smooth normelization

This commit is contained in:
Pialat 2019-09-12 16:55:33 +02:00
parent 2670960ec4
commit dc8fd641ad

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@ -59,8 +59,8 @@ class CalmarHyperOptLoss(IHyperOptLoss):
abs_mediam_simulated_drawdowns = Series(simulated_drawdowns).median()
calmar_ratio = return_avg_per_year/abs_mediam_simulated_drawdowns
# Normalize loss value to be float between (0, 1)
calmar_loss = 1 - (norm.cdf(calmar_ratio, 0, 100))
# Normalize loss value to be float between (0, 1) : 0.5 value mean no profit
calmar_loss = 1 - (norm.cdf(calmar_ratio, 0, 10))
# feel free to add other criterias (e.g avg expected time duration)
loss = (calmar_loss * CALMAR_LOSS_WEIGHT)