Merge pull request #5678 from sidml/develop
Hyperopt loss function using max drawdown
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@@ -24,7 +24,8 @@ ORDERTYPE_POSSIBILITIES = ['limit', 'market']
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ORDERTIF_POSSIBILITIES = ['gtc', 'fok', 'ioc']
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HYPEROPT_LOSS_BUILTIN = ['ShortTradeDurHyperOptLoss', 'OnlyProfitHyperOptLoss',
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'SharpeHyperOptLoss', 'SharpeHyperOptLossDaily',
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'SortinoHyperOptLoss', 'SortinoHyperOptLossDaily']
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'SortinoHyperOptLoss', 'SortinoHyperOptLossDaily',
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'MaxDrawDownHyperOptLoss']
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AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList',
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'AgeFilter', 'OffsetFilter', 'PerformanceFilter',
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'PrecisionFilter', 'PriceFilter', 'RangeStabilityFilter',
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41
freqtrade/optimize/hyperopt_loss_max_drawdown.py
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41
freqtrade/optimize/hyperopt_loss_max_drawdown.py
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@@ -0,0 +1,41 @@
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"""
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MaxDrawDownHyperOptLoss
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This module defines the alternative HyperOptLoss class which can be used for
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Hyperoptimization.
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"""
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from datetime import datetime
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from pandas import DataFrame
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from freqtrade.data.btanalysis import calculate_max_drawdown
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from freqtrade.optimize.hyperopt import IHyperOptLoss
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class MaxDrawDownHyperOptLoss(IHyperOptLoss):
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"""
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Defines the loss function for hyperopt.
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This implementation optimizes for max draw down and profit
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Less max drawdown more profit -> Lower return value
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"""
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@staticmethod
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def hyperopt_loss_function(results: DataFrame, trade_count: int,
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min_date: datetime, max_date: datetime,
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*args, **kwargs) -> float:
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"""
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Objective function.
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Uses profit ratio weighted max_drawdown when drawdown is available.
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Otherwise directly optimizes profit ratio.
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"""
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total_profit = results['profit_abs'].sum()
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try:
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max_drawdown = calculate_max_drawdown(results, value_col='profit_abs')
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except ValueError:
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# No losing trade, therefore no drawdown.
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return -total_profit
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return -total_profit / max_drawdown[0]
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