# source: https://raw.githubusercontent.com/reuniware/FreqTrade_Work/1242db6ddb25d808d1118a72f7988d6de17974df/202210-freqtrade-work/ETUDE001/strat-ichimoku-008-binance.py # 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 Github_reuniware_FreqTrade_Work__strat_ichimoku_008_binance__20221023_122014(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 = False #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": 0.01 } # Optimal stoploss designed for the strategy. # This attribute will be overridden if the config file contains "stoploss". stoploss = -0.005 # 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 = False # 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, '1m') for pair in pairs] 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", "1m"), ("BTC/USDT", "15m"), ("BTC/USDT", "30m"), ("BTC/USDT", "1h"), ("BTC/USDT", "4h"),] informative_pairs += [("BTC/USDT", "1m"), ("BTC/USDT", "5m"),] return informative_pairs informativeBTC1M : DataFrame informativeBTC5M : DataFrame #informativeBTC15M : DataFrame #informativeBTC30M : DataFrame #informativeBTC1H : DataFrame #informativeBTC4H : DataFrame #informative1M : DataFrame informative5M : DataFrame informative15M : DataFrame #informative30M : DataFrame #informative1H : DataFrame #informative4H : DataFrame def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: global informativeBTC1M global informativeBTC5M #global informativeBTC15M #global informativeBTC30M #global informativeBTC1H #global informativeBTC4H #global informative1M global informative5M global informative15M #global informative30M #global informative1H #global informative4H #log_to_results(metadata['pair']) currentPair = str(metadata['pair']) inf_tf = '1m' informativeBTC1M = self.dp.get_pair_dataframe(pair="BTC/USDT", timeframe=inf_tf) inf_tf = '5m' informativeBTC5M = self.dp.get_pair_dataframe(pair="BTC/USDT", timeframe=inf_tf) #inf_tf = '15m' #informativeBTC15M = self.dp.get_pair_dataframe(pair="BTC/USDT", timeframe=inf_tf) #inf_tf = '30m' #informativeBTC30M = self.dp.get_pair_dataframe(pair="BTC/USDT", timeframe=inf_tf) #inf_tf = '1h' #informativeBTC1H = self.dp.get_pair_dataframe(pair="BTC/USDT", timeframe=inf_tf) #inf_tf = '4h' #informativeBTC4H = self.dp.get_pair_dataframe(pair="BTC/USDT", timeframe=inf_tf) #inf_tf = '1m' #informative1M = self.dp.get_pair_dataframe(pair=currentPair, 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 1m informativeBTC1M['BTC_ICH_SSB_1M'] = taichi.trend.ichimoku_b(informativeBTC1M['high'], informativeBTC1M['low'], window2=26, window3=52).shift(26) informativeBTC1M['BTC_ICH_SSA_1M'] = taichi.trend.ichimoku_a(informativeBTC1M['high'], informativeBTC1M['low'], window1=9, window2=26).shift(26) informativeBTC1M['BTC_ICH_KS_1M'] = taichi.trend.ichimoku_base_line(informativeBTC1M['high'], informativeBTC1M['low']) informativeBTC1M['BTC_ICH_TS_1M'] = taichi.trend.ichimoku_conversion_line(informativeBTC1M['high'], informativeBTC1M['low']) informativeBTC1M['BTC_ICH_CS_1M'] = informativeBTC1M['close'] informativeBTC1M['BTC_ICH_CS_HIGH_1M'] = informativeBTC1M['high'].shift(26) informativeBTC1M['BTC_ICH_CS_LOW_1M'] = informativeBTC1M['low'].shift(26) informativeBTC1M['BTC_ICH_CS_KS_1M'] = informativeBTC1M['BTC_ICH_KS_1M'].shift(26) informativeBTC1M['BTC_ICH_CS_TS_1M'] = informativeBTC1M['BTC_ICH_TS_1M'].shift(26) informativeBTC1M['BTC_ICH_CS_SSA_1M'] = informativeBTC1M['BTC_ICH_SSA_1M'].shift(26) informativeBTC1M['BTC_ICH_CS_SSB_1M'] = informativeBTC1M['BTC_ICH_SSB_1M'].shift(26) #Ichimoku calculations for the BTC in 5m