From Biological to Financial Contagion: the COVID19 Outbreak Impact on International Stock Markets

Abstract

This study adds to the recent literature on contagion due to spillover, examining the presence of pairwise contagion or volatility transmissions between the Chinese and the US capital markets and other 13 international stock market returns during the immediate effects of the COVID-19 pandemic. To achieve this purpose, we employ the diagonal and scalar parameterization of Bollerslev's (1986) generalized autoregressive conditional heteroskedasticity (GARCH) to estimate the multivariate GARCH framework, commonly known as the BEKK (Baba Engle Kraft and Kroner) model, to analyse stock market returns of thirteen international stock markets vs China and the US. Two Distributional assumptions are used: Gauss and t-Student. Intraday data from January 2nd to June 25th, 2020, are used.  BEKK models results suggest the Diagonal approach under t-Student Distribution and No-Targeting, in almost all the cases, is the best model to capture the dynamic relationship between the Chinese and the US market and the rest of the indexes. The empirical results show that the model captures the volatility spillovers and display statistical significance for own past mean and volatility with both short- and long-run persistence effects. Originality relies in the extension and size of the sample and approaches employed: thousands of intraday data and thirteen univariate models and more than one hundred multivariate models. The research results have practical, empirical, and social implications in terms of asset allocation, risk management, hedging and provide knowledge on the relationship between stock markets, which are crucial financing spaces in local markets.