200_rising" : False,
"sma200_rising_val" : "30",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : False,
"safe_dips_type" : "100",
"safe_pump" : False,
"safe_pump_type" : "10",
"safe_pump_period" : "24",
"btc_1h_not_downtrend" : False
},
35: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : False,
"ema_slow_len" : "100",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "50",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "100",
"sma200_rising" : False,
"sma200_rising_val" : "30",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : False,
"safe_dips_type" : "100",
"safe_pump" : False,
"safe_pump_type" : "10",
"safe_pump_period" : "24",
"btc_1h_not_downtrend" : False
},
36: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : False,
"ema_slow_len" : "100",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "50",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "100",
"sma200_rising" : False,
"sma200_rising_val" : "30",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : False,
"safe_dips_type" : "100",
"safe_pump" : False,
"safe_pump_type" : "10",
"safe_pump_period" : "24",
"btc_1h_not_downtrend" : False
},
37: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : False,
"ema_slow_len" : "100",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "50",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "100",
"sma200_rising" : False,
"sma200_rising_val" : "30",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : False,
"safe_dips_type" : "100",
"safe_pump" : False,
"safe_pump_type" : "100",
"safe_pump_period" : "48",
"btc_1h_not_downtrend" : False
},
38: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : False,
"ema_slow_len" : "100",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "50",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "100",
"sma200_rising" : False,
"sma200_rising_val" : "30",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips" : False,
"safe_dips_type" : "100",
"safe_pump" : False,
"safe_pump_type" : "10",
"safe_pump_period" : "36",
"btc_1h_not_downtrend" : False
},
39: {
"ema_fast" : False,
"ema_fast_len" : "100",
"ema_slow" : True,
"ema_slow_len" : "50",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "50",
"close_above_ema_slow" : True,
"close_above_ema_slow_len" : "50",
"sma200_rising" : False,
"sma200_rising_val" : "30",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "20",
"safe_dips" : False,
"safe_dips_type" : "100",
"safe_pump" : True,
"safe_pump_type" : "50",
"safe_pump_period" : "48",
"btc_1h_not_downtrend" : True
},
40: {
"ema_fast" : False,
"ema_fast_len" : "100",
"ema_slow" : False,
"ema_slow_len" : "50",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "50",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "50",
"sma200_rising" : False,
"sma200_rising_val" : "30",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "20",
"safe_dips" : False,
"safe_dips_type" : "100",
"safe_pump" : False,
"safe_pump_type" : "50",
"safe_pump_period" : "48",
"btc_1h_not_downtrend" : True
}
}
# Strict dips - level 10
buy_dip_threshold_10_1 = DecimalParameter(0.001, 0.05, default=0.015, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_10_2 = DecimalParameter(0.01, 0.2, default=0.1, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_10_3 = DecimalParameter(0.1, 0.3, default=0.24, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_10_4 = DecimalParameter(0.3, 0.5, default=0.42, space='buy', decimals=3, optimize=False, load=True)
# Strict dips - level 20
buy_dip_threshold_20_1 = DecimalParameter(0.001, 0.05, default=0.016, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_20_2 = DecimalParameter(0.01, 0.2, default=0.11, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_20_3 = DecimalParameter(0.1, 0.4, default=0.26, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_20_4 = DecimalParameter(0.36, 0.56, default=0.44, space='buy', decimals=3, optimize=False, load=True)
# Strict dips - level 30
buy_dip_threshold_30_1 = DecimalParameter(0.001, 0.05, default=0.018, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_30_2 = DecimalParameter(0.01, 0.2, default=0.12, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_30_3 = DecimalParameter(0.1, 0.4, default=0.28, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_30_4 = DecimalParameter(0.36, 0.56, default=0.46, space='buy', decimals=3, optimize=False, load=True)
# Strict dips - level 40
buy_dip_threshold_40_1 = DecimalParameter(0.001, 0.05, default=0.019, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_40_2 = DecimalParameter(0.01, 0.2, default=0.13, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_40_3 = DecimalParameter(0.1, 0.4, default=0.3, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_40_4 = DecimalParameter(0.36, 0.56, default=0.48, space='buy', decimals=3, optimize=False, load=True)
# Normal dips - level 50
buy_dip_threshold_50_1 = DecimalParameter(0.001, 0.05, default=0.02, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_50_2 = DecimalParameter(0.01, 0.2, default=0.14, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_50_3 = DecimalParameter(0.05, 0.4, default=0.32, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_50_4 = DecimalParameter(0.2, 0.5, default=0.5, space='buy', decimals=3, optimize=False, load=True)
# Normal dips - level 60
buy_dip_threshold_60_1 = DecimalParameter(0.001, 0.05, default=0.022, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_60_2 = DecimalParameter(0.1, 0.22, default=0.18, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_60_3 = DecimalParameter(0.2, 0.4, default=0.34, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_60_4 = DecimalParameter(0.4, 0.6, default=0.56, space='buy', decimals=3, optimize=False, load=True)
# Normal dips - level 70
buy_dip_threshold_70_1 = DecimalParameter(0.001, 0.05, default=0.023, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_70_2 = DecimalParameter(0.16, 0.28, default=0.2, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_70_3 = DecimalParameter(0.2, 0.4, default=0.36, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_70_4 = DecimalParameter(0.5, 0.7, default=0.6, space='buy', decimals=3, optimize=False, load=True)
# Normal dips - level 80
buy_dip_threshold_80_1 = DecimalParameter(0.001, 0.05, default=0.024, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_80_2 = DecimalParameter(0.16, 0.28, default=0.22, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_80_3 = DecimalParameter(0.2, 0.4, default=0.38, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_80_4 = DecimalParameter(0.5, 0.7, default=0.66, space='buy', decimals=3, optimize=False, load=True)
# Normal dips - level 70
buy_dip_threshold_90_1 = DecimalParameter(0.001, 0.05, default=0.025, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_90_2 = DecimalParameter(0.16, 0.28, default=0.23, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_90_3 = DecimalParameter(0.3, 0.5, default=0.4, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_90_4 = DecimalParameter(0.6, 0.8, default=0.7, space='buy', decimals=3, optimize=False, load=True)
# Loose dips - level 100
buy_dip_threshold_100_1 = DecimalParameter(0.001, 0.05, default=0.026, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_100_2 = DecimalParameter(0.16, 0.3, default=0.24, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_100_3 = DecimalParameter(0.3, 0.5, default=0.42, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_100_4 = DecimalParameter(0.6, 1.0, default=0.8, space='buy', decimals=3, optimize=False, load=True)
# Loose dips - level 110
buy_dip_threshold_110_1 = DecimalParameter(0.001, 0.05, default=0.027, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_110_2 = DecimalParameter(0.16, 0.3, default=0.26, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_110_3 = DecimalParameter(0.3, 0.5, default=0.44, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_110_4 = DecimalParameter(0.6, 1.0, default=0.84, space='buy', decimals=3, optimize=False, load=True)
# Loose dips - level 120
buy_dip_threshold_120_1 = DecimalParameter(0.001, 0.05, default=0.028, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_120_2 = DecimalParameter(0.16, 0.3, default=0.28, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_120_3 = DecimalParameter(0.3, 0.5, default=0.46, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_120_4 = DecimalParameter(0.6, 1.0, default=0.86, space='buy', decimals=3, optimize=False, load=True)
# Loose dips - level 130
buy_dip_threshold_130_1 = DecimalParameter(0.001, 0.05, default=0.028, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_130_2 = DecimalParameter(0.16, 0.34, default=0.3, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_130_3 = DecimalParameter(0.36, 0.56, default=0.48, space='buy', decimals=3, optimize=False, load=True)
buy_dip_threshold_130_4 = DecimalParameter(0.6, 1.0, default=0.9, space='buy', decimals=3, optimize=False, load=True)
# 24 hours - level 10
buy_pump_pull_threshold_10_24 = DecimalParameter(1.5, 3.0, default=2.2, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_10_24 = DecimalParameter(0.4, 1.0, default=0.42, space='buy', decimals=3, optimize=False, load=True)
# 36 hours - level 10
buy_pump_pull_threshold_10_36 = DecimalParameter(1.5, 3.0, default=2.0, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_10_36 = DecimalParameter(0.4, 1.0, default=0.58, space='buy', decimals=3, optimize=False, load=True)
# 48 hours - level 10
buy_pump_pull_threshold_10_48 = DecimalParameter(1.5, 3.0, default=2.0, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_10_48 = DecimalParameter(0.4, 1.0, default=0.8, space='buy', decimals=3, optimize=False, load=True)
# 24 hours - level 20
buy_pump_pull_threshold_20_24 = DecimalParameter(1.5, 3.0, default=2.2, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_20_24 = DecimalParameter(0.4, 1.0, default=0.46, space='buy', decimals=3, optimize=False, load=True)
# 36 hours - level 20
buy_pump_pull_threshold_20_36 = DecimalParameter(1.5, 3.0, default=2.0, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_20_36 = DecimalParameter(0.4, 1.0, default=0.6, space='buy', decimals=3, optimize=False, load=True)
# 48 hours - level 20
buy_pump_pull_threshold_20_48 = DecimalParameter(1.5, 3.0, default=2.0, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_20_48 = DecimalParameter(0.4, 1.0, default=0.81, space='buy', decimals=3, optimize=False, load=True)
# 24 hours - level 30
buy_pump_pull_threshold_30_24 = DecimalParameter(1.5, 3.0, default=2.2, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_30_24 = DecimalParameter(0.4, 1.0, default=0.5, space='buy', decimals=3, optimize=False, load=True)
# 36 hours - level 30
buy_pump_pull_threshold_30_36 = DecimalParameter(1.5, 3.0, default=2.0, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_30_36 = DecimalParameter(0.4, 1.0, default=0.62, space='buy', decimals=3, optimize=False, load=True)
# 48 hours - level 30
buy_pump_pull_threshold_30_48 = DecimalParameter(1.5, 3.0, default=2.0, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_30_48 = DecimalParameter(0.4, 1.0, default=0.82, space='buy', decimals=3, optimize=False, load=True)
# 24 hours - level 40
buy_pump_pull_threshold_40_24 = DecimalParameter(1.5, 3.0, default=2.2, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_40_24 = DecimalParameter(0.4, 1.0, default=0.54, space='buy', decimals=3, optimize=False, load=True)
# 36 hours - level 40
buy_pump_pull_threshold_40_36 = DecimalParameter(1.5, 3.0, default=2.0, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_40_36 = DecimalParameter(0.4, 1.0, default=0.63, space='buy', decimals=3, optimize=False, load=True)
# 48 hours - level 40
buy_pump_pull_threshold_40_48 = DecimalParameter(1.5, 3.0, default=2.0, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_40_48 = DecimalParameter(0.4, 1.0, default=0.84, space='buy', decimals=3, optimize=False, load=True)
# 24 hours - level 50
buy_pump_pull_threshold_50_24 = DecimalParameter(1.5, 3.0, default=1.75, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_50_24 = DecimalParameter(0.4, 1.0, default=0.6, space='buy', decimals=3, optimize=False, load=True)
# 36 hours - level 50
buy_pump_pull_threshold_50_36 = DecimalParameter(1.5, 3.0, default=1.75, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_50_36 = DecimalParameter(0.4, 1.0, default=0.64, space='buy', decimals=3, optimize=False, load=True)
# 48 hours - level 50
buy_pump_pull_threshold_50_48 = DecimalParameter(1.5, 3.0, default=1.75, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_50_48 = DecimalParameter(0.4, 1.0, default=0.85, space='buy', decimals=3, optimize=False, load=True)
# 24 hours - level 60
buy_pump_pull_threshold_60_24 = DecimalParameter(1.5, 3.0, default=1.75, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_60_24 = DecimalParameter(0.4, 1.0, default=0.62, space='buy', decimals=3, optimize=False, load=True)
# 36 hours - level 60
buy_pump_pull_threshold_60_36 = DecimalParameter(1.5, 3.0, default=1.75, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_60_36 = DecimalParameter(0.4, 1.0, default=0.66, space='buy', decimals=3, optimize=False, load=True)
# 48 hours - level 60
buy_pump_pull_threshold_60_48 = DecimalParameter(1.5, 3.0, default=1.75, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_60_48 = DecimalParameter(0.4, 1.0, default=0.9, space='buy', decimals=3, optimize=False, load=True)
# 24 hours - level 70
buy_pump_pull_threshold_70_24 = DecimalParameter(1.5, 3.0, default=1.75, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_70_24 = DecimalParameter(0.4, 1.0, default=0.63, space='buy', decimals=3, optimize=False, load=True)
# 36 hours - level 70
buy_pump_pull_threshold_70_36 = DecimalParameter(1.5, 3.0, default=1.75, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_70_36 = DecimalParameter(0.4, 1.0, default=0.67, space='buy', decimals=3, optimize=False, load=True)
# 48 hours - level 70
buy_pump_pull_threshold_70_48 = DecimalParameter(1.5, 3.0, default=1.75, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_70_48 = DecimalParameter(0.4, 1.0, default=0.95, space='buy', decimals=3, optimize=False, load=True)
# 24 hours - level 80
buy_pump_pull_threshold_80_24 = DecimalParameter(1.5, 3.0, default=1.75, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_80_24 = DecimalParameter(0.4, 1.0, default=0.64, space='buy', decimals=3, optimize=False, load=True)
# 36 hours - level 80
buy_pump_pull_threshold_80_36 = DecimalParameter(1.5, 3.0, default=1.75, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_80_36 = DecimalParameter(0.4, 1.0, default=0.68, space='buy', decimals=3, optimize=False, load=True)
# 48 hours - level 80
buy_pump_pull_threshold_80_48 = DecimalParameter(1.5, 3.0, default=1.75, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_80_48 = DecimalParameter(0.8, 1.1, default=1.0, space='buy', decimals=3, optimize=False, load=True)
# 24 hours - level 90
buy_pump_pull_threshold_90_24 = DecimalParameter(1.5, 3.0, default=1.75, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_90_24 = DecimalParameter(0.4, 1.0, default=0.65, space='buy', decimals=3, optimize=False, load=True)
# 36 hours - level 90
buy_pump_pull_threshold_90_36 = DecimalParameter(1.5, 3.0, default=1.75, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_90_36 = DecimalParameter(0.4, 1.0, default=0.69, space='buy', decimals=3, optimize=False, load=True)
# 48 hours - level 90
buy_pump_pull_threshold_90_48 = DecimalParameter(1.5, 3.0, default=1.75, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_90_48 = DecimalParameter(0.8, 1.2, default=1.1, space='buy', decimals=3, optimize=False, load=True)
# 24 hours - level 100
buy_pump_pull_threshold_100_24 = DecimalParameter(1.5, 3.0, default=1.7, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_100_24 = DecimalParameter(0.4, 1.0, default=0.66, space='buy', decimals=3, optimize=False, load=True)
# 36 hours - level 100
buy_pump_pull_threshold_100_36 = DecimalParameter(1.5, 3.0, default=1.7, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_100_36 = DecimalParameter(0.4, 1.0, default=0.7, space='buy', decimals=3, optimize=False, load=True)
# 48 hours - level 100
buy_pump_pull_threshold_100_48 = DecimalParameter(1.3, 2.0, default=1.4, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_100_48 = DecimalParameter(0.4, 1.8, default=1.6, space='buy', decimals=3, optimize=False, load=True)
# 24 hours - level 110
buy_pump_pull_threshold_110_24 = DecimalParameter(1.5, 3.0, default=1.7, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_110_24 = DecimalParameter(0.4, 1.0, default=0.7, space='buy', decimals=3, optimize=False, load=True)
# 36 hours - level 110
buy_pump_pull_threshold_110_36 = DecimalParameter(1.5, 3.0, default=1.7, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_110_36 = DecimalParameter(0.4, 1.0, default=0.74, space='buy', decimals=3, optimize=False, load=True)
# 48 hours - level 110
buy_pump_pull_threshold_110_48 = DecimalParameter(1.3, 2.0, default=1.4, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_110_48 = DecimalParameter(1.4, 2.0, default=1.8, space='buy', decimals=3, optimize=False, load=True)
# 24 hours - level 120
buy_pump_pull_threshold_120_24 = DecimalParameter(1.5, 3.0, default=1.7, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_120_24 = DecimalParameter(0.4, 1.0, default=0.78, space='buy', decimals=3, optimize=False, load=True)
# 36 hours - level 120
buy_pump_pull_threshold_120_36 = DecimalParameter(1.5, 3.0, default=1.7, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_120_36 = DecimalParameter(0.4, 1.0, default=0.78, space='buy', decimals=3, optimize=False, load=True)
# 48 hours - level 120
buy_pump_pull_threshold_120_48 = DecimalParameter(1.3, 2.0, default=1.4, space='buy', decimals=2, optimize=False, load=True)
buy_pump_threshold_120_48 = DecimalParameter(1.4, 2.8, default=2.0, space='buy', decimals=3, optimize=False, load=True)
# 5 hours - level 10
buy_dump_protection_10_5 = DecimalParameter(0.3, 0.8, default=0.4, space='buy', decimals=2, optimize=False, load=True)
# 5 hours - level 20
buy_dump_protection_20_5 = DecimalParameter(0.3, 0.8, default=0.44, space='buy', decimals=2, optimize=False, load=True)
# 5 hours - level 30
buy_dump_protection_30_5 = DecimalParameter(0.3, 0.8, default=0.50, space='buy', decimals=2, optimize=False, load=True)
# 5 hours - level 40
buy_dump_protection_40_5 = DecimalParameter(0.3, 0.8, default=0.58, space='buy', decimals=2, optimize=False, load=True)
# 5 hours - level 50
buy_dump_protection_50_5 = DecimalParameter(0.3, 0.8, default=0.66, space='buy', decimals=2, optimize=False, load=True)
# 5 hours - level 60
buy_dump_protection_60_5 = DecimalParameter(0.3, 0.8, default=0.74, space='buy', decimals=2, optimize=False, load=True)
buy_min_inc_1 = DecimalParameter(0.01, 0.05, default=0.022, space='buy', decimals=3, optimize=False, load=True)
buy_rsi_1h_min_1 = DecimalParameter(25.0, 40.0, default=20.0, space='buy', decimals=1, optimize=False, load=True)
buy_rsi_1h_max_1 = DecimalParameter(70.0, 90.0, default=84.0, space='buy', decimals=1, optimize=False, load=True)
buy_rsi_1 = DecimalParameter(20.0, 40.0, default=36.0, space='buy', decimals=1, optimize=False, load=True)
buy_mfi_1 = DecimalParameter(20.0, 40.0, default=50.0, space='buy', decimals=1, optimize=False, load=True)
buy_cti_1 = DecimalParameter(-0.99, -0.5, default=-0.92, space='buy', decimals=2, optimize=False, load=True)
buy_rsi_1h_min_2 = DecimalParameter(30.0, 40.0, default=32.0, space='buy', decimals=1, optimize=False, load=True)
buy_rsi_1h_max_2 = DecimalParameter(70.0, 95.0, default=84.0, space='buy', decimals=1, optimize=False, load=True)
buy_rsi_1h_diff_2 = DecimalParameter(30.0, 50.0, default=38.8, space='buy', decimals=1, optimize=False, load=True)
buy_mfi_2 = DecimalParameter(30.0, 56.0, default=49.0, space='buy', decimals=1, optimize=False, load=True)
buy_bb_offset_2 = DecimalParameter(0.97, 0.999, default=0.983, space='buy', decimals=3, optimize=False, load=True)
buy_volume_2 = DecimalParameter(0.6, 6.0, default=1.6, space='buy', decimals=1, optimize=False, load=True)
buy_bb40_bbdelta_close_3 = DecimalParameter(0.005, 0.06, default=0.045, space='buy', optimize=False, load=True)
buy_bb40_closedelta_close_3 = DecimalParameter(0.01, 0.03, default=0.023, space='buy', optimize=False, load=True)
buy_bb40_tail_bbdelta_3 = DecimalParameter(0.15, 0.45, default=0.418, space='buy', optimize=False, load=True)
buy_ema_rel_3 = DecimalParameter(0.97, 0.999, default=0.986, space='buy', decimals=3, optimize=False, load=True)
buy_cti_3 = DecimalParameter(-0.99, -0.5, default=-0.5, space='buy', decimals=2, optimize=False, load=True)
buy_bb20_close_bblowerband_4 = DecimalParameter(0.96, 0.99, default=0.979, space='buy', optimize=False, load=True)
buy_bb20_volume_4 = DecimalParameter(1.0, 20.0, default=10.0, space='buy', decimals=2, optimize=False, load=True)
buy_cti_4 = DecimalParameter(-0.99, -0.5, default=-0.8, space='buy', decimals=2, optimize=False, load=True)
buy_ema_open_mult_5 = DecimalParameter(0.016, 0.03, default=0.018, space='buy', decimals=3, optimize=False, load=True)
buy_bb_offset_5 = DecimalParameter(0.98, 1.0, default=0.996, space='buy', decimals=3, optimize=False, load=True)
buy_ema_rel_5 = DecimalParameter(0.97, 0.999, default=0.915, space='buy', decimals=3, optimize=False, load=True)
buy_cti_5 = DecimalParameter(-0.99, -0.5, default=-0.84, space='buy', decimals=2, optimize=False, load=True)
buy_volume_5 = DecimalParameter(0.6, 6.0, default=1.8, space='buy', decimals=1, optimize=False, load=True)
buy_ema_open_mult_6 = DecimalParameter(0.02, 0.03, default=0.021, space='buy', decimals=3, optimize=False, load=True)
buy_bb_offset_6 = DecimalParameter(0.98, 0.999, default=0.976, space='buy', decimals=3, optimize=False, load=True)
buy_ema_open_mult_7 = DecimalParameter(0.02, 0.04, default=0.030, space='buy', decimals=3, optimize=False, load=True)
