diff --git a/src/fxhnt/domain/equity_backtest.py b/src/fxhnt/domain/equity_backtest.py
index 250c588..e0debed 100644
--- a/src/fxhnt/domain/equity_backtest.py
+++ b/src/fxhnt/domain/equity_backtest.py
@@ -4,6 +4,8 @@ from __future__ import annotations
 
 import datetime as dt
 
+from fxhnt.domain.strategies.equity_factor import book_return
+
 _SECONDS_PER_DAY = 86_400
 
 
@@ -43,3 +45,23 @@ def month_end_rebalance_dates(dates: list[str]) -> list[str]:
         y, m, _ = d.split("-")
         last_by_month[(int(y), int(m))] = d
     return [last_by_month[k] for k in sorted(last_by_month)]
+
+
+def daily_returns_for_weights(
+    weights: dict[str, float],
+    closes: dict[str, dict[int, float]],
+    days: list[int],
+    borrow_daily: float,
+) -> list[float]:
+    """Daily book returns of fixed `weights` over consecutive `days` (epoch-days,
+    ascending). For each adjacent (prev, cur) pair, both prices must exist for a
+    symbol to contribute; a step with no usable price pair is dropped (not 0.0)."""
+    out: list[float] = []
+    for prev, cur in zip(days, days[1:]):
+        prev_p = {s: closes[s][prev] for s in weights if s in closes and prev in closes[s] and cur in closes[s]}
+        cur_p = {s: closes[s][cur] for s in prev_p}
+        if not prev_p:
+            continue
+        w = {s: weights[s] for s in prev_p}
+        out.append(book_return(w, prev_p, cur_p, borrow_daily=borrow_daily))
+    return out
diff --git a/tests/unit/test_equity_backtest_domain.py b/tests/unit/test_equity_backtest_domain.py
index e9e308b..e16d6c4 100644
--- a/tests/unit/test_equity_backtest_domain.py
+++ b/tests/unit/test_equity_backtest_domain.py
@@ -40,3 +40,32 @@ def test_month_end_rebalance_dates_one_per_month():
 def test_epoch_day_roundtrip():
     assert _epoch_day("1970-01-01") == 0
     assert _epoch_day("1970-01-02") == 1
+
+
+import pytest
+
+from fxhnt.domain.equity_backtest import daily_returns_for_weights
+
+
+def test_daily_returns_long_only_matches_weighted_price_change():
+    weights = {"A": 0.5, "B": 0.5}
+    closes = {
+        "A": {0: 100.0, 1: 110.0},
+        "B": {0: 50.0, 1: 50.0},
+    }
+    rets = daily_returns_for_weights(weights, closes, [0, 1], borrow_daily=0.0)
+    assert rets == pytest.approx([0.05])
+
+
+def test_daily_returns_applies_borrow_on_short_notional():
+    weights = {"A": -1.0}
+    closes = {"A": {0: 100.0, 1: 100.0}}
+    rets = daily_returns_for_weights(weights, closes, [0, 1], borrow_daily=0.001)
+    assert rets == [-0.001]
+
+
+def test_daily_returns_skips_day_with_missing_price():
+    weights = {"A": 1.0}
+    closes = {"A": {0: 100.0, 2: 121.0}}   # day 1 missing
+    rets = daily_returns_for_weights(weights, closes, [0, 1, 2], borrow_daily=0.0)
+    assert rets == []