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Add factor builder leakage tests

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Gahow Wang
2026-04-07 16:21:05 +08:00
parent 7e8d24c1e9
commit 7e44ece569
1 changed files with 42 additions and 0 deletions
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42
tests/test_factor_attribution.py
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@@ -316,6 +316,48 @@ class LocalFactorConstructionTests(unittest.TestCase):
self.assertTrue(factors.iloc[260:].notna().all().all())
self.assertGreater(factors.iloc[260:].abs().sum().sum(), 0.0)
def test_build_extension_factors_does_not_use_future_prices(self):
prices = self._make_price_frame(benchmark="SPY")
mutated = prices.copy()
future_start = prices.index[280]
mutated.loc[future_start:, "A"] = mutated.loc[future_start:, "A"] * 1.8
mutated.loc[future_start:, "B"] = mutated.loc[future_start:, "B"] * 0.4
original = build_extension_factors(prices, benchmark="SPY", market="us")
changed = build_extension_factors(mutated, benchmark="SPY", market="us")
comparison_end = prices.index[279]
pd.testing.assert_frame_equal(original.loc[:comparison_end], changed.loc[:comparison_end])
self.assertGreater(
(original.loc[future_start:] - changed.loc[future_start:]).abs().sum().sum(),
0.0,
)
def test_build_proxy_core_factors_does_not_use_future_prices(self):
prices = self._make_price_frame(benchmark="000300.SS")
mutated = prices.copy()
future_start = prices.index[280]
mutated.loc[future_start:, "C"] = mutated.loc[future_start:, "C"] * 0.35
mutated.loc[future_start:, "D"] = mutated.loc[future_start:, "D"] * 1.6
original = build_proxy_core_factors(prices, benchmark="000300.SS", market="cn")
changed = build_proxy_core_factors(mutated, benchmark="000300.SS", market="cn")
comparison_end = prices.index[279]
pd.testing.assert_frame_equal(original.loc[:comparison_end], changed.loc[:comparison_end])
self.assertGreater(
(original.loc[future_start:] - changed.loc[future_start:]).abs().sum().sum(),
0.0,
)
def test_build_proxy_core_factors_falls_back_to_equal_weight_market_when_benchmark_missing(self):
prices = self._make_price_frame(benchmark="CN_BENCH").drop(columns=["CN_BENCH"])
factors = build_proxy_core_factors(prices, benchmark="000300.SS", market="cn")
expected_market = prices.pct_change().mean(axis=1)
pd.testing.assert_series_equal(factors["MKT"], expected_market, check_names=False)
def _make_price_frame(self, benchmark: str) -> pd.DataFrame:
dates = pd.date_range("2025-01-01", periods=320, freq="B")
steps = np.arange(len(dates), dtype=float)