# Source: generated via dynamic_strategy_generator from freqtrade.strategy import IStrategy from pandas import DataFrame import talib.abstract as ta import freqtrade.vendor.qtpylib.indicators as qtpylib class ACO_94_7(IStrategy): timeframe = '1h' # Standard ROI and Stoploss minimal_roi = {"0": 0.1, "60": 0.05, "120": 0.0} stoploss = -0.05 def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe['adx'] = ta.ADX(dataframe, timeperiod=14) dataframe['atr'] = ta.ATR(dataframe, timeperiod=14) dataframe['natr'] = ta.NATR(dataframe, timeperiod=14) macd = ta.MACD(dataframe, fastperiod=8, slowperiod=17, signalperiod=9) dataframe['macd'] = macd['macd'] dataframe['macdsignal'] = macd['macdsignal'] dataframe['macdhist'] = macd['macdhist'] dataframe['plus_di'] = ta.PLUS_DI(dataframe, timeperiod=14) dataframe['minus_di'] = ta.MINUS_DI(dataframe, timeperiod=14) dataframe['ppo'] = ta.PPO(dataframe, fastperiod=5, slowperiod=20) bbands = ta.BBANDS(dataframe, timeperiod=14, nbdevup=2.0, nbdevdn=2.0) dataframe['upperband'] = bbands['upperband'] dataframe['middleband'] = bbands['middleband'] dataframe['lowerband'] = bbands['lowerband'] return dataframe def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (dataframe['adx'] > 25) ) & ( (dataframe['natr'] > 2.0) ), 'enter_long'] = 1 return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( qtpylib.crossed_below(dataframe['macd'], dataframe['macdsignal']) ) & ( qtpylib.crossed_below(dataframe['plus_di'], dataframe['minus_di']) ) & ( qtpylib.crossed_below(dataframe['ppo'], 0) ) & ( (dataframe['close'] > dataframe['upperband'] * 0.98) ), 'exit_long'] = 1 return dataframe