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Fix calculation of calmar ratio

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Pialat 2019-09-12 16:03:03 +02:00
parent 84aac56dd3
commit 6958160ae6
1 changed files with 1 additions and 2 deletions
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3
freqtrade/optimize/hyperopt_loss_calmar.py
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@ -41,7 +41,6 @@ class CalmarHyperOptLoss(IHyperOptLoss):
results['profit_percent'] -= SLIPPAGE_PERCENT results['profit_percent'] -= SLIPPAGE_PERCENT
return_avg_per_year = (results.profit_percent.sum() / backtest_duration_years) return_avg_per_year = (results.profit_percent.sum() / backtest_duration_years)
return_avg_simulation_duration = return_avg_per_year * SIMULATION_YEAR_DURATION
sample_size = round(trade_count_average_per_year * SIMULATION_YEAR_DURATION) sample_size = round(trade_count_average_per_year * SIMULATION_YEAR_DURATION)
@ -58,7 +57,7 @@ class CalmarHyperOptLoss(IHyperOptLoss):
simulated_drawdowns.append(simulated_drawdown) simulated_drawdowns.append(simulated_drawdown)
abs_mediam_simulated_drawdowns = Series(simulated_drawdowns).median() abs_mediam_simulated_drawdowns = Series(simulated_drawdowns).median()
calmar_ratio = return_avg_simulation_duration/abs_mediam_simulated_drawdowns calmar_ratio = return_avg_per_year/abs_mediam_simulated_drawdowns
# Normalize loss value to be float between (0, 1) # Normalize loss value to be float between (0, 1)
calmar_loss = 1 - (norm.cdf(calmar_ratio, 0, 100)) calmar_loss = 1 - (norm.cdf(calmar_ratio, 0, 100))