Updated 3/24/2018 4:35PMC
Updated 3/24/2018 4:35PMC Added example notes on how to configure your strategy.
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@ -13,9 +13,35 @@ import freqtrade.vendor.qtpylib.indicators as qtpylib
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import numpy # noqa
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import numpy # noqa
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# Make a backup of default_strategy then move this file over your default strategy in freqtrade/strategy and to run run with -s all to find best values when running hyperopt.
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# Make a backup of default_strategy then move this file over your default strategy in freqtrade/strategy and to run:
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#
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# 'python3.6 freqtrade/main.py -c config.json hyperopt -s all --realistic-simulation -i 5'
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# Make sure to take note of the if statements at the bottom of the file, and the pattern of > < and >= <= and the triggers configuration.
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# Make sure to take note of the if statements at the bottom of the file, and the pattern of > < and >= <= and the triggers configuration.
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# Then, take note of the results: There is one trigger in the results, map the trigger as an example:
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# 'Trigger: 7'
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# The 7th trigger in this file's if statement such as:
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# 'sar_reversal': (qtpylib.crossed_above(
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# dataframe['close'], dataframe['sar']
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#
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# Drop the trigger into 'def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:' as:
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# dataframe['close'], dataframe['sar'] &
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# Then for your other values such as: 'Mfi-Value: 15.00'
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# The if statement looks like: conditions.append(dataframe['mfi'] < params['mfi']['value']
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# Drop this in as:
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# (dataframe['mfi'] < 15.00) &
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# The last condition in 'def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:' will have no &
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### As an example the sell/buy trend looks like this:
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# dataframe.loc[
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# (
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# (dataframe['adx'] > 70) &
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# (dataframe['tema'] < dataframe['tema'].shift(1))
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# ),
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# 'sell'] = 1
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#
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class_name = 'DefaultStrategy'
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class_name = 'DefaultStrategy'
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