total_pnl now uses edge_net × net_cost instead of (0.5 - entry_price) × shares.
The old formula overestimated BUY_NO trades at low entry prices by 3–10× because
buying at price 0.158 yields 3164 shares — any exit-at-0.5 assumption produced
$1072 PnL on $500 deployed. edge_net × net_cost is bounded by net_cost per trade
and uses the model's own signal, giving $122 for the same position.
calibration_score is now None (null in API) instead of 1 - 2×|avg_edge|. That
formula was not a real calibration: it requires knowing market resolutions
(YES=1/NO=0) which we do not store yet. Returning null is more honest than
returning 0.0 or a meaningless proxy. Fix 3 will compute it from closed trades.
check_promotion_thresholds updated to handle None calibration (null → not ready).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
chemavx
chemavx