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implement expected number of trades

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Pialat 2019-09-16 11:58:51 +02:00
parent 2a06a95e77
commit 12288362c3
1 changed files with 7 additions and 0 deletions
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7
freqtrade/optimize/hyperopt_loss_calmar.py
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@ -10,6 +10,8 @@ SIMULATION_YEAR_DURATION = 3
CALMAR_LOSS_WEIGHT = 1 CALMAR_LOSS_WEIGHT = 1
SLIPPAGE_PERCENT = 0.000 SLIPPAGE_PERCENT = 0.000
NB_EXPECTED_TRADES = 600
EXPECTED_TRADES_WEIGHT = 0.5
class CalmarHyperOptLoss(IHyperOptLoss): class CalmarHyperOptLoss(IHyperOptLoss):
@ -64,6 +66,11 @@ class CalmarHyperOptLoss(IHyperOptLoss):
# Normalize loss value to be float between (0, 1) : 0.5 value mean no profit # Normalize loss value to be float between (0, 1) : 0.5 value mean no profit
calmar_loss = 1 - (norm.cdf(calmar_ratio, 0, 10)) calmar_loss = 1 - (norm.cdf(calmar_ratio, 0, 10))
"""
Normalize loss value to be float between (0, 0.5) :
Closed to 0 mean trade_count = NB_EXPECTED_TRADES
"""
expected_trade_loss_penalty = 1 - norm.cdf(trade_count-NB_EXPECTED_TRADES,-NB_EXPECTED_TRADES,(NB_EXPECTED_TRADES*(2/3))*EXPECTED_TRADES_WEIGHT)
# feel free to add other criterias (e.g avg expected time duration) # feel free to add other criterias (e.g avg expected time duration)
loss = (calmar_loss * CALMAR_LOSS_WEIGHT) loss = (calmar_loss * CALMAR_LOSS_WEIGHT)