Timeframe
1m
Direction
Long Only
Stoploss
-25.0%
Trailing Stop
No
ROI
0m: 25.0%, 30m: 1.0%, 60m: 1.0%
Interface Version
3
Startup Candles
N/A
Indicators
2
freqtrade/freqtrade-strategies
freqtrade/freqtrade-strategies
this is an example class, implementing a PSAR based trailing stop loss you are supposed to take the `custom_stoploss()` and `populate_indicators()` parts and adapt it to your own strategy
freqtrade/freqtrade-strategies
Strategy 003 author@: Gerald Lonlas github@: https://github.com/freqtrade/freqtrade-strategies
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
# flake8: noqa: F401
# isort: skip_file
# --- Do not remove these libs ---
import numpy as np # noqa
import pandas as pd # noqa
from pandas import DataFrame
import os
from datetime import datetime
from freqtrade.strategy import (BooleanParameter, CategoricalParameter, DecimalParameter,
IStrategy, IntParameter, RealParameter)
from freqtrade.strategy import merge_informative_pair
# --------------------------------
# Add your lib to import here
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
import ta as taichi
pd.set_option('display.max_columns', 100)
pd.set_option('display.max_rows', None)
pd.set_option('display.expand_frame_repr', True)
def delete_log_results():
if os.path.exists("mylogs.txt"):
os.remove("mylogs.txt")
def log_to_results(str_to_log):
fr = open("mylogs.txt", "a")
#fr.write(str(datetime.now()) + " : " + str_to_log + "\n")
fr.write(str_to_log + "\n")
fr.close()
# This class is a sample. Feel free to customize it.
class StratIchimoku007(IStrategy):
delete_log_results()
# Strategy interface version - allow new iterations of the strategy interface.
# Check the documentation or the Sample strategy to get the latest version.
INTERFACE_VERSION = 3
# Can this strategy go short?
can_short: bool = True
#roi0 = RealParameter(0.01, 0.09, decimals=1, default=0.04, space="buy")
# Minimal ROI designed for the strategy.
# This attribute will be overridden if the config file contains "minimal_roi".
minimal_roi = {
#"60": 0.01,
#"30": 0.01,
"0": 0.25
}
# Optimal stoploss designed for the strategy.
# This attribute will be overridden if the config file contains "stoploss".
stoploss = -0.25
# Trailing stoploss
trailing_stop = False
# trailing_only_offset_is_reached = False
trailing_stop_positive = 0.0025
# trailing_stop_positive_offset = 0.0 # Disabled / not configured
# Optimal timeframe for the strategy.
timeframe = '1m'
# Run "populate_indicators()" only for new candle.
process_only_new_candles = True
# These values can be overridden in the config.
use_exit_signal = True
exit_profit_only = False
ignore_roi_if_entry_signal = False
# Number of candles the strategy requires before producing valid signals
startup_candle_count: int = 26
# Optional order type mapping.
order_types = {
'entry': 'limit',
'exit': 'limit',
'stoploss': 'market',
'stoploss_on_exchange': False
}
# Optional order time in force.
order_time_in_force = {
'entry': 'gtc',
'exit': 'gtc'
}
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, '5m') for pair in pairs]
informative_pairs += [(pair, '15m') for pair in pairs]
informative_pairs += [(pair, '30m') for pair in pairs]
informative_pairs += [(pair, '1h') for pair in pairs]
informative_pairs += [(pair, '4h') for pair in pairs]