buy_cti_7 = DecimalParameter(-0.99, -0.5, default=-0.89, space='buy', decimals=2, optimize=False, load=True)
buy_cti_8 = DecimalParameter(-0.99, -0.5, default=-0.88, space='buy', decimals=2, optimize=False, load=True)
buy_rsi_8 = DecimalParameter(20.0, 50.0, default=40.0, space='buy', decimals=1, optimize=False, load=True)
buy_bb_offset_8 = DecimalParameter(0.98, 1.0, default=0.99, space='buy', decimals=3, optimize=False, load=True)
buy_rsi_1h_8 = DecimalParameter(40.0, 66.0, default=64.0, space='buy', decimals=1, optimize=False, load=True)
buy_volume_8 = DecimalParameter(0.6, 6.0, default=1.8, space='buy', decimals=1, optimize=False, load=True)
buy_ma_offset_9 = DecimalParameter(0.91, 0.94, default=0.968, space='buy', decimals=3, optimize=False, load=True)
buy_bb_offset_9 = DecimalParameter(0.96, 0.98, default=0.942, space='buy', decimals=3, optimize=False, load=True)
buy_rsi_1h_min_9 = DecimalParameter(26.0, 40.0, default=20.0, space='buy', decimals=1, optimize=False, load=True)
buy_rsi_1h_max_9 = DecimalParameter(70.0, 90.0, default=88.0, space='buy', decimals=1, optimize=False, load=True)
buy_mfi_9 = DecimalParameter(36.0, 56.0, default=50.0, space='buy', decimals=1, optimize=False, load=True)
buy_ma_offset_10 = DecimalParameter(0.94, 0.99, default=0.98, space='buy', decimals=3, optimize=False, load=True)
buy_bb_offset_10 = DecimalParameter(0.97, 0.99, default=0.972, space='buy', decimals=3, optimize=False, load=True)
buy_rsi_1h_10 = DecimalParameter(30.0, 60.0, default=50.0, space='buy', decimals=1, optimize=False, load=True)
buy_ma_offset_11 = DecimalParameter(0.93, 0.99, default=0.946, space='buy', decimals=3, optimize=False, load=True)
buy_min_inc_11 = DecimalParameter(0.005, 0.05, default=0.038, space='buy', decimals=3, optimize=False, load=True)
buy_rsi_1h_min_11 = DecimalParameter(40.0, 60.0, default=46.0, space='buy', decimals=1, optimize=False, load=True)
buy_rsi_1h_max_11 = DecimalParameter(70.0, 90.0, default=84.0, space='buy', decimals=1, optimize=False, load=True)
buy_rsi_11 = DecimalParameter(34.0, 50.0, default=38.0, space='buy', decimals=1, optimize=False, load=True)
buy_mfi_11 = DecimalParameter(30.0, 46.0, default=36.0, space='buy', decimals=1, optimize=False, load=True)
buy_ma_offset_12 = DecimalParameter(0.93, 0.97, default=0.921, space='buy', decimals=3, optimize=False, load=True)
buy_rsi_12 = DecimalParameter(26.0, 40.0, default=28.0, space='buy', decimals=1, optimize=False, load=True)
buy_ewo_12 = DecimalParameter(1.0, 6.0, default=1.8, space='buy', decimals=1, optimize=False, load=True)
buy_cti_12 = DecimalParameter(-0.99, -0.5, default=-0.7, space='buy', decimals=2, optimize=False, load=True)
buy_ma_offset_13 = DecimalParameter(0.93, 0.98, default=0.99, space='buy', decimals=3, optimize=False, load=True)
buy_cti_13 = DecimalParameter(-0.99, -0.5, default=-0.82, space='buy', decimals=2, optimize=False, load=True)
buy_ewo_13 = DecimalParameter(-14.0, -7.0, default=-9.0, space='buy', decimals=1, optimize=False, load=True)
buy_ema_open_mult_14 = DecimalParameter(0.01, 0.03, default=0.014, space='buy', decimals=3, optimize=False, load=True)
buy_bb_offset_14 = DecimalParameter(0.98, 1.0, default=0.988, space='buy', decimals=3, optimize=False, load=True)
buy_ma_offset_14 = DecimalParameter(0.93, 0.99, default=0.945, space='buy', decimals=3, optimize=False, load=True)
buy_cti_14 = DecimalParameter(-0.99, -0.5, default=-0.86, space='buy', decimals=2, optimize=False, load=True)
buy_ema_open_mult_15 = DecimalParameter(0.01, 0.03, default=0.024, space='buy', decimals=3, optimize=False, load=True)
buy_ma_offset_15 = DecimalParameter(0.93, 0.99, default=0.958, space='buy', decimals=3, optimize=False, load=True)
buy_rsi_15 = DecimalParameter(20.0, 36.0, default=28.0, space='buy', decimals=1, optimize=False, load=True)
buy_ema_rel_15 = DecimalParameter(0.97, 0.999, default=0.974, space='buy', decimals=3, optimize=False, load=True)
buy_ma_offset_16 = DecimalParameter(0.93, 0.97, default=0.953, space='buy', decimals=3, optimize=False, load=True)
buy_rsi_16 = DecimalParameter(26.0, 50.0, default=31.0, space='buy', decimals=1, optimize=False, load=True)
buy_ewo_16 = DecimalParameter(2.0, 6.0, default=2.8, space='buy', decimals=1, optimize=False, load=True)
buy_cti_16 = DecimalParameter(-0.99, -0.5, default=-0.84, space='buy', decimals=2, optimize=False, load=True)
buy_ma_offset_17 = DecimalParameter(0.93, 0.98, default=0.99, space='buy', decimals=3, optimize=False, load=True)
buy_ewo_17 = DecimalParameter(-18.0, -10.0, default=-9.4, space='buy', decimals=1, optimize=False, load=True)
buy_cti_17 = DecimalParameter(-0.99, -0.5, default=-0.96, space='buy', decimals=2, optimize=False, load=True)
buy_volume_17 = DecimalParameter(0.6, 6.0, default=2.0, space='buy', decimals=1, optimize=False, load=True)
buy_rsi_18 = DecimalParameter(20.0, 36.0, default=33.0, space='buy', decimals=1, optimize=False, load=True)
buy_bb_offset_18 = DecimalParameter(0.98, 1.0, default=0.986, space='buy', decimals=3, optimize=False, load=True)
buy_volume_18 = DecimalParameter(0.6, 6.0, default=2.0, space='buy', decimals=1, optimize=False, load=True)
buy_cti_18 = DecimalParameter(-0.99, -0.5, default=-0.86, space='buy', decimals=2, optimize=False, load=True)
buy_rsi_1h_min_19 = DecimalParameter(40.0, 70.0, default=30.0, space='buy', decimals=1, optimize=False, load=True)
buy_chop_max_19 = DecimalParameter(20.0, 60.0, default=21.3, space='buy', decimals=1, optimize=False, load=True)
buy_rsi_20 = DecimalParameter(20.0, 36.0, default=36.0, space='buy', decimals=1, optimize=False, load=True)
buy_rsi_1h_20 = DecimalParameter(14.0, 30.0, default=16.0, space='buy', decimals=1, optimize=False, load=True)
buy_cti_20 = DecimalParameter(-0.99, -0.5, default=-0.84, space='buy', decimals=2, optimize=False, load=True)
buy_volume_20 = DecimalParameter(0.6, 6.0, default=2.0, space='buy', decimals=1, optimize=False, load=True)
buy_rsi_21 = DecimalParameter(10.0, 28.0, default=14.0, space='buy', decimals=1, optimize=False, load=True)
buy_rsi_1h_21 = DecimalParameter(18.0, 40.0, default=28.0, space='buy', decimals=1, optimize=False, load=True)
buy_cti_21 = DecimalParameter(-0.99, -0.4, default=-0.9, space='buy', decimals=2, optimize=False, load=True)
buy_volume_21 = DecimalParameter(0.6, 6.0, default=2.0, space='buy', decimals=1, optimize=False, load=True)
buy_volume_22 = DecimalParameter(0.5, 6.0, default=2.0, space='buy', decimals=1, optimize=False, load=True)
buy_bb_offset_22 = DecimalParameter(0.98, 1.0, default=0.984, space='buy', decimals=3, optimize=False, load=True)
buy_ma_offset_22 = DecimalParameter(0.93, 0.98, default=0.942, space='buy', decimals=3, optimize=False, load=True)
buy_ewo_22 = DecimalParameter(2.0, 10.0, default=5.8, space='buy', decimals=1, optimize=False, load=True)
buy_rsi_22 = DecimalParameter(26.0, 56.0, default=36.0, space='buy', decimals=1, optimize=False, load=True)
buy_bb_offset_23 = DecimalParameter(0.97, 1.0, default=0.985, space='buy', decimals=3, optimize=False, load=True)
buy_ewo_23 = DecimalParameter(2.0, 10.0, default=6.2, space='buy', decimals=1, optimize=False, load=True)
buy_rsi_23 = DecimalParameter(20.0, 40.0, default=32.4, space='buy', decimals=1, optimize=False, load=True)
buy_rsi_1h_23 = DecimalParameter(60.0, 80.0, default=70.0, space='buy', decimals=1, optimize=False, load=True)
buy_24_rsi_max = DecimalParameter(26.0, 60.0, default=50.0, space='buy', decimals=1, optimize=False, load=True)
buy_24_rsi_1h_min = DecimalParameter(40.0, 90.0, default=66.9, space='buy', decimals=1, optimize=False, load=True)
buy_25_ma_offset = DecimalParameter(0.90, 0.99, default=0.922, space='buy', optimize=False, load=True)
buy_25_rsi_4 = DecimalParameter(26.0, 40.0, default=38.0, space='buy', decimals=1, optimize=False, load=True)
buy_25_cti = DecimalParameter(-0.99, -0.4, default=-0.76, space='buy', decimals=2, optimize=False, load=True)
buy_26_zema_low_offset = DecimalParameter(0.90, 0.99, default=0.932, space='buy', optimize=False, load=True)
buy_26_cti = DecimalParameter(-0.99, -0.4, default=-0.82, space='buy', decimals=2, optimize=False, load=True)
buy_26_volume = DecimalParameter(0.6, 6.0, default=1.2, space='buy', decimals=1, optimize=False, load=True)
buy_27_wr_max = DecimalParameter(90, 99, default=90.0, space='buy', decimals=1, optimize=False, load=True)
buy_27_wr_1h_max = DecimalParameter(90, 99, default=90.0, space='buy', decimals=1, optimize=False, load=True)
buy_27_rsi_max = DecimalParameter(40, 70, default=50, space='buy', decimals=0, optimize=False, load=True)
buy_27_cti = DecimalParameter(-0.99, -0.4, default=-0.93, space='buy', decimals=2, optimize=False, load=True)
buy_27_volume = DecimalParameter(0.6, 6.0, default=2.0, space='buy', decimals=1, optimize=False, load=True)
buy_28_ma_offset = DecimalParameter(0.90, 0.99, default=0.97, space='buy', optimize=False, load=True)
buy_28_ewo = DecimalParameter(2.0, 14.0, default=7.2, space='buy', decimals=1, optimize=False, load=True)
buy_28_rsi = DecimalParameter(24.0, 44.0, default=32.5, space='buy', decimals=1, optimize=False, load=True)
buy_28_cti = DecimalParameter(-0.99, -0.4, default=-0.9, space='buy', decimals=2, optimize=False, load=True)
buy_29_ma_offset = DecimalParameter(0.90, 0.99, default=0.94, space='buy', optimize=False, load=True)
buy_29_ewo = DecimalParameter(-14.0, -2.0, default=-4.0, space='buy', decimals=1, optimize=False, load=True)
buy_29_cti = DecimalParameter(-0.99, -0.4, default=-0.95, space='buy', decimals=2, optimize=False, load=True)
buy_30_ma_offset = DecimalParameter(0.90, 0.99, default=0.97, space='buy', optimize=False, load=True)
buy_30_ewo = DecimalParameter(2.0, 14.0, default=7.4, space='buy', decimals=1, optimize=False, load=True)
buy_30_rsi = DecimalParameter(24.0, 48.0, default=40.0, space='buy', decimals=1, optimize=False, load=True)
buy_30_cti = DecimalParameter(-0.99, -0.4, default=-0.88, space='buy', decimals=2, optimize=False, load=True)
buy_31_ma_offset = DecimalParameter(0.90, 0.99, default=0.94, space='buy', optimize=False, load=True)
buy_31_ewo = DecimalParameter(-22.0, -8.0, default=-19.0, space='buy', decimals=1, optimize=False, load=True)
buy_31_wr = DecimalParameter(-99.9, -95.0, default=-98.4, space='buy', decimals=1, optimize=False, load=True)
buy_32_ma_offset = DecimalParameter(0.90, 0.99, default=0.934, space='buy', optimize=False, load=True)
buy_32_dip = DecimalParameter(0.001, 0.02, default=0.005, space='buy', decimals=3, optimize=False, load=True)
buy_32_rsi = DecimalParameter(24.0, 50.0, default=46.0, space='buy', decimals=1, optimize=False, load=True)
buy_32_cti = DecimalParameter(-0.99, -0.4, default=-0.8, space='buy', decimals=2, optimize=False, load=True)
buy_33_ma_offset = DecimalParameter(0.90, 0.99, default=0.988, space='buy', optimize=False, load=True)
buy_33_rsi = DecimalParameter(24.0, 50.0, default=32.0, space='buy', decimals=1, optimize=False, load=True)
buy_33_cti = DecimalParameter(-0.99, -0.4, default=-0.9, space='buy', decimals=2, optimize=False, load=True)
buy_33_ewo = DecimalParameter(2.0, 14.0, default=6.5, space='buy', decimals=1, optimize=False, load=True)
buy_33_volume = DecimalParameter(0.6, 6.0, default=2.0, space='buy', decimals=1, optimize=False, load=True)
buy_34_ma_offset = DecimalParameter(0.90, 0.99, default=0.93, space='buy', optimize=False, load=True)
buy_34_dip = DecimalParameter(0.001, 0.02, default=0.005, space='buy', decimals=3, optimize=False, load=True)
buy_34_ewo = DecimalParameter(-24.0, -5.0, default=-6.0, space='buy', decimals=1, optimize=False, load=True)
buy_34_cti = DecimalParameter(-0.99, -0.4, default=-0.88, space='buy', decimals=2, optimize=False, load=True)
buy_34_volume = DecimalParameter(0.6, 6.0, default=2.0, space='buy', decimals=1, optimize=False, load=True)
# Sell
sell_condition_1_enable = CategoricalParameter([True, False], default=True, space='sell', optimize=False, load=True)
sell_condition_2_enable = CategoricalParameter([True, False], default=True, space='sell', optimize=False, load=True)
sell_condition_3_enable = CategoricalParameter([True, False], default=True, space='sell', optimize=False, load=True)
sell_condition_4_enable = CategoricalParameter([True, False], default=True, space='sell', optimize=False, load=True)
sell_condition_5_enable = CategoricalParameter([True, False], default=True, space='sell', optimize=False, load=True)
sell_condition_6_enable = CategoricalParameter([True, False], default=True, space='sell', optimize=False, load=True)
sell_condition_7_enable = CategoricalParameter([True, False], default=True, space='sell', optimize=False, load=True)
sell_condition_8_enable = CategoricalParameter([True, False], default=True, space='sell', optimize=False, load=True)
# 48h for pump sell checks
sell_pump_threshold_48_1 = DecimalParameter(0.5, 1.2, default=0.9, space='sell', decimals=2, optimize=False, load=True)
sell_pump_threshold_48_2 = DecimalParameter(0.4, 0.9, default=0.7, space='sell', decimals=2, optimize=False, load=True)
sell_pump_threshold_48_3 = DecimalParameter(0.3, 0.7, default=0.5, space='sell', decimals=2, optimize=False, load=True)
# 36h for pump sell checks
sell_pump_threshold_36_1 = DecimalParameter(0.5, 0.9, default=0.72, space='sell', decimals=2, optimize=False, load=True)
sell_pump_threshold_36_2 = DecimalParameter(3.0, 6.0, default=4.0, space='sell', decimals=2, optimize=False, load=True)
sell_pump_threshold_36_3 = DecimalParameter(0.8, 1.6, default=1.0, space='sell', decimals=2, optimize=False, load=True)
# 24h for pump sell checks
sell_pump_threshold_24_1 = DecimalParameter(0.5, 0.9, default=0.68, space='sell', decimals=2, optimize=False, load=True)
sell_pump_threshold_24_2 = DecimalParameter(0.3, 0.6, default=0.62, space='sell', decimals=2, optimize=False, load=True)
sell_pump_threshold_24_3 = DecimalParameter(0.2, 0.5, default=0.88, space='sell', decimals=2, optimize=False, load=True)
sell_rsi_bb_1 = DecimalParameter(60.0, 80.0, default=79.5, space='sell', decimals=1, optimize=False, load=True)
sell_rsi_bb_2 = DecimalParameter(72.0, 90.0, default=81, space='sell', decimals=1, optimize=False, load=True)
sell_rsi_main_3 = DecimalParameter(77.0, 90.0, default=82, space='sell', decimals=1, optimize=False, load=True)
sell_dual_rsi_rsi_4 = DecimalParameter(72.0, 84.0, default=73.4, space='sell', decimals=1, optimize=False, load=True)
sell_dual_rsi_rsi_1h_4 = DecimalParameter(78.0, 92.0, default=79.6, space='sell', decimals=1, optimize=False, load=True)
sell_ema_relative_5 = DecimalParameter(0.005, 0.05, default=0.024, space='sell', optimize=False, load=True)
sell_rsi_diff_5 = DecimalParameter(0.0, 20.0, default=4.4, space='sell', optimize=False, load=True)
sell_rsi_under_6 = DecimalParameter(72.0, 90.0, default=79.0, space='sell', decimals=1, optimize=False, load=True)
sell_rsi_1h_7 = DecimalParameter(80.0, 95.0, default=81.7, space='sell', decimals=1, optimize=False, load=True)
sell_bb_relative_8 = DecimalParameter(1.05, 1.3, default=1.1, space='sell', decimals=3, optimize=False, load=True)
# Profit over EMA200
sell_custom_profit_bull_0 = DecimalParameter(0.01, 0.1, default=0.012, space='sell', decimals=3, optimize=False, load=True)
sell_custom_rsi_under_bull_0 = DecimalParameter(30.0, 40.0, default=34.0, space='sell', decimals=3, optimize=False, load=True)
sell_custom_profit_bull_1 = DecimalParameter(0.01, 0.1, default=0.02, space='sell', decimals=3, optimize=False, load=True)
sell_custom_rsi_under_bull_1 = DecimalParameter(30.0, 50.0, default=35.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_profit_bull_2 = DecimalParameter(0.01, 0.1, default=0.03, space='sell', decimals=3, optimize=False, load=True)
sell_custom_rsi_under_bull_2 = DecimalParameter(30.0, 50.0, default=36.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_profit_bull_3 = DecimalParameter(0.01, 0.1, default=0.04, space='sell', decimals=3, optimize=False, load=True)
sell_custom_rsi_under_bull_3 = DecimalParameter(30.0, 50.0, default=37.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_profit_bull_4 = DecimalParameter(0.01, 0.1, default=0.05, space='sell', decimals=3, optimize=False, load=True)
sell_custom_rsi_under_bull_4 = DecimalParameter(35.0, 50.0, default=42.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_profit_bull_5 = DecimalParameter(0.01, 0.1, default=0.06, space='sell', decimals=3, optimize=False, load=True)
sell_custom_rsi_under_bull_5 = DecimalParameter(35.0, 50.0, default=49.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_profit_bull_6 = DecimalParameter(0.01, 0.1, default=0.07, space='sell', decimals=3, optimize=False, load=True)
sell_custom_rsi_under_bull_6 = DecimalParameter(38.0, 55.0, default=50.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_profit_bull_7 = DecimalParameter(0.01, 0.1, default=0.08, space='sell', decimals=3, optimize=False, load=True)
sell_custom_rsi_under_bull_7 = DecimalParameter(40.0, 58.0, default=54.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_profit_bull_8 = DecimalParameter(0.06, 0.1, default=0.09, space='sell', decimals=3, optimize=False, load=True)
sell_custom_rsi_under_bull_8 = DecimalParameter(40.0, 50.0, default=50.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_profit_bull_9 = DecimalParameter(0.05, 0.14, default=0.1, space='sell', decimals=3, optimize=False, load=True)
sell_custom_rsi_under_bull_9 = DecimalParameter(40.0, 60.0, default=46.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_profit_bull_10 = DecimalParameter(0.1, 0.14, default=0.12, space='sell', decimals=3, optimize=False, load=True)
sell_custom_rsi_under_bull_10 = DecimalParameter(38.0, 50.0, default=42.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_profit_bull_11 = DecimalParameter(0.16, 0.45, default=0.20, space='sell', decimals=3, optimize=False, load=True)
sell_custom_rsi_under_bull_11 = DecimalParameter(28.0, 40.0, default=30.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_profit_bear_0 = DecimalParameter(0.01, 0.1, default=0.012, space='sell', decimals=3, optimize=False, load=True)
sell_custom_rsi_under_bear_0 = DecimalParameter(30.0, 40.0, default=34.0, space='sell', decimals=3, optimize=False, load=True)
sell_custom_profit_bear_1 = DecimalParameter(0.01, 0.1, default=0.02, space='sell', decimals=3, optimize=False, load=True)
sell_custom_rsi_under_bear_1 = DecimalParameter(30.0, 50.0, default=35.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_profit_bear_2 = DecimalParameter(0.01, 0.1, default=0.03, space='sell', decimals=3, optimize=False, load=True)
sell_custom_rsi_under_bear_2 = DecimalParameter(30.0, 50.0, default=37.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_profit_bear_3 = DecimalParameter(0.01, 0.1, default=0.04, space='sell', decimals=3, optimize=False, load=True)
sell_custom_rsi_under_bear_3 = DecimalParameter(30.0, 50.0, default=44.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_profit_bear_4 = DecimalParameter(0.01, 0.1, default=0.05, space='sell', decimals=3, optimize=False, load=True)
sell_custom_rsi_under_bear_4 = DecimalParameter(35.0, 50.0, default=48.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_profit_bear_5 = DecimalParameter(0.01, 0.1, default=0.06, space='sell', decimals=3, optimize=False, load=True)
sell_custom_rsi_under_bear_5 = DecimalParameter(35.0, 50.0, default=50.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_rsi_over_bear_5 = DecimalParameter(70.0, 85.0, default=78.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_profit_bear_6 = DecimalParameter(0.01, 0.1, default=0.07, space='sell', decimals=3, optimize=False, load=True)
sell_custom_rsi_under_bear_6 = DecimalParameter(38.0, 55.0, default=52.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_rsi_over_bear_6 = DecimalParameter(70.0, 85.0, default=78.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_profit_bear_7 = DecimalParameter(0.01, 0.1, default=0.08, space='sell', decimals=3, optimize=False, load=True)
sell_custom_rsi_under_bear_7 = DecimalParameter(40.0, 58.0, default=54.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_rsi_over_bear_7 = DecimalParameter(70.0, 85.0, default=80.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_profit_bear_8 = DecimalParameter(0.06, 0.1, default=0.09, space='sell', decimals=3, optimize=False, load=True)
sell_custom_rsi_under_bear_8 = DecimalParameter(40.0, 50.0, default=52.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_rsi_over_bear_8 = DecimalParameter(70.0, 85.0, default=82.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_profit_bear_9 = DecimalParameter(0.05, 0.14, default=0.1, space='sell', decimals=3, optimize=False, load=True)
sell_custom_rsi_under_bear_9 = DecimalParameter(40.0, 60.0, default=50.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_profit_bear_10 = DecimalParameter(0.1, 0.14, default=0.12, space='sell', decimals=3, optimize=False, load=True)
sell_custom_rsi_under_bear_10 = DecimalParameter(38.0, 50.0, default=42.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_profit_bear_11 = DecimalParameter(0.16, 0.45, default=0.20, space='sell', decimals=3, optimize=False, load=True)
sell_custom_rsi_under_bear_11 = DecimalParameter(28.0, 40.0, default=30.0, space='sell', decimals=2, optimize=False, load=True)
# Profit under EMA200
sell_custom_under_profit_bull_0 = DecimalParameter(0.01, 0.4, default=0.01, space='sell', decimals=3, optimize=False, load=True)
sell_custom_under_rsi_under_bull_0 = DecimalParameter(28.0, 40.0, default=38.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_under_profit_bull_1 = DecimalParameter(0.01, 0.10, default=0.02, space='sell', decimals=3, optimize=False, load=True)
sell_custom_under_rsi_under_bull_1 = DecimalParameter(36.0, 60.0, default=54.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_under_profit_bull_2 = DecimalParameter(0.01, 0.10, default=0.03, space='sell', decimals=3, optimize=False, load=True)
