Cross-Asset Correlation Analysis

This project analyzes relationships between major asset classes using Python.

Assets studied:

• SPY (US equities)
• QQQ (tech equities)
• TLT / IEF (US Treasuries)
• GLD (gold)
• USO (oil)
• UUP (US dollar)
• VIX (market volatility)

Methods

• Log return calculation
• Correlation matrix
• 60-day rolling correlations
• Principal Component Analysis (PCA)

Key Findings

• SPY and VIX show strong negative correlation.
• SPY–TLT correlation becomes positive post-COVID during inflation shocks.
• PCA reveals dominant factors representing market risk sentiment and macro regimes.

Tools

Python, Pandas, NumPy, Matplotlib, Scikit-Learn