Volatility of and cross-correlation between major international stock indices before and during the COVID-19 pandemic

Abstract

Following the arrival of the year 2020, the extraordinary outbreak of the novel coronavirus (COVID-19), which was initially seen as an epidemic, evolved into an all-out pandemic. Consequently, its effects have shaken the global economies and affected countries across the globe. This thesis investigates the relationship between market disturbances across countries and models the recent COVID-19 pandemic’s influence on the volatility and cross-market correlation in six major stock indices: S&P 500, S&P/TSX, DAX, FTSE 100, Nikkei 225 and SSE. We estimated the pandemic effect on market volatility with a univariate GJR-GARCH model, and employed a multi-variate DCC-GARCH to examine the conditional correlations between six of the largest economies in the world. We also visualized the regime switching between low and high correlation regimes with a two-regime Markov switching model. Our discoveries suggest that the six indices behaved almost identically under the COVID-19 period, with the Nikkei 225 being the only one that did not show evidence of a higher sensitivity towards COVID-19 news. Furthermore, the filtered and smoothed transition-probability charts showed evidence of stronger cross-correlation during periods of distress and uncertainty, and suggestions of one common market in situations like this are valid. Overall, our findings contribute to previous literature seeking to understand the recent pandemic’s influence on capital markets and the negative consequences associated with markets being highly integrated. Keywords: COVID-19, volatility, contagion, capital markets JEL Classification: C12, C15, C32, C58