# Optionally Add additional "static" pairs
informative_pairs += [("BTC/USDT:USDT", "15m"), ("BTC/USDT:USDT", "30m"), ("BTC/USDT:USDT", "1h"), ("BTC/USDT:USDT", "4h"),]
return informative_pairs
informativeBTC15M : DataFrame
informativeBTC30M : DataFrame
informativeBTC1H : DataFrame
informativeBTC4H : DataFrame
informative5M : DataFrame
informative15M : DataFrame
informative30M : DataFrame
informative1H : DataFrame
informative4H : DataFrame
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
global informativeBTC15M
global informativeBTC30M
global informativeBTC1H
global informativeBTC4H
global informative5M
global informative15M
global informative30M
global informative1H
global informative4H
#log_to_results(metadata['pair'])
currentPair = str(metadata['pair'])
inf_tf = '15m'
informativeBTC15M = self.dp.get_pair_dataframe(pair="BTC/USDT:USDT", timeframe=inf_tf)
inf_tf = '30m'
informativeBTC30M = self.dp.get_pair_dataframe(pair="BTC/USDT:USDT", timeframe=inf_tf)
inf_tf = '1h'
informativeBTC1H = self.dp.get_pair_dataframe(pair="BTC/USDT:USDT", timeframe=inf_tf)
inf_tf = '4h'
informativeBTC4H = self.dp.get_pair_dataframe(pair="BTC/USDT:USDT", timeframe=inf_tf)
inf_tf = '5m'
informative5M = self.dp.get_pair_dataframe(pair=currentPair, timeframe=inf_tf)
inf_tf = '15m'
informative15M = self.dp.get_pair_dataframe(pair=currentPair, timeframe=inf_tf)
inf_tf = '30m'
informative30M = self.dp.get_pair_dataframe(pair=currentPair, timeframe=inf_tf)
inf_tf = '1h'
informative1H = self.dp.get_pair_dataframe(pair=currentPair, timeframe=inf_tf)
inf_tf = '4h'
informative4H = self.dp.get_pair_dataframe(pair=currentPair, timeframe=inf_tf)
log_to_results(informative15M.to_string())
#Ichimoku calculations for the BTC in 15m
informativeBTC15M['BTC_ICH_SSB_15M'] = taichi.trend.ichimoku_b(informativeBTC15M['high'], informativeBTC15M['low'], window2=26, window3=52).shift(26)
informativeBTC15M['BTC_ICH_SSA_15M'] = taichi.trend.ichimoku_a(informativeBTC15M['high'], informativeBTC15M['low'], window1=9, window2=26).shift(26)
informativeBTC15M['BTC_ICH_KS_15M'] = taichi.trend.ichimoku_base_line(informativeBTC15M['high'], informativeBTC15M['low'])
informativeBTC15M['BTC_ICH_TS_15M'] = taichi.trend.ichimoku_conversion_line(informativeBTC15M['high'], informativeBTC15M['low'])
informativeBTC15M['BTC_ICH_CS_15M'] = informativeBTC15M['close']
informativeBTC15M['BTC_ICH_CS_HIGH_15M'] = informativeBTC15M['high'].shift(26)
informativeBTC15M['BTC_ICH_CS_LOW_15M'] = informativeBTC15M['low'].shift(26)
informativeBTC15M['BTC_ICH_CS_KS_15M'] = informativeBTC15M['BTC_ICH_KS_15M'].shift(26)
informativeBTC15M['BTC_ICH_CS_TS_15M'] = informativeBTC15M['BTC_ICH_TS_15M'].shift(26)
informativeBTC15M['BTC_ICH_CS_SSA_15M'] = informativeBTC15M['BTC_ICH_SSA_15M'].shift(26)
informativeBTC15M['BTC_ICH_CS_SSB_15M'] = informativeBTC15M['BTC_ICH_SSB_15M'].shift(26)
#Ichimoku calculations for the BTC in 30m
informativeBTC30M['BTC_ICH_SSB_30M'] = taichi.trend.ichimoku_b(informativeBTC30M['high'], informativeBTC30M['low'], window2=26, window3=52).shift(26)
informativeBTC30M['BTC_ICH_SSA_30M'] = taichi.trend.ichimoku_a(informativeBTC30M['high'], informativeBTC30M['low'], window1=9, window2=26).shift(26)
informativeBTC30M['BTC_ICH_KS_30M'] = taichi.trend.ichimoku_base_line(informativeBTC30M['high'], informativeBTC30M['low'])