informativeBTC5M['BTC_ICH_SSB_5M'] = taichi.trend.ichimoku_b(informativeBTC5M['high'], informativeBTC5M['low'], window2=26, window3=52).shift(26) informativeBTC5M['BTC_ICH_SSA_5M'] = taichi.trend.ichimoku_a(informativeBTC5M['high'], informativeBTC5M['low'], window1=9, window2=26).shift(26) informativeBTC5M['BTC_ICH_KS_5M'] = taichi.trend.ichimoku_base_line(informativeBTC5M['high'], informativeBTC5M['low']) informativeBTC5M['BTC_ICH_TS_5M'] = taichi.trend.ichimoku_conversion_line(informativeBTC5M['high'], informativeBTC5M['low']) informativeBTC5M['BTC_ICH_CS_5M'] = informativeBTC5M['close'] informativeBTC5M['BTC_ICH_CS_HIGH_5M'] = informativeBTC5M['high'].shift(26) informativeBTC5M['BTC_ICH_CS_LOW_5M'] = informativeBTC5M['low'].shift(26) informativeBTC5M['BTC_ICH_CS_KS_5M'] = informativeBTC5M['BTC_ICH_KS_5M'].shift(26) informativeBTC5M['BTC_ICH_CS_TS_5M'] = informativeBTC5M['BTC_ICH_TS_5M'].shift(26) informativeBTC5M['BTC_ICH_CS_SSA_5M'] = informativeBTC5M['BTC_ICH_SSA_5M'].shift(26) informativeBTC5M['BTC_ICH_CS_SSB_5M'] = informativeBTC5M['BTC_ICH_SSB_5M'].shift(26) #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 1m #informative1M['ICH_SSB_1M'] = taichi.trend.ichimoku_b(informative1M['high'], informative1M['low'], window2=26, window3=52).shift(26) #informative1M['ICH_SSA_1M'] = taichi.trend.ichimoku_a(informative1M['high'], informative1M['low'], window1=9, window2=26).shift(26) #informative1M['ICH_KS_1M'] = taichi.trend.ichimoku_base_line(informative1M['high'], informative1M['low']) #informative1M['ICH_TS_1M'] = taichi.trend.ichimoku_conversion_line(informative1M['high'], informative1M['low']) #informative1M['ICH_CS_1M'] = informative1M['close'] #informative1M['ICH_CS_HIGH_1M'] = informative1M['high'].shift(26) #informative1M['ICH_CS_LOW_1M'] = informative1M['low'].shift(26) #informative1M['ICH_CS_KS_1M'] = informative1M['ICH_KS_1M'].shift(26) #informative1M['ICH_CS_TS_1M'] = informative1M['ICH_TS_1M'].shift(26) #informative1M['ICH_CS_SSA_1M'] = informative1M['ICH_SSA_1M'].shift(26) #informative1M['ICH_CS_SSB_1M'] = informative1M['ICH_SSB_1M'].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 informativeBTC1M global informativeBTC5M #global informativeBTC15M #global informativeBTC30M #global informativeBTC1H #global informativeBTC4H #global informative1M 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_SSA']) & (dataframe['ICH_CS'] > dataframe['ICH_CS_SSB']) & (dataframe['ICH_CS'] > dataframe['ICH_CS_TS']) & (dataframe['ICH_CS'] > dataframe['ICH_CS_KS']) & (informative5M['close'] > informative5M['open']) & (informative5M['close'] > informative5M['ICH_SSA_5M']) & (informative5M['close'] > informative5M['ICH_SSB_5M']) & (informative5M['close'] > informative5M['ICH_TS_5M']) & (informative5M['close'] > informative5M['ICH_KS_5M']) & (informative5M['ICH_CS_5M'] > informative5M['ICH_CS_HIGH_5M']) & (informative5M['ICH_CS_5M'] > informative5M['ICH_CS_SSA_5M']) & (informative5M['ICH_CS_5M'] > informative5M['ICH_CS_SSB_5M']) & (informative5M['ICH_CS_5M'] > informative5M['ICH_CS_TS_5M']) & (informative5M['ICH_CS_5M'] > informative5M['ICH_CS_KS_5M']) & (informative15M['close'] > informative15M['open']) & (informative15M['close'] > informative15M['ICH_SSA_15M']) & (informative15M['close'] > informative15M['ICH_SSB_15M']) & (informative15M['close'] > informative15M['ICH_TS_15M']) & (informative15M['close'] > informative15M['ICH_KS_15M']) & (informative15M['ICH_CS_15M'] > informative15M['ICH_CS_HIGH_15M']) & (informative15M['ICH_CS_15M'] > informative15M['ICH_CS_SSA_15M']) & (informative15M['ICH_CS_15M'] > informative15M['ICH_CS_SSB_15M']) & (informative15M['ICH_CS_15M'] > informative15M['ICH_CS_TS_15M']) & (informative15M['ICH_CS_15M'] > informative15M['ICH_CS_KS_15M']) & (informativeBTC1M['close'] > informativeBTC1M['open']) & (informativeBTC1M['close'] > informativeBTC1M['BTC_ICH_SSA_1M']) & (informativeBTC1M['close'] > informativeBTC1M['BTC_ICH_SSB_1M']) & (informativeBTC1M['close'] > informativeBTC1M['BTC_ICH_TS_1M']) & (informativeBTC1M['