Predictive Signals from VIX Spikes: A Comparative Study of Linear, Logistic, and GARCH-Based Return Forecasting Models

This study investigates the relationship between market volatility, especially VIX levels and spikes above 45, and future equity returns. The analysis stems from the tactical decisions investors face during sharp market drawdowns. We explore whether volatility indicators, combined with investor sentiment measures, can inform shifts from defensive to opportunistic portfolio positions. Using U.S. data from 2008 to 2025, we test linear regression, logistic regression, and GARCH (1,1) models to evaluate return predictability. Results show that extreme VIX spikes offer contrarian signals, with significant positive returns over three-month horizons. Logistic regression confirms significance over both three-month and one-year periods. These findings remain robust after controlling for valuation, credit spreads, PMI, sentiment ratios, and interaction effects. While GARCH captures conditional variance, it lacks forward-looking predictive power in high-stress regimes. Overall, the evidence suggests that volatility timing merits consideration as part of a tactical allocation framework. Our findings also contribute to the market efficiency debate by integrating market expectations with economic indicators for risk-aware decision-making.