Quick Start
git clone https://github.com/Digital-AI-Finance/CB-Speeches-Analysis.git
cd CB-Speeches-Analysis && pip install -r requirements.txt
python -c "from analysis.run_all import run_pipeline; run_pipeline()"
cd charts && python run_all_charts.py
Requirements
- Python 3.9+
- ~500MB disk space
- Dependencies: pandas, numpy, scikit-learn, matplotlib, ruptures
Pipeline Steps
1. Run Analysis
python -c "from analysis.run_all import run_pipeline; run_pipeline(use_cached=True)"
2. Generate Charts
cd charts && python run_all_charts.py
3. Run Tests
python -m pytest tests/ -v
4. Launch Dashboard
streamlit run app.py
Output Files
data/pca_components.csv- PC1 and PC2 time seriesdata/breakpoints.json- Structural break datesdata/sentiment_aggregated.csv- Monthly sentiment countsdata/correlation_matrix.csv- First-difference correlationscharts/*/chart.pdf- 12 publication-ready figures