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Implement Data Driven - External data integration #22

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opened 2026-02-04 16:12:29 +09:00 by agentson · 0 comments
agentson commented 2026-02-04 16:12:29 +09:00
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Goal

Behavioral Rule: Data Driven

Integrate objective external data sources to make decisions based on facts, not just user assumptions.

Background

사용자의 말에만 의존하지 말고, 외부 소스(객관적 데이터)를 기반으로 판단할 것.

Tasks

1. Financial News API

  • Integrate news sentiment analysis
  • Real-time news feed per stock
  • Sentiment scoring (-1 to +1)
  • News impact weighting

Candidate APIs:

  • Alpha Vantage (free tier)
  • Financial Modeling Prep
  • NewsAPI
  • Reddit/Twitter sentiment

2. Economic Calendar

  • Major economic events (FOMC, GDP, CPI)
  • Earnings calendar per stock
  • Dividend schedules
  • Ex-dividend dates

3. Market Data Enrichment

  • Insider trading activity
  • Short interest data
  • Institutional holdings changes
  • Analyst ratings and price targets

4. Sector Rotation Indicators

  • Sector performance tracking
  • Industry momentum
  • Relative strength analysis

5. Integration with Brain

  • Enhance Gemini prompts with external data
  • Context-aware data selection
  • Data freshness tracking
  • Fallback when APIs unavailable

Implementation Files

  • src/data/news_api.py - News integration
  • src/data/economic_calendar.py - Economic events
  • src/data/market_data.py - Additional market data
  • src/brain/gemini_client.py - Integrate into prompts
  • tests/test_data_integration.py - Tests

Acceptance Criteria

  • At least 2 external data sources integrated
  • News sentiment included in decisions
  • Economic calendar checked before trades
  • Graceful degradation if APIs fail
  • Data freshness < 5 minutes
  • Tests achieve ≥80% coverage

Priority

MEDIUM - Adds value but requires API costs/integration

Cost Considerations

  • Start with free tier APIs
  • Monitor usage and costs
  • Upgrade only if ROI proven

Related

Behavioral Rule: Data Driven
Enhances: Brain decision quality

## Goal Behavioral Rule: Data Driven Integrate objective external data sources to make decisions based on facts, not just user assumptions. ## Background 사용자의 말에만 의존하지 말고, 외부 소스(객관적 데이터)를 기반으로 판단할 것. ## Tasks ### 1. Financial News API - Integrate news sentiment analysis - Real-time news feed per stock - Sentiment scoring (-1 to +1) - News impact weighting Candidate APIs: - Alpha Vantage (free tier) - Financial Modeling Prep - NewsAPI - Reddit/Twitter sentiment ### 2. Economic Calendar - Major economic events (FOMC, GDP, CPI) - Earnings calendar per stock - Dividend schedules - Ex-dividend dates ### 3. Market Data Enrichment - Insider trading activity - Short interest data - Institutional holdings changes - Analyst ratings and price targets ### 4. Sector Rotation Indicators - Sector performance tracking - Industry momentum - Relative strength analysis ### 5. Integration with Brain - Enhance Gemini prompts with external data - Context-aware data selection - Data freshness tracking - Fallback when APIs unavailable ## Implementation Files - `src/data/news_api.py` - News integration - `src/data/economic_calendar.py` - Economic events - `src/data/market_data.py` - Additional market data - `src/brain/gemini_client.py` - Integrate into prompts - `tests/test_data_integration.py` - Tests ## Acceptance Criteria - [ ] At least 2 external data sources integrated - [ ] News sentiment included in decisions - [ ] Economic calendar checked before trades - [ ] Graceful degradation if APIs fail - [ ] Data freshness < 5 minutes - [ ] Tests achieve ≥80% coverage ## Priority **MEDIUM** - Adds value but requires API costs/integration ## Cost Considerations - Start with free tier APIs - Monitor usage and costs - Upgrade only if ROI proven ## Related Behavioral Rule: Data Driven Enhances: Brain decision quality
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Reference: jihoson/The-Ouroboros#22
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