📉 VIX Analysis & S&P 500 Comparison

A quantitative study of market volatility and equity behavior using Python.

This project analyzes the CBOE Volatility Index (VIX) from 1990 to 2025 and compares it with the S&P 500 to identify volatility regimes and their relationship with equity returns.

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What This Project Does

Starting from daily VIX data, the analysis classifies market conditions into volatility regimes and then cross-references them with monthly S&P 500 returns to quantify how fear and equity performance interact over time.

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Key Analyses

• Volatility Regimes: markets are classified as Calm or Stress based on VIX thresholds, making it easy to isolate periods of elevated fear
• Returns & Dynamics: daily and monthly log returns, intraday ranges, and realized volatility capture how the market moves within each regime
• Trend Smoothing: moving averages filter noise and highlight long-term structural trends
• VIX vs S&P 500: monthly comparison using dual-axis plots to preserve scale, showing the typical inverse relationship between volatility and equity returns
• Rolling Correlation: 12-month rolling correlation tracks how the VIX-equity relationship evolves across different market cycles

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Visualizations

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Data & Sources

VIX

• Source: CBOE Volatility Index time series available on GitHub finance-vix dataset
• Dataset file used in this project: available here

S&P 500

• Source: S&P 500 historical monthly data on Macrotrends
• Dataset file used in this project: available here