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Compute residual vol for square regressions

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Gahow Wang
2026-04-07 16:57:58 +08:00
parent 3d934b3316
commit 18174a9e11
2 changed files with 3 additions and 3 deletions
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4
factor_attribution.py
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@@ -308,6 +308,8 @@ def run_factor_regression(
fitted = x @ coefficients fitted = x @ coefficients
residuals = y.to_numpy() - fitted residuals = y.to_numpy() - fitted
residual_series = pd.Series(residuals, index=regression_frame.index)
residual_vol_ann = float(residual_series.std(ddof=1) * np.sqrt(TRADING_DAYS_PER_YEAR))
dof = n_obs - param_count dof = n_obs - param_count
if dof > 0: if dof > 0:
@@ -323,12 +325,10 @@ def run_factor_regression(
where=standard_errors > 0, where=standard_errors > 0,
) )
p_values = 2.0 * stats.t.sf(np.abs(t_stats), df=dof) p_values = 2.0 * stats.t.sf(np.abs(t_stats), df=dof)
residual_vol_ann = float(pd.Series(residuals, index=regression_frame.index).std(ddof=1) * np.sqrt(TRADING_DAYS_PER_YEAR))
adj_r_squared_is_defined = True adj_r_squared_is_defined = True
else: else:
t_stats = np.full_like(coefficients, np.nan, dtype=float) t_stats = np.full_like(coefficients, np.nan, dtype=float)
p_values = np.full_like(coefficients, np.nan, dtype=float) p_values = np.full_like(coefficients, np.nan, dtype=float)
residual_vol_ann = float("nan")
adj_r_squared_is_defined = False adj_r_squared_is_defined = False
ss_total = float(((y - y.mean()) ** 2).sum()) ss_total = float(((y - y.mean()) ** 2).sum())

2
tests/test_factor_attribution.py
View File

@@ -499,7 +499,7 @@ class RegressionTests(unittest.TestCase):
self.assertTrue(np.isnan(result["p_values"]["MKT_RF"])) self.assertTrue(np.isnan(result["p_values"]["MKT_RF"]))
self.assertTrue(np.isnan(result["p_values"]["SMB"])) self.assertTrue(np.isnan(result["p_values"]["SMB"]))
self.assertTrue(np.isnan(result["adj_r_squared"])) self.assertTrue(np.isnan(result["adj_r_squared"]))
self.assertTrue(np.isnan(result["residual_vol_ann"])) self.assertAlmostEqual(result["residual_vol_ann"], 0.0, places=12)
def test_run_factor_regression_rejects_rank_deficient_designs(self): def test_run_factor_regression_rejects_rank_deficient_designs(self):
dates = pd.date_range("2024-01-01", periods=6, freq="B") dates = pd.date_range("2024-01-01", periods=6, freq="B")