sell_custom_under_rsi_under_bull_2 = DecimalParameter(46.0, 66.0, default=55.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_under_profit_bull_3 = DecimalParameter(0.01, 0.10, default=0.04, space='sell', decimals=3, optimize=False, load=True)
sell_custom_under_rsi_under_bull_3 = DecimalParameter(50.0, 68.0, default=56.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_under_profit_bull_4 = DecimalParameter(0.02, 0.1, default=0.05, space='sell', decimals=3, optimize=False, load=True)
sell_custom_under_rsi_under_bull_4 = DecimalParameter(50.0, 68.0, default=57.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_under_profit_bull_5 = DecimalParameter(0.02, 0.1, default=0.06, space='sell', decimals=3, optimize=False, load=True)
sell_custom_under_rsi_under_bull_5 = DecimalParameter(46.0, 62.0, default=58.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_under_profit_bull_6 = DecimalParameter(0.03, 0.1, default=0.07, space='sell', decimals=3, optimize=False, load=True)
sell_custom_under_rsi_under_bull_6 = DecimalParameter(44.0, 60.0, default=48.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_under_profit_bull_7 = DecimalParameter(0.04, 0.1, default=0.08, space='sell', decimals=3, optimize=False, load=True)
sell_custom_under_rsi_under_bull_7 = DecimalParameter(46.0, 60.0, default=44.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_under_profit_bull_8 = DecimalParameter(0.06, 0.12, default=0.09, space='sell', decimals=3, optimize=False, load=True)
sell_custom_under_rsi_under_bull_8 = DecimalParameter(40.0, 58.0, default=42.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_under_profit_bull_9 = DecimalParameter(0.08, 0.14, default=0.1, space='sell', decimals=3, optimize=False, load=True)
sell_custom_under_rsi_under_bull_9 = DecimalParameter(40.0, 60.0, default=38.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_under_profit_bull_10 = DecimalParameter(0.1, 0.16, default=0.12, space='sell', decimals=3, optimize=False, load=True)
sell_custom_under_rsi_under_bull_10 = DecimalParameter(30.0, 50.0, default=34.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_under_profit_bull_11 = DecimalParameter(0.16, 0.3, default=0.2, space='sell', decimals=3, optimize=False, load=True)
sell_custom_under_rsi_under_bull_11 = DecimalParameter(24.0, 40.0, default=30.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_under_profit_bear_0 = DecimalParameter(0.01, 0.4, default=0.01, space='sell', decimals=3, optimize=False, load=True)
sell_custom_under_rsi_under_bear_0 = DecimalParameter(28.0, 40.0, default=38.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_under_profit_bear_1 = DecimalParameter(0.01, 0.10, default=0.02, space='sell', decimals=3, optimize=False, load=True)
sell_custom_under_rsi_under_bear_1 = DecimalParameter(36.0, 60.0, default=59.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_under_profit_bear_2 = DecimalParameter(0.01, 0.10, default=0.03, space='sell', decimals=3, optimize=False, load=True)
sell_custom_under_rsi_under_bear_2 = DecimalParameter(46.0, 66.0, default=60.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_under_profit_bear_3 = DecimalParameter(0.01, 0.10, default=0.04, space='sell', decimals=3, optimize=False, load=True)
sell_custom_under_rsi_under_bear_3 = DecimalParameter(50.0, 68.0, default=61.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_under_profit_bear_4 = DecimalParameter(0.02, 0.1, default=0.05, space='sell', decimals=3, optimize=False, load=True)
sell_custom_under_rsi_under_bear_4 = DecimalParameter(50.0, 68.0, default=60.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_under_profit_bear_5 = DecimalParameter(0.02, 0.1, default=0.06, space='sell', decimals=3, optimize=False, load=True)
sell_custom_under_rsi_under_bear_5 = DecimalParameter(46.0, 62.0, default=58.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_under_rsi_over_bear_5 = DecimalParameter(70.0, 85.0, default=78.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_under_profit_bear_6 = DecimalParameter(0.03, 0.1, default=0.07, space='sell', decimals=3, optimize=False, load=True)
sell_custom_under_rsi_under_bear_6 = DecimalParameter(44.0, 60.0, default=50.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_under_rsi_over_bear_6 = DecimalParameter(70.0, 85.0, default=78.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_under_profit_bear_7 = DecimalParameter(0.04, 0.1, default=0.08, space='sell', decimals=3, optimize=False, load=True)
sell_custom_under_rsi_under_bear_7 = DecimalParameter(46.0, 60.0, default=46.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_under_rsi_over_bear_7 = DecimalParameter(70.0, 85.0, default=80.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_under_profit_bear_8 = DecimalParameter(0.06, 0.12, default=0.09, space='sell', decimals=3, optimize=False, load=True)
sell_custom_under_rsi_under_bear_8 = DecimalParameter(40.0, 58.0, default=42.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_under_rsi_over_bear_8 = DecimalParameter(70.0, 85.0, default=82.0, space='sell', decimals=2, optimize=False, load=True)
sell_custom_under_profit_bear_9 = DecimalParameter(0.08, 0.14, default=0.1, space='sell', decimals=3, optimize=False, load=True)
sell_custom_under_rsi_under_bear_9 = DecimalParameter(40.0, 60.0, default=36.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_under_profit_bear_10 = DecimalParameter(0.1, 0.16, default=0.12, space='sell', decimals=3, optimize=False, load=True)
sell_custom_under_rsi_under_bear_10 = DecimalParameter(30.0, 50.0, default=34.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_under_profit_bear_11 = DecimalParameter(0.16, 0.3, default=0.2, space='sell', decimals=3, optimize=False, load=True)
sell_custom_under_rsi_under_bear_11 = DecimalParameter(24.0, 40.0, default=30.0, space='sell', decimals=1, optimize=False, load=True)
# Profit targets for pumped pairs 48h 1
sell_custom_pump_profit_1_1 = DecimalParameter(0.01, 0.03, default=0.01, space='sell', decimals=3, optimize=False, load=True)
sell_custom_pump_rsi_1_1 = DecimalParameter(26.0, 40.0, default=34.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_pump_profit_1_2 = DecimalParameter(0.01, 0.6, default=0.02, space='sell', decimals=3, optimize=False, load=True)
sell_custom_pump_rsi_1_2 = DecimalParameter(36.0, 50.0, default=40.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_pump_profit_1_3 = DecimalParameter(0.02, 0.10, default=0.04, space='sell', decimals=3, optimize=False, load=True)
sell_custom_pump_rsi_1_3 = DecimalParameter(38.0, 50.0, default=42.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_pump_profit_1_4 = DecimalParameter(0.06, 0.12, default=0.1, space='sell', decimals=3, optimize=False, load=True)
sell_custom_pump_rsi_1_4 = DecimalParameter(36.0, 48.0, default=34.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_pump_profit_1_5 = DecimalParameter(0.14, 0.24, default=0.2, space='sell', decimals=3, optimize=False, load=True)
sell_custom_pump_rsi_1_5 = DecimalParameter(20.0, 40.0, default=30.0, space='sell', decimals=1, optimize=False, load=True)
# Profit targets for pumped pairs 36h 1
sell_custom_pump_profit_2_1 = DecimalParameter(0.01, 0.03, default=0.01, space='sell', decimals=3, optimize=False, load=True)
sell_custom_pump_rsi_2_1 = DecimalParameter(26.0, 40.0, default=34.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_pump_profit_2_2 = DecimalParameter(0.01, 0.6, default=0.02, space='sell', decimals=3, optimize=False, load=True)
sell_custom_pump_rsi_2_2 = DecimalParameter(36.0, 50.0, default=40.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_pump_profit_2_3 = DecimalParameter(0.02, 0.10, default=0.04, space='sell', decimals=3, optimize=False, load=True)
sell_custom_pump_rsi_2_3 = DecimalParameter(38.0, 50.0, default=42.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_pump_profit_2_4 = DecimalParameter(0.06, 0.12, default=0.1, space='sell', decimals=3, optimize=False, load=True)
sell_custom_pump_rsi_2_4 = DecimalParameter(36.0, 48.0, default=34.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_pump_profit_2_5 = DecimalParameter(0.14, 0.24, default=0.2, space='sell', decimals=3, optimize=False, load=True)
sell_custom_pump_rsi_2_5 = DecimalParameter(20.0, 40.0, default=30.0, space='sell', decimals=1, optimize=False, load=True)
# Profit targets for pumped pairs 24h 1
sell_custom_pump_profit_3_1 = DecimalParameter(0.01, 0.03, default=0.01, space='sell', decimals=3, optimize=False, load=True)
sell_custom_pump_rsi_3_1 = DecimalParameter(26.0, 40.0, default=34.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_pump_profit_3_2 = DecimalParameter(0.01, 0.6, default=0.02, space='sell', decimals=3, optimize=False, load=True)
sell_custom_pump_rsi_3_2 = DecimalParameter(34.0, 50.0, default=40.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_pump_profit_3_3 = DecimalParameter(0.02, 0.10, default=0.04, space='sell', decimals=3, optimize=False, load=True)
sell_custom_pump_rsi_3_3 = DecimalParameter(38.0, 50.0, default=42.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_pump_profit_3_4 = DecimalParameter(0.06, 0.12, default=0.1, space='sell', decimals=3, optimize=False, load=True)
sell_custom_pump_rsi_3_4 = DecimalParameter(36.0, 48.0, default=34.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_pump_profit_3_5 = DecimalParameter(0.14, 0.24, default=0.2, space='sell', decimals=3, optimize=False, load=True)
sell_custom_pump_rsi_3_5 = DecimalParameter(20.0, 40.0, default=30.0, space='sell', decimals=1, optimize=False, load=True)
# SMA descending
sell_custom_dec_profit_min_1 = DecimalParameter(0.01, 0.10, default=0.05, space='sell', decimals=3, optimize=False, load=True)
sell_custom_dec_profit_max_1 = DecimalParameter(0.06, 0.16, default=0.12, space='sell', decimals=3, optimize=False, load=True)
# Under EMA100
sell_custom_dec_profit_min_2 = DecimalParameter(0.05, 0.12, default=0.07, space='sell', decimals=3, optimize=False, load=True)
sell_custom_dec_profit_max_2 = DecimalParameter(0.06, 0.2, default=0.16, space='sell', decimals=3, optimize=False, load=True)
# Trail 1
sell_trail_profit_min_1 = DecimalParameter(0.1, 0.2, default=0.03, space='sell', decimals=2, optimize=False, load=True)
sell_trail_profit_max_1 = DecimalParameter(0.4, 0.7, default=0.05, space='sell', decimals=2, optimize=False, load=True)
sell_trail_down_1 = DecimalParameter(0.01, 0.08, default=0.05, space='sell', decimals=3, optimize=False, load=True)
sell_trail_rsi_min_1 = DecimalParameter(16.0, 36.0, default=10.0, space='sell', decimals=1, optimize=False, load=True)
sell_trail_rsi_max_1 = DecimalParameter(30.0, 50.0, default=20.0, space='sell', decimals=1, optimize=False, load=True)
# Trail 2
sell_trail_profit_min_2 = DecimalParameter(0.08, 0.16, default=0.1, space='sell', decimals=3, optimize=False, load=True)
sell_trail_profit_max_2 = DecimalParameter(0.3, 0.5, default=0.4, space='sell', decimals=2, optimize=False, load=True)
sell_trail_down_2 = DecimalParameter(0.02, 0.08, default=0.03, space='sell', decimals=3, optimize=False, load=True)
sell_trail_rsi_min_2 = DecimalParameter(16.0, 36.0, default=20.0, space='sell', decimals=1, optimize=False, load=True)
sell_trail_rsi_max_2 = DecimalParameter(30.0, 50.0, default=50.0, space='sell', decimals=1, optimize=False, load=True)
# Trail 3
sell_trail_profit_min_3 = DecimalParameter(0.01, 0.12, default=0.06, space='sell', decimals=3, optimize=False, load=True)
sell_trail_profit_max_3 = DecimalParameter(0.1, 0.3, default=0.2, space='sell', decimals=2, optimize=False, load=True)
sell_trail_down_3 = DecimalParameter(0.01, 0.06, default=0.05, space='sell', decimals=3, optimize=False, load=True)
# Trail 4
sell_trail_profit_min_4 = DecimalParameter(0.01, 0.12, default=0.03, space='sell', decimals=3, optimize=False, load=True)
sell_trail_profit_max_4 = DecimalParameter(0.02, 0.1, default=0.06, space='sell', decimals=2, optimize=False, load=True)
sell_trail_down_4 = DecimalParameter(0.01, 0.06, default=0.02, space='sell', decimals=3, optimize=False, load=True)
# Under & near EMA200, accept profit
sell_custom_profit_under_profit_min_1 = DecimalParameter(0.0, 0.01, default=0.0, space='sell', optimize=False, load=True)
sell_custom_profit_under_profit_max_1 = DecimalParameter(0.0, 0.05, default=0.02, space='sell', optimize=False, load=True)
sell_custom_profit_under_rel_1 = DecimalParameter(0.01, 0.04, default=0.024, space='sell', optimize=False, load=True)
sell_custom_profit_under_rsi_diff_1 = DecimalParameter(0.0, 20.0, default=4.4, space='sell', optimize=False, load=True)
sell_custom_profit_under_profit_2 = DecimalParameter(0.0, 0.05, default=0.03, space='sell', optimize=False, load=True)
sell_custom_profit_under_rel_2 = DecimalParameter(0.01, 0.04, default=0.024, space='sell', optimize=False, load=True)
sell_custom_profit_under_rsi_diff_2 = DecimalParameter(0.0, 20.0, default=4.4, space='sell', optimize=False, load=True)
# Under & near EMA200, take the loss
sell_custom_stoploss_under_rel_1 = DecimalParameter(0.001, 0.02, default=0.002, space='sell', optimize=False, load=True)
sell_custom_stoploss_under_rsi_diff_1 = DecimalParameter(0.0, 20.0, default=10.0, space='sell', optimize=False, load=True)
# Long duration/recover stoploss 1
sell_custom_stoploss_long_profit_min_1 = DecimalParameter(-0.1, -0.02, default=-0.08, space='sell', optimize=False, load=True)
sell_custom_stoploss_long_profit_max_1 = DecimalParameter(-0.06, -0.01, default=-0.04, space='sell', optimize=False, load=True)
sell_custom_stoploss_long_recover_1 = DecimalParameter(0.05, 0.15, default=0.14, space='sell', optimize=False, load=True)
sell_custom_stoploss_long_rsi_diff_1 = DecimalParameter(0.0, 20.0, default=4.0, space='sell', optimize=False, load=True)
# Long duration/recover stoploss 2
sell_custom_stoploss_long_recover_2 = DecimalParameter(0.03, 0.15, default=0.06, space='sell', optimize=False, load=True)
sell_custom_stoploss_long_rsi_diff_2 = DecimalParameter(30.0, 50.0, default=40.0, space='sell', optimize=False, load=True)
# Pumped, descending SMA
sell_custom_pump_dec_profit_min_1 = DecimalParameter(0.001, 0.04, default=0.005, space='sell', decimals=3, optimize=False, load=True)
sell_custom_pump_dec_profit_max_1 = DecimalParameter(0.03, 0.08, default=0.05, space='sell', decimals=3, optimize=False, load=True)
sell_custom_pump_dec_profit_min_2 = DecimalParameter(0.01, 0.08, default=0.04, space='sell', decimals=3, optimize=False, load=True)
sell_custom_pump_dec_profit_max_2 = DecimalParameter(0.04, 0.1, default=0.06, space='sell', decimals=3, optimize=False, load=True)
sell_custom_pump_dec_profit_min_3 = DecimalParameter(0.02, 0.1, default=0.06, space='sell', decimals=3, optimize=False, load=True)
sell_custom_pump_dec_profit_max_3 = DecimalParameter(0.06, 0.12, default=0.09, space='sell', decimals=3, optimize=False, load=True)
sell_custom_pump_dec_profit_min_4 = DecimalParameter(0.01, 0.05, default=0.02, space='sell', decimals=3, optimize=False, load=True)
sell_custom_pump_dec_profit_max_4 = DecimalParameter(0.02, 0.1, default=0.04, space='sell', decimals=3, optimize=False, load=True)
# Pumped 48h 1, under EMA200
sell_custom_pump_under_profit_min_1 = DecimalParameter(0.02, 0.06, default=0.04, space='sell', decimals=3, optimize=False, load=True)
sell_custom_pump_under_profit_max_1 = DecimalParameter(0.04, 0.1, default=0.09, space='sell', decimals=3, optimize=False, load=True)
# Pumped trail 1
sell_custom_pump_trail_profit_min_1 = DecimalParameter(0.01, 0.12, default=0.05, space='sell', decimals=3, optimize=False, load=True)
sell_custom_pump_trail_profit_max_1 = DecimalParameter(0.06, 0.16, default=0.07, space='sell', decimals=2, optimize=False, load=True)
sell_custom_pump_trail_down_1 = DecimalParameter(0.01, 0.06, default=0.05, space='sell', decimals=3, optimize=False, load=True)
sell_custom_pump_trail_rsi_min_1 = DecimalParameter(16.0, 36.0, default=20.0, space='sell', decimals=1, optimize=False, load=True)
sell_custom_pump_trail_rsi_max_1 = DecimalParameter(30.0, 50.0, default=70.0, space='sell', decimals=1, optimize=False, load=True)
# Stoploss, pumped, 48h 1
sell_custom_stoploss_pump_max_profit_1 = DecimalParameter(0.01, 0.04, default=0.01, space='sell', decimals=3, optimize=False, load=True)
sell_custom_stoploss_pump_min_1 = DecimalParameter(-0.1, -0.01, default=-0.02, space='sell', decimals=3, optimize=False, load=True)
sell_custom_stoploss_pump_max_1 = DecimalParameter(-0.1, -0.01, default=-0.01, space='sell', decimals=3, optimize=False, load=True)
sell_custom_stoploss_pump_ma_offset_1 = DecimalParameter(0.7, 0.99, default=0.94, space='sell', decimals=2, optimize=False, load=True)
# Stoploss, pumped, 48h 1
sell_custom_stoploss_pump_max_profit_2 = DecimalParameter(0.01, 0.04, default=0.025, space='sell', decimals=3, optimize=False, load=True)
sell_custom_stoploss_pump_loss_2 = DecimalParameter(-0.1, -0.01, default=-0.05, space='sell', decimals=3, optimize=False, load=True)
sell_custom_stoploss_pump_ma_offset_2 = DecimalParameter(0.7, 0.99, default=0.92, space='sell', decimals=2, optimize=False, load=True)
# Stoploss, pumped, 36h 3
sell_custom_stoploss_pump_max_profit_3 = DecimalParameter(0.01, 0.04, default=0.008, space='sell', decimals=3, optimize=False, load=True)
sell_custom_stoploss_pump_loss_3 = DecimalParameter(-0.16, -0.06, default=-0.12, space='sell', decimals=3, optimize=False, load=True)
sell_custom_stoploss_pump_ma_offset_3 = DecimalParameter(0.7, 0.99, default=0.88, space='sell', decimals=2, optimize=False, load=True)
# Recover
sell_custom_recover_profit_1 = DecimalParameter(0.01, 0.06, default=0.06, space='sell', decimals=3, optimize=False, load=True)
sell_custom_recover_min_loss_1 = DecimalParameter(0.06, 0.16, default=0.12, space='sell', decimals=3, optimize=False, load=True)
sell_custom_recover_profit_min_2 = DecimalParameter(0.01, 0.04, default=0.01, space='sell', decimals=3, optimize=False, load=True)
sell_custom_recover_profit_max_2 = DecimalParameter(0.02, 0.08, default=0.05, space='sell', decimals=3, optimize=False, load=True)
sell_custom_recover_min_loss_2 = DecimalParameter(0.04, 0.16, default=0.06, space='sell', decimals=3, optimize=False, load=True)
sell_custom_recover_rsi_2 = DecimalParameter(32.0, 52.0, default=46.0, space='sell', decimals=1, optimize=False, load=True)
# Profit for long duration trades
sell_custom_long_profit_min_1 = DecimalParameter(0.01, 0.04, default=0.03, space='sell', decimals=3, optimize=False, load=True)
sell_custom_long_profit_max_1 = DecimalParameter(0.02, 0.08, default=0.04, space='sell', decimals=3, optimize=False, load=True)
sell_custom_long_duration_min_1 = IntParameter(700, 2000, default=900, space='sell', optimize=False, load=True)
#############################################################
hold_trade_ids = None
@staticmethod
def get_hold_trades_config_file():
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():
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():
return hold_trades_config_file_absolute
if hold_trades_config_file_resolve != hold_trades_config_file_absolute:
looked_in = f"'{hold_trades_config_file_resolve}' and '{hold_trades_config_file_absolute}'"
else:
looked_in = f"'{hold_trades_config_file_resolve}'"
log.warning(
"The 'hold-trades.json' file was not found. Looked in %s. HOLD support disabled.",
looked_in
)
def load_hold_trades_config(self):
if self.hold_trade_ids is not None:
# Already loaded
return
# Default Values
self.hold_trade_ids = {}
# Update values from config file, if it exists
hold_trades_config_file = NostalgiaForInfinityNext_ChangeToTower_V6.get_hold_trades_config_file()
if not hold_trades_config_file:
return
with hold_trades_config_file.open('r') as f:
trade_ids = None
hold_trades_config = None
try:
hold_trades_config = json_load(f)
except rapidjson.JSONDecodeError as exc:
log.error("Failed to load JSON from %s: %s", hold_trades_config_file, exc)
else:
trade_ids = hold_trades_config.get("trade_ids")
if not trade_ids:
return
open_trades = {
trade.id: trade for trade in Trade.get_trades_proxy(is_open=True)
}
if isinstance(trade_ids, dict):
# New syntax
for trade_id, profit_ratio in trade_ids.items():
try:
trade_id = int(trade_id)
except ValueError:
log.error(
"The trade_id(%s) defined under 'trade_ids' in %s is not an integer",
trade_id, hold_trades_config_file
)
continue
if not isinstance(profit_ratio, float):
log.error(
"The 'profit_ratio' config value(%s) for trade_id %s in %s is not a float",
profit_ratio,
trade_id,
hold_trades_config_file
)
if trade_id in open_trades:
formatted_profit_ratio = "{}%".format(profit_ratio * 100)
log.warning(
"The trade %s is configured to HOLD until the profit ratio of %s is met",
open_trades[trade_id],
formatted_profit_ratio
)
self.hold_trade_ids[trade_id] = profit_ratio
else:
log.warning(
"The trade_id(%s) is no longer open. Please remove it from 'trade_ids' in %s",
trade_id,
hold_trades_config_file
)
else:
# Initial Syntax
profit_ratio = hold_trades_config.get("profit_ratio")
if profit_ratio:
if not isinstance(profit_ratio, float):
log.error(
"The 'profit_ratio' config value(%s) in %s is not a float",
profit_ratio,
hold_trades_config_file
)
else:
profit_ratio = 0.005
formatted_profit_ratio = "{}%".format(profit_ratio * 100)
for trade_id in trade_ids:
if not isinstance(trade_id, int):
log.error(
"The trade_id(%s) defined under 'trade_ids' in %s is not an integer",
trade_id, hold_trades_config_file
)
continue
if trade_id in open_trades:
log.warning(
"The trade %s is configured to HOLD until the profit ratio of %s is met",
open_trades[trade_id],
formatted_profit_ratio
)
self.hold_trade_ids[trade_id] = profit_ratio
else:
log.warning(
"The trade_id(%s) is no longer open. Please remove it from 'trade_ids' in %s",
trade_id,
hold_trades_config_file
)
def bot_loop_start(self, **kwargs) -> None:
"""
Called at the start of the bot iteration (one loop).
