feat: strategy builder

backend/routers/strategy_builder.py

@@ -282,6 +282,47 @@ def price(req: PriceRequest):
     result["spot"] = chain_slice["spot"]
     result["scenario_spot"] = surface_scenario.spot
     result["proxy"] = chain_slice["proxy"]
+
+    # Debug trace for two open questions (nominal/entry_cost not matching the UI's own bid/
+    # ask math, and "-∞" risk on structures that look bounded by hand): log EXACTLY what was
+    # received and computed, so both can be checked from System Logs (source=strategy_price_debug,
+    # or filter level=WARNING to jump straight to the unbounded cases) instead of digging
+    # through the browser's Network tab. Remove once both are confirmed resolved.
+    from services.database import log_system_event
+    bounded_risk = result.get("bounded_risk")
+    log_system_event(
+        level="INFO" if bounded_risk else "WARNING",
+        source="strategy_price_debug",
+        message=(
+            f"/price {req.scenario.symbol}: {len(legs)} jambe(s), nominal={req.scenario.contract_size}, "
+            f"entry_cost={result.get('entry_cost')} (mid={result.get('entry_cost_mid')}), "
+            f"broker_spread_cost={result.get('broker_spread_cost')}, "
+            f"max_gain={result.get('max_gain')}, max_loss={result.get('max_loss')}, bounded_risk={bounded_risk}"
+        ),
+        ticker=req.scenario.symbol,
+        details={
+            "legs_received": legs,
+            "scenario_received": {
+                "contract_size": req.scenario.contract_size,
+                "horizon_days": req.scenario.horizon_days,
+                "spot_shock_pct": req.scenario.spot_shock_pct,
+                "iv_level_shift": req.scenario.iv_level_shift,
+                "skew_tilt": req.scenario.skew_tilt,
+                "term_slope_shift": req.scenario.term_slope_shift,
+                "has_spot_path": bool(req.scenario.spot_path),
+                "has_iv_path": bool(req.scenario.iv_path),
+                "has_skew_path": bool(req.scenario.skew_path),
+                "has_term_path": bool(req.scenario.term_path),
+            },
+            "priced": {
+                "entry_cost": result.get("entry_cost"), "entry_cost_mid": result.get("entry_cost_mid"),
+                "broker_spread_cost": result.get("broker_spread_cost"),
+                "max_gain": result.get("max_gain"), "max_loss": result.get("max_loss"),
+                "bounded_risk": bounded_risk,
+            },
+            "risk_debug": result.get("risk_debug"),
+        },
+    )
     return result
 
 

backend/services/strategy_engine.py

@@ -224,6 +224,7 @@ def price_combo(
         "max_gain": bounded["max_gain"],
         "max_loss": bounded["max_loss"],
         "bounded_risk": bounded["bounded"],
+        "risk_debug": bounded.get("risk_debug"),
         "greeks_now": greeks_at(legs, spot_now, 0, surface_now, r),
         "greeks_scenario": greeks_at(legs, spot_scenario, horizon_days, surface_scenario, r),
         "net_delta_now": delta_now,
@@ -281,6 +282,16 @@ def check_bounded_risk(
     loss_bounded = (lo_edge >= lo_in - tol) and (hi_edge >= hi_in - tol)
     gain_bounded = (lo_edge <= lo_in + tol) and (hi_edge <= hi_in + tol)
 
+    # Diagnostic snapshot of exactly why loss/gain were classified (un)bounded — surfaced
+    # up through price_combo/payoff_curves so the /price router can log it (system_logs)
+    # instead of this being a black box every time "-∞" shows up in the UI.
+    risk_debug = {
+        "eval_days": eval_days, "spot": spot, "entry_ref": round(entry_ref, 2), "tol": round(tol, 4),
+        "lo_tail_price": round(float(tail_grid[0]), 6), "lo_edge_pnl": round(lo_edge, 2), "lo_inner_pnl": round(lo_in, 2),
+        "hi_tail_price": round(float(tail_grid[-1]), 6), "hi_edge_pnl": round(hi_edge, 2), "hi_inner_pnl": round(hi_in, 2),
+        "loss_bounded": loss_bounded, "gain_bounded": gain_bounded,
+    }
+
     # Dense linear sweep across the legs' own strikes — needed even in the fast path (see
     # docstring above), only the final 1-D refinement is reserved for precise=True.
     strikes = [l["strike"] for l in legs]
@@ -294,6 +305,7 @@ def check_bounded_risk(
             "bounded": loss_bounded,
             "max_loss": round(min(combined_values), 2) if loss_bounded else None,
             "max_gain": round(max(combined_values), 2) if gain_bounded else None,
+            "risk_debug": risk_debug,
         }
 
     # Any FIXED grid — however dense — is a different finite sampling of the same
@@ -330,6 +342,7 @@ def check_bounded_risk(
         "bounded": loss_bounded,
         "max_loss": round(refine(False), 2) if loss_bounded else None,
         "max_gain": round(refine(True), 2) if gain_bounded else None,
+        "risk_debug": risk_debug,
     }