International Evidence of COVID-19 and Stock Market Returns: An Event Study Analysis

We study the effect of the first registered case of COVID-19 on stock market returns using event study analysis. Mean-adjusted returns and market model methods are used to estimate cumulative abnormal returns for 30 countries. The results show that stock market returns experience a downwards trend as well as significant negative returns following the COVID-19 outbreak.

In December 2019, an infectious disease identified as coronavirus first appeared in Wuhan, the Capital of Hubei province in the People's Republic of China (PRC) and since then has spread rapidly across the globe. On 11 February 2020 the World Health Organization (WHO) announced that the new name for agent responsible for the coronavirus disease is COVID-19. (Centers for Disease Control & Prevention, 2020) On 11 March 2020 the WHO announced that COVID-19 is a global pandemic. As of 5 May 2020, the number of registered cases is around 3.6 million and the death toll is in the order of 252.8 thousand (Worldometer, 2020).
The emergence of the current COVID-19 pandemic caused financial markets to suffer historic losses in the first quarter of 2020 at a level not seen since 1987 (BBC, 31 March 2020). For example, the Dow Jones, S&P and NASDAQ declined 3.5%, 3.3% and 3.7%, respectively (BBC, 24 February 2020). This has led researchers to extensively investigate its effect on stock market returns. For example, Al-Awadhi et al. (2020) study the effect of COVID-19 on the Chinese stock market using panel data regression. They find that COVID-19 has a negative effect on all companies in that market. Baig et al. (2020) investigate the effect of COVID-19 on the United States (US) equity markets and find that it increases market illiquidity and volatility. Using wavelet coherence analysis, Demir et al. (2020) find a negative and positive relationship between COVID-19 and cryptocurrencies. In addition, Zhang et al. (2020) find that both financial market risk and uncertainty increase following the outbreak of COVID-19.
The remainder of this paper is organised as follows: in the next section we discuss the data and methodology. We analyse the results in Section 3 and in Section 4 we conclude the paper.

DATA AND METHODOLOGY
We obtain stock index daily data from EOD Historical Data and Morgan Stanley Capital International (MSCI). 1 The date of the first registered case and the number of the top 30 countries in terms of the number of registered cases of COVID-19 are obtained from the European Centre for Disease Prevention and Control. Table 1 shows the top 30 countries in terms of the number of registered cases (as of 24 April 2020), their stock index and their first registered case, which is treated as the event day. Countries whose first case was registered on a weekend are excluded from the study as stock market index data are not available for weekends.
We use simple arithmetic returns to calculate daily index return. In addition, we calculate abnormal returns (ABR n,d ) and cumulative abnormal returns (CABR n,d ) for each day in the event window for each index using the following methods: (1) mean-adjusted returns; and (2) the market model. 1 Eodhistoricaldata.com and msci.com/end-of-day-data-search.
1) Mean-adjusted returns As in Brown and Warner (1985), we use standard mean-adjusted returns to calculate abnormal returns (ABR n,d ) for index n on day d: where R n,d is the return of index n on day d and is the average return of index n's daily returns during the estimation window (-250, -11).
2) Market model In addition to the mean-adjusted returns, we calculate abnormal returns (ABR n,d ) using market model methodology as in Dodd and Warner (1983) and Brown and Warner (1985) as follows: where R n,d is the return of index n on day d. R m,d is the return of the MSCI All-Country World Equity Index. α n and β n are regression coefficients for the estimation window (-250, -11) obtained by ordinary least squares estimation (OLS).

RESULTS
Figures 1 and 2 show ABR n,d and CABR n,d for all indices calculated using mean-adjusted returns and the market model,    respectively. They show that CABR n,d experiences a downwards trend following the event day. Tables 2 and 3 present descriptive statistics for all indices, whose distribution is negatively skewed following the event day, indicating the existence of extreme negative values. Moreover, the kurtosis values demonstrate that the distribution is leptokurtic, suggesting the presence of extreme outlier values.
Tables 4 and 5 show mean and median equality tests for all indices calculated using the two methods (mean-adjusted returns and the market model). The event windows we use are [-1, 1], [-3, 3], [-5, 5], [-10, 10], [-10, 15] and [-10, 20]. Table 4 shows that using mean-adjusted returns, market responses following the event day are negative and highly significant during all event windows with the exception of [-1,1], which is insignificant according to the Wilcoxon-Mann-Whitney signed rank median test. 2 Table 5 shows that using the market model, market reactions following the event day are negative and highly significant during all event windows but [-1,1] and [-3, 3], which are insignificant according to the Wilcoxon-Mann-Whitney signed rank median test. Taken together, the results indicate that indices are negatively affected by the COVID-19 outbreak. 3

CONCLUSION
After analysing the returns of 30 stock market indices following the outbreak of COVID-19, we conclude that stock market returns reaction is significantly negative. This result is obtained using mean-adjusted returns and the market model methods for different event windows.