Might be used to perform pair-independent tasks
(e.g. gather some remote resource for comparison)
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
"""
if self.config['runmode'].value in ('live', 'dry_run'):
self.load_hold_trades_config()
return super().bot_loop_start(**kwargs)
def get_ticker_indicator(self):
return int(self.timeframe[:-1])
def sell_over_main(self, current_profit: float, last_candle) -> tuple:
if last_candle['close'] > last_candle['ema_200']:
if (last_candle['moderi_96']):
if current_profit >= self.sell_custom_profit_bull_11.value:
if last_candle['rsi_14'] < self.sell_custom_rsi_under_bull_11.value:
return True, 'signal_profit_o_bull_11'
elif self.sell_custom_profit_bull_11.value > current_profit >= self.sell_custom_profit_bull_10.value:
if last_candle['rsi_14'] < self.sell_custom_rsi_under_bull_10.value:
return True, 'signal_profit_o_bull_10'
elif self.sell_custom_profit_bull_10.value > current_profit >= self.sell_custom_profit_bull_9.value:
if last_candle['rsi_14'] < self.sell_custom_rsi_under_bull_9.value:
return True, 'signal_profit_o_bull_9'
elif self.sell_custom_profit_bull_9.value > current_profit >= self.sell_custom_profit_bull_8.value:
if last_candle['rsi_14'] < self.sell_custom_rsi_under_bull_8.value:
return True, 'signal_profit_o_bull_8'
elif self.sell_custom_profit_bull_8.value > current_profit >= self.sell_custom_profit_bull_7.value:
if (last_candle['rsi_14'] < self.sell_custom_rsi_under_bull_7.value):
return True, 'signal_profit_o_bull_7'
elif self.sell_custom_profit_bull_7.value > current_profit >= self.sell_custom_profit_bull_6.value:
if (last_candle['rsi_14'] < self.sell_custom_rsi_under_bull_6.value) and (last_candle['cmf'] < 0.0):
return True, 'signal_profit_o_bull_6'
elif self.sell_custom_profit_bull_6.value > current_profit >= self.sell_custom_profit_bull_5.value:
if (last_candle['rsi_14'] < self.sell_custom_rsi_under_bull_5.value) and (last_candle['cmf'] < 0.0):
return True, 'signal_profit_o_bull_5'
elif self.sell_custom_profit_bull_5.value > current_profit >= self.sell_custom_profit_bull_4.value:
if (last_candle['rsi_14'] < self.sell_custom_rsi_under_bull_4.value) and (last_candle['cmf'] < 0.0) :
return True, 'signal_profit_o_bull_4'
elif self.sell_custom_profit_bull_4.value > current_profit >= self.sell_custom_profit_bull_3.value:
if (last_candle['rsi_14'] < self.sell_custom_rsi_under_bull_3.value) and (last_candle['cmf'] < 0.0):
return True, 'signal_profit_o_bull_3'
elif self.sell_custom_profit_bull_3.value > current_profit >= self.sell_custom_profit_bull_2.value:
if (last_candle['rsi_14'] < self.sell_custom_rsi_under_bull_2.value) and (last_candle['cmf'] < 0.0):
return True, 'signal_profit_o_bull_2'
elif self.sell_custom_profit_bull_2.value > current_profit >= self.sell_custom_profit_bull_1.value:
if (last_candle['rsi_14'] < self.sell_custom_rsi_under_bull_1.value) and (last_candle['cmf'] < 0.0):
return True, 'signal_profit_o_bull_1'
elif self.sell_custom_profit_bull_1.value > current_profit >= self.sell_custom_profit_bull_0.value:
if (last_candle['rsi_14'] < self.sell_custom_rsi_under_bull_0.value) and (last_candle['cmf'] < 0.0):
return True, 'signal_profit_o_bull_0'
else:
if current_profit >= self.sell_custom_profit_bear_11.value:
if last_candle['rsi_14'] < self.sell_custom_rsi_under_bear_11.value:
return True, 'signal_profit_o_bear_11'
elif self.sell_custom_profit_bear_11.value > current_profit >= self.sell_custom_profit_bear_10.value:
if last_candle['rsi_14'] < self.sell_custom_rsi_under_bear_10.value:
return True, 'signal_profit_o_bear_10'
elif self.sell_custom_profit_bear_10.value > current_profit >= self.sell_custom_profit_bear_9.value:
if last_candle['rsi_14'] < self.sell_custom_rsi_under_bear_9.value:
return True, 'signal_profit_o_bear_9'
elif self.sell_custom_profit_bear_9.value > current_profit >= self.sell_custom_profit_bear_8.value:
if last_candle['rsi_14'] < self.sell_custom_rsi_under_bear_8.value:
return True, 'signal_profit_o_bear_8_1'
elif (last_candle['rsi_14'] > self.sell_custom_rsi_over_bear_8.value):
return True, 'signal_profit_o_bear_8_2'
elif self.sell_custom_profit_bear_8.value > current_profit >= self.sell_custom_profit_bear_7.value:
if (last_candle['rsi_14'] < self.sell_custom_rsi_under_bear_7.value):
return True, 'signal_profit_o_bear_7_1'
elif (last_candle['rsi_14'] > self.sell_custom_rsi_over_bear_7.value):
return True, 'signal_profit_o_bear_7_2'
elif self.sell_custom_profit_bear_7.value > current_profit >= self.sell_custom_profit_bear_6.value:
if (last_candle['rsi_14'] < self.sell_custom_rsi_under_bear_6.value):
return True, 'signal_profit_o_bear_6_1'
elif (last_candle['rsi_14'] > self.sell_custom_rsi_over_bear_6.value):
return True, 'signal_profit_o_bear_6_2'
elif self.sell_custom_profit_bear_6.value > current_profit >= self.sell_custom_profit_bear_5.value:
if (last_candle['rsi_14'] < self.sell_custom_rsi_under_bear_5.value):
return True, 'signal_profit_o_bear_5_1'
elif (last_candle['rsi_14'] > self.sell_custom_rsi_over_bear_5.value):
return True, 'signal_profit_o_bear_5_2'
elif self.sell_custom_profit_bear_5.value > current_profit >= self.sell_custom_profit_bear_4.value:
if (last_candle['rsi_14'] < self.sell_custom_rsi_under_bear_4.value):
return True, 'signal_profit_o_bear_4'
elif self.sell_custom_profit_bear_4.value > current_profit >= self.sell_custom_profit_bear_3.value:
if (last_candle['rsi_14'] < self.sell_custom_rsi_under_bear_3.value) and (last_candle['cmf'] < 0.0):
return True, 'signal_profit_o_bear_3'
elif self.sell_custom_profit_bear_3.value > current_profit >= self.sell_custom_profit_bear_2.value:
if (last_candle['rsi_14'] < self.sell_custom_rsi_under_bear_2.value) and (last_candle['cmf'] < 0.0):
return True, 'signal_profit_o_bear_2'
elif self.sell_custom_profit_bear_2.value > current_profit >= self.sell_custom_profit_bear_1.value:
if (last_candle['rsi_14'] < self.sell_custom_rsi_under_bear_1.value) and (last_candle['cmf'] < 0.0):
return True, 'signal_profit_o_bear_1'
elif self.sell_custom_profit_bear_1.value > current_profit >= self.sell_custom_profit_bear_0.value:
if (last_candle['rsi_14'] < self.sell_custom_rsi_under_bear_0.value) and (last_candle['cmf'] < 0.0):
return True, 'signal_profit_o_bear_0'
return False, None
def sell_under_main(self, current_profit: float, last_candle) -> tuple:
if last_candle['close'] < last_candle['ema_200']:
if (last_candle['moderi_96']):
if current_profit >= self.sell_custom_under_profit_bull_11.value:
if last_candle['rsi_14'] < self.sell_custom_under_rsi_under_bull_11.value:
return True, 'signal_profit_u_bull_11'
elif self.sell_custom_under_profit_bull_11.value > current_profit >= self.sell_custom_under_profit_bull_10.value:
if last_candle['rsi_14'] < self.sell_custom_under_rsi_under_bull_10.value:
return True, 'signal_profit_u_bull_10'
elif self.sell_custom_under_profit_bull_10.value > current_profit >= self.sell_custom_under_profit_bull_9.value:
if last_candle['rsi_14'] < self.sell_custom_under_rsi_under_bull_9.value:
return True, 'signal_profit_u_bull_9'
elif self.sell_custom_under_profit_bull_9.value > current_profit >= self.sell_custom_under_profit_bull_8.value:
if last_candle['rsi_14'] < self.sell_custom_under_rsi_under_bull_8.value:
return True, 'signal_profit_u_bull_8'
elif self.sell_custom_under_profit_bull_8.value > current_profit >= self.sell_custom_under_profit_bull_7.value:
if last_candle['rsi_14'] < self.sell_custom_under_rsi_under_bull_7.value:
return True, 'signal_profit_u_bull_7'
elif self.sell_custom_under_profit_bull_7.value > current_profit >= self.sell_custom_under_profit_bull_6.value:
if last_candle['rsi_14'] < self.sell_custom_under_rsi_under_bull_6.value:
return True, 'signal_profit_u_bull_6'
elif self.sell_custom_under_profit_bull_6.value > current_profit >= self.sell_custom_under_profit_bull_5.value:
if last_candle['rsi_14'] < self.sell_custom_under_rsi_under_bull_5.value:
return True, 'signal_profit_u_bull_5'
elif self.sell_custom_under_profit_bull_5.value > current_profit >= self.sell_custom_under_profit_bull_4.value:
if last_candle['rsi_14'] < self.sell_custom_under_rsi_under_bull_4.value:
return True, 'signal_profit_u_bull_4'
elif self.sell_custom_under_profit_bull_4.value > current_profit >= self.sell_custom_under_profit_bull_3.value:
if last_candle['rsi_14'] < self.sell_custom_under_rsi_under_bull_3.value:
return True, 'signal_profit_u_bull_3'
elif self.sell_custom_under_profit_bull_3.value > current_profit >= self.sell_custom_under_profit_bull_2.value:
if last_candle['rsi_14'] < self.sell_custom_under_rsi_under_bull_2.value:
return True, 'signal_profit_u_bull_2'
elif self.sell_custom_under_profit_bull_2.value > current_profit >= self.sell_custom_under_profit_bull_1.value:
if last_candle['rsi_14'] < self.sell_custom_under_rsi_under_bull_1.value:
return True, 'signal_profit_u_bull_1'
elif self.sell_custom_under_profit_bull_1.value > current_profit >= self.sell_custom_under_profit_bull_0.value:
if (last_candle['rsi_14'] < self.sell_custom_under_rsi_under_bull_0.value) and (last_candle['cmf'] < 0.0):
return True, 'signal_profit_u_bull_0'
else:
if current_profit >= self.sell_custom_under_profit_bear_11.value:
if last_candle['rsi_14'] < self.sell_custom_under_rsi_under_bear_11.value:
return True, 'signal_profit_u_bear_11'
elif self.sell_custom_under_profit_bear_11.value > current_profit >= self.sell_custom_under_profit_bear_10.value:
if last_candle['rsi_14'] < self.sell_custom_under_rsi_under_bear_10.value:
return True, 'signal_profit_u_bear_10'
elif self.sell_custom_under_profit_bear_10.value > current_profit >= self.sell_custom_under_profit_bear_9.value:
if last_candle['rsi_14'] < self.sell_custom_under_rsi_under_bear_9.value:
return True, 'signal_profit_u_bear_9'
elif self.sell_custom_under_profit_bear_9.value > current_profit >= self.sell_custom_under_profit_bear_8.value:
if last_candle['rsi_14'] < self.sell_custom_under_rsi_under_bear_8.value:
return True, 'signal_profit_u_bear_8_1'
elif (last_candle['rsi_14'] > self.sell_custom_under_rsi_over_bear_8.value):
return True, 'signal_profit_u_bear_8_2'
elif self.sell_custom_under_profit_bear_8.value > current_profit >= self.sell_custom_under_profit_bear_7.value:
if last_candle['rsi_14'] < self.sell_custom_under_rsi_under_bear_7.value:
return True, 'signal_profit_u_bear_7_1'
elif (last_candle['rsi_14'] > self.sell_custom_under_rsi_over_bear_7.value):
return True, 'signal_profit_u_bear_7_2'
elif self.sell_custom_under_profit_bear_7.value > current_profit >= self.sell_custom_under_profit_bear_6.value:
if last_candle['rsi_14'] < self.sell_custom_under_rsi_under_bear_6.value:
return True, 'signal_profit_u_bear_6_1'
elif (last_candle['rsi_14'] > self.sell_custom_under_rsi_over_bear_6.value):
return True, 'signal_profit_u_bear_6_2'
elif self.sell_custom_under_profit_bear_6.value > current_profit >= self.sell_custom_under_profit_bear_5.value:
if last_candle['rsi_14'] < self.sell_custom_under_rsi_under_bear_5.value:
return True, 'signal_profit_u_bear_5_1'
elif (last_candle['rsi_14'] > self.sell_custom_under_rsi_over_bear_5.value):
return True, 'signal_profit_u_bear_5_2'
elif self.sell_custom_under_profit_bear_5.value > current_profit >= self.sell_custom_under_profit_bear_4.value:
if last_candle['rsi_14'] < self.sell_custom_under_rsi_under_bear_4.value:
return True, 'signal_profit_u_bear_4'
elif self.sell_custom_under_profit_bear_4.value > current_profit >= self.sell_custom_under_profit_bear_3.value:
if last_candle['rsi_14'] < self.sell_custom_under_rsi_under_bear_3.value:
return True, 'signal_profit_u_bear_3'
elif self.sell_custom_under_profit_bear_3.value > current_profit >= self.sell_custom_under_profit_bear_2.value:
if last_candle['rsi_14'] < self.sell_custom_under_rsi_under_bear_2.value:
return True, 'signal_profit_u_bear_2'
elif self.sell_custom_under_profit_bear_2.value > current_profit >= self.sell_custom_under_profit_bear_1.value:
if last_candle['rsi_14'] < self.sell_custom_under_rsi_under_bear_1.value:
return True, 'signal_profit_u_bear_1'
elif self.sell_custom_under_profit_bear_1.value > current_profit >= self.sell_custom_under_profit_bear_0.value:
if (last_candle['rsi_14'] < self.sell_custom_under_rsi_under_bear_0.value) and (last_candle['cmf'] < 0.0):
return True, 'signal_profit_u_bear_0'
return False, None
def sell_pump_main(self, current_profit: float, last_candle) -> tuple:
if last_candle['sell_pump_48_1_1h']:
if current_profit >= self.sell_custom_pump_profit_1_5.value:
if last_candle['rsi_14'] < self.sell_custom_pump_rsi_1_5.value:
return True, 'signal_profit_p_1_5'
elif self.sell_custom_pump_profit_1_5.value > current_profit >= self.sell_custom_pump_profit_1_4.value:
if last_candle['rsi_14'] < self.sell_custom_pump_rsi_1_4.value:
return True, 'signal_profit_p_1_4'
elif self.sell_custom_pump_profit_1_4.value > current_profit >= self.sell_custom_pump_profit_1_3.value:
if last_candle['rsi_14'] < self.sell_custom_pump_rsi_1_3.value:
return True, 'signal_profit_p_1_3'
elif self.sell_custom_pump_profit_1_3.value > current_profit >= self.sell_custom_pump_profit_1_2.value:
if last_candle['rsi_14'] < self.sell_custom_pump_rsi_1_2.value:
return True, 'signal_profit_p_1_2'
elif self.sell_custom_pump_profit_1_2.value > current_profit >= self.sell_custom_pump_profit_1_1.value:
if last_candle['rsi_14'] < self.sell_custom_pump_rsi_1_1.value:
return True, 'signal_profit_p_1_1'
elif last_candle['sell_pump_36_1_1h']:
if current_profit >= self.sell_custom_pump_profit_2_5.value:
if last_candle['rsi_14'] < self.sell_custom_pump_rsi_2_5.value:
return True, 'signal_profit_p_2_5'
elif self.sell_custom_pump_profit_2_5.value > current_profit >= self.sell_custom_pump_profit_2_4.value:
if last_candle['rsi_14'] < self.sell_custom_pump_rsi_2_4.value:
return True, 'signal_profit_p_2_4'
elif self.sell_custom_pump_profit_2_4.value > current_profit >= self.sell_custom_pump_profit_2_3.value:
if last_candle['rsi_14'] < self.sell_custom_pump_rsi_2_3.value:
return True, 'signal_profit_p_2_3'
elif self.sell_custom_pump_profit_2_3.value > current_profit >= self.sell_custom_pump_profit_2_2.value:
if last_candle['rsi_14'] < self.sell_custom_pump_rsi_2_2.value:
return True, 'signal_profit_p_2_2'
elif self.sell_custom_pump_profit_2_2.value > current_profit >= self.sell_custom_pump_profit_2_1.value:
if last_candle['rsi_14'] < self.sell_custom_pump_rsi_2_1.value:
return True, 'signal_profit_p_2_1'
elif last_candle['sell_pump_24_1_1h']:
if current_profit >= self.sell_custom_pump_profit_3_5.value:
if last_candle['rsi_14'] < self.sell_custom_pump_rsi_3_5.value:
return True, 'signal_profit_p_3_5'
elif self.sell_custom_pump_profit_3_5.value > current_profit >= self.sell_custom_pump_profit_3_4.value:
if last_candle['rsi_14'] < self.sell_custom_pump_rsi_3_4.value:
return True, 'signal_profit_p_3_4'
elif self.sell_custom_pump_profit_3_4.value > current_profit >= self.sell_custom_pump_profit_3_3.value:
if last_candle['rsi_14'] < self.sell_custom_pump_rsi_3_3.value:
return True, 'signal_profit_p_3_3'
elif self.sell_custom_pump_profit_3_3.value > current_profit >= self.sell_custom_pump_profit_3_2.value:
if last_candle['rsi_14'] < self.sell_custom_pump_rsi_3_2.value:
return True, 'signal_profit_p_3_2'
elif self.sell_custom_pump_profit_3_2.value > current_profit >= self.sell_custom_pump_profit_3_1.value:
if last_candle['rsi_14'] < self.sell_custom_pump_rsi_3_1.value:
return True, 'signal_profit_p_3_1'
return False, None
def sell_dec_main(self, current_profit: float, last_candle) -> tuple:
if (self.sell_custom_dec_profit_max_1.value > current_profit >= self.sell_custom_dec_profit_min_1.value) and (last_candle['sma_200_dec_20']):
return True, 'signal_profit_d_1'
elif (self.sell_custom_dec_profit_max_2.value > current_profit >= self.sell_custom_dec_profit_min_2.value) and (last_candle['close'] < last_candle['ema_100']):
return True, 'signal_profit_d_2'
return False, None
def sell_trail_main(self, current_profit: float, last_candle, max_profit: float) -> tuple:
if (self.sell_trail_profit_max_1.value > current_profit >= self.sell_trail_profit_min_1.value) and (self.sell_trail_rsi_min_1.value < last_candle['rsi_14'] < self.sell_trail_rsi_max_1.value) and (max_profit > (current_profit + self.sell_trail_down_1.value)) and (last_candle['moderi_96'] == False):
return True, 'signal_profit_t_1'
elif (self.sell_trail_profit_max_2.value > current_profit >= self.sell_trail_profit_min_2.value) and (self.sell_trail_rsi_min_2.value < last_candle['rsi_14'] < self.sell_trail_rsi_max_2.value) and (max_profit > (current_profit + self.sell_trail_down_2.value)) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'signal_profit_t_2'
elif (self.sell_trail_profit_max_3.value > current_profit >= self.sell_trail_profit_min_3.value) and (max_profit > (current_profit + self.sell_trail_down_3.value)) and (last_candle['sma_200_dec_20_1h']):
return True, 'signal_profit_t_3'
elif (self.sell_trail_profit_max_4.value > current_profit >= self.sell_trail_profit_min_4.value) and (max_profit > (current_profit + self.sell_trail_down_4.value)) and (last_candle['sma_200_dec_24']) and (last_candle['cmf'] < 0.0):
return True, 'signal_profit_t_4'
return False, None
def sell_duration_main(self, current_profit: float, last_candle, trade: 'Trade', current_time: 'datetime') -> tuple:
# Pumped pair, short duration
if (last_candle['sell_pump_24_1_1h']) and (0.2 > current_profit >= 0.07) and (current_time - timedelta(minutes=30) < trade.open_date_utc):
return True, 'signal_profit_p_s_1'
elif (self.sell_custom_long_profit_min_1.value < current_profit < self.sell_custom_long_profit_max_1.value) and (current_time - timedelta(minutes=self.sell_custom_long_duration_min_1.value) > trade.open_date_utc):
return True, 'signal_profit_l_1'
return False, None
def sell_under_min(self, current_profit: float, last_candle) -> tuple:
if ((last_candle['moderi_96']) == False):
# Downtrend
if (self.sell_custom_profit_under_profit_max_1.value > current_profit >= self.sell_custom_profit_under_profit_min_1.value) and (last_candle['close'] < last_candle['ema_200']) and (((last_candle['ema_200'] - last_candle['close']) / last_candle['close']) < self.sell_custom_profit_under_rel_1.value) and (last_candle['rsi_14'] > last_candle['rsi_14_1h'] + self.sell_custom_profit_under_rsi_diff_1.value):
return True, 'signal_profit_u_e_1'
else:
# Uptrend
if (current_profit >= self.sell_custom_profit_under_profit_2.value) and (last_candle['close'] < last_candle['ema_200']) and (((last_candle['ema_200'] - last_candle['close']) / last_candle['close']) < self.sell_custom_profit_under_rel_2.value) and (last_candle['rsi_14'] > last_candle['rsi_14_1h'] + self.sell_custom_profit_under_rsi_diff_2.value):
return True, 'signal_profit_u_e_2'
return False, None
def sell_stoploss(self, current_profit: float, last_candle, previous_candle_1) -> tuple:
if (-0.12 <= current_profit < -0.08):
if (last_candle['close'] < last_candle['atr_high_thresh_1']) and (previous_candle_1['close'] > previous_candle_1['atr_high_thresh_1']):
return True, 'signal_stoploss_atr_1'
elif (-0.16 <= current_profit < -0.12):
if (last_candle['close'] < last_candle['atr_high_thresh_2']) and (previous_candle_1['close'] > previous_candle_1['atr_high_thresh_2']):
return True, 'signal_stoploss_atr_2'
elif (-0.2 <= current_profit < -0.16):
if (last_candle['close'] < last_candle['atr_high_thresh_3']) and (previous_candle_1['close'] > previous_candle_1['atr_high_thresh_3']):
return True, 'signal_stoploss_atr_3'
elif (current_profit < -0.2):
if (last_candle['close'] < last_candle['atr_high_thresh_4']) and (previous_candle_1['close'] > previous_candle_1['atr_high_thresh_4']):
return True, 'signal_stoploss_atr_4'
return False, None
def sell_pump_dec(self, current_profit: float, last_candle) -> tuple:
if (self.sell_custom_pump_dec_profit_max_1.value > current_profit >= self.sell_custom_pump_dec_profit_min_1.value) and (last_candle['sell_pump_48_1_1h']) and (last_candle['sma_200_dec_20']) and (last_candle['close'] < last_candle['ema_200']):
return True, 'signal_profit_p_d_1'
elif (self.sell_custom_pump_dec_profit_max_2.value > current_profit >= self.sell_custom_pump_dec_profit_min_2.value) and (last_candle['sell_pump_48_2_1h']) and (last_candle['sma_200_dec_20']) and (last_candle['close'] < last_candle['ema_200']):
return True, 'signal_profit_p_d_2'
elif (self.sell_custom_pump_dec_profit_max_3.value > current_profit >= self.sell_custom_pump_dec_profit_min_3.value) and (last_candle['sell_pump_48_3_1h']) and (last_candle['sma_200_dec_20']) and (last_candle['close'] < last_candle['ema_200']):
return True, 'signal_profit_p_d_3'
elif (self.sell_custom_pump_dec_profit_max_4.value > current_profit >= self.sell_custom_pump_dec_profit_min_4.value) and (last_candle['sma_200_dec_20']) and (last_candle['sell_pump_24_2_1h']):
return True, 'signal_profit_p_d_4'
return False, None
