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I Luk Kim d4ae900286 feat: expand data pipeline and integrate event features into scoring ... Data expansion: - Poll SEC 8-K filings from 2025-10-01 to 2026-03-12 (was ~2 months) - Pipeline: 36 new filings → 24 new events → total 44 events, 15 symbols - Re-export with merged features (market_v1+event_v1+financial_v1) - Parquet columns: 7 → 41 (adds signal_strength, guidance_direction, document_quality, oneoff_penalty, eps_growth_qoq, etc.) Score model v2: - Add event quality component (15% weight): signal_strength_score, guidance_direction_score, document_quality_score - Add risk penalty component (10% weight): inverted oneoff_penalty - Rebalance market weights: reaction 25%, close 25%, volume 15%, gap 10% - Graceful degradation when event features are absent (returns 0.5) Export pipeline: - Add --feature-versions CLI flag to merge multiple feature types - export_dataset_snapshot() accepts feature_versions list parameter - Groups features by event_id and merges feature_json dicts Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>		5 months ago
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main.py	feat: expand data pipeline and integrate event features into scoring	5 months ago