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Commit 70a2c33

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ENH: Add Alpha & Beta stats (#1221)
* added beta & alpha / resolved merge conflict * simplified beta calculation * remove DS_store * move beta & alpha / use log return * Update backtesting/_stats.py * Update backtesting/_stats.py * alpha & beta test * #noqa: E501 * add space * update docs * Revert unrelated change * Add comment
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‎README.md

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@@ -68,6 +68,8 @@ CAGR [%] 16.80
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Sharpe Ratio 0.66
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Sortino Ratio 1.30
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Calmar Ratio 0.77
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Alpha [%] 450.62
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Beta 0.02
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Max. Drawdown [%] -33.08
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Avg. Drawdown [%] -5.58
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Max. Drawdown Duration 688 days 00:00:00

‎backtesting/_stats.py

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@@ -152,6 +152,13 @@ def _round_timedelta(value, _period=_data_period(index)):
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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
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max_dd = -np.nan_to_num(dd.max())
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s.loc['Calmar Ratio'] = annualized_return / (-max_dd or np.nan)
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equity_log_returns = np.log(equity[1:] / equity[:-1])
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market_log_returns = np.log(c[1:] / c[:-1])
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cov_matrix = np.cov(equity_log_returns, market_log_returns)
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beta = cov_matrix[0, 1] / cov_matrix[1, 1]
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# Jensen CAPM Alpha: can be strongly positive when beta is negative and B&H Return is large
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s.loc['Alpha [%]'] = s.loc['Return [%]'] - risk_free_rate * 100 - beta * (s.loc['Buy & Hold Return [%]'] - risk_free_rate * 100) # noqa: E501
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s.loc['Beta'] = beta
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s.loc['Max. Drawdown [%]'] = max_dd * 100
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s.loc['Avg. Drawdown [%]'] = -dd_peaks.mean() * 100
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s.loc['Max. Drawdown Duration'] = _round_timedelta(dd_dur.max())

‎backtesting/backtesting.py

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@@ -1262,6 +1262,8 @@ def run(self, **kwargs) -> pd.Series:
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Sharpe Ratio 0.58038
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Sortino Ratio 1.08479
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Calmar Ratio 0.44144
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Alpha [%] 394.37391
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Beta 0.03803
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Max. Drawdown [%] -47.98013
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Avg. Drawdown [%] -5.92585
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Max. Drawdown Duration 584 days 00:00:00

‎backtesting/test/_test.py

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@@ -317,6 +317,8 @@ def test_compute_stats(self):
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'Start': pd.Timestamp('2004年08月19日 00:00:00'),
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'Win Rate [%]': 46.96969696969697,
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'Worst Trade [%]': -18.39887353835481,
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'Alpha [%]': 394.37391142027462,
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'Beta': 0.03803390709192,
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})
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def almost_equal(a, b):

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