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43 lines
1.1 KiB
Python
43 lines
1.1 KiB
Python
"""
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CalmarHyperOptLoss
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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.constants import Config
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from freqtrade.data.metrics import calculate_calmar
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from freqtrade.optimize.hyperopt import IHyperOptLoss
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class CalmarHyperOptLoss(IHyperOptLoss):
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"""
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Defines the loss function for hyperopt.
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This implementation uses the Calmar Ratio calculation.
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"""
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@staticmethod
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def hyperopt_loss_function(
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results: DataFrame,
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trade_count: int,
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min_date: datetime,
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max_date: datetime,
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config: Config,
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*args,
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**kwargs,
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) -> float:
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"""
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Objective function, returns smaller number for more optimal results.
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Uses Calmar Ratio calculation.
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"""
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starting_balance = config["dry_run_wallet"]
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calmar_ratio = calculate_calmar(results, min_date, max_date, starting_balance)
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# print(expected_returns_mean, max_drawdown, calmar_ratio)
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return -calmar_ratio
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