# 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_9_5(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['trix'] = ta.TRIX(dataframe, timeperiod=21) dataframe['ultosc'] = ta.ULTOSC(dataframe, timeperiod1=7, timeperiod2=14, timeperiod3=28) bbands = ta.BBANDS(dataframe, timeperiod=20, nbdevup=2.5, nbdevdn=2.5) dataframe['upperband'] = bbands['upperband'] dataframe['middleband'] = bbands['middleband'] dataframe['lowerband'] = bbands['lowerband'] dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14) dataframe['cci'] = ta.CCI(dataframe, timeperiod=7) dataframe['ema_fast'] = ta.EMA(dataframe, timeperiod=20) dataframe['ema_slow'] = ta.EMA(dataframe, timeperiod=50) dataframe['sar'] = ta.SAR(dataframe, acceleration=0.02, maximum=0.2) return dataframe def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (dataframe['adx'] > 30) ) & ( qtpylib.crossed_above(dataframe['trix'], 0) ) & ( (dataframe['ultosc'] < 35) ) & ( (dataframe['close'] < dataframe['lowerband'] * 1.0) ), 'enter_long'] = 1 return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (dataframe['rsi'] > 70) ) & ( (dataframe['rsi'] > 65) ) & ( (dataframe['cci'] > 80) ) & ( qtpylib.crossed_below(dataframe['ema_fast'], dataframe['ema_slow']) ) & ( qtpylib.crossed_below(dataframe['close'], dataframe['sar']) ), 'exit_long'] = 1 return dataframe