feat: option lab

backend/routers/portfolio.py

@@ -1,4 +1,4 @@
-from fastapi import APIRouter, HTTPException
+from fastapi import APIRouter, HTTPException, Query
 import traceback as tb_mod
 from pydantic import BaseModel
 from typing import Optional, List, Dict, Any
@@ -179,6 +179,21 @@ def position_payoff(pos_id: str):
     return compute_payoff(pos)
 
 
+@router.get("/positions/{pos_id}/retrospective-optimal")
+def position_retrospective_optimal(pos_id: str, as_of: str = Query(None)):
+    """"What would have been optimal, in hindsight?" — reprices the position's real legs
+    and runs the Strategy Builder optimizer against the REAL historical Saxo chain and the
+    REALIZED spot/IV move since entry (not a guessed scenario) — see
+    services.strategy_comparison.compute_retrospective_comparison. Expensive (runs the full
+    template-search optimizer), so this is on-demand from the Portfolio position detail, not
+    auto-computed for every open position."""
+    from services.strategy_comparison import compute_retrospective_comparison
+    pos = next((p for p in get_positions("open") + get_positions("closed") if p["id"] == pos_id), None)
+    if not pos:
+        raise HTTPException(status_code=404, detail=f"Position '{pos_id}' introuvable")
+    return compute_retrospective_comparison(pos, as_of=as_of)
+
+
 @router.get("/scenario-exposure")
 def scenario_exposure():
     """Reprices every open position under a handful of named macro scenarios (Risk-Off,

backend/routers/saxo.py

@@ -248,3 +248,19 @@ def saxo_iv_snapshot(symbol: str):
 def saxo_iv_history(symbol: str, days: int = Query(90, ge=1, le=730)):
     from services.saxo_iv_engine import get_saxo_iv_history
     return get_saxo_iv_history(symbol, days)
+
+
+@router.get("/pricing-check")
+def saxo_pricing_check(
+    ticker: str = Query(...),
+    date_a: str = Query(..., description="YYYY-MM-DD"),
+    date_b: str = Query(..., description="YYYY-MM-DD"),
+    target_dte: Optional[int] = Query(None, ge=1, le=365, description="Overrides the default (expiry closest to date_b)"),
+):
+    """Options Lab — was this option well priced between two dates? Picks the strike closest
+    to the underlying's actual outcome at date_b (hindsight), and by default the expiry
+    closest to date_b too (same hindsight principle, overridable via target_dte), reprices
+    it at both dates from real Saxo history, and decomposes the price move into
+    Delta/Theta/Vega contributions — see services.pricing_check.analyze_option_pricing."""
+    from services.pricing_check import analyze_option_pricing
+    return analyze_option_pricing(ticker, date_a, date_b, target_dte)