3 Commits

Author	SHA1	Message	Date
Youssef Aitousarrah	43bdd6de11	feat: discovery pipeline enhancements with ML signal scanner ... Major additions: - ML win probability scanner: scans ticker universe using trained LightGBM/TabPFN model, surfaces candidates with P(WIN) above threshold - 30-feature engineering pipeline (20 base + 10 interaction features) computed from OHLCV data via stockstats + pandas - Triple-barrier labeling for training data generation - Dataset builder and training script with calibration analysis - Discovery enrichment: confluence scoring, short interest extraction, earnings estimates, options signal normalization, quant pre-score - Configurable prompt logging (log_prompts_console flag) - Enhanced ranker investment thesis (4-6 sentence reasoning) - Typed DiscoveryConfig dataclass for all discovery settings - Console price charts for visual ticker analysis Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-02-09 22:53:42 -08:00
Youssef Aitousarrah	6f202f88f2	docs: add volume analysis enhancements design document ... Complete design for transforming get_unusual_volume into sophisticated multi-signal analysis tool with: - Volume pattern analysis (accumulation, compression, distribution) - Sector-relative comparison (percentile ranking vs peers) - Price-volume divergence detection (bullish/bearish signals) Includes architecture, implementation details, testing strategy, and performance considerations. Estimated 30-40% signal quality improvement with 2-3x execution time trade-off. Phased implementation approach: Phase 1: Pattern analysis (3-4h) Phase 2: Divergence detection (4-5h) Phase 3: Sector comparison (5-6h) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>	2026-02-06 08:38:06 -08:00
Youssef Aitousarrah	5cf57e5d97	Update	2025-12-02 20:49:42 -08:00