# 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_15_0(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['sar'] = ta.SAR(dataframe, acceleration=0.02, maximum=0.2) bbands = ta.BBANDS(dataframe, timeperiod=20, nbdevup=1.5, nbdevdn=1.5) dataframe['upperband'] = bbands['upperband'] dataframe['middleband'] = bbands['middleband'] dataframe['lowerband'] = bbands['lowerband'] dataframe['ad'] = ta.AD(dataframe) dataframe['ad_sma'] = ta.SMA(dataframe, timeperiod=20, price='ad') dataframe['mom'] = ta.MOM(dataframe, timeperiod=20) dataframe['aroonosc'] = ta.AROONOSC(dataframe, timeperiod=14) dataframe['sma_fast'] = ta.SMA(dataframe, timeperiod=20) dataframe['sma_slow'] = ta.SMA(dataframe, timeperiod=50) dataframe['natr'] = ta.NATR(dataframe, timeperiod=14) return dataframe def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( qtpylib.crossed_above(dataframe['close'], dataframe['sar']) ) & ( (dataframe['close'] < dataframe['lowerband'] * 1.0) ) & ( qtpylib.crossed_above(dataframe['ad'], dataframe['ad_sma']) ) & ( qtpylib.crossed_above(dataframe['ad'], dataframe['ad_sma']) ), 'enter_long'] = 1 return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( qtpylib.crossed_below(dataframe['mom'], 0) ) & ( qtpylib.crossed_below(dataframe['aroonosc'], 0) ) & ( qtpylib.crossed_below(dataframe['sma_fast'], dataframe['sma_slow']) ), 'exit_long'] = 1 return dataframe