Merge pull request #2834 from yazeed/consistent_main_sharpe_hyperopt_loss

better readability on sharpe ratio loss method
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Matthias 2020-02-02 11:12:56 +01:00 committed by GitHub
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@ -28,18 +28,19 @@ class SharpeHyperOptLoss(IHyperOptLoss):
Uses Sharpe Ratio calculation. Uses Sharpe Ratio calculation.
""" """
total_profit = results.profit_percent total_profit = results["profit_percent"]
days_period = (max_date - min_date).days days_period = (max_date - min_date).days
# adding slippage of 0.1% per trade # adding slippage of 0.1% per trade
total_profit = total_profit - 0.0005 total_profit = total_profit - 0.0005
expected_yearly_return = total_profit.sum() / days_period expected_returns_mean = total_profit.sum() / days_period
up_stdev = np.std(total_profit)
if (np.std(total_profit) != 0.): if (np.std(total_profit) != 0.):
sharp_ratio = expected_yearly_return / np.std(total_profit) * np.sqrt(365) sharp_ratio = expected_returns_mean / up_stdev * np.sqrt(365)
else: else:
# Define high (negative) sharpe ratio to be clear that this is NOT optimal. # Define high (negative) sharpe ratio to be clear that this is NOT optimal.
sharp_ratio = -20. sharp_ratio = -20.
# print(expected_yearly_return, np.std(total_profit), sharp_ratio) # print(expected_returns_mean, up_stdev, sharp_ratio)
return -sharp_ratio return -sharp_ratio