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removed clipping to return negative SR, calmar and sortino ratios #473

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6 changes: 3 additions & 3 deletions backtesting/_stats.py
Original file line number Diff line number Diff line change
Expand Up @@ -117,11 +117,11 @@ def _round_timedelta(value, _period=_data_period(index)):

# Our Sharpe mismatches `empyrical.sharpe_ratio()` because they use arithmetic mean return
# and simple standard deviation
s.loc['Sharpe Ratio'] = np.clip((s.loc['Return (Ann.) [%]'] - risk_free_rate) / (s.loc['Volatility (Ann.) [%]'] or np.nan), 0, np.inf) # noqa: E501
s.loc['Sharpe Ratio'] = s.loc['Return (Ann.) [%]'] - risk_free_rate) / (s.loc['Volatility (Ann.) [%]'] or np.nan # noqa: E501
# Our Sortino mismatches `empyrical.sortino_ratio()` because they use arithmetic mean return
s.loc['Sortino Ratio'] = np.clip((annualized_return - risk_free_rate) / (np.sqrt(np.mean(day_returns.clip(-np.inf, 0)**2)) * np.sqrt(annual_trading_days)), 0, np.inf) # noqa: E501
s.loc['Sortino Ratio'] = annualized_return - risk_free_rate) / (np.sqrt(np.mean(day_returns.clip(-np.inf, 0)**2)) * np.sqrt(annual_trading_days) # noqa: E501
max_dd = -np.nan_to_num(dd.max())
s.loc['Calmar Ratio'] = np.clip(annualized_return / (-max_dd or np.nan), 0, np.inf)
s.loc['Calmar Ratio'] = annualized_return / (-max_dd or np.nan)
s.loc['Max. Drawdown [%]'] = max_dd * 100
s.loc['Avg. Drawdown [%]'] = -dd_peaks.mean() * 100
s.loc['Max. Drawdown Duration'] = _round_timedelta(dd_dur.max())
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