feat: add selectable daily backtest cadence

tests/unit/test_backtest_service.py

@@ -658,6 +658,36 @@ class TestSimulatePortfolio:
             for row in comparison_rows
         )
 
+    def test_production_cadence_comparison_names_exact_two_arms(self):
+        monitor = {
+            "runs": [
+                {
+                    "comparison_arm": "live_no_lockdown",
+                    "lookback": "all",
+                    "reentry_lockdown_sessions": 0,
+                    "trades": 10,
+                    "equity_curve": [{"date": "2026-01-01", "value": 1.0}],
+                },
+                {
+                    "comparison_arm": "live_lockdown_5",
+                    "lookback": "all",
+                    "reentry_lockdown_sessions": 5,
+                    "trades": 8,
+                    "benchmark_curve": [{"date": "2026-01-01", "value": 1.0}],
+                },
+            ]
+        }
+
+        comparison = bt._production_cadence_comparison(monitor, "daily")
+
+        assert comparison is not None
+        assert [row["arm"] for row in comparison["arms"]] == [
+            "prod_live_setup_daily",
+            "cooldown_5_daily",
+        ]
+        assert all("equity_curve" not in row for row in comparison["arms"])
+        assert all("benchmark_curve" not in row for row in comparison["arms"])
+
     def test_initial_stop_can_refresh_lower_and_survive_same_bar(self):
         closes = [100.0, 94.0, 96.0]
         prices = {"AAA": _sim_prices(self.ORD, closes)}
@@ -929,6 +959,15 @@ def test_backtest_target_model_is_small_and_validated():
         bt.validate_backtest_target_model("legacy_range_grid_touch")
 
 
+def test_backtest_cadence_is_small_validated_and_session_based():
+    assert bt.validate_backtest_cadence(" WEEKLY ") == "weekly"
+    assert bt.validate_backtest_cadence("daily") == "daily"
+    assert bt.backtest_step_sessions("weekly") == 5
+    assert bt.backtest_step_sessions("daily") == 1
+    with pytest.raises(ValueError, match="Unknown backtest cadence"):
+        bt.validate_backtest_cadence("monthly")
+
+
 def _flat_window_records():
     return [
         SimpleNamespace(
@@ -1022,6 +1061,46 @@ def test_replay_ticker_candidates_carry_gate_fields():
         assert c.get("action") is not None
         assert "risk_level" in c
         assert c["target_model"] == bt.PRODUCTION_GTL_TARGET_MODEL
+        assert c["ranking_period"][0] == "week"
+
+    daily_cands = bt._replay_ticker(
+        "OSC",
+        bars,
+        dict(DEFAULT_RECOMMENDATION_CONFIG),
+        dict(ACTIVATION_DEFAULTS),
+        cadence="daily",
+    )
+    assert len(daily_cands) > len(cands)
+    assert all(c["ranking_period"][0] == "date" for c in daily_cands)
+
+
+def test_daily_replay_uses_exact_date_ranking_periods():
+    candidates = [
+        {
+            "iso_week": (2026, 1),
+            "ranking_period": ("date", date(2026, 1, 5).toordinal()),
+            "momentum": 0.10,
+        },
+        {
+            "iso_week": (2026, 1),
+            "ranking_period": ("date", date(2026, 1, 5).toordinal()),
+            "momentum": 0.20,
+        },
+        {
+            "iso_week": (2026, 1),
+            "ranking_period": ("date", date(2026, 1, 6).toordinal()),
+            "momentum": 0.90,
+        },
+        {
+            "iso_week": (2026, 1),
+            "ranking_period": ("date", date(2026, 1, 6).toordinal()),
+            "momentum": 0.30,
+        },
+    ]
+
+    bt._assign_momentum_percentiles(candidates)
+
+    assert [row["momentum_percentile"] for row in candidates] == [0.0, 100.0, 100.0, 0.0]
 
 
 async def _seed_oscillating_ticker(session, symbol: str, n: int = 160) -> None:
@@ -1063,6 +1142,8 @@ async def test_run_backtest_smoke(session):
     assert report["params"]["cost_per_side_pct"] == pytest.approx(bt.COST_PER_SIDE * 100)
     assert report["params"]["target_model"] == bt.PRODUCTION_GTL_TARGET_MODEL
     assert report["params"]["is_production_target_model"] is True
+    assert report["params"]["entry_cadence"] == "weekly"
+    assert report["params"]["step_sessions"] == 5
     assert (
         report["params"]["production_reentry_lockdown_sessions"]
         == bt.REENTRY_LOCKDOWN_SESSIONS
@@ -1073,6 +1154,11 @@ async def test_run_backtest_smoke(session):
     # carries the hold-to-horizon grading alongside the target model
     ablation = {r["variant"]: r for r in report["gate_ablation"]}
     assert ablation["all_floors"]["total"] == report["overall_qualified"]["total"]
+
+    daily_report = await bt.run_backtest(session, cadence="daily")
+    assert daily_report["params"]["entry_cadence"] == "daily"
+    assert daily_report["params"]["step_sessions"] == 1
+    assert daily_report["candidates"] > report["candidates"]
     for row in report["gate_ablation"]:
         assert "hold_net_avg_r" in row