39 lines
1.2 KiB
Python
39 lines
1.2 KiB
Python
"""
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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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#
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# Note, this is ratio. 3.85 stated above means 385Σ%, 3.0 means 300Σ%.
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#
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# In this implementation it's only used in calculation of the resulting value
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# of the objective function as a normalization coefficient and does not
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# represent any limit for profits as in the Freqtrade legacy default loss function.
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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 1 - total_profit / EXPECTED_MAX_PROFIT
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