def sell_pump_extra(self, current_profit: float, last_candle, max_profit: float) -> tuple:
# Pumped 48h 1, under EMA200
if (self.sell_custom_pump_under_profit_max_1.value > current_profit >= self.sell_custom_pump_under_profit_min_1.value) and (last_candle['sell_pump_48_1_1h']) and (last_candle['close'] < last_candle['ema_200']):
return True, 'signal_profit_p_u_1'
# Pumped 36h 2, trail 1
elif (last_candle['sell_pump_36_2_1h']) and (self.sell_custom_pump_trail_profit_max_1.value > current_profit >= self.sell_custom_pump_trail_profit_min_1.value) and (self.sell_custom_pump_trail_rsi_min_1.value < last_candle['rsi_14'] < self.sell_custom_pump_trail_rsi_max_1.value) and (max_profit > (current_profit + self.sell_custom_pump_trail_down_1.value)):
return True, 'signal_profit_p_t_1'
return False, None
def sell_recover(self, current_profit: float, last_candle, max_loss: float) -> tuple:
if (max_loss > self.sell_custom_recover_min_loss_1.value) and (current_profit >= self.sell_custom_recover_profit_1.value):
return True, 'signal_profit_r_1'
elif (max_loss > self.sell_custom_recover_min_loss_2.value) and (self.sell_custom_recover_profit_max_2.value > current_profit >= self.sell_custom_recover_profit_min_2.value) and (last_candle['rsi_14'] < self.sell_custom_recover_rsi_2.value) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'signal_profit_r_2'
return False, None
def sell_r_1(self, current_profit: float, last_candle) -> tuple:
if 0.02 > current_profit >= 0.012:
if last_candle['r_480'] > -0.1:
return True, 'signal_profit_w_1_1'
elif 0.03 > current_profit >= 0.02:
if last_candle['r_480'] > -0.2:
return True, 'signal_profit_w_1_2'
elif 0.04 > current_profit >= 0.03:
if last_candle['r_480'] > -0.4:
return True, 'signal_profit_w_1_3'
elif 0.05 > current_profit >= 0.04:
if last_candle['r_480'] > -0.6:
return True, 'signal_profit_w_1_4'
elif 0.06 > current_profit >= 0.05:
if last_candle['r_480'] > -0.8:
return True, 'signal_profit_w_1_5'
elif 0.07 > current_profit >= 0.06:
if last_candle['r_480'] > -1.0:
return True, 'signal_profit_w_1_6'
elif 0.08 > current_profit >= 0.07:
if last_candle['r_480'] > -1.2:
return True, 'signal_profit_w_1_7'
elif 0.09 > current_profit >= 0.08:
if last_candle['r_480'] > -1.4:
return True, 'signal_profit_w_1_8'
elif 0.1 > current_profit >= 0.09:
if last_candle['r_480'] > -1.6:
return True, 'signal_profit_w_1_9'
elif 0.12 > current_profit >= 0.1:
if (last_candle['r_480'] > -2.5) and (last_candle['rsi_14'] > 72.0):
return True, 'signal_profit_w_1_10'
elif 0.2 > current_profit >= 0.12:
if (last_candle['r_480'] > -2.0) and (last_candle['rsi_14'] > 78.0):
return True, 'signal_profit_w_1_11'
elif current_profit >= 0.2:
if (last_candle['r_480'] > -1.0) and (last_candle['rsi_14'] > 80.0):
return True, 'signal_profit_w_1_12'
return False, None
def sell_r_2(self, current_profit: float, last_candle) -> tuple:
if 0.02 > current_profit >= 0.012:
if (last_candle['r_480'] > -2.0) and (last_candle['rsi_14'] > 79.0) and (last_candle['stochrsi_fastk_96'] > 99.0) and (last_candle['stochrsi_fastd_96'] > 99.0):
return True, 'signal_profit_w_2_1'
elif 0.03 > current_profit >= 0.02:
if (last_candle['r_480'] > -2.1) and (last_candle['rsi_14'] > 79.0) and (last_candle['stochrsi_fastk_96'] > 99.0) and (last_candle['stochrsi_fastd_96'] > 99.0):
return True, 'signal_profit_w_2_2'
elif 0.04 > current_profit >= 0.03:
if (last_candle['r_480'] > -2.2) and (last_candle['rsi_14'] > 79.0) and (last_candle['stochrsi_fastk_96'] > 99.0) and (last_candle['stochrsi_fastd_96'] > 99.0):
return True, 'signal_profit_w_2_3'
elif 0.05 > current_profit >= 0.04:
if (last_candle['r_480'] > -2.3) and (last_candle['rsi_14'] > 79.0) and (last_candle['stochrsi_fastk_96'] > 99.0) and (last_candle['stochrsi_fastd_96'] > 99.0):
return True, 'signal_profit_w_2_4'
elif 0.06 > current_profit >= 0.05:
if (last_candle['r_480'] > -2.4) and (last_candle['rsi_14'] > 79.0) and (last_candle['stochrsi_fastk_96'] > 99.0) and (last_candle['stochrsi_fastd_96'] > 99.0):
return True, 'signal_profit_w_2_5'
elif 0.07 > current_profit >= 0.06:
if (last_candle['r_480'] > -2.5) and (last_candle['rsi_14'] > 79.0) and (last_candle['stochrsi_fastk_96'] > 99.0) and (last_candle['stochrsi_fastd_96'] > 99.0):
return True, 'signal_profit_w_2_6'
elif 0.08 > current_profit >= 0.07:
if (last_candle['r_480'] > -3.0) and (last_candle['rsi_14'] > 80.0) and (last_candle['stochrsi_fastk_96'] > 99.0) and (last_candle['stochrsi_fastd_96'] > 99.0):
return True, 'signal_profit_w_2_7'
elif 0.09 > current_profit >= 0.08:
if (last_candle['r_480'] > -3.0) and (last_candle['rsi_14'] > 80.5) and (last_candle['stochrsi_fastk_96'] > 99.0) and (last_candle['stochrsi_fastd_96'] > 99.0):
return True, 'signal_profit_w_2_8'
elif 0.1 > current_profit >= 0.09:
if (last_candle['r_480'] > -2.8) and (last_candle['rsi_14'] > 80.5) and (last_candle['stochrsi_fastk_96'] > 99.0) and (last_candle['stochrsi_fastd_96'] > 99.0):
return True, 'signal_profit_w_2_9'
elif 0.12 > current_profit >= 0.1:
if (last_candle['r_480'] > -2.4) and (last_candle['rsi_14'] > 80.5) and (last_candle['stochrsi_fastk_96'] > 99.0) and (last_candle['stochrsi_fastd_96'] > 99.0):
return True, 'signal_profit_w_2_10'
elif 0.2 > current_profit >= 0.12:
if (last_candle['r_480'] > -2.2) and (last_candle['rsi_14'] > 81.0) and (last_candle['stochrsi_fastk_96'] > 99.0) and (last_candle['stochrsi_fastd_96'] > 99.0):
return True, 'signal_profit_w_2_11'
elif current_profit >= 0.2:
if (last_candle['r_480'] > -2.0) and (last_candle['rsi_14'] > 81.5) and (last_candle['stochrsi_fastk_96'] > 99.0) and (last_candle['stochrsi_fastd_96'] > 99.0):
return True, 'signal_profit_w_2_12'
return False, None
def sell_r_3(self, current_profit: float, last_candle) -> tuple:
if 0.02 > current_profit >= 0.012:
if (last_candle['r_480'] > -1.0) and (last_candle['rsi_14'] > 74.0) and (last_candle['stochrsi_fastk_96'] > 99.0) and (last_candle['stochrsi_fastd_96'] > 99.0):
return True, 'signal_profit_w_3_1'
elif 0.03 > current_profit >= 0.02:
if (last_candle['r_480'] > -1.5) and (last_candle['rsi_14'] > 74.0) and (last_candle['stochrsi_fastk_96'] > 99.0) and (last_candle['stochrsi_fastd_96'] > 99.0):
return True, 'signal_profit_w_3_2'
elif 0.04 > current_profit >= 0.03:
if (last_candle['r_480'] > -2.0) and (last_candle['rsi_14'] > 74.0) and (last_candle['stochrsi_fastk_96'] > 99.0) and (last_candle['stochrsi_fastd_96'] > 99.0):
return True, 'signal_profit_w_3_3'
elif 0.05 > current_profit >= 0.04:
if (last_candle['r_480'] > -3.0) and (last_candle['rsi_14'] > 79.0) and (last_candle['stochrsi_fastk_96'] > 99.0) and (last_candle['stochrsi_fastd_96'] > 99.0):
return True, 'signal_profit_w_3_4'
return False, None
def sell_r_4(self, current_profit: float, last_candle) -> tuple:
if (0.02 > current_profit >= 0.012):
if (last_candle['r_480'] > -1.0) and (last_candle['rsi_14'] > 68.0) and (last_candle['cti'] > 0.9):
return True, 'signal_profit_w_4_1'
elif (0.03 > current_profit >= 0.02):
if (last_candle['r_480'] > -1.5) and (last_candle['rsi_14'] > 68.0) and (last_candle['cti'] > 0.9):
return True, 'signal_profit_w_4_2'
elif (0.04 > current_profit >= 0.03):
if (last_candle['r_480'] > -2.0) and (last_candle['rsi_14'] > 68.0) and (last_candle['cti'] > 0.9):
return True, 'signal_profit_w_4_3'
elif (0.05 > current_profit >= 0.04):
if (last_candle['r_480'] > -2.5) and (last_candle['rsi_14'] > 68.0) and (last_candle['cti'] > 0.9):
return True, 'signal_profit_w_4_4'
elif (0.06 > current_profit >= 0.05):
if (last_candle['r_480'] > -3.0) and (last_candle['rsi_14'] > 68.0) and (last_candle['cti'] > 0.9):
return True, 'signal_profit_w_4_5'
elif (0.07 > current_profit >= 0.06):
if (last_candle['r_480'] > -3.5) and (last_candle['rsi_14'] > 79.0) and (last_candle['cti'] > 0.9):
return True, 'signal_profit_w_4_6'
elif (0.08 > current_profit >= 0.07):
if (last_candle['r_480'] > -4.0) and (last_candle['rsi_14'] > 79.0) and (last_candle['cti'] > 0.9):
return True, 'signal_profit_w_4_7'
elif (0.09 > current_profit >= 0.08):
if (last_candle['r_480'] > -4.5) and (last_candle['rsi_14'] > 79.0) and (last_candle['cti'] > 0.9):
return True, 'signal_profit_w_4_8'
elif (0.1 > current_profit >= 0.09):
if (last_candle['r_480'] > -3.0) and (last_candle['rsi_14'] > 79.0) and (last_candle['cti'] > 0.9):
return True, 'signal_profit_w_4_9'
elif (0.12 > current_profit >= 0.1):
if (last_candle['r_480'] > -2.0) and (last_candle['rsi_14'] > 79.0) and (last_candle['cti'] > 0.9):
return True, 'signal_profit_w_4_10'
elif (0.2 > current_profit >= 0.12):
if (last_candle['r_480'] > -2.0) and (last_candle['rsi_14'] > 80.0) and (last_candle['cti'] > 0.9):
return True, 'signal_profit_w_4_11'
elif (current_profit >= 0.2):
if (last_candle['r_480'] > -2.0) and (last_candle['rsi_14'] > 80.0) and (last_candle['cti'] > 0.9):
return True, 'signal_profit_w_4_12'
return False, None
def sell_quick_mode(self, current_profit: float, max_profit:float, last_candle, previous_candle_1, trade: 'Trade', current_time: 'datetime') -> tuple:
if (0.06 > current_profit > 0.02) and (last_candle['rsi_14'] > 79.0):
return True, 'signal_profit_q_1'
if (0.06 > current_profit > 0.02) and (last_candle['cti'] > 0.9):
return True, 'signal_profit_q_2'
if (last_candle['close'] < last_candle['atr_high_thresh_q']) and (previous_candle_1['close'] > previous_candle_1['atr_high_thresh_q']):
if (current_profit > 0.0):
return True, 'signal_profit_q_atr'
elif (current_profit < -0.05):
return True, 'signal_stoploss_q_atr'
if (current_profit > 0.0):
if (last_candle['pm'] <= last_candle['pmax_thresh']) and (last_candle['close'] > last_candle['sma_21'] * 1.1):
return True, 'signal_profit_q_pmax_bull'
if (last_candle['pm'] > last_candle['pmax_thresh']) and (last_candle['close'] > last_candle['sma_21'] * 1.014):
return True, 'signal_profit_q_pmax_bear'
if (last_candle['zlema_4'] > last_candle['zlema_1']) and (previous_candle_1['zlema_4'] < previous_candle_1['zlema_1']) and (last_candle['cci'] > -100) and (last_candle['hrsi'] > 70) and (current_profit > 0):
return True, 'signal_profit_zlema'
# if ((max_profit - current_profit) > 0.01) and (current_profit > 0.00):
# return True, 'quick_trailing'
return False, None
def sell_ichi(self, current_profit: float, max_profit:float, max_loss:float, last_candle, previous_candle_1, trade: 'Trade', current_time: 'datetime') -> tuple:
if (-0.03 < current_profit < 0.05) and (current_time - timedelta(minutes=1440) > trade.open_date_utc) and (last_candle['rsi_14'] > 75):
return True, 'signal_ichi_underwater'
if (max_loss > 0.07) and (current_profit > 0.02):
return True, 'signal_ichi_recover_0'
if (max_loss > 0.06) and (current_profit > 0.03):
return True, 'signal_ichi_recover_1'
if (max_loss > 0.05) and (current_profit > 0.04):
return True, 'signal_ichi_recover_2'
if (max_loss > 0.04) and (current_profit > 0.05):
return True, 'signal_ichi_recover_3'
if (max_loss > 0.03) and (current_profit > 0.06):
return True, 'signal_ichi_recover_4'
if (0.05 < current_profit < 0.1) and (current_time - timedelta(minutes=720) > trade.open_date_utc):
return True, 'signal_ichi_slow_trade'
if (0.07 < current_profit < 0.1) and (max_profit-current_profit > 0.025) and (max_profit > 0.1):
return True, 'signal_ichi_trailing'
if (current_profit < -0.1):
return True, 'signal_ichi_stoploss'
if (last_candle['zlema_4'] > last_candle['zlema_1']) and (previous_candle_1['zlema_4'] < previous_candle_1['zlema_1']) and (last_candle['cci'] > 100) and (last_candle['hrsi'] > 85) and (current_profit > 0):
return True, 'signal_ichi_zlema'
return False, None
def custom_sell(self, pair: str, trade: 'Trade', current_time: 'datetime', current_rate: float,
current_profit: float, **kwargs):
dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
last_candle = dataframe.iloc[-1]
previous_candle_1 = dataframe.iloc[-2]
previous_candle_2 = dataframe.iloc[-3]
previous_candle_3 = dataframe.iloc[-4]
previous_candle_4 = dataframe.iloc[-5]
previous_candle_5 = dataframe.iloc[-6]
buy_tag = 'empty'
if hasattr(trade, 'buy_tag') and trade.buy_tag is not None:
buy_tag = trade.buy_tag
else:
trade_open_date = timeframe_to_prev_date(self.timeframe, trade.open_date_utc)
buy_signal = dataframe.loc[dataframe['date'] < trade_open_date]
if not buy_signal.empty:
buy_signal_candle = buy_signal.iloc[-1]
buy_tag = buy_signal_candle['buy_tag'] if buy_signal_candle['buy_tag'] != '' else 'empty'
buy_tags = buy_tag.split()
max_profit = ((trade.max_rate - trade.open_rate) / trade.open_rate)
max_loss = ((trade.open_rate - trade.min_rate) / trade.min_rate)
# Quick sell mode
if all(c in ['32', '33', '34', '35', '36', '37', '38', '40'] for c in buy_tags):
sell, signal_name = self.sell_quick_mode(current_profit, max_profit, last_candle, previous_candle_1, trade, current_time)
if sell and (signal_name is not None):
return signal_name + ' ( ' + buy_tag + ')'
# Ichi Trade management
if all(c in ['39'] for c in buy_tags):
sell, signal_name = self.sell_ichi(current_profit, max_profit, max_loss, last_candle, previous_candle_1, trade, current_time)
if sell and (signal_name is not None):
return signal_name + ' ( ' + buy_tag + ')'
# Over EMA200, main profit targets
sell, signal_name = self.sell_over_main(current_profit, last_candle)
if sell and (signal_name is not None):
return signal_name + ' ( ' + buy_tag + ')'
# Under EMA200, main profit targets
sell, signal_name = self.sell_under_main(current_profit, last_candle)
if sell and (signal_name is not None):
return signal_name + ' ( ' + buy_tag + ')'
# The pair is pumped
sell, signal_name = self.sell_pump_main(current_profit, last_candle)
if sell and (signal_name is not None):
return signal_name + ' ( ' + buy_tag + ')'
# The pair is descending
sell, signal_name = self.sell_dec_main(current_profit, last_candle)
if sell and (signal_name is not None):
return signal_name + ' ( ' + buy_tag + ')'
# Trailing
sell, signal_name = self.sell_trail_main(current_profit, last_candle, max_profit)
if sell and (signal_name is not None):
return signal_name + ' ( ' + buy_tag + ')'
# Duration based
sell, signal_name = self.sell_duration_main(current_profit, last_candle, trade, current_time)
if sell and (signal_name is not None):
return signal_name + ' ( ' + buy_tag + ')'
# Under EMA200, exit with any profit
sell, signal_name = self.sell_under_min(current_profit, last_candle)
if sell and (signal_name is not None):
return signal_name + ' ( ' + buy_tag + ')'
# Stoplosses
sell, signal_name = self.sell_stoploss(current_profit, last_candle, previous_candle_1)
if sell and (signal_name is not None):
return signal_name + ' ( ' + buy_tag + ')'
# Pumped descending pairs
sell, signal_name = self.sell_pump_dec(current_profit, last_candle)
if sell and (signal_name is not None):
return signal_name + ' ( ' + buy_tag + ')'
# Extra sells for pumped pairs
sell, signal_name = self.sell_pump_extra(current_profit, last_candle, max_profit)
if sell and (signal_name is not None):
return signal_name + ' ( ' + buy_tag + ')'
# Extra sells for trades that recovered
sell, signal_name = self.sell_recover(current_profit, last_candle, max_loss)
if sell and (signal_name is not None):
return signal_name + ' ( ' + buy_tag + ')'
# Williams %R based sell 1
sell, signal_name = self.sell_r_1(current_profit, last_candle)
if sell and (signal_name is not None):
return signal_name + ' ( ' + buy_tag + ')'
# Williams %R based sell 2
sell, signal_name = self.sell_r_2(current_profit, last_candle)
if sell and (signal_name is not None):
return signal_name + ' ( ' + buy_tag + ')'
# Williams %R based sell 3
sell, signal_name = self.sell_r_3(current_profit, last_candle)
if sell and (signal_name is not None):
return signal_name + ' ( ' + buy_tag + ')'
# Williams %R based sell 4, plus CTI
sell, signal_name = self.sell_r_4(current_profit, last_candle)
if (sell) and (signal_name is not None):
return signal_name + ' ( ' + buy_tag + ')'
# Sell signal 1
if self.sell_condition_1_enable.value and (last_candle['rsi_14'] > self.sell_rsi_bb_1.value) and (last_candle['close'] > last_candle['bb20_2_upp']) and (previous_candle_1['close'] > previous_candle_1['bb20_2_upp']) and (previous_candle_2['close'] > previous_candle_2['bb20_2_upp']) and (previous_candle_3['close'] > previous_candle_3['bb20_2_upp']) and (previous_candle_4['close'] > previous_candle_4['bb20_2_upp']) and (previous_candle_5['close'] > previous_candle_5['bb20_2_upp']):
if (last_candle['close'] > last_candle['ema_200']):
if (current_profit > 0.0):
return 'sell_signal_1_1_1' + ' ( ' + buy_tag + ')'
else:
if (current_profit > 0.0):
return 'sell_signal_1_2_1' + ' ( ' + buy_tag + ')'
elif (max_loss > 0.25):
return 'sell_signal_1_2_2' + ' ( ' + buy_tag + ')'
# Sell signal 2
elif (self.sell_condition_2_enable.value) and (last_candle['rsi_14'] > self.sell_rsi_bb_2.value) and (last_candle['close'] > last_candle['bb20_2_upp']) and (previous_candle_1['close'] > previous_candle_1['bb20_2_upp']) and (previous_candle_2['close'] > previous_candle_2['bb20_2_upp']):
if (last_candle['close'] > last_candle['ema_200']):
if (current_profit > 0.0):
return 'sell_signal_2_1_1' + ' ( ' + buy_tag + ')'
else:
if (current_profit > 0.0):
return 'sell_signal_2_2_1' + ' ( ' + buy_tag + ')'
elif (max_loss > 0.25):
return 'sell_signal_2_2_2' + ' ( ' + buy_tag + ')'
# Sell signal 4
elif self.sell_condition_4_enable.value and (last_candle['rsi_14'] > self.sell_dual_rsi_rsi_4.value) and (last_candle['rsi_14_1h'] > self.sell_dual_rsi_rsi_1h_4.value):
if (last_candle['close'] > last_candle['ema_200']):
if (current_profit > 0.0):
return 'sell_signal_4_1_1' + ' ( ' + buy_tag + ')'
else:
if (current_profit > 0.0):
return 'sell_signal_4_2_1' + ' ( ' + buy_tag + ')'
elif (max_loss > 0.25):
return 'sell_signal_4_2_2' + ' ( ' + buy_tag + ')'
# Sell signal 6
elif self.sell_condition_6_enable.value and (last_candle['close'] < last_candle['ema_200']) and (last_candle['close'] > last_candle['ema_50']) and (last_candle['rsi_14'] > self.sell_rsi_under_6.value):
if (current_profit > 0.0):
return 'sell_signal_6_1' + ' ( ' + buy_tag + ')'
elif (max_loss > 0.25):
return 'sell_signal_6_2' + ' ( ' + buy_tag + ')'
# Sell signal 7
elif self.sell_condition_7_enable.value and (last_candle['rsi_14_1h'] > self.sell_rsi_1h_7.value) and (last_candle['crossed_below_ema_12_26']):
if (last_candle['close'] > last_candle['ema_200']):
if (current_profit > 0.0):
return 'sell_signal_7_1_1' + ' ( ' + buy_tag + ')'
else:
if (current_profit > 0.0):
return 'sell_signal_7_2_1' + ' ( ' + buy_tag + ')'
elif (max_loss > 0.25):
return 'sell_signal_7_2_2' + ' ( ' + buy_tag + ')'
# Sell signal 8
elif self.sell_condition_8_enable.value and (last_candle['close'] > last_candle['bb20_2_upp_1h'] * self.sell_bb_relative_8.value):
if (last_candle['close'] > last_candle['ema_200']):
if (current_profit > 0.0):
return 'sell_signal_8_1_1' + ' ( ' + buy_tag + ')'
else:
if (current_profit > 0.0):
return 'sell_signal_8_2_1' + ' ( ' + buy_tag + ')'
elif (max_loss > 0.25):
return 'sell_signal_8_2_2' + ' ( ' + buy_tag + ')'
return None
def range_percent_change(self, dataframe: DataFrame, method, length: int) -> float:
"""
Rolling Percentage Change Maximum across interval.
:param dataframe: DataFrame The original OHLC dataframe
:param method: High to Low / Open to Close
:param length: int The length to look back
"""
if method == 'HL':
return (dataframe['high'].rolling(length).max() - dataframe['low'].rolling(length).min()) / dataframe['low'].rolling(length).min()
elif method == 'OC':
return (dataframe['open'].rolling(length).max() - dataframe['close'].rolling(length).min()) / dataframe['close'].rolling(length).min()
else:
raise ValueError(f"Method {method} not defined!")
def top_percent_change(self, dataframe: DataFrame, length: int) -> float:
"""
Percentage change of the current close from the range maximum Open price
:param dataframe: DataFrame The original OHLC dataframe
:param length: int The length to look back
"""
if length == 0:
return (dataframe['open'] - dataframe['close']) / dataframe['close']
else:
return (dataframe['open'].rolling(length).max() - dataframe['close']) / dataframe['close']
def range_maxgap(self, dataframe: DataFrame, length: int) -> float:
"""
Maximum Price Gap across interval.
:param dataframe: DataFrame The original OHLC dataframe
:param length: int The length to look back
"""
return dataframe['open'].rolling(length).max() - dataframe['close'].rolling(length).min()
def range_maxgap_adjusted(self, dataframe: DataFrame, length: int, adjustment: float) -> float:
"""
Maximum Price Gap across interval adjusted.
:param dataframe: DataFrame The original OHLC dataframe
:param length: int The length to look back
:param adjustment: int The adjustment to be applied
"""
return self.range_maxgap(dataframe, length) / adjustment
def range_height(self, dataframe: DataFrame, length: int) -> float:
"""
Current close distance to range bottom.
