renamed after slippage profit_percent so it wont affect _calculate_results_metrics()
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@ -29,16 +29,16 @@ class SharpeHyperOptLossDaily(IHyperOptLoss):
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Uses Sharpe Ratio calculation.
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"""
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# get profit_percent and apply slippage of 0.1% per trade
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results.loc[:, 'profit_percent'] = results['profit_percent'] - 0.0005
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results.loc[:, 'profit_percent_after_slippage'] = results['profit_percent'] - 0.0005
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sum_daily = (
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results.resample("D", on="close_time").agg(
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{"profit_percent": sum}
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{"profit_percent_after_slippage": sum}
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)
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* 100.0
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)
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total_profit = sum_daily["profit_percent"]
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total_profit = sum_daily["profit_percent_after_slippage"]
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expected_returns_mean = total_profit.mean()
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up_stdev = np.std(total_profit)
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