feat: add daily reentry policy matrix

tests/unit/test_backtest_service.py

@@ -543,6 +543,7 @@ class TestSimulatePortfolio:
         sim = bt._simulate_portfolio([cand], prices, None, "hold", 3)
         assert sim is not None
         assert sim["trades"] == 1
+        assert sim["cost_per_side_pct"] == pytest.approx(0.1)
         # 20 shares (1% risk / $5 stop distance), exit at the day-3 close 106:
         # pnl = 2120 − 2000 − 2.00 entry cost − 2.12 exit cost = 115.88
         assert sim["final_equity"] == pytest.approx(10_115.88, abs=0.01)
@@ -556,6 +557,29 @@ class TestSimulatePortfolio:
             {"year": 2025, "return_pct": pytest.approx(1.2, abs=0.05)}
         ]
 
+    def test_cost_parameter_changes_cash_and_position_path(self):
+        closes = [100.0, 102.0, 104.0, 106.0]
+        prices = {"AAA": _sim_prices(self.ORD, closes)}
+        cand = _sim_cand("AAA", self.ORD, entry=100.0, stop=95.0, target=130.0)
+
+        free = bt._simulate_portfolio(
+            [cand], prices, None, "hold", 3, cost_per_side=0.0
+        )
+        stressed = bt._simulate_portfolio(
+            [cand], prices, None, "hold", 3, cost_per_side=0.002
+        )
+
+        assert free is not None and stressed is not None
+        assert free["final_equity"] == pytest.approx(10_120.0, abs=0.01)
+        assert stressed["cost_per_side_pct"] == pytest.approx(0.2)
+        assert stressed["final_equity"] == pytest.approx(10_111.76, abs=0.01)
+
+    def test_cost_parameter_rejects_invalid_rate(self):
+        with pytest.raises(ValueError, match="cost_per_side"):
+            bt._simulate_portfolio(
+                [], {}, None, "hold", 3, cost_per_side=-0.001
+            )
+
     def test_target_policy_exits_at_target(self):
         closes = [100.0, 102.0, 104.0, 106.0, 108.0, 110.0]
         prices = {"AAA": _sim_prices(self.ORD, closes)}
@@ -626,6 +650,35 @@ class TestSimulatePortfolio:
             self.ORD + 6
         ).isoformat()
 
+    def test_post_stop_reentry_cannot_cross_holdout_end(self):
+        prices = {"AAA": _sim_prices(self.ORD, [100.0, 94.0, 96.0, 98.0])}
+        candidate = _sim_cand(
+            "AAA", self.ORD, entry=100.0, stop=95.0, target=120.0
+        )
+        callback_dates: list[int] = []
+
+        def reenter_after_split(symbol, asof_ord, _state, _bar):
+            callback_dates.append(asof_ord)
+            if asof_ord < self.ORD + 2:
+                return None
+            return _sim_cand(
+                symbol, asof_ord, entry=96.0, stop=90.0, target=115.0
+            )
+
+        sim = bt._simulate_portfolio(
+            [candidate],
+            prices,
+            None,
+            "hold",
+            3,
+            end_date=date.fromordinal(self.ORD + 2),
+            post_stop_reentry_fn=reenter_after_split,
+        )
+
+        assert sim is not None
+        assert sim["trades"] == 1
+        assert callback_dates == [self.ORD + 1]
+
     def test_production_monitor_applies_live_reentry_lockdown(self, monkeypatch):
         def fake_simulator(*_args, **kwargs):
             return {

tests/unit/test_daily_reentry_matrix.py

@@ -0,0 +1,97 @@
+from datetime import date
+
+from scripts.run_daily_reentry_matrix import PrecomputedDailyEngine, ReentryPolicy
+
+
+RANKING_KEY = "strategy_rank"
+ORD = date(2025, 1, 6).toordinal()
+
+
+def _candidate(day_ord: int, *, stop: float = 91.0, rank: float = 81.0) -> dict:
+    return {
+        "qualified": True,
+        "direction": "long",
+        "symbol": "AAA",
+        "date": date.fromordinal(day_ord).isoformat(),
+        "entry": 100.0,
+        "stop": stop,
+        "target": 120.0,
+        RANKING_KEY: rank,
+    }
+
+
+def _state(sessions: int = 0) -> dict:
+    return {
+        "sessions_since_stop": sessions,
+        "previous_stop": 90.0,
+        "previous_rank": 80.0,
+        "gate_went_unqualified": False,
+    }
+
+
+def _call(policy: ReentryPolicy, day_ord: int, state: dict, sessions: int):
+    state["sessions_since_stop"] = sessions
+    return policy("AAA", day_ord, state, object())
+
+
+def test_next_session_blocks_only_stop_day():
+    engine = PrecomputedDailyEngine([_candidate(ORD), _candidate(ORD + 1)])
+    policy = ReentryPolicy("next_session", engine, RANKING_KEY)
+    state = _state()
+
+    assert _call(policy, ORD, state, 0) is None
+    assert _call(policy, ORD + 1, state, 1) is not None
+
+
+def test_five_session_cooldown_unlocks_at_exact_boundary():
+    engine = PrecomputedDailyEngine([_candidate(ORD + 4), _candidate(ORD + 5)])
+    policy = ReentryPolicy("cooldown_5", engine, RANKING_KEY)
+    state = _state()
+
+    assert _call(policy, ORD + 4, state, 4) is None
+    assert _call(policy, ORD + 5, state, 5) is not None
+
+
+def test_gate_reset_requires_failure_before_requalification():
+    engine = PrecomputedDailyEngine([_candidate(ORD), _candidate(ORD + 2)])
+    policy = ReentryPolicy("gate_reset", engine, RANKING_KEY)
+    state = _state()
+
+    assert _call(policy, ORD, state, 0) is None
+    assert _call(policy, ORD + 1, state, 1) is None
+    emitted = _call(policy, ORD + 2, state, 2)
+    assert emitted is not None
+    assert emitted["_reentry_reason"] == "gate_failed_then_requalified"
+
+
+def test_improved_gate_reset_requires_better_stop_and_non_weaker_rank():
+    engine = PrecomputedDailyEngine([
+        _candidate(ORD + 1, stop=89.0, rank=82.0),
+        _candidate(ORD + 2, stop=92.0, rank=79.0),
+        _candidate(ORD + 3, stop=92.0, rank=81.0),
+    ])
+    policy = ReentryPolicy("gate_reset_improved", engine, RANKING_KEY)
+    state = _state()
+
+    assert _call(policy, ORD, state, 0) is None
+    assert _call(policy, ORD + 1, state, 1) is None
+    assert _call(policy, ORD + 2, state, 2) is None
+    emitted = _call(policy, ORD + 3, state, 3)
+    assert emitted is not None
+    assert emitted["_reentry_reason"] == "gate_reset_with_improved_stop_and_rank"
+
+
+def test_two_session_confirmation_excludes_stop_day_close():
+    engine = PrecomputedDailyEngine([
+        _candidate(ORD),
+        _candidate(ORD + 1),
+        _candidate(ORD + 2),
+    ])
+    policy = ReentryPolicy("two_session_confirmation", engine, RANKING_KEY)
+    state = _state()
+
+    assert _call(policy, ORD, state, 0) is None
+    assert _call(policy, ORD + 1, state, 1) is None
+    emitted = _call(policy, ORD + 2, state, 2)
+    assert emitted is not None
+    assert emitted["_reentry_reason"] == "two_qualified_post_stop_closes"