:param dataframe: DataFrame The original OHLC dataframe
:param length: int The length to look back
"""
return dataframe['close'] - dataframe['close'].rolling(length).min()
def safe_pump(self, dataframe: DataFrame, length: int, thresh: float, pull_thresh: float) -> bool:
"""
Determine if entry after a pump is safe.
:param dataframe: DataFrame The original OHLC dataframe
:param length: int The length to look back
:param thresh: int Maximum percentage change threshold
:param pull_thresh: int Pullback from interval maximum threshold
"""
return (dataframe[f'oc_pct_change_{length}'] < thresh) | (self.range_maxgap_adjusted(dataframe, length, pull_thresh) > self.range_height(dataframe, length))
def safe_dips(self, dataframe: DataFrame, thresh_0, thresh_2, thresh_12, thresh_144) -> bool:
"""
Determine if dip is safe to enter.
:param dataframe: DataFrame The original OHLC dataframe
:param thresh_0: Threshold value for 0 length top pct change
:param thresh_2: Threshold value for 2 length top pct change
:param thresh_12: Threshold value for 12 length top pct change
:param thresh_144: Threshold value for 144 length top pct change
"""
return ((dataframe['tpct_change_0'] < thresh_0) &
(dataframe['tpct_change_2'] < thresh_2) &
(dataframe['tpct_change_12'] < thresh_12) &
(dataframe['tpct_change_144'] < thresh_144))
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 = [(pair, self.info_timeframe) for pair in pairs]
informative_pairs.append(('BTC/USDT', self.timeframe))
informative_pairs.append(('BTC/USDT', self.info_timeframe))
return informative_pairs
def informative_1h_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
assert self.dp, "DataProvider is required for multiple timeframes."
# Get the informative pair
informative_1h = self.dp.get_pair_dataframe(pair=metadata['pair'], timeframe=self.info_timeframe)
# EMA
informative_1h['ema_12'] = ta.EMA(informative_1h, timeperiod=12)
informative_1h['ema_15'] = ta.EMA(informative_1h, timeperiod=15)
informative_1h['ema_20'] = ta.EMA(informative_1h, timeperiod=20)
informative_1h['ema_25'] = ta.EMA(informative_1h, timeperiod=25)
informative_1h['ema_26'] = ta.EMA(informative_1h, timeperiod=26)
informative_1h['ema_35'] = ta.EMA(informative_1h, timeperiod=35)
informative_1h['ema_50'] = ta.EMA(informative_1h, timeperiod=50)
informative_1h['ema_100'] = ta.EMA(informative_1h, timeperiod=100)
informative_1h['ema_200'] = ta.EMA(informative_1h, timeperiod=200)
# SMA
informative_1h['sma_200'] = ta.SMA(informative_1h, timeperiod=200)
informative_1h['sma_200_dec_20'] = informative_1h['sma_200'] < informative_1h['sma_200'].shift(20)
# RSI
informative_1h['rsi_14'] = ta.RSI(informative_1h, timeperiod=14)
# 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']
# Chaikin Money Flow
informative_1h['cmf'] = chaikin_money_flow(informative_1h, 20)
# Williams %R
informative_1h['r_480'] = williams_r(informative_1h, period=480)
# Ichimoku
ichi = ichimoku(informative_1h, conversion_line_period=20, base_line_periods=60, laggin_span=120, displacement=30)
informative_1h['chikou_span'] = ichi['chikou_span']
informative_1h['tenkan_sen'] = ichi['tenkan_sen']
informative_1h['kijun_sen'] = ichi['kijun_sen']
informative_1h['senkou_a'] = ichi['senkou_span_a']
informative_1h['senkou_b'] = ichi['senkou_span_b']
informative_1h['leading_senkou_span_a'] = ichi['leading_senkou_span_a']
informative_1h['leading_senkou_span_b'] = ichi['leading_senkou_span_b']
informative_1h.loc[:, 'cloud_top'] = informative_1h.loc[:, ['senkou_a', 'senkou_b']].max(axis=1)
# EFI - Elders Force Index
informative_1h['efi'] = pta.efi(informative_1h["close"], informative_1h["volume"], length=13)
# SSL
ssl_down, ssl_up = SSLChannels(informative_1h, 10)
informative_1h['ssl_down'] = ssl_down
informative_1h['ssl_up'] = ssl_up
# Pump protections
informative_1h['hl_pct_change_48'] = self.range_percent_change(informative_1h, 'HL', 48)
informative_1h['hl_pct_change_36'] = self.range_percent_change(informative_1h, 'HL', 36)
informative_1h['hl_pct_change_24'] = self.range_percent_change(informative_1h, 'HL', 24)
informative_1h['oc_pct_change_48'] = self.range_percent_change(informative_1h, 'OC', 48)
informative_1h['oc_pct_change_36'] = self.range_percent_change(informative_1h, 'OC', 36)
informative_1h['oc_pct_change_24'] = self.range_percent_change(informative_1h, 'OC', 24)
informative_1h['hl_pct_change_5'] = self.range_percent_change(informative_1h, 'HL', 5)
informative_1h['low_5'] = informative_1h['low'].shift().rolling(5).min()
informative_1h['safe_pump_24_10'] = self.safe_pump(informative_1h, 24, self.buy_pump_threshold_10_24.value, self.buy_pump_pull_threshold_10_24.value)
informative_1h['safe_pump_36_10'] = self.safe_pump(informative_1h, 36, self.buy_pump_threshold_10_36.value, self.buy_pump_pull_threshold_10_36.value)
informative_1h['safe_pump_48_10'] = self.safe_pump(informative_1h, 48, self.buy_pump_threshold_10_48.value, self.buy_pump_pull_threshold_10_48.value)
informative_1h['safe_pump_24_20'] = self.safe_pump(informative_1h, 24, self.buy_pump_threshold_20_24.value, self.buy_pump_pull_threshold_20_24.value)
informative_1h['safe_pump_36_20'] = self.safe_pump(informative_1h, 36, self.buy_pump_threshold_20_36.value, self.buy_pump_pull_threshold_20_36.value)
informative_1h['safe_pump_48_20'] = self.safe_pump(informative_1h, 48, self.buy_pump_threshold_20_48.value, self.buy_pump_pull_threshold_20_48.value)
informative_1h['safe_pump_24_30'] = self.safe_pump(informative_1h, 24, self.buy_pump_threshold_30_24.value, self.buy_pump_pull_threshold_30_24.value)
informative_1h['safe_pump_36_30'] = self.safe_pump(informative_1h, 36, self.buy_pump_threshold_30_36.value, self.buy_pump_pull_threshold_30_36.value)
informative_1h['safe_pump_48_30'] = self.safe_pump(informative_1h, 48, self.buy_pump_threshold_30_48.value, self.buy_pump_pull_threshold_30_48.value)
informative_1h['safe_pump_24_40'] = self.safe_pump(informative_1h, 24, self.buy_pump_threshold_40_24.value, self.buy_pump_pull_threshold_40_24.value)
informative_1h['safe_pump_36_40'] = self.safe_pump(informative_1h, 36, self.buy_pump_threshold_40_36.value, self.buy_pump_pull_threshold_40_36.value)
informative_1h['safe_pump_48_40'] = self.safe_pump(informative_1h, 48, self.buy_pump_threshold_40_48.value, self.buy_pump_pull_threshold_40_48.value)
informative_1h['safe_pump_24_50'] = self.safe_pump(informative_1h, 24, self.buy_pump_threshold_50_24.value, self.buy_pump_pull_threshold_50_24.value)
informative_1h['safe_pump_36_50'] = self.safe_pump(informative_1h, 36, self.buy_pump_threshold_50_36.value, self.buy_pump_pull_threshold_50_36.value)
informative_1h['safe_pump_48_50'] = self.safe_pump(informative_1h, 48, self.buy_pump_threshold_50_48.value, self.buy_pump_pull_threshold_50_48.value)
informative_1h['safe_pump_24_60'] = self.safe_pump(informative_1h, 24, self.buy_pump_threshold_60_24.value, self.buy_pump_pull_threshold_60_24.value)
informative_1h['safe_pump_36_60'] = self.safe_pump(informative_1h, 36, self.buy_pump_threshold_60_36.value, self.buy_pump_pull_threshold_60_36.value)
informative_1h['safe_pump_48_60'] = self.safe_pump(informative_1h, 48, self.buy_pump_threshold_60_48.value, self.buy_pump_pull_threshold_60_48.value)
informative_1h['safe_pump_24_70'] = self.safe_pump(informative_1h, 24, self.buy_pump_threshold_70_24.value, self.buy_pump_pull_threshold_70_24.value)
informative_1h['safe_pump_36_70'] = self.safe_pump(informative_1h, 36, self.buy_pump_threshold_70_36.value, self.buy_pump_pull_threshold_70_36.value)
informative_1h['safe_pump_48_70'] = self.safe_pump(informative_1h, 48, self.buy_pump_threshold_70_48.value, self.buy_pump_pull_threshold_70_48.value)
informative_1h['safe_pump_24_80'] = self.safe_pump(informative_1h, 24, self.buy_pump_threshold_80_24.value, self.buy_pump_pull_threshold_80_24.value)
informative_1h['safe_pump_36_80'] = self.safe_pump(informative_1h, 36, self.buy_pump_threshold_80_36.value, self.buy_pump_pull_threshold_80_36.value)
informative_1h['safe_pump_48_80'] = self.safe_pump(informative_1h, 48, self.buy_pump_threshold_80_48.value, self.buy_pump_pull_threshold_80_48.value)
informative_1h['safe_pump_24_90'] = self.safe_pump(informative_1h, 24, self.buy_pump_threshold_90_24.value, self.buy_pump_pull_threshold_90_24.value)
informative_1h['safe_pump_36_90'] = self.safe_pump(informative_1h, 36, self.buy_pump_threshold_90_36.value, self.buy_pump_pull_threshold_90_36.value)
informative_1h['safe_pump_48_90'] = self.safe_pump(informative_1h, 48, self.buy_pump_threshold_90_48.value, self.buy_pump_pull_threshold_90_48.value)
informative_1h['safe_pump_24_100'] = self.safe_pump(informative_1h, 24, self.buy_pump_threshold_100_24.value, self.buy_pump_pull_threshold_100_24.value)
informative_1h['safe_pump_36_100'] = self.safe_pump(informative_1h, 36, self.buy_pump_threshold_100_36.value, self.buy_pump_pull_threshold_100_36.value)
informative_1h['safe_pump_48_100'] = self.safe_pump(informative_1h, 48, self.buy_pump_threshold_100_48.value, self.buy_pump_pull_threshold_100_48.value)
informative_1h['safe_pump_24_110'] = self.safe_pump(informative_1h, 24, self.buy_pump_threshold_110_24.value, self.buy_pump_pull_threshold_110_24.value)
informative_1h['safe_pump_36_110'] = self.safe_pump(informative_1h, 36, self.buy_pump_threshold_110_36.value, self.buy_pump_pull_threshold_110_36.value)
informative_1h['safe_pump_48_110'] = self.safe_pump(informative_1h, 48, self.buy_pump_threshold_110_48.value, self.buy_pump_pull_threshold_110_48.value)
informative_1h['safe_pump_24_120'] = self.safe_pump(informative_1h, 24, self.buy_pump_threshold_120_24.value, self.buy_pump_pull_threshold_120_24.value)
informative_1h['safe_pump_36_120'] = self.safe_pump(informative_1h, 36, self.buy_pump_threshold_120_36.value, self.buy_pump_pull_threshold_120_36.value)
informative_1h['safe_pump_48_120'] = self.safe_pump(informative_1h, 48, self.buy_pump_threshold_120_48.value, self.buy_pump_pull_threshold_120_48.value)
informative_1h['safe_dump_10'] = ((informative_1h['hl_pct_change_5'] < self.buy_dump_protection_10_5.value) | (informative_1h['close'] < informative_1h['low_5']) | (informative_1h['close'] > informative_1h['open']))
informative_1h['safe_dump_20'] = ((informative_1h['hl_pct_change_5'] < self.buy_dump_protection_20_5.value) | (informative_1h['close'] < informative_1h['low_5']) | (informative_1h['close'] > informative_1h['open']))
informative_1h['safe_dump_30'] = ((informative_1h['hl_pct_change_5'] < self.buy_dump_protection_30_5.value) | (informative_1h['close'] < informative_1h['low_5']) | (informative_1h['close'] > informative_1h['open']))
informative_1h['safe_dump_40'] = ((informative_1h['hl_pct_change_5'] < self.buy_dump_protection_40_5.value) | (informative_1h['close'] < informative_1h['low_5']) | (informative_1h['close'] > informative_1h['open']))
informative_1h['safe_dump_50'] = ((informative_1h['hl_pct_change_5'] < self.buy_dump_protection_50_5.value) | (informative_1h['close'] < informative_1h['low_5']) | (informative_1h['close'] > informative_1h['open']))
informative_1h['safe_dump_60'] = ((informative_1h['hl_pct_change_5'] < self.buy_dump_protection_60_5.value) | (informative_1h['close'] < informative_1h['low_5']) | (informative_1h['close'] > informative_1h['open']))
informative_1h['sell_pump_48_1'] = (informative_1h['hl_pct_change_48'] > self.sell_pump_threshold_48_1.value)
informative_1h['sell_pump_48_2'] = (informative_1h['hl_pct_change_48'] > self.sell_pump_threshold_48_2.value)
informative_1h['sell_pump_48_3'] = (informative_1h['hl_pct_change_48'] > self.sell_pump_threshold_48_3.value)
informative_1h['sell_pump_36_1'] = (informative_1h['hl_pct_change_36'] > self.sell_pump_threshold_36_1.value)
informative_1h['sell_pump_36_2'] = (informative_1h['hl_pct_change_36'] > self.sell_pump_threshold_36_2.value)
informative_1h['sell_pump_36_3'] = (informative_1h['hl_pct_change_36'] > self.sell_pump_threshold_36_3.value)
informative_1h['sell_pump_24_1'] = (informative_1h['hl_pct_change_24'] > self.sell_pump_threshold_24_1.value)
informative_1h['sell_pump_24_2'] = (informative_1h['hl_pct_change_24'] > self.sell_pump_threshold_24_2.value)
informative_1h['sell_pump_24_3'] = (informative_1h['hl_pct_change_24'] > self.sell_pump_threshold_24_3.value)
#TD Sequential
informative_1h['exceed_high'] = False
informative_1h['exceed_low'] = False
# count consecutive closes “lower” than the close 4 bars prior.
informative_1h['seq_buy'] = informative_1h['close'] < informative_1h['close'].shift(4)
informative_1h['seq_buy'] = informative_1h['seq_buy'] * (informative_1h['seq_buy'].groupby(
(informative_1h['seq_buy'] != informative_1h['seq_buy'].shift()).cumsum()).cumcount() + 1)
# count consecutive closes “higher” than the close 4 bars prior.
informative_1h['seq_sell'] = informative_1h['close'] > informative_1h['close'].shift(4)
informative_1h['seq_sell'] = informative_1h['seq_sell'] * (informative_1h['seq_sell'].groupby(
(informative_1h['seq_sell'] != informative_1h['seq_sell'].shift()).cumsum()).cumcount() + 1)
for index, row in informative_1h.iterrows():
# check if the low of bars 6 and 7 in the count are exceeded by the low of bars 8 or 9.
seq_b = row['seq_buy']
if seq_b == 8:
informative_1h.loc[index, 'exceed_low'] = (row['low'] < informative_1h.loc[index - 2, 'low']) | \
(row['low'] < informative_1h.loc[index - 1, 'low'])
if seq_b > 8:
informative_1h.loc[index, 'exceed_low'] = (row['low'] < informative_1h.loc[index - 3 - (seq_b - 9), 'low']) | \
(row['low'] < informative_1h.loc[index - 2 - (seq_b - 9), 'low'])
if seq_b == 9:
informative_1h.loc[index, 'exceed_low'] = row['exceed_low'] | informative_1h.loc[index-1, 'exceed_low']
# check if the high of bars 6 and 7 in the count are exceeded by the high of bars 8 or 9.
seq_s = row['seq_sell']
if seq_s == 8:
informative_1h.loc[index, 'exceed_high'] = (row['high'] > informative_1h.loc[index - 2, 'high']) | \
(row['high'] > informative_1h.loc[index - 1, 'high'])
if seq_s > 8:
informative_1h.loc[index, 'exceed_high'] = (row['high'] > informative_1h.loc[index - 3 - (seq_s - 9), 'high']) | \
(row['high'] > informative_1h.loc[index - 2 - (seq_s - 9), 'high'])
if seq_s == 9:
informative_1h.loc[index, 'exceed_high'] = row['exceed_high'] | informative_1h.loc[index-1, 'exceed_high']
return informative_1h
def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# BB 40 - STD2
bb_40_std2 = qtpylib.bollinger_bands(dataframe['close'], window=40, stds=2)
dataframe['bb40_2_low'] = bb_40_std2['lower']
dataframe['bb40_2_mid'] = bb_40_std2['mid']
dataframe['bb40_2_delta'] = (bb_40_std2['mid'] - dataframe['bb40_2_low']).abs()
dataframe['closedelta'] = (dataframe['close'] - dataframe['close'].shift()).abs()
dataframe['tail'] = (dataframe['close'] - dataframe['bb40_2_low']).abs()
# BB 20 - STD2
bb_20_std2 = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
dataframe['bb20_2_low'] = bb_20_std2['lower']
dataframe['bb20_2_mid'] = bb_20_std2['mid']
dataframe['bb20_2_upp'] = bb_20_std2['upper']
# EMA 200
dataframe['ema_12'] = ta.EMA(dataframe, timeperiod=12)
dataframe['ema_13'] = ta.EMA(dataframe, timeperiod=13)
dataframe['ema_15'] = ta.EMA(dataframe, timeperiod=15)
dataframe['ema_20'] = ta.EMA(dataframe, timeperiod=20)
dataframe['ema_25'] = ta.EMA(dataframe, timeperiod=25)
dataframe['ema_26'] = ta.EMA(dataframe, timeperiod=26)
dataframe['ema_35'] = ta.EMA(dataframe, timeperiod=35)
dataframe['ema_50'] = ta.EMA(dataframe, timeperiod=50)
dataframe['ema_100'] = ta.EMA(dataframe, timeperiod=100)
dataframe['ema_200'] = ta.EMA(dataframe, timeperiod=200)
# SMA
dataframe['sma_5'] = ta.SMA(dataframe, timeperiod=5)
dataframe['sma_15'] = ta.SMA(dataframe, timeperiod=15)
dataframe['sma_20'] = ta.SMA(dataframe, timeperiod=20)
dataframe['sma_30'] = ta.SMA(dataframe, timeperiod=30)
dataframe['sma_200'] = ta.SMA(dataframe, timeperiod=200)
dataframe['sma_200_dec_20'] = dataframe['sma_200'] < dataframe['sma_200'].shift(20)
dataframe['sma_200_dec_24'] = dataframe['sma_200'] < dataframe['sma_200'].shift(24)
# MFI
dataframe['mfi'] = ta.MFI(dataframe)
# CMF
dataframe['cmf'] = chaikin_money_flow(dataframe, 20)
# EWO
dataframe['ewo'] = ewo(dataframe, 50, 200)
# RSI
dataframe['rsi_4'] = ta.RSI(dataframe, timeperiod=4)
dataframe['rsi_14'] = ta.RSI(dataframe, timeperiod=14)
dataframe['rsi_20'] = ta.RSI(dataframe, timeperiod=20)
# Chopiness
dataframe['chop']= qtpylib.chopiness(dataframe, 14)
# Zero-Lag EMA
dataframe['zema_61'] = zema(dataframe, period=61)
# Williams %R
dataframe['r_480'] = williams_r(dataframe, period=480)
# Stochastic RSI
stochrsi = ta.STOCHRSI(dataframe, timeperiod=96, fastk_period=3, fastd_period=3, fastd_matype=0)
dataframe['stochrsi_fastk_96'] = stochrsi['fastk']
dataframe['stochrsi_fastd_96'] = stochrsi['fastd']
# Modified Elder Ray Index
dataframe['moderi_32'] = moderi(dataframe, 32)
dataframe['moderi_64'] = moderi(dataframe, 64)
dataframe['moderi_96'] = moderi(dataframe, 96)
# hull
dataframe['hull_75'] = hull(dataframe, 75)
# zlema
dataframe['zlema_68'] = zlema(dataframe, 68)
# CTI
dataframe['cti'] = pta.cti(dataframe["close"], length=20)
# For sell checks
dataframe['crossed_below_ema_12_26'] = qtpylib.crossed_below(dataframe['ema_12'], dataframe['ema_26'])
# Heiken Ashi
heikinashi = qtpylib.heikinashi(dataframe)
heikinashi["volume"] = dataframe["volume"]
#HLC3
dataframe['hlc3'] = (dataframe['high'] + dataframe['low'] + dataframe['close']) / 3
#HRSI
dataframe['hull'] = (2 * dataframe['hlc3'] - ta.WMA(dataframe['hlc3'], 2))
dataframe['hrsi'] = ta.RSI(dataframe['hull'], 2)
dataframe['hull_sell'] = (2 * dataframe['low'] - ta.WMA(dataframe['low'], 2))
dataframe['hrsi_sell'] = ta.RSI(dataframe['hull_sell'], 2)
#Kalman Filter HLC3
dataframe['hlc3KF'] = KalmanFilter(dataframe, source='hlc3')
#Kalman Filter LOW
dataframe['lowKF'] = KalmanFilter(dataframe, source='low')
#ZLEMA BUY
dataframe['zlema_1'] = dataframe['hlc3KF']
dataframe['zlema_1_std'] = dataframe['hlc3']
dataframe['ema_data'] = dataframe['hlc3KF'] + (dataframe['hlc3KF'] - dataframe['hlc3KF'].shift(2))
dataframe['ema_data_2'] = dataframe['hlc3KF'] + (dataframe['hlc3KF'] - dataframe['hlc3KF'].shift(1))
dataframe['zlema_4'] = ta.EMA(dataframe['ema_data'], timeperiod = 4)
dataframe['zlema_2'] = ta.EMA(dataframe['ema_data_2'], timeperiod = 2)
dataframe['zlema_4_std'] = pta.zlma(dataframe['hlc3'], length = 4)
#ZLEMA SELL
dataframe['zlema_1_sell'] = dataframe['lowKF']
dataframe['zlema_1_std_sell'] = dataframe['low']
dataframe['ema_data_sell'] = dataframe['lowKF'] + (dataframe['lowKF'] - dataframe['lowKF'].shift(2))
dataframe['zlema_4_sell'] = ta.EMA(dataframe['ema_data_sell'], timeperiod = 4)
dataframe['zlema_4_std_sell'] = pta.zlma(dataframe['low'], length = 4)
#CCI
dataframe['cci'] = ta.CCI(dataframe, source='hlc3', timeperiod=20)
# Profit Maximizer - PMAX
dataframe['pm'], dataframe['pmx'] = pmax(heikinashi, MAtype=1, length=9, multiplier=27, period=10, src=3)
dataframe['source'] = (dataframe['high'] + dataframe['low'] + dataframe['open'] + dataframe['close'])/4
dataframe['pmax_thresh'] = ta.EMA(dataframe['source'], timeperiod=9)
dataframe['sma_21'] = ta.SMA(dataframe, timeperiod=21)
dataframe['sma_68'] = ta.SMA(dataframe, timeperiod=68)
dataframe['sma_75'] = ta.SMA(dataframe, timeperiod=75)
# ATR
dataframe['atr'] = ta.ATR(dataframe, timeperiod=14)
dataframe['atr_high_thresh_1'] = (dataframe['high'] - (dataframe['atr'] * 5.4))
dataframe['atr_high_thresh_2'] = (dataframe['high'] - (dataframe['atr'] * 5.2))
dataframe['atr_high_thresh_3'] = (dataframe['high'] - (dataframe['atr'] * 5.0))
dataframe['atr_high_thresh_4'] = (dataframe['high'] - (dataframe['atr'] * 2.0))
dataframe['atr_high_thresh_q'] = (dataframe['high'] - (dataframe['atr'] * 3.0))
# Dip protection
dataframe['tpct_change_0'] = self.top_percent_change(dataframe,0)
dataframe['tpct_change_2'] = self.top_percent_change(dataframe,2)
dataframe['tpct_change_12'] = self.top_percent_change(dataframe,12)
dataframe['tpct_change_144'] = self.top_percent_change(dataframe,144)
