The purpose of this study is to examine the effect of the Severe Acute Respiratory Syndrome (S.A.R.S.) epidemic on the long-run relationship between China and four Asian stock markets. To this end, we first employ the advanced smooth time-varying cointegration model to investigate the existence of a time-varying cointegration relation among these markets and then employ the difference-indifferences approach to analyse whether or not the S.A.R.S. epidemic impacted the long-run relation between China and these four markets during the period 1998-2008, covering 5 years before and after the S.A.R.S. outbreak. Our results support the existence of a time-varying cointegration relation in the aggregate stock price indices, and that the S.A.R.S. epidemic did weaken the long-run relationship between China and the four markets. Therefore, stockholders and policy makers should be concerned about the influence of catastrophic epidemic diseases on the financial integration of stock market in Asia.

This research crucially investigates COVID-19 variables’ impacts on the changing distributions of travel and leisure industry returns across 65 countries via a quantile regression model that uses daily data from December 2019 to May 2020 to provide early evidences from a panel of countries. We find that the change rate in COVID-19 deaths exerts more substantial negative effects on industry returns at majority quantiles than does the impact from the number of confirmed cases. The latter number only saliently and negatively influences the lowest return quantiles, revealing a nonlinear effect of confirmed cases. The study identifies a V-shape correlation between the number of cases recovered and travel and leisure industry returns (i.e. a negative impact at the lower quantiles, but a positive impact at higher quantiles) across return quantiles. This likely denotes that confirmed cases grow exponentially and that their effect may overwhelm the impact of the number of recovered cases. Lastly, this study presents a positive correlation between government response stringency index and returns.