informativeBTC30M['BTC_ICH_TS_30M'] = taichi.trend.ichimoku_conversion_line(informativeBTC30M['high'], informativeBTC30M['low'])
informativeBTC30M['BTC_ICH_CS_30M'] = informativeBTC30M['close']
informativeBTC30M['BTC_ICH_CS_HIGH_30M'] = informativeBTC30M['high'].shift(26)
informativeBTC30M['BTC_ICH_CS_LOW_30M'] = informativeBTC30M['low'].shift(26)
informativeBTC30M['BTC_ICH_CS_KS_30M'] = informativeBTC30M['BTC_ICH_KS_30M'].shift(26)
informativeBTC30M['BTC_ICH_CS_TS_30M'] = informativeBTC30M['BTC_ICH_TS_30M'].shift(26)
informativeBTC30M['BTC_ICH_CS_SSA_30M'] = informativeBTC30M['BTC_ICH_SSA_30M'].shift(26)
informativeBTC30M['BTC_ICH_CS_SSB_30M'] = informativeBTC30M['BTC_ICH_SSB_30M'].shift(26)
#Ichimoku calculations for the BTC in 1h
informativeBTC1H['BTC_ICH_SSB_1H'] = taichi.trend.ichimoku_b(informativeBTC1H['high'], informativeBTC1H['low'], window2=26, window3=52).shift(26)
informativeBTC1H['BTC_ICH_SSA_1H'] = taichi.trend.ichimoku_a(informativeBTC1H['high'], informativeBTC1H['low'], window1=9, window2=26).shift(26)
informativeBTC1H['BTC_ICH_KS_1H'] = taichi.trend.ichimoku_base_line(informativeBTC1H['high'], informativeBTC1H['low'])
informativeBTC1H['BTC_ICH_TS_1H'] = taichi.trend.ichimoku_conversion_line(informativeBTC1H['high'], informativeBTC1H['low'])
informativeBTC1H['BTC_ICH_CS_1H'] = informativeBTC1H['close']
informativeBTC1H['BTC_ICH_CS_HIGH_1H'] = informativeBTC1H['high'].shift(26)
informativeBTC1H['BTC_ICH_CS_LOW_1H'] = informativeBTC1H['low'].shift(26)
informativeBTC1H['BTC_ICH_CS_KS_1H'] = informativeBTC1H['BTC_ICH_KS_1H'].shift(26)
informativeBTC1H['BTC_ICH_CS_TS_1H'] = informativeBTC1H['BTC_ICH_TS_1H'].shift(26)
informativeBTC1H['BTC_ICH_CS_SSA_1H'] = informativeBTC1H['BTC_ICH_SSA_1H'].shift(26)
informativeBTC1H['BTC_ICH_CS_SSB_1H'] = informativeBTC1H['BTC_ICH_SSB_1H'].shift(26)
#Ichimoku calculations for the BTC in 4h
informativeBTC4H['BTC_ICH_SSB_4H'] = taichi.trend.ichimoku_b(informativeBTC4H['high'], informativeBTC4H['low'], window2=26, window3=52).shift(26)
informativeBTC4H['BTC_ICH_SSA_4H'] = taichi.trend.ichimoku_a(informativeBTC4H['high'], informativeBTC4H['low'], window1=9, window2=26).shift(26)
informativeBTC4H['BTC_ICH_KS_4H'] = taichi.trend.ichimoku_base_line(informativeBTC4H['high'], informativeBTC4H['low'])
informativeBTC4H['BTC_ICH_TS_4H'] = taichi.trend.ichimoku_conversion_line(informativeBTC4H['high'], informativeBTC4H['low'])
informativeBTC4H['BTC_ICH_CS_4H'] = informativeBTC4H['close']
informativeBTC4H['BTC_ICH_CS_HIGH_4H'] = informativeBTC4H['high'].shift(26)
informativeBTC4H['BTC_ICH_CS_LOW_4H'] = informativeBTC4H['low'].shift(26)
informativeBTC4H['BTC_ICH_CS_KS_4H'] = informativeBTC4H['BTC_ICH_KS_4H'].shift(26)
informativeBTC4H['BTC_ICH_CS_TS_4H'] = informativeBTC4H['BTC_ICH_TS_4H'].shift(26)
informativeBTC4H['BTC_ICH_CS_SSA_4H'] = informativeBTC4H['BTC_ICH_SSA_4H'].shift(26)
informativeBTC4H['BTC_ICH_CS_SSB_4H'] = informativeBTC4H['BTC_ICH_SSB_4H'].shift(26)
#Ichimoku calculations for the current pair in 5m
informative5M['ICH_SSB_5M'] = taichi.trend.ichimoku_b(informative5M['high'], informative5M['low'], window2=26, window3=52).shift(26)
informative5M['ICH_SSA_5M'] = taichi.trend.ichimoku_a(informative5M['high'], informative5M['low'], window1=9, window2=26).shift(26)
