adjusted to keep perfomance in percent consistent, while allowing to buy large swings
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@ -23,6 +23,8 @@ class Quickie(IStrategy):
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# This attribute will be overridden if the config file contains "minimal_roi"
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minimal_roi = {
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"100": 0.01,
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"45": 0.02,
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"30": 0.03,
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"15": 0.06,
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"10": 0.15,
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}
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@ -35,13 +37,10 @@ class Quickie(IStrategy):
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ticker_interval = 5
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def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
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macd = ta.MACD(dataframe)
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dataframe['macd'] = macd['macd']
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dataframe['macdsignal'] = macd['macdsignal']
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dataframe['macdhist'] = macd['macdhist']
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dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)
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dataframe['sma_200'] = ta.SMA(dataframe,timeperiod=200)
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dataframe['sma_200'] = ta.SMA(dataframe, timeperiod=200)
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dataframe['sma_50'] = ta.SMA(dataframe, timeperiod=50)
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dataframe['adx'] = ta.ADX(dataframe)
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# required for graphing
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@ -55,10 +54,17 @@ class Quickie(IStrategy):
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def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
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dataframe.loc[
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(
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(dataframe['adx'] > 30) &
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(dataframe['tema'] < dataframe['bb_middleband']) &
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(dataframe['tema'] > dataframe['tema'].shift(1)) &
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(dataframe['sma_200'] > dataframe['close'])
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(
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(dataframe['adx'] > 30) &
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(dataframe['tema'] < dataframe['bb_middleband']) &
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(dataframe['tema'] > dataframe['tema'].shift(1)) &
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(dataframe['sma_200'] > dataframe['close'])
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)
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(
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(dataframe['sma_200'] > dataframe['close']) &
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(dataframe['sma_50'] < dataframe['sma_200'])
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)
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),
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'buy'] = 1
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return dataframe
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