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Final changes, use sqrt i.o. statistics.pstdev

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hroff-1902 2020-02-28 23:50:25 +03:00 committed by GitHub
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1 changed files with 3 additions and 2 deletions
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5
freqtrade/optimize/hyperopt_loss_sortino_daily.py
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@ -5,7 +5,6 @@ This module defines the alternative HyperOptLoss class which can be used for
Hyperoptimization. Hyperoptimization.
""" """
import math import math
import statistics
from datetime import datetime from datetime import datetime
from pandas import DataFrame, date_range from pandas import DataFrame, date_range
@ -56,7 +55,9 @@ class SortinoHyperOptLossDaily(IHyperOptLoss):
sum_daily['downside_returns'] = 0 sum_daily['downside_returns'] = 0
sum_daily.loc[total_profit < 0, 'downside_returns'] = total_profit sum_daily.loc[total_profit < 0, 'downside_returns'] = total_profit
total_downside = sum_daily['downside_returns'] total_downside = sum_daily['downside_returns']
down_stdev = statistics.pstdev(total_downside, 0) # Here total_downside contains min(0, P - MAR) values,
# where P = sum_daily["profit_percent_after_slippage"]
down_stdev = math.sqrt((total_downside**2).sum() / len(total_downside))
if (down_stdev != 0.): if (down_stdev != 0.):
sortino_ratio = expected_returns_mean / down_stdev * math.sqrt(days_in_year) sortino_ratio = expected_returns_mean / down_stdev * math.sqrt(days_in_year)