Commit Graph

21 Commits

Author SHA1 Message Date
github-actions[bot] d9dcdb3918 chore(hypotheses): picks 2026-04-16 for insider_buying-min-txn-100k 2026-04-16 09:26:56 +00:00
github-actions[bot] 2cdd6cedbc chore(hypotheses): picks 2026-04-15 for insider_buying-min-txn-100k 2026-04-15 09:24:17 +00:00
github-actions[bot] 8d8dfac9ac chore(hypotheses): picks 2026-04-13 for insider_buying-min-txn-100k 2026-04-13 10:03:02 +00:00
Youssef Aitousarrah 84101992e0 chore(hypotheses): picks 2026-04-10 for insider_buying-min-txn-100k 2026-04-10 11:12:14 -07:00
Youssef Aitousarrah aec19783eb hypothesis(insider_buying): add picks tracker for min-txn-100k
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-10 11:05:17 -07:00
Youssef Aitousarrah d3065f59f1 feat(hypotheses): initialize hypothesis registry 2026-04-10 09:26:17 -07:00
Youssef Aitousarrah e0b6e28a3b docs(plan): hypothesis backtesting implementation plan
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-10 09:04:58 -07:00
Youssef Aitousarrah 36884966f1 docs(spec): fix hypothesis capacity — running experiments never paused
Pending hypotheses queue by priority and promote when a slot opens,
rather than pausing a running experiment mid-streak.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-09 23:50:55 -07:00
Youssef Aitousarrah de4ef56c91 docs(spec): hypothesis backtesting system design
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-09 23:34:39 -07:00
Youssef Aitousarrah 47bcbdc70b fix(iteration-system): add .gitkeep to track empty research/ directory 2026-04-08 08:10:26 -07:00
Youssef Aitousarrah 3fb82e8180 feat(iteration-system): add knowledge base folder structure with seeded scanner files
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-08 08:09:07 -07:00
Youssef Aitousarrah ec2b3c2a45 docs(iteration-system): add implementation plan
Covers 5 tasks: knowledge base structure, /iterate command,
/research-strategy command, and two GitHub Actions workflows with
rolling PR logic.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-08 07:54:18 -07:00
Youssef Aitousarrah fa3166c494 docs(iteration-system): switch to rolling PR strategy
At most one open PR per skill at any time. Daily runs push onto the
existing branch and update the PR description. Merging resets the cycle.
Prevents PR accumulation from unreviewed automated runs.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-08 07:45:03 -07:00
Youssef Aitousarrah 8ba5b8fd7e docs(iteration-system): collapse strategies/ into scanners/
Scanners and strategies are 1:1 in the current codebase — separate folder
was artificial. Each scanner file now captures both implementation and thesis.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-08 07:35:40 -07:00
Youssef Aitousarrah 05168c7a96 docs(iteration-system): add GitHub Actions automation layer
Adds daily /iterate and weekly /research-strategy cron workflows to the
spec — full autonomous loop with PR-gated merges, no auto-merge to main.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-07 20:34:21 -07:00
Youssef Aitousarrah 91279fe60b docs: add iteration system design spec
Defines /iterate and /research-strategy skills + docs/iterations/ folder
structure for a generic learn-improve-repeat cycle, demonstrated with the
trading agent discovery pipeline.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-07 20:24:12 -07:00
Youssef Aitousarrah 1c20dc8c90 feat: improve all 9 scanners and add 3 new scanners
Phase 1 - Fix existing scanners:
- Options flow: apply min_premium filter, scan 3 expirations
- Volume accumulation: distinguish accumulation vs distribution
- Reddit DD: use LLM quality score for priority (skip <60)
- Reddit trending: add mention counts, scale priority by volume
- Semantic news: include headlines, add catalyst classification
- Earnings calendar: add pre-earnings accumulation + EPS estimates
- Market movers: add price ($5) and volume (500K) validation
- ML signal: raise min_win_prob from 35% to 50%

Phase 2 - New scanners:
- Analyst upgrades: monitors rating changes via Alpha Vantage
- Technical breakout: volume-confirmed breakouts above 20d high
- Sector rotation: finds laggards in accelerating sectors

All 12 scanners register with valid Strategy enum values.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-20 08:36:18 -08:00
Youssef Aitousarrah 2b74d298da Add scanner improvements design document
Documents the approved plan to fix signal quality issues in all 9
existing scanners and add 3 new scanners (analyst upgrades, technical
breakout, sector rotation).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-20 08:36:18 -08:00
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