TradingAgents/tradingagents/database/services
Joseph O'Brien 1ba647ae4a feat: add quantitative scoring with multi-timeframe analysis and CLI enhancements
Add quantitative scoring pipeline for discovery with technical indicator analysis:
- Momentum, volume, relative strength, and risk/reward scoring
- Support/resistance level detection
- Gap analysis for price momentum signals
- Configurable caching to reduce API calls

Implement multi-timeframe signal analysis:
- Short-term (5/20 day), medium-term (20/50 day), and long-term (50/200 day) signals
- Timeframe alignment detection (aligned_bullish, aligned_bearish, mixed, neutral)
- Signal strength calculation based on indicator agreement

Enhance CLI discovery display:
- Color-coded conviction scores (green/yellow/red thresholds)
- Signal column showing timeframe alignment status
- News mentions count column

Update tests to support new quantitative filtering configuration.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-03 17:04:18 -05:00
..
__init__.py feat: add database-backed caching to dataflows interface 2025-12-03 11:45:46 -05:00
analysis.py feat: integrate database persistence with TradingAgentsGraph 2025-12-03 11:31:21 -05:00
discovery.py feat: integrate database persistence with TradingAgentsGraph 2025-12-03 11:31:21 -05:00
market_data.py feat: add quantitative scoring with multi-timeframe analysis and CLI enhancements 2025-12-03 17:04:18 -05:00
trading.py feat: integrate database persistence with TradingAgentsGraph 2025-12-03 11:31:21 -05:00