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How Hedge Funds Trade News Data: What NLP Can Really Extract From Text
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0:00lesson
News Data Formats and Metadata — JSON/XML, programmatic consumption
- News data formats include JSON/XML for programmatic reading
- Metadata includes timestamp, headline, language, source, subjects
- NLP enables structured sentiment analysis for filtering news
- Three-class sentiment scores: positive/negative/neutral
2:02lesson
Sentiment Probabilities — 3-class scores for companies
- Sentiment scores: +1/-1/0 based on highest probability class
- Hedge funds use precomputed sentiment signals directly
- Micro-sentiments include volatility, production volume, urgency
- News items tagged with entities: companies, people, orgs
4:02lesson
Kalman Filter for Noise Reduction — State Space Models
- Kalman filter reduces noise in high-frequency sentiment data
- State space models process text-based signals for trading
- Granger causality tests sentiment's predictive power
- Entity relationships: affiliates, acquisitions, joint ventures
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