feat: add daily reentry policy matrix

app/services/backtest_service.py

@@ -1405,6 +1405,7 @@ def _simulate_portfolio(
     max_positions: int = SIM_MAX_POSITIONS,
     risk_per_trade: float = SIM_RISK_PER_TRADE,
     atr_trail_multiplier: float = ATR_TRAIL_MULTIPLIER,
+    cost_per_side: float = COST_PER_SIDE,
     reentry_cooldown_sessions: int = 0,
     initial_stop_refresh_fn: (
         Callable[[str, int, float, dict, Any], float | None] | None
@@ -1436,8 +1437,12 @@ def _simulate_portfolio(
     checked against the same bar. ``post_stop_reentry_fn`` turns an initial
     stop-out into a stateful episode and is the only path by which that ticker
     can re-enter until the callback emits a new candidate. Returns None when
-    there is nothing to trade.
+    there is nothing to trade. ``cost_per_side`` is charged on entry and exit
+    and therefore changes both cash availability and subsequent position sizing.
     """
+    cost_rate = float(cost_per_side)
+    if not 0.0 <= cost_rate < 1.0:
+        raise ValueError("cost_per_side must be between 0 (inclusive) and 1")
     if qualified_fn is None:
         def _default_qualified(c: dict) -> bool:
             return bool(c.get("qualified"))
@@ -1565,7 +1570,7 @@ def _simulate_portfolio(
         nonlocal cash
         pos = positions.pop(sym)
         proceeds = pos["shares"] * fill
-        cost = proceeds * COST_PER_SIDE
+        cost = proceeds * cost_rate
         cash += proceeds - cost
         risk = pos["entry"] - pos["initial_stop"]
         trades.append({
@@ -1641,6 +1646,7 @@ def _simulate_portfolio(
                             "exit_fill": float(fill),
                             "previous_entry": float(closed_pos["entry"]),
                             "previous_stop": float(closed_pos["initial_stop"]),
+                            "previous_rank": closed_pos["entry_rank"],
                             "gate_went_unqualified": False,
                         }
                     continue
@@ -1677,7 +1683,9 @@ def _simulate_portfolio(
         equity = _marked_equity()
         fixed_todays = list(entries_by_ord.get(o, ()))
         reentry_todays: list[dict] = []
-        if post_stop_reentry_fn is not None:
+        if post_stop_reentry_fn is not None and (
+            end_ord is None or o < end_ord
+        ):
             fixed_todays = [
                 candidate
                 for candidate in fixed_todays
@@ -1718,11 +1726,11 @@ def _simulate_portfolio(
             shares = min(
                 (equity * risk_per_trade) / risk_ps,
                 (equity * SIM_NOTIONAL_CAP) / entry,
-                max(cash, 0.0) / (entry * (1.0 + COST_PER_SIDE)),
+                max(cash, 0.0) / (entry * (1.0 + cost_rate)),
             )
             if shares * entry < 1.0:  # can't fund a meaningful position
                 continue
-            entry_cost = shares * entry * COST_PER_SIDE
+            entry_cost = shares * entry * cost_rate
             cash -= shares * entry + entry_cost
             is_reentry = bool(c.get("_post_stop_reentry"))
             reentry_wait_sessions: int | None = None
@@ -1748,6 +1756,9 @@ def _simulate_portfolio(
                 "bars_held": 0,
                 "last_close": entry,
                 "highest_close": entry,
+                "entry_rank": (
+                    float(c[ranking_key]) if c.get(ranking_key) is not None else None
+                ),
                 "stop_refreshes": 0,
                 "is_reentry": is_reentry,
                 "reentry_wait_sessions": reentry_wait_sessions,
@@ -1856,6 +1867,7 @@ def _simulate_portfolio(
 
     result = {
         "starting_capital": SIM_STARTING_CAPITAL,
+        "cost_per_side_pct": round(cost_rate * 100.0, 3),
         "final_equity": round(final_equity, 2),
         "total_return_pct": round(total_return_pct, 1),
         "cagr_pct": round(cagr_pct, 1) if cagr_pct is not None else None,