adf2917cda
CI/CD / build-and-push (push) Successful in 1m52s
Adds alpha attribution by dominant signal feature — which feat_*_lo had the largest absolute log-odds value on each trade. Changes: - _dominant_feature() helper in api/main.py: picks the winning feature from signal_components (threshold 0.0001, same as "triggered" in /api/metrics/features) - _enrich_trade() refactored to single exit point; adds dominant_feature field to every open trade in /api/trades - compute_attribution_from_db() in db.py: VALUES subquery finds dominant feature per trade in SQL, then aggregates trade_count/avg_edge_net/ unrealized_pnl_est/realized_pnl/resolved_count/win_rate per group - /api/metrics/attribution endpoint: returns attribution dict + total_attributed_trades No schema changes, no strategy changes. Pure observability. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>