close'] > informativeBTC1M['BTC_ICH_KS_1M']) & (informativeBTC1M['BTC_ICH_CS_1M'] > informativeBTC1M['BTC_ICH_CS_KS_1M']) & (informativeBTC1M['BTC_ICH_CS_1M'] > informativeBTC1M['BTC_ICH_CS_TS_1M']) & (informativeBTC1M['BTC_ICH_CS_1M'] > informativeBTC1M['BTC_ICH_CS_SSA_1M']) & (informativeBTC1M['BTC_ICH_CS_1M'] > informativeBTC1M['BTC_ICH_CS_SSB_1M']) & (informativeBTC1M['BTC_ICH_CS_1M'] > informativeBTC1M['BTC_ICH_CS_HIGH_1M']) & (informativeBTC5M['close'] > informativeBTC5M['open']) & (informativeBTC5M['close'] > informativeBTC5M['BTC_ICH_SSA_5M']) & (informativeBTC5M['close'] > informativeBTC5M['BTC_ICH_SSB_5M']) & (informativeBTC5M['close'] > informativeBTC5M['BTC_ICH_TS_5M']) & (informativeBTC5M['close'] > informativeBTC5M['BTC_ICH_KS_5M']) & (informativeBTC5M['BTC_ICH_CS_5M'] > informativeBTC5M['BTC_ICH_CS_KS_5M']) & (informativeBTC5M['BTC_ICH_CS_5M'] > informativeBTC5M['BTC_ICH_CS_TS_5M']) & (informativeBTC5M['BTC_ICH_CS_5M'] > informativeBTC5M['BTC_ICH_CS_SSA_5M']) & (informativeBTC5M['BTC_ICH_CS_5M'] > informativeBTC5M['BTC_ICH_CS_SSB_5M']) & (informativeBTC5M['BTC_ICH_CS_5M'] > informativeBTC5M['BTC_ICH_CS_HIGH_5M']) ), '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_SSA']) & (dataframe['ICH_CS'] < dataframe['ICH_CS_SSB']) & (dataframe['ICH_CS'] < dataframe['ICH_CS_TS']) & (dataframe['ICH_CS'] < dataframe['ICH_CS_KS']) & (informative5M['close'] < informative5M['open']) & (informative5M['close'] < informative5M['ICH_SSA_5M']) & (informative5M['close'] < informative5M['ICH_SSB_5M']) & (informative5M['close'] < informative5M['ICH_TS_5M']) & (informative5M['close'] < informative5M['ICH_KS_5M']) & (informative5M['ICH_CS_5M'] < informative5M['ICH_CS_LOW_5M']) & (informative5M['ICH_CS_5M'] < informative5M['ICH_CS_SSA_5M']) & (informative5M['ICH_CS_5M'] < informative5M['ICH_CS_SSB_5M']) & (informative5M['ICH_CS_5M'] < informative5M['ICH_CS_TS_5M']) & (informative5M['ICH_CS_5M'] < informative5M['ICH_CS_KS_5M']) & (informative15M['close'] < informative15M['open']) & (informative15M['close'] < informative15M['ICH_SSA_15M']) & (informative15M['close'] < informative15M['ICH_SSB_15M']) & (informative15M['close'] < informative15M['ICH_TS_15M']) & (informative15M['close'] < informative15M['ICH_KS_15M']) & (informative15M['ICH_CS_15M'] < informative15M['ICH_CS_LOW_15M']) & (informative15M['ICH_CS_15M'] < informative15M['ICH_CS_SSA_15M']) & (informative15M['ICH_CS_15M'] < informative15M['ICH_CS_SSB_15M']) & (informative15M['ICH_CS_15M'] < informative15M['ICH_CS_TS_15M']) & (informative15M['ICH_CS_15M'] < informative15M['ICH_CS_KS_15M']) & (informativeBTC1M['close'] < informativeBTC1M['open']) & (informativeBTC1M['BTC_ICH_CS_1M'] < informativeBTC1M['BTC_ICH_CS_KS_1M']) & (informativeBTC1M['BTC_ICH_CS_1M'] < informativeBTC1M['BTC_ICH_CS_TS_1M']) & (informativeBTC1M['BTC_ICH_CS_1M'] < informativeBTC1M['BTC_ICH_CS_SSA_1M']) & (informativeBTC1M['BTC_ICH_CS_1M'] < informativeBTC1M['BTC_ICH_CS_SSB_1M']) & (informativeBTC1M['BTC_ICH_CS_1M'] < informativeBTC1M['BTC_ICH_CS_LOW_1M']) & (informativeBTC5M['close'] < informativeBTC5M['open']) & (informativeBTC5M['BTC_ICH_CS_5M'] < informativeBTC5M['BTC_ICH_CS_KS_5M']) & (informativeBTC5M['BTC_ICH_CS_5M'] < informativeBTC5M['BTC_ICH_CS_TS_5M']) & (informativeBTC5M['BTC_ICH_CS_5M'] < informativeBTC5M['BTC_ICH_CS_SSA_5M']) & (informativeBTC5M['BTC_ICH_CS_5M'] < informativeBTC5M['BTC_ICH_CS_SSB_5M']) & (informativeBTC5M['BTC_ICH_CS_5M'] < informativeBTC5M['BTC_ICH_CS_LOW_5M']) ), 'enter_short'] = 1 return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: global informativeBTC1M global informativeBTC5M #global informativeBTC15M #global informativeBTC30M #global informativeBTC1H #global informativeBTC4H #global informative1M 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