# Heracles Strategy: Strongest Son of GodStra # ( With just 1 Genome! its a bacteria :D ) # Author: @Mablue (Masoud Azizi) # github: https://github.com/mablue/ # IMPORTANT:Add to your pairlists inside config.json (Under StaticPairList): # { # "method": "AgeFilter", # "min_days_listed": 100 # }, # IMPORTANT: INSTALL TA BEFOUR RUN(pip install ta) # ###################################################################### # Optimal config settings: # "max_open_trades": 100, # "stake_amount": "unlimited", # --- Do not remove these libs --- import logging from numpy.lib import math from freqtrade.strategy.interface import IStrategy from pandas import DataFrame # -------------------------------- # Add your lib to import here # import talib.abstract as ta import pandas as pd import ta from ta.utils import dropna import freqtrade.vendor.qtpylib.indicators as qtpylib from functools import reduce import numpy as np class Heracles(IStrategy): INTERFACE_VERSION = 3 # 65/600: 2275 trades. 1438/7/830 W/D/L. # Avg profit 3.10%. Median profit 3.06%. # Total profit 113171 USDT ( 7062 Σ%). # Avg duration 345 min. Objective: -23.0 # Buy hyperspace params: entry_params = {'entry-cross-0': 'volatility_kcw', 'entry-indicator-0': 'volatility_dcp', 'entry-oper-0': '<'} # Sell hyperspace params: exit_params = {'exit-cross-0': 'trend_macd_signal', 'exit-indicator-0': 'trend_ema_fast', 'exit-oper-0': '='} # ROI table: minimal_roi = {'0': 0.32836, '1629': 0.17896, '6302': 0.05372, '10744': 0} # Stoploss: stoploss = -0.04655 # Trailing stop: trailing_stop = True trailing_stop_positive = 0.02444 trailing_stop_positive_offset = 0.04406 trailing_only_offset_is_reached = True # Buy hypers timeframe = '5m' def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: # Add all ta features dataframe = dropna(dataframe) dataframe['volatility_kcw'] = ta.volatility.keltner_channel_wband(dataframe['high'], dataframe['low'], dataframe['close'], window=20, window_atr=10, fillna=False, original_version=True) dataframe['volatility_dcp'] = ta.volatility.donchian_channel_pband(dataframe['high'], dataframe['low'], dataframe['close'], window=10, offset=0, fillna=False) dataframe['trend_macd_signal'] = ta.trend.macd_signal(dataframe['close'], window_slow=26, window_fast=12, window_sign=9, fillna=False) dataframe['trend_ema_fast'] = ta.trend.EMAIndicator(close=dataframe['close'], window=12, fillna=False).ema_indicator() return dataframe def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: IND = self.entry_params['entry-indicator-0'] CRS = self.entry_params['entry-cross-0'] DFIND = dataframe[IND] DFCRS = dataframe[CRS] dataframe.loc[DFIND < DFCRS, 'enter_long'] = 1 return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: IND = self.exit_params['exit-indicator-0'] CRS = self.exit_params['exit-cross-0'] DFIND = dataframe[IND] DFCRS = dataframe[CRS] dataframe.loc[qtpylib.crossed_below(DFIND, DFCRS), 'exit_long'] = 1 return dataframe