73 lines
3.0 KiB
Python
73 lines
3.0 KiB
Python
"""Pure equity-factor math: winsorized z-score, family/composite scores, 3 construction weightings, book return."""
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from __future__ import annotations
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import pytest
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from fxhnt.domain.strategies import equity_factor as ef
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def test_robust_z_winsorizes_and_standardizes() -> None:
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z = ef.robust_z([1.0, 2.0, 3.0, 4.0, 100.0], k=2.0) # 100 is an outlier
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assert max(z) == pytest.approx(2.0) # winsorized at +k
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assert all(-2.0 - 1e-9 <= v <= 2.0 + 1e-9 for v in z)
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def test_robust_z_missing_is_neutral_zero() -> None:
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z = ef.robust_z([1.0, None, 3.0])
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assert z[1] == 0.0 # missing -> neutral
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def test_composite_is_equal_weight_of_families() -> None:
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c = ef.composite(value_z=[1.0, -1.0], quality_z=[1.0, -1.0], momentum_z=[1.0, -1.0])
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assert c == pytest.approx([1.0, -1.0])
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def test_lowvol_score_low_vol_ranks_high() -> None:
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# low-volatility anomaly: lowest trailing vol -> highest score, highest vol -> lowest
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z = ef.lowvol_score([0.10, 0.20, 0.30, 0.40, 0.50, None])
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assert z[0] == max(z[:5]) # lowest vol -> highest score
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assert z[4] == min(z[:5]) # highest vol -> lowest score
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assert z[5] == 0.0 # None -> neutral
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def test_composite_price_equal_weight() -> None:
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c = ef.composite_price(momentum_z=[1.0, -1.0], lowvol_z=[1.0, -1.0])
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assert c == pytest.approx([1.0, -1.0])
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# momentum and lowvol disagree -> equal-weight mean
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c2 = ef.composite_price(momentum_z=[2.0, 0.0], lowvol_z=[0.0, 2.0])
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assert c2 == pytest.approx([1.0, 1.0])
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def test_long_only_weights_top_quintile_sum_to_one() -> None:
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scores = [float(i) for i in range(10)] # 0..9; top quintile = top 2 (8,9)
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w = ef.construction_weights(scores, "long", quantile=0.2)
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assert sum(w) == pytest.approx(1.0)
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assert w[9] == pytest.approx(0.5) and w[8] == pytest.approx(0.5)
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assert all(w[i] == 0.0 for i in range(8))
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def test_long_short_is_market_neutral_gross_two() -> None:
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scores = [float(i) for i in range(10)]
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w = ef.construction_weights(scores, "ls", quantile=0.2)
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assert sum(w) == pytest.approx(0.0)
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assert sum(abs(x) for x in w) == pytest.approx(2.0)
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assert w[9] == pytest.approx(0.5) and w[0] == pytest.approx(-0.5)
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def test_tilt_is_long_only_rank_weighted_sum_one() -> None:
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scores = [float(i) for i in range(10)]
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w = ef.construction_weights(scores, "tilt")
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assert sum(w) == pytest.approx(1.0)
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assert all(x >= 0.0 for x in w)
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assert w[9] > w[5] >= 0.0
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def test_book_return_weighted_minus_short_borrow() -> None:
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prev_w = {"A": 0.5, "B": -0.5}
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prev_p = {"A": 100.0, "B": 100.0}
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cur_p = {"A": 110.0, "B": 90.0}
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r = ef.book_return(prev_w, prev_p, cur_p, borrow_daily=0.0)
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assert r == pytest.approx(0.5 * 0.10 + (-0.5) * (-0.10)) # +0.10
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r2 = ef.book_return(prev_w, prev_p, cur_p, borrow_daily=0.001)
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assert r2 == pytest.approx(r - 0.001 * 0.5)
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