fomc_language_intelligence_tracker

AI-powered FOMC decision tracker built for macro hedge fund research. Combines LLM analysis with rates data to generate real-time policy tone intelligence.

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🔥 What This Project Does

• Reads and analyzes official FOMC statements (2020–2025)
• Applies an AI LLM (OpenAI's GPT-4o) to score hawkishness/dovishness per meeting
• Extracts key macro topics (growth, inflation, labor market, financial stability)
• Aligns scores with real Fed Funds Rate movements
• Visualizes policy cycles and annotates pivotal shifts ("First Cut", "Pivot Signal", etc.)

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🎯 Why It Matters

• Macro regime changes often start with language shifts before markets move.
• Tracking FOMC tone + real rates helps predict policy pivots earlier.
• LLMs unlock insights at scale – enhancing discretionary macro investing.

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🛠️ Technology Stack

• Python (pandas, matplotlib)
• OpenAI API (chat models for FOMC analysis)
• Data:
  • Official FOMC Statements (2020–2025)
  • Federal Funds Effective Rate (Monthly)

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📊 Key Outputs

• Hawkishness Score Trends (Smoothed Analysis)
• Hawkishness vs Fed Funds Rate Overlay
• Policy Regime Shift Annotations
• Macro Topic Extraction (via Word Cloud)

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🚀 Project Vision

This is the foundation of a full FOMC Decision Tracker Dashboard:

🧠 Bringing AI-powered macro understanding directly into hedge fund investment processes.

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👤 Author

JO