informative5M['ICH_KS_5M'] = taichi.trend.ichimoku_base_line(informative5M['high'], informative5M['low'])
informative5M['ICH_TS_5M'] = taichi.trend.ichimoku_conversion_line(informative5M['high'], informative5M['low'])
informative5M['ICH_CS_5M'] = informative5M['close']
informative5M['ICH_CS_HIGH_5M'] = informative5M['high'].shift(26)
informative5M['ICH_CS_LOW_5M'] = informative5M['low'].shift(26)
informative5M['ICH_CS_KS_5M'] = informative5M['ICH_KS_5M'].shift(26)
informative5M['ICH_CS_TS_5M'] = informative5M['ICH_TS_5M'].shift(26)
informative5M['ICH_CS_SSA_5M'] = informative5M['ICH_SSA_5M'].shift(26)
informative5M['ICH_CS_SSB_5M'] = informative5M['ICH_SSB_5M'].shift(26)
#Ichimoku calculations for the current pair in 15m
informative15M['ICH_SSB_15M'] = taichi.trend.ichimoku_b(informative15M['high'], informative15M['low'], window2=26, window3=52).shift(26)
informative15M['ICH_SSA_15M'] = taichi.trend.ichimoku_a(informative15M['high'], informative15M['low'], window1=9, window2=26).shift(26)
informative15M['ICH_KS_15M'] = taichi.trend.ichimoku_base_line(informative15M['high'], informative15M['low'])
informative15M['ICH_TS_15M'] = taichi.trend.ichimoku_conversion_line(informative15M['high'], informative15M['low'])
informative15M['ICH_CS_15M'] = informative15M['close']
informative15M['ICH_CS_HIGH_15M'] = informative15M['high'].shift(26)
informative15M['ICH_CS_LOW_15M'] = informative15M['low'].shift(26)
informative15M['ICH_CS_KS_15M'] = informative15M['ICH_KS_15M'].shift(26)
informative15M['ICH_CS_TS_15M'] = informative15M['ICH_TS_15M'].shift(26)
informative15M['ICH_CS_SSA_15M'] = informative15M['ICH_SSA_15M'].shift(26)
informative15M['ICH_CS_SSB_15M'] = informative15M['ICH_SSB_15M'].shift(26)
#Ichimoku calculations for the current pair in 30m
informative30M['ICH_SSB_30M'] = taichi.trend.ichimoku_b(informative30M['high'], informative30M['low'], window2=26, window3=52).shift(26)
informative30M['ICH_SSA_30M'] = taichi.trend.ichimoku_a(informative30M['high'], informative30M['low'], window1=9, window2=26).shift(26)
informative30M['ICH_KS_30M'] = taichi.trend.ichimoku_base_line(informative30M['high'], informative30M['low'])
informative30M['ICH_TS_30M'] = taichi.trend.ichimoku_conversion_line(informative30M['high'], informative30M['low'])
informative30M['ICH_CS_30M'] = informative30M['close']
informative30M['ICH_CS_HIGH_30M'] = informative30M['high'].shift(26)
informative30M['ICH_CS_LOW_30M'] = informative30M['low'].shift(26)
informative30M['ICH_CS_KS_30M'] = informative30M['ICH_KS_30M'].shift(26)
informative30M['ICH_CS_TS_30M'] = informative30M['ICH_TS_30M'].shift(26)
informative30M['ICH_CS_SSA_30M'] = informative30M['ICH_SSA_30M'].shift(26)
informative30M['ICH_CS_SSB_30M'] = informative30M['ICH_SSB_30M'].shift(26)
#Ichimoku calculations for the current pair in 1h
informative1H['ICH_SSB_1H'] = taichi.trend.ichimoku_b(informative1H['high'], informative1H['low'], window2=26, window3=52).shift(26)
informative1H['ICH_SSA_1H'] = taichi.trend.ichimoku_a(informative1H['high'], informative1H['low'], window1=9, window2=26).shift(26)
informative1H['ICH_KS_1H'] = taichi.trend.ichimoku_base_line(informative1H['high'], informative1H['low'])
informative1H['ICH_TS_1H'] = taichi.trend.ichimoku_conversion_line(informative1H['high'], informative1H['low'])
