diff --git a/src/fxhnt/domain/strategies/equity_factor.py b/src/fxhnt/domain/strategies/equity_factor.py
index 48339b5..b4b2f6a 100644
--- a/src/fxhnt/domain/strategies/equity_factor.py
+++ b/src/fxhnt/domain/strategies/equity_factor.py
@@ -1,5 +1,13 @@
-"""Pure cross-sectional factor math: winsorized z-scores, value/quality/momentum families, composite,
-and the three portfolio constructions (long / long-short / tilt) + realized book return. No I/O."""
+"""Pure cross-sectional factor math: winsorized z-scores, price/fundamentals factor families,
+composites, and the three portfolio constructions (long / long-short / tilt) + realized book return.
+No I/O.
+
+The ACTIVE sleeve is PRICE-ONLY (momentum + low-vol) via `composite_price`, because prices are
+available broadly across the universe (including delisted names). The fundamentals factors
+(`value_score`, `quality_score`) and the 3-factor `composite` are RETAINED for a future Tiingo
+fundamentals upgrade — the current Tiingo plan exposes fundamentals for DOW-30 only, so they cannot
+score a broad universe yet. They are intentionally not used by `composite_price`.
+"""
 from __future__ import annotations
 
 import math
@@ -52,10 +60,22 @@ def momentum_score(mom_12_1: list[float | None]) -> list[float]:
     return robust_z(mom_12_1)
 
 
+def lowvol_score(vols: list[float | None]) -> list[float]:
+    """Low-volatility anomaly: LOWER trailing realized vol -> HIGHER score (None stays neutral 0.0)."""
+    return robust_z([None if v is None else -v for v in vols])
+
+
 def composite(value_z: list[float], quality_z: list[float], momentum_z: list[float]) -> list[float]:
+    """3-factor (value+quality+momentum) composite. RETAINED for a future Tiingo fundamentals
+    upgrade (fundamentals currently DOW-30-only); NOT used by the active price-only sleeve."""
     return _mean_z([value_z, quality_z, momentum_z])
 
 
+def composite_price(momentum_z: list[float], lowvol_z: list[float]) -> list[float]:
+    """ACTIVE price-only composite for the pivoted sleeve: equal-weight mean of momentum + low-vol z."""
+    return _mean_z([momentum_z, lowvol_z])
+
+
 def _quintile_cut(scores: list[float], quantile: float) -> tuple[float, float]:
     s = sorted(scores)
     n = len(s)
diff --git a/tests/integration/test_equity_factor.py b/tests/integration/test_equity_factor.py
index e46ee7a..1faa1e9 100644
--- a/tests/integration/test_equity_factor.py
+++ b/tests/integration/test_equity_factor.py
@@ -22,6 +22,22 @@ def test_composite_is_equal_weight_of_families() -> None:
     assert c == pytest.approx([1.0, -1.0])
 
 
+def test_lowvol_score_low_vol_ranks_high() -> None:
+    # low-volatility anomaly: lowest trailing vol -> highest score, highest vol -> lowest
+    z = ef.lowvol_score([0.10, 0.20, 0.30, 0.40, 0.50, None])
+    assert z[0] == max(z[:5])                               # lowest vol -> highest score
+    assert z[4] == min(z[:5])                               # highest vol -> lowest score
+    assert z[5] == 0.0                                      # None -> neutral
+
+
+def test_composite_price_equal_weight() -> None:
+    c = ef.composite_price(momentum_z=[1.0, -1.0], lowvol_z=[1.0, -1.0])
+    assert c == pytest.approx([1.0, -1.0])
+    # momentum and lowvol disagree -> equal-weight mean
+    c2 = ef.composite_price(momentum_z=[2.0, 0.0], lowvol_z=[0.0, 2.0])
+    assert c2 == pytest.approx([1.0, 1.0])
+
+
 def test_long_only_weights_top_quintile_sum_to_one() -> None:
     scores = [float(i) for i in range(10)]                 # 0..9; top quintile = top 2 (8,9)
     w = ef.construction_weights(scores, "long", quantile=0.2)