Stylized patterns in implied volatility indices and stock market returns : a cross country analysis across developed and emerging markets

Purpose: This paper examines the associative and causal relationship between changes in the implied volatility index (VIX) and stock market returns, with data from 15 countries representing both developed and emerging economies.1 We also examine the dynamic variation, if any in the nature of the relationship across bull and bear market swings in these markets. Design/Methodology/Approach: We use daily time series data between January 2013 to July 2019, on VIX and stock index from these countries and employ regression and causality models to explore the nature of the relationship between VIX and stock market movements. We also explore differential patterns, if any, across the countries and bull and bear market cycles in each of these countries. We substantiate our results from the main analysis using a series of robustness tests. Findings: For most countries, we find strong evidence of a negative and asymmetric relationship between the stock market and VIX movement, irrespective of the bear and bull market cycles. We also find that this relation is asymmetric in nature i.e. volatility spikes are more in market downturns than during market upswings. We find strong evidence of the "leverage hypothesis" explaining this asymmetric relation for all countries across all market cycles. We also find weak evidence of reverse causality i.e VIX changes to market movements as per the "volatility feedback hypothesis" holding during bear periods only in developed countries. We suspect that two important pre-conditions of volatility feedback hypothesis to hold, namely volatility persistence and contemporaneous positive volatility return relation might not be holding. We do not find any significant changes in these patterns across bull and bear market cycles. Value: These results indicate that investors can effectively use signals imminent in VIX movements, to determine potential entry and exit points both in emerging as well as developed markets. This should provide them an additional tool in addition to standard analysis approaches before allocating resources in a particular market.