Add trade setup outcome tracking and performance stats

Closes the feedback loop on R:R scanner signals:

- Nightly outcome_evaluator job replays unresolved setups against daily
  OHLCV bars: target_hit / stop_hit / ambiguous (same-bar, counted as
  loss) / expired after OUTCOME_EVALUATION_MAX_BARS (default 30)
- Migration 004: evaluated_at + outcome_date on trade_setups
- GET /trades/performance: hit rate, expectancy (avg R), total R with
  breakdowns by direction, recommended action, and confidence bucket
- New Performance page (stat cards, breakdown tables, Evaluate Now,
  methodology disclosure) wired into sidebar and mobile nav
- 17 new unit tests for evaluation logic and stats aggregation

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

app/schemas/trade_setup.py

@@ -2,7 +2,7 @@
 
 from __future__ import annotations
 
-from datetime import datetime
+from datetime import date, datetime
 
 from pydantic import BaseModel, Field
 
@@ -44,4 +44,6 @@ class TradeSetupResponse(BaseModel):
     reasoning: str | None = None
     risk_level: str | None = None
     actual_outcome: str | None = None
+    outcome_date: date | None = None
+    evaluated_at: datetime | None = None
     recommendation_summary: RecommendationSummaryResponse | None = None