import MAX_LOSS constant instead create a new one
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@ -1,12 +1,12 @@
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from datetime import datetime
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from datetime import datetime
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from pandas import DataFrame, Series
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from pandas import DataFrame, Series
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from freqtrade.optimize.hyperopt import IHyperOptLoss
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import numpy as np
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import numpy as np
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from scipy.stats import norm
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from scipy.stats import norm
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from freqtrade.optimize.hyperopt import IHyperOptLoss, MAX_LOSS
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NB_SIMULATIONS = 1000
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NB_SIMULATIONS = 1000
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SIMULATION_YEAR_DURATION = 3
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SIMULATION_YEAR_DURATION = 3
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HIGH_NUMBER = 100000
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CALMAR_LOSS_WEIGHT = 1
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CALMAR_LOSS_WEIGHT = 1
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SLIPPAGE_PERCENT = 0.001
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SLIPPAGE_PERCENT = 0.001
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@ -42,7 +42,7 @@ class CalmarHyperOptLoss(IHyperOptLoss):
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# exclude the case when no trade was lost
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# exclude the case when no trade was lost
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if(results.profit_percent.min() >= 0):
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if(results.profit_percent.min() >= 0):
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return HIGH_NUMBER
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return MAX_LOSS
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# simulate n years of run to define a median max drawdown
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# simulate n years of run to define a median max drawdown
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for i in range(0, NB_SIMULATIONS):
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for i in range(0, NB_SIMULATIONS):
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