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Fix on max drawdown formula to match tests
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@ -566,7 +566,7 @@ Currently, the following loss functions are builtin:
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* `SortinoHyperOptLoss` - optimizes Sortino Ratio calculated on trade returns relative to **downside** standard deviation.
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* `SortinoHyperOptLossDaily` - optimizes Sortino Ratio calculated on **daily** trade returns relative to **downside** standard deviation.
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* `MaxDrawDownHyperOptLoss` - Optimizes Maximum absolute drawdown.
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* `MaxDrawDownRelativeHyperOptLoss` - Similar as the above, but also optimizes Maximum relative drawdown.
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* `MaxDrawDownRelativeHyperOptLoss` - Optimizes both maximum absolute drawdown while also adjusting for maximum relative drawdown.
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* `CalmarHyperOptLoss` - Optimizes Calmar Ratio calculated on trade returns relative to max drawdown.
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* `ProfitDrawDownHyperOptLoss` - Optimizes by max Profit & min Drawdown objective. `DRAWDOWN_MULT` variable within the hyperoptloss file can be adjusted to be stricter or more flexible on drawdown purposes.
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@ -153,7 +153,7 @@ def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_date'
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max_drawdown_rel = max_drawdown_df.loc[idxmin, 'drawdown_relative']
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return (
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abs(min(max_drawdown_df['drawdown'])),
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abs(max_drawdown_df.loc[idxmin, 'drawdown']),
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high_date,
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low_date,
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high_val,
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@ -380,7 +380,7 @@ def test_calculate_max_drawdown2():
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@pytest.mark.parametrize('profits,relative,highd,lowd,result,result_rel', [
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([0.0, -500.0, 500.0, 10000.0, -1000.0], False, 3, 4, 1000.0, 0.090909),
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([0.0, -500.0, 500.0, 10000.0, -1000.0], True, 0, 1, 1000.0, 0.5),
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([0.0, -500.0, 500.0, 10000.0, -1000.0], True, 0, 1, 500.0, 0.5),
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])
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def test_calculate_max_drawdown_abs(profits, relative, highd, lowd, result, result_rel):
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