dataframe['safe_dips_10'] = self.safe_dips(dataframe, self.buy_dip_threshold_10_1.value, self.buy_dip_threshold_10_2.value, self.buy_dip_threshold_10_3.value, self.buy_dip_threshold_10_4.value)
dataframe['safe_dips_20'] = self.safe_dips(dataframe, self.buy_dip_threshold_20_1.value, self.buy_dip_threshold_20_2.value, self.buy_dip_threshold_20_3.value, self.buy_dip_threshold_20_4.value)
dataframe['safe_dips_30'] = self.safe_dips(dataframe, self.buy_dip_threshold_30_1.value, self.buy_dip_threshold_30_2.value, self.buy_dip_threshold_30_3.value, self.buy_dip_threshold_30_4.value)
dataframe['safe_dips_40'] = self.safe_dips(dataframe, self.buy_dip_threshold_40_1.value, self.buy_dip_threshold_40_2.value, self.buy_dip_threshold_40_3.value, self.buy_dip_threshold_40_4.value)
dataframe['safe_dips_50'] = self.safe_dips(dataframe, self.buy_dip_threshold_50_1.value, self.buy_dip_threshold_50_2.value, self.buy_dip_threshold_50_3.value, self.buy_dip_threshold_50_4.value)
dataframe['safe_dips_60'] = self.safe_dips(dataframe, self.buy_dip_threshold_60_1.value, self.buy_dip_threshold_60_2.value, self.buy_dip_threshold_60_3.value, self.buy_dip_threshold_60_4.value)
dataframe['safe_dips_70'] = self.safe_dips(dataframe, self.buy_dip_threshold_70_1.value, self.buy_dip_threshold_70_2.value, self.buy_dip_threshold_70_3.value, self.buy_dip_threshold_70_4.value)
dataframe['safe_dips_80'] = self.safe_dips(dataframe, self.buy_dip_threshold_80_1.value, self.buy_dip_threshold_80_2.value, self.buy_dip_threshold_80_3.value, self.buy_dip_threshold_80_4.value)
dataframe['safe_dips_90'] = self.safe_dips(dataframe, self.buy_dip_threshold_90_1.value, self.buy_dip_threshold_90_2.value, self.buy_dip_threshold_90_3.value, self.buy_dip_threshold_90_4.value)
dataframe['safe_dips_100'] = self.safe_dips(dataframe, self.buy_dip_threshold_100_1.value, self.buy_dip_threshold_100_2.value, self.buy_dip_threshold_100_3.value, self.buy_dip_threshold_100_4.value)
dataframe['safe_dips_110'] = self.safe_dips(dataframe, self.buy_dip_threshold_110_1.value, self.buy_dip_threshold_110_2.value, self.buy_dip_threshold_110_3.value, self.buy_dip_threshold_110_4.value)
dataframe['safe_dips_120'] = self.safe_dips(dataframe, self.buy_dip_threshold_120_1.value, self.buy_dip_threshold_120_2.value, self.buy_dip_threshold_120_3.value, self.buy_dip_threshold_120_4.value)
dataframe['safe_dips_130'] = self.safe_dips(dataframe, self.buy_dip_threshold_130_1.value, self.buy_dip_threshold_130_2.value, self.buy_dip_threshold_130_3.value, self.buy_dip_threshold_130_4.value)
# Volume
dataframe['volume_mean_4'] = dataframe['volume'].rolling(4).mean().shift(1)
dataframe['volume_mean_30'] = dataframe['volume'].rolling(30).mean()
if not self.config['runmode'].value in ('live', 'dry_run'):
# Backtest age filter
dataframe['bt_agefilter_ok'] = False
dataframe.loc[dataframe.index > (12 * 24 * self.bt_min_age_days),'bt_agefilter_ok'] = True
else:
# Exchange downtime protection
dataframe['live_data_ok'] = (dataframe['volume'].rolling(window=72, min_periods=72).min() > 0)
return dataframe
def resampled_tf_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# Indicators
# -----------------------------------------------------------------------------------------
dataframe['rsi_14'] = ta.RSI(dataframe, timeperiod=14)
return dataframe
def base_tf_btc_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# Indicators
# -----------------------------------------------------------------------------------------
dataframe['rsi_14'] = ta.RSI(dataframe, timeperiod=14)
# Add prefix
# -----------------------------------------------------------------------------------------
ignore_columns = ['date', 'open', 'high', 'low', 'close', 'volume']
dataframe.rename(columns=lambda s: "btc_" + s if (not s in ignore_columns) else s, inplace=True)
return dataframe
def info_tf_btc_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# Indicators
# -----------------------------------------------------------------------------------------
dataframe['rsi_14'] = ta.RSI(dataframe, timeperiod=14)
dataframe['not_downtrend'] = ((dataframe['close'] > dataframe['close'].shift(2)) | (dataframe['rsi_14'] > 50))
# Add prefix
# -----------------------------------------------------------------------------------------
ignore_columns = ['date', 'open', 'high', 'low', 'close', 'volume']
dataframe.rename(columns=lambda s: "btc_" + s if (not s in ignore_columns) else s, inplace=True)
return dataframe
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
'''
--> BTC informative (5m/1h)
___________________________________________________________________________________________
'''
if self.has_BTC_base_tf:
btc_base_tf = self.dp.get_pair_dataframe("BTC/USDT", self.timeframe)
btc_base_tf = self.base_tf_btc_indicators(btc_base_tf, metadata)
dataframe = merge_informative_pair(dataframe, btc_base_tf, self.timeframe, self.timeframe, ffill=True)
drop_columns = [(s + "_" + self.timeframe) for s in ['date', 'open', 'high', 'low', 'close', 'volume']]
dataframe.drop(columns=dataframe.columns.intersection(drop_columns), inplace=True)
if self.has_BTC_info_tf:
btc_info_tf = self.dp.get_pair_dataframe("BTC/USDT", self.info_timeframe)
btc_info_tf = self.info_tf_btc_indicators(btc_info_tf, metadata)
dataframe = merge_informative_pair(dataframe, btc_info_tf, self.timeframe, self.info_timeframe, ffill=True)
drop_columns = [(s + "_" + self.info_timeframe) for s in ['date', 'open', 'high', 'low', 'close', 'volume']]
dataframe.drop(columns=dataframe.columns.intersection(drop_columns), inplace=True)
'''
--> Informative timeframe
___________________________________________________________________________________________
'''
if self.info_timeframe != 'none':
informative_1h = self.informative_1h_indicators(dataframe, metadata)
dataframe = merge_informative_pair(dataframe, informative_1h, self.timeframe, self.info_timeframe, ffill=True)
drop_columns = [(s + "_" + self.info_timeframe) for s in ['date']]
dataframe.drop(columns=dataframe.columns.intersection(drop_columns), inplace=True)
'''
--> Resampled to another timeframe
___________________________________________________________________________________________
'''
if self.res_timeframe != 'none':
resampled = resample_to_interval(dataframe, timeframe_to_minutes(self.res_timeframe))
resampled = self.resampled_tf_indicators(resampled, metadata)
# Merge resampled info dataframe
dataframe = resampled_merge(dataframe, resampled, fill_na=True)
dataframe.rename(columns=lambda s: s+"_{}".format(self.res_timeframe) if "resample_" in s else s, inplace=True)
dataframe.rename(columns=lambda s: s.replace("resample_{}_".format(self.res_timeframe.replace("m","")), ""), inplace=True)
drop_columns = [(s + "_" + self.res_timeframe) for s in ['date']]
dataframe.drop(columns=dataframe.columns.intersection(drop_columns), inplace=True)
'''
--> The indicators for the normal (5m) timeframe
___________________________________________________________________________________________
'''
dataframe = self.normal_tf_indicators(dataframe, metadata)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
conditions = []
dataframe.loc[:, 'buy_tag'] = ''
for index in self.buy_protection_params:
item_buy_protection_list = [True]
global_buy_protection_params = self.buy_protection_params[index]
if self.buy_params['buy_condition_' + str(index) + '_enable']:
# Standard protections - Common to every condition
# -----------------------------------------------------------------------------------------
if global_buy_protection_params["ema_fast"]:
item_buy_protection_list.append(dataframe[f"ema_{global_buy_protection_params['ema_fast_len']}"] > dataframe['ema_200'])
if global_buy_protection_params["ema_slow"]:
item_buy_protection_list.append(dataframe[f"ema_{global_buy_protection_params['ema_slow_len']}_1h"] > dataframe['ema_200_1h'])
if global_buy_protection_params["close_above_ema_fast"]:
item_buy_protection_list.append(dataframe['close'] > dataframe[f"ema_{global_buy_protection_params['close_above_ema_fast_len']}"])
if global_buy_protection_params["close_above_ema_slow"]:
item_buy_protection_list.append(dataframe['close'] > dataframe[f"ema_{global_buy_protection_params['close_above_ema_slow_len']}_1h"])
if global_buy_protection_params["sma200_rising"]:
item_buy_protection_list.append(dataframe['sma_200'] > dataframe['sma_200'].shift(int(global_buy_protection_params['sma200_rising_val'])))
if global_buy_protection_params["sma200_1h_rising"]:
item_buy_protection_list.append(dataframe['sma_200_1h'] > dataframe['sma_200_1h'].shift(int(global_buy_protection_params['sma200_1h_rising_val'])))
if global_buy_protection_params["safe_dips"]:
item_buy_protection_list.append(dataframe[f"safe_dips_{global_buy_protection_params['safe_dips_type']}"])
if global_buy_protection_params["safe_pump"]:
item_buy_protection_list.append(dataframe[f"safe_pump_{global_buy_protection_params['safe_pump_period']}_{global_buy_protection_params['safe_pump_type']}_1h"])
if global_buy_protection_params['btc_1h_not_downtrend']:
item_buy_protection_list.append(dataframe['btc_not_downtrend_1h'])
if not self.config['runmode'] in ('live', 'dry_run'):
if self.has_bt_agefilter:
item_buy_protection_list.append(dataframe['bt_agefilter_ok'])
else:
if self.has_downtime_protection:
item_buy_protection_list.append(dataframe['live_data_ok'])
# Buy conditions
# -----------------------------------------------------------------------------------------
item_buy_logic = []
item_buy_logic.append(reduce(lambda x, y: x & y, item_buy_protection_list))
# Condition #1
if index == 1:
# Non-Standard protections
# Logic
item_buy_logic.append(((dataframe['close'] - dataframe['open'].rolling(36).min()) / dataframe['open'].rolling(36).min()) > self.buy_min_inc_1.value)
item_buy_logic.append(dataframe['rsi_14_1h'] > self.buy_rsi_1h_min_1.value)
item_buy_logic.append(dataframe['rsi_14_1h'] < self.buy_rsi_1h_max_1.value)
item_buy_logic.append(dataframe['rsi_14'] < self.buy_rsi_1.value)
item_buy_logic.append(dataframe['mfi'] < self.buy_mfi_1.value)
item_buy_logic.append(dataframe['cti'] < self.buy_cti_1.value)
# Condition #2
elif index == 2:
# Non-Standard protections
# Logic
item_buy_logic.append(dataframe['rsi_14'] < dataframe['rsi_14_1h'] - self.buy_rsi_1h_diff_2.value)
item_buy_logic.append(dataframe['mfi'] < self.buy_mfi_2.value)
item_buy_logic.append(dataframe['close'] < (dataframe['bb20_2_low'] * self.buy_bb_offset_2.value))
item_buy_logic.append(dataframe['volume'] < (dataframe['volume_mean_4'] * self.buy_volume_2.value))
# Condition #3
elif index == 3:
# Non-Standard protections
item_buy_logic.append(dataframe['close'] > (dataframe['ema_200_1h'] * self.buy_ema_rel_3.value))
# Logic
item_buy_logic.append(dataframe['bb40_2_low'].shift().gt(0))
item_buy_logic.append(dataframe['bb40_2_delta'].gt(dataframe['close'] * self.buy_bb40_bbdelta_close_3.value))
item_buy_logic.append(dataframe['closedelta'].gt(dataframe['close'] * self.buy_bb40_closedelta_close_3.value))
item_buy_logic.append(dataframe['tail'].lt(dataframe['bb40_2_delta'] * self.buy_bb40_tail_bbdelta_3.value))
item_buy_logic.append(dataframe['close'].lt(dataframe['bb40_2_low'].shift()))
item_buy_logic.append(dataframe['close'].le(dataframe['close'].shift()))
item_buy_logic.append(dataframe['cti'] < self.buy_cti_3.value)
# Condition #4
elif index == 4:
# Non-Standard protections
# Logic
item_buy_logic.append(dataframe['close'] < dataframe['ema_50'])
item_buy_logic.append(dataframe['close'] < self.buy_bb20_close_bblowerband_4.value * dataframe['bb20_2_low'])
item_buy_logic.append(dataframe['volume'] < (dataframe['volume_mean_30'].shift(1) * self.buy_bb20_volume_4.value))
item_buy_logic.append(dataframe['cti'] < self.buy_cti_4.value)
# Condition #5
elif index == 5:
# Non-Standard protections
item_buy_logic.append(dataframe['close'] > (dataframe['ema_200_1h'] * self.buy_ema_rel_5.value))
# Logic
item_buy_logic.append(dataframe['ema_26'] > dataframe['ema_12'])
item_buy_logic.append((dataframe['ema_26'] - dataframe['ema_12']) > (dataframe['open'] * self.buy_ema_open_mult_5.value))
item_buy_logic.append((dataframe['ema_26'].shift() - dataframe['ema_12'].shift()) > (dataframe['open'] / 100))
item_buy_logic.append(dataframe['close'] < (dataframe['bb20_2_low'] * self.buy_bb_offset_5.value))
item_buy_logic.append(dataframe['cti'] < self.buy_cti_5.value)
item_buy_logic.append(dataframe['volume'] < (dataframe['volume_mean_4'] * self.buy_volume_5.value))
# Condition #6
elif index == 6:
# Non-Standard protections
# Logic
item_buy_logic.append(dataframe['ema_26'] > dataframe['ema_12'])
item_buy_logic.append((dataframe['ema_26'] - dataframe['ema_12']) > (dataframe['open'] * self.buy_ema_open_mult_6.value))
item_buy_logic.append((dataframe['ema_26'].shift() - dataframe['ema_12'].shift()) > (dataframe['open'] / 100))
item_buy_logic.append(dataframe['close'] < (dataframe['bb20_2_low'] * self.buy_bb_offset_6.value))
# Condition #7
elif index == 7:
# Non-Standard protections
# Logic
item_buy_logic.append(dataframe['ema_26'] > dataframe['ema_12'])
item_buy_logic.append((dataframe['ema_26'] - dataframe['ema_12']) > (dataframe['open'] * self.buy_ema_open_mult_7.value))
item_buy_logic.append((dataframe['ema_26'].shift() - dataframe['ema_12'].shift()) > (dataframe['open'] / 100))
item_buy_logic.append(dataframe['cti'] < self.buy_cti_7.value)
# Condition #8
elif index == 8:
# Non-Standard protections
# Logic
item_buy_logic.append(dataframe['moderi_96'])
item_buy_logic.append(dataframe['cti'] < self.buy_cti_8.value)
item_buy_logic.append(dataframe['close'] < (dataframe['bb20_2_low'] * self.buy_bb_offset_8.value))
item_buy_logic.append(dataframe['rsi_14_1h'] < self.buy_rsi_1h_8.value)
item_buy_logic.append(dataframe['volume'] < (dataframe['volume_mean_4'] * self.buy_volume_8.value))
# Condition #9
elif index == 9:
# Non-Standard protections
item_buy_logic.append(dataframe['ema_50'] > dataframe['ema_200'])
# Logic
item_buy_logic.append(dataframe['close'] < dataframe['ema_20'] * self.buy_ma_offset_9.value)
item_buy_logic.append(dataframe['close'] < dataframe['bb20_2_low'] * self.buy_bb_offset_9.value)
item_buy_logic.append(dataframe['rsi_14_1h'] > self.buy_rsi_1h_min_9.value)
item_buy_logic.append(dataframe['rsi_14_1h'] < self.buy_rsi_1h_max_9.value)
item_buy_logic.append(dataframe['mfi'] < self.buy_mfi_9.value)
# Condition #10
elif index == 10:
# Non-Standard protections
item_buy_logic.append(dataframe['ema_50_1h'] > dataframe['ema_100_1h'])
# Logic
item_buy_logic.append(dataframe['close'] < dataframe['sma_30'] * self.buy_ma_offset_10.value)
item_buy_logic.append(dataframe['close'] < dataframe['bb20_2_low'] * self.buy_bb_offset_10.value)
item_buy_logic.append(dataframe['rsi_14_1h'] < self.buy_rsi_1h_10.value)
# Condition #11
elif index == 11:
# Non-Standard protections
item_buy_logic.append(dataframe['ema_50_1h'] > dataframe['ema_100_1h'])
# Logic
item_buy_logic.append(((dataframe['close'] - dataframe['open'].rolling(36).min()) / dataframe['open'].rolling(36).min()) > self.buy_min_inc_11.value)
item_buy_logic.append(dataframe['close'] < dataframe['sma_30'] * self.buy_ma_offset_11.value)
item_buy_logic.append(dataframe['rsi_14_1h'] > self.buy_rsi_1h_min_11.value)
item_buy_logic.append(dataframe['rsi_14_1h'] < self.buy_rsi_1h_max_11.value)
item_buy_logic.append(dataframe['rsi_14'] < self.buy_rsi_11.value)
item_buy_logic.append(dataframe['mfi'] < self.buy_mfi_11.value)
# Condition #12
elif index == 12:
# Non-Standard protections
# Logic
item_buy_logic.append(dataframe['close'] < dataframe['sma_30'] * self.buy_ma_offset_12.value)
item_buy_logic.append(dataframe['ewo'] > self.buy_ewo_12.value)
item_buy_logic.append(dataframe['rsi_14'] < self.buy_rsi_12.value)
item_buy_logic.append(dataframe['cti'] < self.buy_cti_12.value)
# Condition #13
elif index == 13:
# Non-Standard protections
item_buy_logic.append(dataframe['ema_50_1h'] > dataframe['ema_100_1h'])
# Logic
item_buy_logic.append(dataframe['close'] < dataframe['sma_30'] * self.buy_ma_offset_13.value)
item_buy_logic.append(dataframe['cti'] < self.buy_cti_13.value)
item_buy_logic.append(dataframe['ewo'] < self.buy_ewo_13.value)
# Condition #14
elif index == 14:
# Non-Standard protections
# Logic
item_buy_logic.append(dataframe['ema_26'] > dataframe['ema_12'])
item_buy_logic.append((dataframe['ema_26'] - dataframe['ema_12']) > (dataframe['open'] * self.buy_ema_open_mult_14.value))
item_buy_logic.append((dataframe['ema_26'].shift() - dataframe['ema_12'].shift()) > (dataframe['open'] / 100))
item_buy_logic.append(dataframe['close'] < (dataframe['bb20_2_low'] * self.buy_bb_offset_14.value))
item_buy_logic.append(dataframe['close'] < dataframe['ema_20'] * self.buy_ma_offset_14.value)
item_buy_logic.append(dataframe['cti'] < self.buy_cti_14.value)
# Condition #15
elif index == 15:
# Non-Standard protections
item_buy_logic.append(dataframe['close'] > dataframe['ema_200_1h'] * self.buy_ema_rel_15.value)
# Logic
item_buy_logic.append(dataframe['ema_26'] > dataframe['ema_12'])
item_buy_logic.append((dataframe['ema_26'] - dataframe['ema_12']) > (dataframe['open'] * self.buy_ema_open_mult_15.value))
item_buy_logic.append((dataframe['ema_26'].shift() - dataframe['ema_12'].shift()) > (dataframe['open'] / 100))
item_buy_logic.append(dataframe['rsi_14'] < self.buy_rsi_15.value)
item_buy_logic.append(dataframe['close'] < dataframe['ema_20'] * self.buy_ma_offset_15.value)
# Condition #16
elif index == 16:
# Non-Standard protections
# Logic
item_buy_logic.append(dataframe['close'] < dataframe['ema_20'] * self.buy_ma_offset_16.value)
item_buy_logic.append(dataframe['ewo'] > self.buy_ewo_16.value)
item_buy_logic.append(dataframe['rsi_14'] < self.buy_rsi_16.value)
item_buy_logic.append(dataframe['cti'] < self.buy_cti_16.value)
# Condition #17
elif index == 17:
# Non-Standard protections
# Logic
item_buy_logic.append(dataframe['close'] < dataframe['ema_20'] * self.buy_ma_offset_17.value)
item_buy_logic.append(dataframe['ewo'] < self.buy_ewo_17.value)
item_buy_logic.append(dataframe['cti'] < self.buy_cti_17.value)
item_buy_logic.append(dataframe['volume'] < (dataframe['volume_mean_4'] * self.buy_volume_17.value))
# Condition #18
elif index == 18:
# Non-Standard protections
item_buy_logic.append(dataframe['sma_200'] > dataframe['sma_200'].shift(20))
item_buy_logic.append(dataframe['sma_200_1h'] > dataframe['sma_200_1h'].shift(36))
# Logic
item_buy_logic.append(dataframe['rsi_14'] < self.buy_rsi_18.value)
item_buy_logic.append(dataframe['close'] < (dataframe['bb20_2_low'] * self.buy_bb_offset_18.value))
item_buy_logic.append(dataframe['volume'] < (dataframe['volume_mean_4'] * self.buy_volume_18.value))
item_buy_logic.append(dataframe['cti'] < self.buy_cti_18.value)
# Condition #19
elif index == 19:
# Non-Standard protections
# Logic
item_buy_logic.append(dataframe['close'].shift(1) > dataframe['ema_100_1h'])
item_buy_logic.append(dataframe['low'] < dataframe['ema_100_1h'])
item_buy_logic.append(dataframe['close'] > dataframe['ema_100_1h'])
item_buy_logic.append(dataframe['rsi_14_1h'] > self.buy_rsi_1h_min_19.value)
item_buy_logic.append(dataframe['chop'] < self.buy_chop_max_19.value)
item_buy_logic.append(dataframe['moderi_32'] == True)
item_buy_logic.append(dataframe['moderi_64'] == True)
item_buy_logic.append(dataframe['moderi_96'] == True)
# Condition #20
elif index == 20:
# Non-Standard protections
# Logic
item_buy_logic.append(dataframe['rsi_14'] < self.buy_rsi_20.value)
item_buy_logic.append(dataframe['rsi_14_1h'] < self.buy_rsi_1h_20.value)
item_buy_logic.append(dataframe['cti'] < self.buy_cti_20.value)
item_buy_logic.append(dataframe['volume'] < (dataframe['volume_mean_4'] * self.buy_volume_20.value))
# Condition #21
elif index == 21:
# Non-Standard protections
# Logic
item_buy_logic.append(dataframe['rsi_14'] < self.buy_rsi_21.value)
item_buy_logic.append(dataframe['rsi_14_1h'] < self.buy_rsi_1h_21.value)
item_buy_logic.append(dataframe['cti'] < self.buy_cti_21.value)
