chemavx 5a3df975d9 fix(metrics): replace inflated PnL formula; drop fake calibration_score ...

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>

2026-04-21 16:47:05 +00:00

..

__init__.py

feat: initial commit — polymarket-bot source + CI/CD pipeline

2026-04-13 16:05:45 +00:00

main.py

fix(metrics): replace inflated PnL formula; drop fake calibration_score

2026-04-21 16:47:05 +00:00