Abstract
Infectious diseases and widespread outbreaks influence different sectors of the economy, including the stock market. In this article, we investigate the effect of EBOV and COVID-19 outbreaks on stock market indices. We employ time-varying and constant bivariate copula methods to measure the dependence structure between the infectious disease equity market volatility index (IEMV) and the stock market indices of several sectors. The results show that the financial and communication services sectors have the highest and the lowest negative dependency on IEMV during the Ebola virus (EBOV) pandemic, respectively. However, the health care and energy sectors have the highest and lowest negative dependency on IEMV during the COVID-19 outbreak, respectively. Therefore, the results confirm the heterogeneous time-varying dependency between infectious diseases and the stock market indices. The finding of our study contributes to the ongoing literature on the impact of disease outbreaks, especially the novel coronavirus outbreak on global large-cap companies in the stock market.
Highlights
Infectious disease outbreaks have a significant impact on economic activity
The results indicate that there is a negative dependency between IEMV and other sectoral stock market indices during Ebola virus (EBOV) and COVID-19 periods, but the dependency during the coronavirus outbreak is much higher
The results confirm that there is a positive dependency between IEMV and other sectoral stock indices during Pre-EBOV and Pre-COVID-19 eras except for material, which indicates negative dependency with IEMV during the pre-COVID-19 period
Summary
Infectious disease outbreaks have a significant impact on economic activity. The pandemics affect the sectors of the economy and the economic policies [3]. Several studies investigate the impact of a disease outbreak on the economy separately, which will be presented in the literature review. This paper employs the copula method to investigate the dependence structure between stock market indices during the COVID-19 and EBOV outbreaks. For this purpose, we first use the time-varying copula method to extract time-varying and constant dependence structure to all pandemic time.
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