# --- Do not remove these libs --- from freqtrade.strategy.interface import IStrategy from typing import Dict, List from functools import reduce from pandas import DataFrame # -------------------------------- import talib.abstract as ta class MACDStrategy(IStrategy): """ author@: Gert Wohlgemuth idea: uptrend definition: MACD above MACD signal and CCI < -50 downtrend definition: MACD below MACD signal and CCI > 100 """ # Minimal ROI designed for the strategy. # This attribute will be overridden if the config file contains "minimal_roi" minimal_roi = { "0": 0.1858737982036954, "27": 0.02524445335072633, "80": 0.013912072159850514, "154": 0 } # Optimal stoploss designed for the strategy # This attribute will be overridden if the config file contains "stoploss" stoploss = -0.27408960533563953 # Optimal timeframe for the strategy timeframe = '5m' def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: macd = ta.MACD(dataframe) dataframe['macd'] = macd['macd'] dataframe['macdsignal'] = macd['macdsignal'] dataframe['macdhist'] = macd['macdhist'] dataframe['cci'] = ta.CCI(dataframe) return dataframe def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: """ Based on TA indicators, populates the buy signal for the given dataframe :param dataframe: DataFrame :return: DataFrame with buy column """ dataframe.loc[ ( (dataframe['macd'] > dataframe['macdsignal']) & (dataframe['cci'] <= -205.0) ), 'buy'] = 1 return dataframe def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: """ Based on TA indicators, populates the sell signal for the given dataframe :param dataframe: DataFrame :return: DataFrame with buy column """ dataframe.loc[ ( (dataframe['macd'] < dataframe['macdsignal']) & (dataframe['cci'] >= 360.0) ), 'sell'] = 1 return dataframe