Implement P1 local matcher/ledger and P2 strategy engine.

Co-authored-by: Cursor <cursoragent@cursor.com>

backend/app/api/stats.py

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+from __future__ import annotations
+
+from typing import Annotated
+
+from fastapi import APIRouter, Depends
+
+from ..models.db import get_db
+from .auth import require_user
+
+router = APIRouter(prefix="/api/stats", tags=["stats"])
+
+
+@router.get("/summary")
+async def stats_summary(_user: Annotated[str, Depends(require_user)]) -> dict:
+    db = get_db()
+    rows = db.fetchall("SELECT * FROM groups WHERE status='closed'")
+    n = len(rows)
+    wins = sum(1 for r in rows if float(r["realized_pnl"] or 0) > 0)
+    total_pnl = sum(float(r["realized_pnl"] or 0) for r in rows)
+    total_fees = sum(float(r["fees"] or 0) for r in rows)
+    total_slip = sum(float(r["slip_cost"] or 0) for r in rows)
+    reasons: dict[str, int] = {}
+    for r in rows:
+        k = str(r["close_reason"] or "unknown")
+        reasons[k] = reasons.get(k, 0) + 1
+    curve = [
+        {
+            "group_id": r["group_id"],
+            "realized_pnl": float(r["realized_pnl"] or 0),
+            "close_at_ms": r["close_at_ms"],
+        }
+        for r in sorted(rows, key=lambda x: int(x["close_at_ms"] or 0))
+    ]
+    return {
+        "groups": n,
+        "wins": wins,
+        "win_rate": (wins / n) if n else 0.0,
+        "total_pnl": total_pnl,
+        "total_fees": total_fees,
+        "total_slip": total_slip,
+        "close_reasons": reasons,
+        "equity_curve": curve,
+    }