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35 lines
1.0 KiB
Python
35 lines
1.0 KiB
Python
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"""
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OnlyProfitHyperOptLoss
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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 pandas import DataFrame
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from freqtrade.optimize.hyperopt import IHyperOptLoss
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# This is assumed to be expected avg profit * expected trade count.
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# For example, for 0.35% avg per trade (or 0.0035 as ratio) and 1100 trades,
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# expected max profit = 3.85
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# Check that the reported Σ% values do not exceed this!
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# Note, this is ratio. 3.85 stated above means 385Σ%.
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EXPECTED_MAX_PROFIT = 3.0
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class OnlyProfitHyperOptLoss(IHyperOptLoss):
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"""
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Defines the loss function for hyperopt.
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This implementation takes only profit into account.
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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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*args, **kwargs) -> float:
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"""
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Objective function, returns smaller number for better results.
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"""
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total_profit = results.profit_percent.sum()
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return max(0, 1 - total_profit / EXPECTED_MAX_PROFIT)
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