informative1H['ICH_CS_1H'] = informative1H['close']
informative1H['ICH_CS_HIGH_1H'] = informative1H['high'].shift(26)
informative1H['ICH_CS_LOW_1H'] = informative1H['low'].shift(26)
informative1H['ICH_CS_KS_1H'] = informative1H['ICH_KS_1H'].shift(26)
informative1H['ICH_CS_TS_1H'] = informative1H['ICH_TS_1H'].shift(26)
informative1H['ICH_CS_SSA_1H'] = informative1H['ICH_SSA_1H'].shift(26)
informative1H['ICH_CS_SSB_1H'] = informative1H['ICH_SSB_1H'].shift(26)
#Ichimoku calculations for the current pair in 4h
informative4H['ICH_SSB_4H'] = taichi.trend.ichimoku_b(informative4H['high'], informative4H['low'], window2=26, window3=52).shift(26)
informative4H['ICH_SSA_4H'] = taichi.trend.ichimoku_a(informative4H['high'], informative4H['low'], window1=9, window2=26).shift(26)
informative4H['ICH_KS_4H'] = taichi.trend.ichimoku_base_line(informative4H['high'], informative4H['low'])
informative4H['ICH_TS_4H'] = taichi.trend.ichimoku_conversion_line(informative4H['high'], informative4H['low'])
informative4H['ICH_CS_4H'] = informative4H['close']
informative4H['ICH_CS_HIGH_4H'] = informative4H['high'].shift(26)
informative4H['ICH_CS_LOW_4H'] = informative4H['low'].shift(26)
informative4H['ICH_CS_KS_4H'] = informative4H['ICH_KS_4H'].shift(26)
informative4H['ICH_CS_TS_4H'] = informative4H['ICH_TS_4H'].shift(26)
informative4H['ICH_CS_SSA_4H'] = informative4H['ICH_SSA_4H'].shift(26)
informative4H['ICH_CS_SSB_4H'] = informative4H['ICH_SSB_4H'].shift(26)
#Ichimoku calculations for the strategy's timeframe
dataframe['ICH_SSB'] = taichi.trend.ichimoku_b(dataframe['high'], dataframe['low'], window2=26, window3=52).shift(26)
dataframe['ICH_SSA'] = taichi.trend.ichimoku_a(dataframe['high'], dataframe['low'], window1=9, window2=26).shift(26)
dataframe['ICH_KS'] = taichi.trend.ichimoku_base_line(dataframe['high'], dataframe['low'])
dataframe['ICH_TS'] = taichi.trend.ichimoku_conversion_line(dataframe['high'], dataframe['low'])
dataframe['ICH_CS'] = dataframe['close']
dataframe['ICH_CS_HIGH'] = dataframe['high'].shift(26)
dataframe['ICH_CS_LOW'] = dataframe['low'].shift(26)
dataframe['ICH_CS_KS'] = dataframe['ICH_KS'].shift(26)
dataframe['ICH_CS_TS'] = dataframe['ICH_TS'].shift(26)
dataframe['ICH_CS_SSA'] = dataframe['ICH_SSA'].shift(26)
dataframe['ICH_CS_SSB'] = dataframe['ICH_SSB'].shift(26)
# RSI
dataframe['rsi'] = ta.RSI(dataframe)
#log_to_results(dataframe.to_string())
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
global informativeBTC15M
global informativeBTC30M
global informativeBTC1H
global informativeBTC4H
global informative5M
global informative15M
global informative30M
global informative1H
global informative4H
dataframe.loc[
(
#Conditions for the current asset being calculated in the strategy's timeframe
(dataframe['close'] > dataframe['open'])
& (dataframe['close'] > dataframe['ICH_SSA'])
& (dataframe['close'] > dataframe['ICH_SSB'])
& (dataframe['close'] > dataframe['ICH_KS'])
& (dataframe['close'] > dataframe['ICH_TS'])
& (dataframe['open'] > dataframe['ICH_SSA'])
& (dataframe['open'] > dataframe['ICH_SSB'])
& (dataframe['open'] < dataframe['ICH_KS'])
& (dataframe['open'] > dataframe['ICH_TS'])
& (dataframe['ICH_CS'] > dataframe['ICH_CS_HIGH'])
& (dataframe['ICH_CS'] > dataframe['ICH_CS_KS'])
& (dataframe['ICH_CS'] > dataframe['ICH_CS_TS'])
