ilia
6b62ae96f7
Phase 2: Disclosure Timing Correlation Engine
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COMPLETE: Match congressional trades to prior market alerts
New Module:
- src/pote/monitoring/disclosure_correlator.py: Core correlation engine
* get_alerts_before_trade(): Find alerts before trade date
* calculate_timing_score(): Score suspicious timing (0-100 scale)
- Factors: alert count, severity, recency, type
- Thresholds: 60+ = suspicious, 80+ = highly suspicious
* analyze_trade(): Complete trade analysis with timing
* analyze_recent_disclosures(): Batch analysis of new filings
* get_official_timing_pattern(): Historical pattern analysis
* get_ticker_timing_analysis(): Per-stock timing patterns
Timing Score Algorithm:
- Base score: alert count × 5 + avg severity × 2
- Recency bonus: +10 per alert within 7 days
- Severity bonus: +15 per high-severity (7+) alert
- Total score: 0-100 (capped)
- Interpretation:
* 80-100: Highly suspicious (likely timing advantage)
* 60-79: Suspicious (possible timing advantage)
* 40-59: Notable (some unusual activity)
* 0-39: Normal (no significant pattern)
New Script:
- scripts/analyze_disclosure_timing.py: CLI analysis tool
* Analyze recent disclosures (--days N)
* Filter by timing score (--min-score)
* Analyze specific official (--official NAME)
* Analyze specific ticker (--ticker SYMBOL)
* Text/JSON output formats
* Detailed reports with prior alerts
Usage Examples:
# Find suspicious trades filed recently
python scripts/analyze_disclosure_timing.py --days 30 --min-score 60
# Analyze specific official
python scripts/analyze_disclosure_timing.py --official "Nancy Pelosi"
# Analyze specific ticker
python scripts/analyze_disclosure_timing.py --ticker NVDA
Report Includes:
- Timing score and suspicion level
- Prior alert details (count, severity, timing)
- Official name, ticker, trade details
- Assessment and reasoning
- Top suspicious trades ranked
Next: Phase 3 - Pattern Detection across officials/stocks
2025-12-15 15:17:09 -05:00
ilia
cfaf38b0be
Phase 1: Real-Time Market Monitoring System
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COMPLETE: Real-time unusual activity detection for congressional tickers
New Database Model:
- MarketAlert: Stores unusual market activity alerts
* Tracks volume spikes, price movements, volatility
* JSON details field for flexible data storage
* Severity scoring (1-10 scale)
* Indexed for efficient queries by ticker/timestamp
New Modules:
- src/pote/monitoring/market_monitor.py: Core monitoring engine
* get_congressional_watchlist(): Top 50 most-traded tickers
* check_ticker(): Analyze single stock for unusual activity
* scan_watchlist(): Batch analysis of multiple tickers
* Detection logic:
- Unusual volume (3x average)
- Price spikes/drops (>5%)
- High volatility (2x normal)
* save_alerts(): Persist to database
* get_recent_alerts(): Query historical alerts
- src/pote/monitoring/alert_manager.py: Alert formatting & filtering
* format_alert_text(): Human-readable output
* format_alert_html(): HTML email format
* filter_alerts(): By severity, ticker, type
* generate_summary_report(): Text/HTML reports
Scripts:
- scripts/monitor_market.py: CLI monitoring tool
* Continuous monitoring mode (--interval)
* One-time scan (--once)
* Custom ticker lists or auto-detect congressional watchlist
* Severity filtering (--min-severity)
* Report generation and saving
Migrations:
- alembic/versions/f44014715b40_add_market_alerts_table.py
Documentation:
- docs/11_live_market_monitoring.md: Complete explanation
* Why you can't track WHO is trading
* What IS possible (timing analysis)
* How hybrid monitoring works
* Data sources and APIs
Usage:
# Monitor congressional tickers (one-time scan)
python scripts/monitor_market.py --once
# Continuous monitoring (every 5 minutes)
python scripts/monitor_market.py --interval 300
# Monitor specific tickers
python scripts/monitor_market.py --tickers NVDA,MSFT,AAPL --once
Next Steps (Phase 2):
- Disclosure correlation engine
- Timing advantage calculator
- Suspicious trade flagging
2025-12-15 15:10:49 -05:00
ilia
b4e6a7c340
Fix analytics tests and add comprehensive testing guide
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Critical Fixes:
- Fixed Price model query to use security_id join with Security
- Added Security import to returns.py module
- Fixed all test fixtures to use test_db_session correctly
- Added AAPL price data to sample_prices fixture
New Tests:
- tests/test_analytics_integration.py: 10 comprehensive integration tests
* Real-world scenarios with synthetic price data
* Return calculations, benchmark comparisons, performance metrics
* Edge cases: missing data, sell trades, disclosure timing
Documentation:
- LOCAL_TEST_GUIDE.md: Complete guide for local testing
* How to test before deploying
* Current data status (live vs fixtures)
* Multiple options for getting real data
* Common issues and fixes
Test Results:
✅ All 55 tests passing
✅ Analytics fully functional
✅ Ready for deployment
Live Data Status:
❌ House Stock Watcher API still down (external issue)
✅ Manual CSV import works
✅ yfinance for prices works
✅ Can use system NOW with manual data
2025-12-15 14:42:20 -05:00
ilia
34aebb1c2e
PR4: Phase 2 Analytics Foundation
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Complete analytics module with returns, benchmarks, and performance metrics.
New Modules:
- src/pote/analytics/returns.py: Return calculator for trades
- src/pote/analytics/benchmarks.py: Benchmark comparison & alpha
- src/pote/analytics/metrics.py: Performance aggregations
Scripts:
- scripts/analyze_official.py: Analyze specific official
- scripts/calculate_all_returns.py: System-wide analysis
Tests:
- tests/test_analytics.py: Full coverage of analytics
Features:
✅ Calculate returns over 30/60/90/180 day windows
✅ Compare to market benchmarks (SPY, QQQ, etc.)
✅ Calculate abnormal returns (alpha)
✅ Aggregate stats by official, sector
✅ Top performer rankings
✅ Disclosure timing analysis
✅ Command-line analysis tools
~1,210 lines of new code, all tested
2025-12-15 11:33:21 -05:00
ilia
204cd0e75b
Initial commit: POTE Phase 1 complete
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- PR1: Project scaffold, DB models, price loader
- PR2: Congressional trade ingestion (House Stock Watcher)
- PR3: Security enrichment + deployment infrastructure
- 37 passing tests, 87%+ coverage
- Docker + Proxmox deployment ready
- Complete documentation
- Works 100% offline with fixtures
2025-12-14 20:45:34 -05:00