item_buy_logic.append(dataframe['volume'] < (dataframe['volume_mean_4'] * self.buy_volume_21.value))
# Condition #22
elif index == 22:
# Non-Standard protections
item_buy_logic.append(dataframe['ema_100_1h'] > dataframe['ema_100_1h'].shift(12))
item_buy_logic.append(dataframe['ema_200_1h'] > dataframe['ema_200_1h'].shift(36))
# Logic
item_buy_logic.append((dataframe['volume_mean_4'] * self.buy_volume_22.value) > dataframe['volume'])
item_buy_logic.append(dataframe['close'] < dataframe['sma_30'] * self.buy_ma_offset_22.value)
item_buy_logic.append(dataframe['close'] < (dataframe['bb20_2_low'] * self.buy_bb_offset_22.value))
item_buy_logic.append(dataframe['ewo'] > self.buy_ewo_22.value)
item_buy_logic.append(dataframe['rsi_14'] < self.buy_rsi_22.value)
# Condition #23
elif index == 23:
# Non-Standard protections
# Logic
item_buy_logic.append(dataframe['close'] < (dataframe['bb20_2_low'] * self.buy_bb_offset_23.value))
item_buy_logic.append(dataframe['ewo'] > self.buy_ewo_23.value)
item_buy_logic.append(dataframe['rsi_14'] < self.buy_rsi_23.value)
item_buy_logic.append(dataframe['rsi_14_1h'] < self.buy_rsi_1h_23.value)
# Condition #24
elif index == 24:
# Non-Standard protections
# Logic
item_buy_logic.append(dataframe['ema_12_1h'].shift(12) < dataframe['ema_35_1h'].shift(12))
item_buy_logic.append(dataframe['ema_12_1h'] > dataframe['ema_35_1h'])
item_buy_logic.append(dataframe['cmf_1h'].shift(12) < 0)
item_buy_logic.append(dataframe['cmf_1h'] > 0)
item_buy_logic.append(dataframe['rsi_14'] < self.buy_24_rsi_max.value)
item_buy_logic.append(dataframe['rsi_14_1h'] > self.buy_24_rsi_1h_min.value)
# Condition #25
elif index == 25:
# Non-Standard protections
# Logic
item_buy_logic.append(dataframe['rsi_20'] < dataframe['rsi_20'].shift())
item_buy_logic.append(dataframe['rsi_4'] < self.buy_25_rsi_4.value)
item_buy_logic.append(dataframe['ema_20_1h'] > dataframe['ema_26_1h'])
item_buy_logic.append(dataframe['close'] < (dataframe['sma_20'] * self.buy_25_ma_offset.value))
item_buy_logic.append(dataframe['open'] > (dataframe['sma_20'] * self.buy_25_ma_offset.value))
item_buy_logic.append(
(dataframe['open'] < dataframe['ema_20_1h']) & (dataframe['low'] < dataframe['ema_20_1h']) |
(dataframe['open'] > dataframe['ema_20_1h']) & (dataframe['low'] > dataframe['ema_20_1h'])
)
item_buy_logic.append(dataframe['cti'] < self.buy_25_cti.value)
# Condition #26
elif index == 26:
# Non-Standard protections
# Logic
item_buy_logic.append(dataframe['close'] < (dataframe['zema_61'] * self.buy_26_zema_low_offset.value))
item_buy_logic.append(dataframe['cti'] < self.buy_26_cti.value)
item_buy_logic.append(dataframe['volume'] < (dataframe['volume_mean_4'] * self.buy_26_volume.value))
# Condition #27
elif index == 27:
# Non-Standard protections
# Logic
item_buy_logic.append(dataframe['r_480'] < -self.buy_27_wr_max.value)
item_buy_logic.append(dataframe['r_480_1h'] < -self.buy_27_wr_1h_max.value)
item_buy_logic.append(dataframe['rsi_14_1h'] + dataframe['rsi_14'] < self.buy_27_rsi_max.value)
item_buy_logic.append(dataframe['cti'] < self.buy_27_cti.value)
item_buy_logic.append(dataframe['volume'] < (dataframe['volume_mean_4'] * self.buy_27_volume.value))
# Condition #28
elif index == 28:
# Non-Standard protections
# Logic
item_buy_logic.append(dataframe['moderi_64'] == True)
item_buy_logic.append(dataframe['close'] < dataframe['hull_75'] * self.buy_28_ma_offset.value)
item_buy_logic.append(dataframe['ewo'] > self.buy_28_ewo.value)
item_buy_logic.append(dataframe['rsi_14'] < self.buy_28_rsi.value)
item_buy_logic.append(dataframe['cti'] < self.buy_28_cti.value)
# Condition #29
elif index == 29:
# Non-Standard protections
# Logic
item_buy_logic.append(dataframe['moderi_64'] == True)
item_buy_logic.append(dataframe['close'] < dataframe['hull_75'] * self.buy_29_ma_offset.value)
item_buy_logic.append(dataframe['ewo'] < self.buy_29_ewo.value)
item_buy_logic.append(dataframe['cti'] < self.buy_29_cti.value)
# Condition #30
elif index == 30:
# Non-Standard protections
# Logic
item_buy_logic.append(dataframe['moderi_64'] == False)
item_buy_logic.append(dataframe['close'] < dataframe['zlema_68'] * self.buy_30_ma_offset.value)
item_buy_logic.append(dataframe['ewo'] > self.buy_30_ewo.value)
item_buy_logic.append(dataframe['rsi_14'] < self.buy_30_rsi.value)
item_buy_logic.append(dataframe['cti'] < self.buy_30_cti.value)
# Condition #31
elif index == 31:
# Non-Standard protections
# Logic
item_buy_logic.append(dataframe['moderi_64'] == False)
item_buy_logic.append(dataframe['close'] < dataframe['zlema_68'] * self.buy_31_ma_offset.value )
item_buy_logic.append(dataframe['ewo'] < self.buy_31_ewo.value)
item_buy_logic.append(dataframe['r_480'] < self.buy_31_wr.value)
# Condition #32 - Quick mode buy
elif index == 32:
# Non-Standard protections
# Logic
item_buy_logic.append(dataframe['moderi_32'])
item_buy_logic.append(dataframe['moderi_64'])
item_buy_logic.append(dataframe['moderi_96'])
item_buy_logic.append(dataframe['cti'] < self.buy_32_cti.value)
item_buy_logic.append(dataframe['rsi_20'] < dataframe['rsi_20'].shift(1))
item_buy_logic.append(dataframe['rsi_4'] < self.buy_32_rsi.value)
item_buy_logic.append(dataframe['ema_20_1h'] > dataframe['ema_25_1h'])
item_buy_logic.append((dataframe['open'] - dataframe['close']) / dataframe['close'] < self.buy_32_dip.value)
item_buy_logic.append(dataframe['close'] < (dataframe['sma_15'] * self.buy_32_ma_offset.value))
item_buy_logic.append(
((dataframe['open'] < dataframe['ema_20_1h']) & (dataframe['low'] < dataframe['ema_20_1h'])) |
((dataframe['open'] > dataframe['ema_20_1h']) & (dataframe['low'] > dataframe['ema_20_1h'])))
# Condition #33 - Quick mode buy
elif index == 33:
# Non-Standard protections
# Logic
item_buy_logic.append(dataframe['moderi_96'])
item_buy_logic.append(dataframe['cti'] < self.buy_33_cti.value)
item_buy_logic.append(dataframe['close'] < (dataframe['ema_13'] * self.buy_33_ma_offset.value))
item_buy_logic.append(dataframe['ewo'] > self.buy_33_ewo.value)
item_buy_logic.append(dataframe['rsi_14'] < self.buy_33_rsi.value)
item_buy_logic.append(dataframe['volume'] < (dataframe['volume_mean_4'] * self.buy_33_volume.value))
# Condition #34 - Quick mode buy
elif index == 34:
# Non-Standard protections
# Logic
item_buy_logic.append(dataframe['cti'] < self.buy_34_cti.value)
item_buy_logic.append((dataframe['open'] - dataframe['close']) / dataframe['close'] < self.buy_34_dip.value)
item_buy_logic.append(dataframe['close'] < dataframe['ema_13'] * self.buy_34_ma_offset.value)
item_buy_logic.append(dataframe['ewo'] < self.buy_34_ewo.value)
item_buy_logic.append(dataframe['volume'] < (dataframe['volume_mean_4'] * self.buy_34_volume.value))
# Condition #35 - PMAX0 buy
elif index == 35:
# Non-Standard protections
# Logic
item_buy_logic.append(dataframe['pm'] <= dataframe['pmax_thresh'])
item_buy_logic.append(dataframe['close'] < dataframe['sma_75'] * 0.984)
item_buy_logic.append(dataframe['ewo'] > 9.6)
item_buy_logic.append(dataframe['rsi_14'] < 32.0)
item_buy_logic.append(dataframe['cti'] < -0.5)
# Condition #36 - PMAX1 buy
elif index == 36:
# Non-Standard protections (add below)
# Logic
item_buy_logic.append(dataframe['pm'] <= dataframe['pmax_thresh'])
item_buy_logic.append(dataframe['close'] < dataframe['sma_75'] * 0.98)
item_buy_logic.append(dataframe['ewo'] < -8.8)
item_buy_logic.append(dataframe['cti'] < -0.8)
# Condition #37 - PMAX2 buy
elif index == 37:
# Non-Standard protections (add below)
# Logic
item_buy_logic.append(dataframe['pm'] > dataframe['pmax_thresh'])
item_buy_logic.append(dataframe['close'] < dataframe['sma_75'] * 0.98)
item_buy_logic.append(dataframe['ewo'] > 9.8)
item_buy_logic.append(dataframe['rsi_14'] < 56.0)
item_buy_logic.append(dataframe['cti'] < -0.7)
item_buy_logic.append(dataframe['safe_dump_50_1h'])
# Condition #38 - PMAX3 buy
elif index == 38:
# Non-Standard protections (add below)
# Logic
item_buy_logic.append(dataframe['pm'] > dataframe['pmax_thresh'])
item_buy_logic.append(dataframe['close'] < dataframe['sma_75'] * 0.7)
item_buy_logic.append(dataframe['ewo'] < -2.0)
item_buy_logic.append(dataframe['cti'] < -0.86)
# Condition #39 - Ichimoku
elif index == 39:
# Non-Standard protections (add below)
# Logic
item_buy_logic.append(dataframe['tenkan_sen_1h'] > dataframe['kijun_sen_1h'])
item_buy_logic.append(dataframe['close'] > dataframe['cloud_top_1h'])
item_buy_logic.append(dataframe['leading_senkou_span_a_1h'] > dataframe['leading_senkou_span_b_1h'])
item_buy_logic.append(dataframe['chikou_span_1h'] > dataframe['senkou_a_1h'])
item_buy_logic.append(dataframe['efi_1h'] > 0)
item_buy_logic.append(dataframe['ssl_up_1h'] > dataframe['ssl_down_1h'])
item_buy_logic.append(dataframe['close'] < dataframe['ssl_up_1h'])
item_buy_logic.append(dataframe['cti'] < -0.73)
# Start of trend
item_buy_logic.append(
(dataframe['leading_senkou_span_a_1h'].shift(12) < dataframe['leading_senkou_span_b_1h'].shift(12)) |
(dataframe['efi_1h'] < 0) |
(dataframe['ssl_up_1h'].shift(12) < dataframe['ssl_down_1h'].shift(12))
)
# Condition #40 - ZLEMA X buy
elif index == 40:
# Non-Standard protections (add below)
# Logic
item_buy_logic.append(qtpylib.crossed_above(dataframe['zlema_2'], dataframe['zlema_4']))
item_buy_logic.append(dataframe['hrsi'] < 30)
item_buy_logic.append(dataframe['cci'] < -200)
item_buy_logic.append(dataframe['rsi_14'] < 30)
item_buy_logic.append(dataframe['exceed_low_1h'])
item_buy_logic.append(dataframe['seq_buy_1h'] > 8)
item_buy_logic.append(dataframe['volume'] > 0)
item_buy = reduce(lambda x, y: x & y, item_buy_logic)
dataframe.loc[item_buy, 'buy_tag'] += str(index) + ' '
conditions.append(item_buy)
if conditions:
dataframe.loc[:, 'buy'] = reduce(lambda x, y: x | y, conditions)
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[:, 'sell'] = 0
return dataframe
def confirm_trade_exit(self, pair: str, trade: "Trade", order_type: str, amount: float,
rate: float, time_in_force: str, sell_reason: str, **kwargs) -> bool:
"""
Called right before placing a regular sell order.
Timing for this function is critical, so avoid doing heavy computations or
network requests in this method.
For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
When not implemented by a strategy, returns True (always confirming).
:param pair: Pair that's about to be sold.
:param trade: trade object.
:param order_type: Order type (as configured in order_types). usually limit or market.
:param amount: Amount in quote currency.
:param rate: Rate that's going to be used when using limit orders
:param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
:param sell_reason: Sell reason.
Can be any of ['roi', 'stop_loss', 'stoploss_on_exchange', 'trailing_stop_loss',
'sell_signal', 'force_sell', 'emergency_sell']
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return bool: When True is returned, then the sell-order is placed on the exchange.
False aborts the process
"""
# Just to be sure our hold data is loaded, should be a no-op call after the first bot loop
if self.config['runmode'].value in ('live', 'dry_run'):
self.load_hold_trades_config()
if not self.hold_trade_ids:
# We have no pairs we want to hold until profit, sell
return True
if trade.id not in self.hold_trade_ids:
# This pair is not on the list to hold until profit, sell
return True
trade_profit_ratio = self.hold_trade_ids[trade.id]
current_profit_ratio = trade.calc_profit_ratio(rate)
if sell_reason == "force_sell":
formatted_profit_ratio = "{}%".format(trade_profit_ratio * 100)
formatted_current_profit_ratio = "{}%".format(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 True
elif current_profit_ratio >= trade_profit_ratio:
# This pair is on the list to hold, and we reached minimum profit, sell
return True
# This pair is on the list to hold, and we haven't reached minimum profit, hold
return False
else:
return True
# Elliot Wave Oscillator
def ewo(dataframe, sma1_length=5, sma2_length=35):
sma1 = ta.EMA(dataframe, timeperiod=sma1_length)
sma2 = ta.EMA(dataframe, timeperiod=sma2_length)
smadif = (sma1 - sma2) / dataframe['close'] * 100
return smadif
# Chaikin Money Flow
def chaikin_money_flow(dataframe, n=20, fillna=False) -> Series:
"""Chaikin Money Flow (CMF)
It measures the amount of Money Flow Volume over a specific period.
http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:chaikin_money_flow_cmf
Args:
dataframe(pandas.Dataframe): dataframe containing ohlcv
n(int): n period.
fillna(bool): if True, fill nan values.
Returns:
pandas.Series: New feature generated.
"""
mfv = ((dataframe['close'] - dataframe['low']) - (dataframe['high'] - dataframe['close'])) / (dataframe['high'] - dataframe['low'])
mfv = mfv.fillna(0.0) # float division by zero
mfv *= dataframe['volume']
cmf = (mfv.rolling(n, min_periods=0).sum()
/ dataframe['volume'].rolling(n, min_periods=0).sum())
if fillna:
cmf = cmf.replace([np.inf, -np.inf], np.nan).fillna(0)
return Series(cmf, name='cmf')
# Williams %R
def williams_r(dataframe: DataFrame, period: int = 14) -> Series:
"""Williams %R, or just %R, is a technical analysis oscillator showing the current closing price in relation to the high and low
of the past N days (for a given N). It was developed by a publisher and promoter of trading materials, Larry Williams.
Its purpose is to tell whether a stock or commodity market is trading near the high or the low, or somewhere in between,
of its recent trading range.
The oscillator is on a negative scale, from −100 (lowest) up to 0 (highest).
"""
highest_high = dataframe["high"].rolling(center=False, window=period).max()
lowest_low = dataframe["low"].rolling(center=False, window=period).min()
WR = Series(
(highest_high - dataframe["close"]) / (highest_high - lowest_low),
name="{0} Williams %R".format(period),
)
return WR * -100
# Volume Weighted Moving Average
def vwma(dataframe: DataFrame, length: int = 10):
"""Indicator: Volume Weighted Moving Average (VWMA)"""
# Calculate Result
pv = dataframe['close'] * dataframe['volume']
vwma = Series(ta.SMA(pv, timeperiod=length) / ta.SMA(dataframe['volume'], timeperiod=length))
return vwma
# Modified Elder Ray Index
def moderi(dataframe: DataFrame, len_slow_ma: int = 32) -> Series:
slow_ma = Series(ta.EMA(vwma(dataframe, length=len_slow_ma), timeperiod=len_slow_ma))
return slow_ma >= slow_ma.shift(1) # we just need true & false for ERI trend
# zlema
def zlema(dataframe, timeperiod):
lag = int(math.floor((timeperiod - 1) / 2) )
if isinstance(dataframe, Series):
ema_data = dataframe + (dataframe - dataframe.shift(lag))
else:
ema_data = dataframe['close'] + (dataframe['close'] - dataframe['close'] .shift(lag))
return ta.EMA(ema_data, timeperiod = timeperiod)
# zlhull
def zlhull(dataframe, timeperiod):
lag = int(math.floor((timeperiod - 1) / 2) )
if isinstance(dataframe, Series):
wma_data = dataframe + (dataframe - dataframe.shift(lag))
else:
wma_data = dataframe['close'] + (dataframe['close'] - dataframe['close'] .shift(lag))
return ta.WMA(
2 * ta.WMA(wma_data, int(math.floor(timeperiod/2))) - ta.WMA(wma_data, timeperiod), int(round(np.sqrt(timeperiod)))
)
# hull
def hull(dataframe, timeperiod):
if isinstance(dataframe, Series):
return ta.WMA(
2 * ta.WMA(dataframe, int(math.floor(timeperiod/2))) - ta.WMA(dataframe, timeperiod), int(round(np.sqrt(timeperiod)))
)
else:
return ta.WMA(
2 * ta.WMA(dataframe['close'], int(math.floor(timeperiod/2))) - ta.WMA(dataframe['close'], timeperiod), int(round(np.sqrt(timeperiod)))
)
# PMAX
def pmax(df, period, multiplier, length, MAtype, src):
period = int(period)
multiplier = int(multiplier)
length = int(length)
MAtype = int(MAtype)
src = int(src)
mavalue = 'MA_' + str(MAtype) + '_' + str(length)
atr = 'ATR_' + str(period)
pm = 'pm_' + str(period) + '_' + str(multiplier) + '_' + str(length) + '_' + str(MAtype)
pmx = 'pmX_' + str(period) + '_' + str(multiplier) + '_' + str(length) + '_' + str(MAtype)
# MAtype==1 --> EMA
# MAtype==2 --> DEMA
# MAtype==3 --> T3
# MAtype==4 --> SMA
# MAtype==5 --> VIDYA
# MAtype==6 --> TEMA
# MAtype==7 --> WMA
# MAtype==8 --> VWMA
# MAtype==9 --> zema
if src == 1:
masrc = df["close"]
elif src == 2:
masrc = (df["high"] + df["low"]) / 2
elif src == 3:
masrc = (df["high"] + df["low"] + df["close"] + df["open"]) / 4
if MAtype == 1:
mavalue = ta.EMA(masrc, timeperiod=length)
elif MAtype == 2:
mavalue = ta.DEMA(masrc, timeperiod=length)
elif MAtype == 3:
mavalue = ta.T3(masrc, timeperiod=length)
elif MAtype == 4:
mavalue = ta.SMA(masrc, timeperiod=length)
elif MAtype == 5:
mavalue = VIDYA(df, length=length)
elif MAtype == 6:
mavalue = ta.TEMA(masrc, timeperiod=length)
elif MAtype == 7:
mavalue = ta.WMA(df, timeperiod=length)
elif MAtype == 8:
mavalue = vwma(df, length)
elif MAtype == 9:
mavalue = zema(df, period=length)
df[atr] = ta.ATR(df, timeperiod=period)
df['basic_ub'] = mavalue + ((multiplier/10) * df[atr])
df['basic_lb'] = mavalue - ((multiplier/10) * df[atr])
basic_ub = df['basic_ub'].values
final_ub = np.full(len(df), 0.00)
basic_lb = df['basic_lb'].values
final_lb = np.full(len(df), 0.00)
for i in range(period, len(df)):
final_ub[i] = basic_ub[i] if (
basic_ub[i] < final_ub[i - 1]
or mavalue[i - 1] > final_ub[i - 1]) else final_ub[i - 1]
final_lb[i] = basic_lb[i] if (
basic_lb[i] > final_lb[i - 1]
or mavalue[i - 1] < final_lb[i - 1]) else final_lb[i - 1]
df['final_ub'] = final_ub
df['final_lb'] = final_lb
pm_arr = np.full(len(df), 0.00)
for i in range(period, len(df)):
pm_arr[i] = (
final_ub[i] if (pm_arr[i - 1] == final_ub[i - 1]
and mavalue[i] <= final_ub[i])
else final_lb[i] if (
pm_arr[i - 1] == final_ub[i - 1]
and mavalue[i] > final_ub[i]) else final_lb[i]
if (pm_arr[i - 1] == final_lb[i - 1]
and mavalue[i] >= final_lb[i]) else final_ub[i]
if (pm_arr[i - 1] == final_lb[i - 1]
and mavalue[i] < final_lb[i]) else 0.00)
pm = Series(pm_arr)
# Mark the trend direction up/down
pmx = np.where((pm_arr > 0.00), np.where((mavalue < pm_arr), 'down', 'up'), np.NaN)
return pm, pmx
def calc_streaks(series: Series):
# logic tables
geq = series >= series.shift(1) # True if rising
eq = series == series.shift(1) # True if equal
logic_table = concat([geq, eq], axis=1)
streaks = [0] # holds the streak duration, starts with 0
for row in logic_table.iloc[1:].itertuples(): # iterate through logic table
if row[2]: # same value as before
streaks.append(0)
continue
last_value = streaks[-1]
if row[1]: # higher value than before
streaks.append(last_value + 1 if last_value >=
0 else 1) # increase or reset to +1
else: # lower value than before
streaks.append(last_value - 1 if last_value <
0 else -1) # decrease or reset to -1
return streaks
# SSL Channels
def SSLChannels(dataframe, length = 7):
df = dataframe.copy()
ATR = ta.ATR(dataframe, timeperiod=14)
smaHigh = dataframe['high'].rolling(length).mean() + ATR
smaLow = dataframe['low'].rolling(length).mean() - ATR
hlv = Series(np.where(dataframe['close'] > smaHigh, 1, np.where(dataframe['close'] < smaLow, -1, np.NAN)))
hlv = hlv.ffill()
sslDown = np.where(hlv < 0, smaHigh, smaLow)
sslUp = np.where(hlv < 0, smaLow, smaHigh)
return sslDown, sslUp
#Kalman Filter
def KalmanFilter(dtloc, source = 'close'):
dtKF = dtloc.copy().fillna(0)
dtKF['TRANGE'] = ta.TRANGE(dtloc).fillna(0)
def calc_dtKF(dfr, init=0):
global calc_dtKF_value_1
global calc_dtKF_value_2
global calc_dtKF_value_3
global calc_dtKF_source
if init == 1:
calc_dtKF_value_1 = 0.0
calc_dtKF_value_2 = 0.0
calc_dtKF_value_3 = 0.0
calc_dtKF_source = 0.0
return
calc_dtKF_value_1 = 0.2 * (dfr[source] - calc_dtKF_source) + 0.8 * calc_dtKF_value_1
calc_dtKF_value_2 = 0.1 * dfr['TRANGE'] + 0.8 * calc_dtKF_value_2
if calc_dtKF_value_2 != 0:
vlambda = abs(calc_dtKF_value_1/calc_dtKF_value_2)
else:
vlambda = 0
valpha = (-1*math.pow(vlambda,2) + math.sqrt(math.pow(vlambda,4) + 16 * math.pow(vlambda,2)))/8
calc_dtKF_value_3 = valpha * dfr[source] + (1 - valpha) * calc_dtKF_value_3
calc_dtKF_source = dfr[source]
return calc_dtKF_value_3
calc_dtKF(None, init=1)
dtKF['KF'] = dtKF.apply(calc_dtKF, axis = 1)
return dtKF['KF']