& (dataframe['ICH_CS'] > dataframe['ICH_CS_SSA'])
& (dataframe['ICH_CS'] > dataframe['ICH_CS_SSB'])
& (informative5M['close'] > informative5M['open'])
& (informative5M['ICH_CS_5M'] > informative5M['ICH_CS_HIGH_5M'])
& (informative5M['ICH_CS_5M'] > informative5M['ICH_CS_KS_5M'])
& (informative5M['ICH_CS_5M'] > informative5M['ICH_CS_TS_5M'])
& (informative5M['ICH_CS_5M'] > informative5M['ICH_CS_SSA_5M'])
& (informative5M['ICH_CS_5M'] > informative5M['ICH_CS_SSB_5M'])
& (informative15M['close'] > informative15M['open'])
& (informative15M['ICH_CS_15M'] > informative15M['ICH_CS_HIGH_15M'])
& (informative15M['ICH_CS_15M'] > informative15M['ICH_CS_KS_15M'])
& (informative15M['ICH_CS_15M'] > informative15M['ICH_CS_TS_15M'])
& (informative15M['ICH_CS_15M'] > informative15M['ICH_CS_SSA_15M'])
& (informative15M['ICH_CS_15M'] > informative15M['ICH_CS_SSB_15M'])
#& (informative30M['close'] > informative30M['open'])
#& (informative30M['ICH_CS_30M'] > informative30M['ICH_CS_HIGH_30M'])
#& (informative30M['ICH_CS_30M'] > informative30M['ICH_CS_KS_30M'])
#& (informative30M['ICH_CS_30M'] > informative30M['ICH_CS_TS_30M'])
#& (informative30M['ICH_CS_30M'] > informative30M['ICH_CS_SSA_30M'])
#& (informative30M['ICH_CS_30M'] > informative30M['ICH_CS_SSB_30M'])
#& (informative1H['ICH_CS_1H'] > informative1H['ICH_CS_HIGH_1H'])
#& (informative1H['ICH_CS_1H'] > informative1H['ICH_CS_KS_1H'])
#& (informative1H['ICH_CS_1H'] > informative1H['ICH_CS_TS_1H'])
#& (informative1H['ICH_CS_1H'] > informative1H['ICH_CS_SSA_1H'])
#& (informative1H['ICH_CS_1H'] > informative1H['ICH_CS_SSB_1H'])
#& (informative4H['ICH_CS_4H'] > informative4H['ICH_CS_HIGH_4H'])
#& (informative4H['ICH_CS_4H'] > informative4H['ICH_CS_KS_4H'])
#& (informative4H['ICH_CS_4H'] > informative4H['ICH_CS_TS_4H'])
#& (informative4H['ICH_CS_4H'] > informative4H['ICH_CS_SSA_4H'])
#& (informative4H['ICH_CS_4H'] > informative4H['ICH_CS_SSB_4H'])
#Conditions for the bitcoin in 15m
#& (informativeBTC15M['close'] > informativeBTC15M['open'])
#& (informativeBTC30M['BTC_ICH_CS_30M'] > informativeBTC30M['BTC_ICH_CS_HIGH_30M'])
#& (informativeBTC30M['BTC_ICH_CS_30M'] > informativeBTC30M['BTC_ICH_CS_KS_30M'])
#& (informativeBTC30M['BTC_ICH_CS_30M'] > informativeBTC30M['BTC_ICH_CS_TS_30M'])
#& (informativeBTC30M['BTC_ICH_CS_30M'] > informativeBTC30M['BTC_ICH_CS_SSA_30M'])
#& (informativeBTC30M['BTC_ICH_CS_30M'] > informativeBTC30M['BTC_ICH_CS_SSB_30M'])
#Conditions for the bitcoin in 30m
#& (informativeBTC30M['close'] > informativeBTC30M['open'])
#& (informativeBTC30M['BTC_ICH_CS_30M'] > informativeBTC30M['BTC_ICH_CS_HIGH_30M'])
#& (informativeBTC30M['BTC_ICH_CS_30M'] > informativeBTC30M['BTC_ICH_CS_KS_30M'])
#& (informativeBTC30M['BTC_ICH_CS_30M'] > informativeBTC30M['BTC_ICH_CS_TS_30M'])
#& (informativeBTC30M['BTC_ICH_CS_30M'] > informativeBTC30M['BTC_ICH_CS_SSA_30M'])
#& (informativeBTC30M['BTC_ICH_CS_30M'] > informativeBTC30M['BTC_ICH_CS_SSB_30M'])
#Conditions for the bitcoin in 1h
#& (informativeBTC1H['close'] > informativeBTC1H['open'])
#& (informativeBTC1H['BTC_ICH_CS_1H'] > informativeBTC1H['BTC_ICH_CS_HIGH_1H'])
#& (informativeBTC1H['BTC_ICH_CS_1H'] > informativeBTC1H['BTC_ICH_CS_KS_1H'])
#& (informativeBTC1H['BTC_ICH_CS_1H'] > informativeBTC1H['BTC_ICH_CS_TS_1H'])
#& (informativeBTC1H['BTC_ICH_CS_1H'] > informativeBTC1H['BTC_ICH_CS_SSA_1H'])
#& (informativeBTC1H['BTC_ICH_CS_1H'] > informativeBTC1H['BTC_ICH_CS_SSB_1H'])
#Conditions for the bitcoin in 4h
#& (informativeBTC4H['close'] > informativeBTC4H['open'])
#& (informativeBTC4H['BTC_ICH_CS_4H'] > informativeBTC4H['BTC_ICH_CS_HIGH_4H'])
#& (informativeBTC4H['BTC_ICH_CS_4H'] > informativeBTC4H['BTC_ICH_CS_KS_4H'])
#& (informativeBTC4H['BTC_ICH_CS_4H'] > informativeBTC4H['BTC_ICH_CS_TS_4H'])
#& (informativeBTC4H['BTC_ICH_CS_4H'] > informativeBTC4H['BTC_ICH_CS_SSA_4H'])
#& (informativeBTC4H['BTC_ICH_CS_4H'] > informativeBTC4H['BTC_ICH_CS_SSB_4H'])
#& (
# (informativeBTC4H['BTC_ICH_SSB_4H'] > informativeBTC4H['BTC_ICH_SSA_4H'])
# #& (informativeBTC4H['open'] < informativeBTC4H['BTC_ICH_SSB_4H'])
# #& (informativeBTC4H['close'] > informativeBTC4H['BTC_ICH_SSB_4H'])
# & (informativeBTC4H['close'] > informativeBTC4H['BTC_ICH_KS_4H'])
# & (informativeBTC4H['close'] > informativeBTC4H['BTC_ICH_TS_4H'])
#)
),
'enter_long'] = 1
dataframe.loc[
(
(dataframe['close'] < dataframe['open'])
& (dataframe['close'] < dataframe['ICH_SSA'])
& (dataframe['close'] < dataframe['ICH_SSB'])
& (dataframe['close'] < dataframe['ICH_KS'])
& (dataframe['close'] < dataframe['ICH_TS'])
& (dataframe['open'] < dataframe['ICH_SSA'])
& (dataframe['open'] < dataframe['ICH_SSB'])
& (dataframe['open'] < dataframe['ICH_KS'])
& (dataframe['open'] < dataframe['ICH_TS'])
& (dataframe['ICH_CS'] < dataframe['ICH_CS_LOW'])
& (dataframe['ICH_CS'] < dataframe['ICH_CS_KS'])
& (dataframe['ICH_CS'] < dataframe['ICH_CS_TS'])
& (dataframe['ICH_CS'] < dataframe['ICH_CS_SSA'])
& (dataframe['ICH_CS'] < dataframe['ICH_CS_SSB'])
& (informative5M['close'] < informative5M['open'])
& (informative5M['ICH_CS_5M'] < informative5M['ICH_CS_HIGH_5M'])
& (informative5M['ICH_CS_5M'] < informative5M['ICH_CS_KS_5M'])
& (informative5M['ICH_CS_5M'] < informative5M['ICH_CS_TS_5M'])
& (informative5M['ICH_CS_5M'] < informative5M['ICH_CS_SSA_5M'])
& (informative5M['ICH_CS_5M'] < informative5M['ICH_CS_SSB_5M'])
& (informative15M['close'] < informative15M['open'])
& (informative15M['ICH_CS_15M'] < informative15M['ICH_CS_LOW_15M'])
& (informative15M['ICH_CS_15M'] < informative15M['ICH_CS_KS_15M'])
& (informative15M['ICH_CS_15M'] < informative15M['ICH_CS_TS_15M'])
& (informative15M['ICH_CS_15M'] < informative15M['ICH_CS_SSA_15M'])
& (informative15M['ICH_CS_15M'] < informative15M['ICH_CS_SSB_15M'])
#& (informative30M['close'] < informative30M['open'])
#& (informative30M['ICH_CS_30M'] < informative30M['ICH_CS_LOW_30M'])
#& (informative30M['ICH_CS_30M'] < informative30M['ICH_CS_KS_30M'])
#& (informative30M['ICH_CS_30M'] < informative30M['ICH_CS_TS_30M'])
#& (informative30M['ICH_CS_30M'] < informative30M['ICH_CS_SSA_30M'])
#& (informative30M['ICH_CS_30M'] < informative30M['ICH_CS_SSB_30M'])
#& (informative1H['ICH_CS_1H'] < informative1H['ICH_CS_LOW_1H'])
#& (informative1H['ICH_CS_1H'] < informative1H['ICH_CS_KS_1H'])
#& (informative1H['ICH_CS_1H'] < informative1H['ICH_CS_TS_1H'])
#& (informative1H['ICH_CS_1H'] < informative1H['ICH_CS_SSA_1H'])
#& (informative1H['ICH_CS_1H'] < informative1H['ICH_CS_SSB_1H'])
#& (informative4H['ICH_CS_4H'] < informative4H['ICH_CS_LOW_4H'])
#& (informative4H['ICH_CS_4H'] < informative4H['ICH_CS_KS_4H'])
#& (informative4H['ICH_CS_4H'] < informative4H['ICH_CS_TS_4H'])
#& (informative4H['ICH_CS_4H'] < informative4H['ICH_CS_SSA_4H'])
#& (informative4H['ICH_CS_4H'] < informative4H['ICH_CS_SSB_4H'])
#Conditions for the bitcoin in 15m
#& (informativeBTC15M['close'] < informativeBTC15M['open'])
#& (informativeBTC15M['BTC_ICH_CS_15M'] < informativeBTC15M['BTC_ICH_CS_LOW_15M'])
#& (informativeBTC15M['BTC_ICH_CS_15M'] < informativeBTC15M['BTC_ICH_CS_KS_15M'])
#& (informativeBTC15M['BTC_ICH_CS_15M'] < informativeBTC15M['BTC_ICH_CS_TS_15M'])
#& (informativeBTC15M['BTC_ICH_CS_15M'] < informativeBTC15M['BTC_ICH_CS_SSA_15M'])
#& (informativeBTC15M['BTC_ICH_CS_15M'] < informativeBTC15M['BTC_ICH_CS_SSB_15M'])
#Conditions for the bitcoin in 30m
#& (informativeBTC30M['close'] < informativeBTC30M['open'])
#& (informativeBTC30M['BTC_ICH_CS_30M'] < informativeBTC30M['BTC_ICH_CS_LOW_30M'])
#& (informativeBTC30M['BTC_ICH_CS_30M'] < informativeBTC30M['BTC_ICH_CS_KS_30M'])
#& (informativeBTC30M['BTC_ICH_CS_30M'] < informativeBTC30M['BTC_ICH_CS_TS_30M'])
#& (informativeBTC30M['BTC_ICH_CS_30M'] < informativeBTC30M['BTC_ICH_CS_SSA_30M'])
#& (informativeBTC30M['BTC_ICH_CS_30M'] < informativeBTC30M['BTC_ICH_CS_SSB_30M'])
#& (informativeBTC1H['close'] < informativeBTC1H['open'])
#& (informativeBTC1H['BTC_ICH_CS_1H'] < informativeBTC1H['BTC_ICH_CS_LOW_1H'])
#& (informativeBTC1H['BTC_ICH_CS_1H'] < informativeBTC1H['BTC_ICH_CS_KS_1H'])
#& (informativeBTC1H['BTC_ICH_CS_1H'] < informativeBTC1H['BTC_ICH_CS_TS_1H'])
#& (informativeBTC1H['BTC_ICH_CS_1H'] < informativeBTC1H['BTC_ICH_CS_SSA_1H'])
#& (informativeBTC1H['BTC_ICH_CS_1H'] < informativeBTC1H['BTC_ICH_CS_SSB_1H'])
#& (informativeBTC4H['close'] < informativeBTC4H['open'])
#& (informativeBTC4H['BTC_ICH_CS_4H'] < informativeBTC4H['BTC_ICH_CS_LOW_4H'])
#& (informativeBTC4H['BTC_ICH_CS_4H'] < informativeBTC4H['BTC_ICH_CS_KS_4H'])
#& (informativeBTC4H['BTC_ICH_CS_4H'] < informativeBTC4H['BTC_ICH_CS_TS_4H'])
#& (informativeBTC4H['BTC_ICH_CS_4H'] < informativeBTC4H['BTC_ICH_CS_SSA_4H'])
#& (informativeBTC4H['BTC_ICH_CS_4H'] < informativeBTC4H['BTC_ICH_CS_SSB_4H'])
#& (
# (informativeBTC4H['BTC_ICH_SSB_4H'] < informativeBTC4H['BTC_ICH_SSA_4H'])
# #& (informativeBTC4H['open'] > informativeBTC4H['BTC_ICH_SSB_4H'])
# #& (informativeBTC4H['close'] < informativeBTC4H['BTC_ICH_SSB_4H'])
# & (informativeBTC4H['close'] < informativeBTC4H['BTC_ICH_KS_4H'])
# & (informativeBTC4H['close'] < informativeBTC4H['BTC_ICH_TS_4H'])
#)
),
'enter_short'] = 1
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
global informativeBTC15M
global informativeBTC30M
global informativeBTC1H
global informativeBTC4H
global informative5M
global informative15M
global informative30M
global informative1H
global informative4H
"""
dataframe.loc[
(
#(dataframe['close'] < dataframe['open'])
#(dataframe['close'] < dataframe['ICH_SSA'])
#| (dataframe['close'] < dataframe['ICH_SSB'])
(dataframe['close'] < dataframe['ICH_KS'])
#| (dataframe['close'] < dataframe['ICH_TS'])
),
'exit_long'] = 1
dataframe.loc[
(
#(dataframe['close'] > dataframe['open'])
#(dataframe['close'] > dataframe['ICH_SSA'])
#| (dataframe['close'] > dataframe['ICH_SSB'])
(dataframe['close'] > dataframe['ICH_KS'])
#| (dataframe['close'] > dataframe['ICH_TS'])
),
'exit_short'] = 1
"""
return dataframe