The effect of COVID‐19 pandemic on global stock markets: Return, volatility, and bad state probability dynamics

• Published date: 01 December 2022
• Author: Mohamed A. K. Basuony,Mohammed Bouaddi,Heba Ali,Rehab EmadEldeen
• Date: 01 December 2022
• DOI: http://doi.org/10.1002/pa.2761

RESEARCH ARTICLE

The effect of COVID-19 pandemic on global stock markets:

Return, volatility, and bad state probability dynamics

Mohamed A. K. Basuony

1

| Mohammed Bouaddi

1

| Heba Ali

2

| Rehab EmadEldeen

1

1

School of Business, The American University

in Cairo, Cairo, Egypt

2

Faculty of Management Technology, German

University in Cairo, New Cairo, Egypt

Correspondence

Heba Ali, Faculty of Management Technology,

German University in Cairo, New Cairo City

11835, Egypt.

Email: heba.abbas-ali@guc.edu.eg

Abstract

This study investigates the impact of COVID-19 pandemic on stock returns, conditional

volatility, conditional skewness and bad state probability. This study utilizes an asymmet-

ric exponential generalized autoregressive conditional heteroscedasticity model to cap-

ture the asymmetric effect of positive and negative shocks (news) on conditional

volatility. Using a sample consisting of international stock market indices in Brazil, China,

Italy, India, Germany, Russia, Spain, United Kingdom, and United States, over the period

from January 1, 2013 to December 31, 2020, we find unprecedented increases in condi-

tional volatilities and bad state probabilities across all the markets. However, this impact

is not symmetric across markets. Furthermore, we find that the negative affect of deaths

is more pronounced, compared to the positive impact of recovered cases.

KEYWORDS

bad state probability, COVID-19, pandemic, stock market, volatility

1|INTRODUCTION

In late 2019, a new virus called “COVID 19”had started to spread,

causing “severe pneumonia.”Thus, this virus led to an extraordinary

rate of death between the elderly and the most vulnerable in society,

leading to an international social distancing and home isolation of

more than 2 billion people worldwide, with tremendous social, politi-

cal and economic consequences (Goodell, 2020; Sharif et al., 2020).

Moreover, one of the commercial effects of this virus was an unex-

pected disruptions in the flow of goods and services, commodity

prices and financial conditions, creating an economic disasters across

many countries because of its impact on the production and supply

chains in China, the United States, Europe, and Japan, as well as the

most important economies in the world (IMF, 2020).

Significant changes in the financial structures of countries was

caused by the “domino effect”created by retrenched investors in

many countries (Kenourgios et al., 2011). This contagion effect in the

global market led to unprecedented disturbing effects in different

economies that were only comparable to the depression of 1920

(Corbet et al., 2020). Moreover, all the countries face a great health

crisis, severe external demand shock, dramatic shrinking in global

financial conditions, and a plunge in the commodity prices that will

have a severe effect on economic activity in commodity exporters

(IMF, 2020). In addition, the outbreak of COVID-19 has been declared

as a global pandemic on June, 2020 by the World Health Organization

(WHO), which shaken the global financial markets. As of June

16, 2020, there are 9,653,048 confirmed cases and 491,128 deaths

across the world for 216 Countries, areas or territories with cases,

including emerging and developed countries (WHO, 2020).

The objective of this research is to analyze the influence of

COVID-19 on the stock price behavior of equity market indices of

selected nine countries. We selected the countries that had the largest

confirmed cases of COVID-19 at the end of March and June 2020.

Accordingly, the final sample included United States, Italy, Spain,

United Kingdom, Germany, China, Brazil, Russia, and India. We also com-

pare how the stock price behavior differs across the periods pre- and dur-

ing the COVID-19 (to examine the initial effect of the shock of COVID-

19 on the markets) and then between the first and second quarters dur-

ing the COVID-19 period (to explore whether the markets are rebounded

after the shock is being assessed and absorbed). Our analysis of stock

market behavior is based on examining stock returns, conditional volatil-

ity, conditional skewness, and bad state probability, measured using a

widely applied econometric model, an asymmetric exponential general-

ized autoregressive conditional heteroscedasticity (EGARCH) model.

Received: 7 March 2021 Revised: 2 September 2021 Accepted: 4 September 2021

DOI: 10.1002/pa.2761

J Public Affairs. 2022;22(Suppl. 1):e2761. wileyonlinelibrary.com/journal/pa © 2021 John Wiley & Sons Ltd. 1of18

https://doi.org/10.1002/pa.2761

The advantage of this model is to allow for capturing the well-

documented asymmetric effect of positive and negative shocks on

conditional volatility as positive shocks may have less impact on vola-

tility than the negative shocks (Alberg et al., 2008; Hentschel, 1995;

Nelson, 1991). It is commonly known fact that volatility clustering

produces heavier tails, as documented by Engle's (1982) seminal paper

on autoregressive conditional heteroscedasticity (ARCH) model and

its generalization by Bollerslev's (1986) paper on generalized auto-

regressive conditional heteroscedasticity (GARCH) model, and others

(e.g., Tsay, 2010). However, since normal GARCH model links directly

the kurtosis to the variance, it is unable to well capture the excess

kurtosis that exists in financial returns and produces low probability of

extreme realizations (extreme returns) than observed in the data. In

addition, inclusion of conditional skewness in the model captures the

asymmetry, and also impacts the persistence in conditional variance

as highlighted by Harvey and Siddique (1999). To overcome these

drawbacks when using the normal GARCH model, our EGARCH

model adds two extra parameters in the distribution of returns,

namely the skewness and kurtosis. Moreover, this model is aug-

mented to capture the impact of the number of death and recovered

cases to distingue between the effects of negative information

(deaths) verses positive information (recovered cases). Moreover, as

any other major crisis, the COVID-19 pandemic was associated with

an adverse impact on the financial markets, caused by panic, uncer-

tainty, negative sentiment and investor pessimism during the pan-

demic. Hence, it was crucial for us to estimate bad state probabilities

(i.e., the probability that stock market returns might fall below the

expected returns) to quantify the likelihood of bad events, and assess

the probability of markets downturns in bad times of high uncertainty.

Therefore, this paper contributes to the literature in several ways.

First, this study extends the evolving literature on the impact of

COVID-19 on stock market behavior. Although several studies have

investigated how financial markets have been affected during COVID-19

period (Baker et al., 2020;Corbetetal.,2020), to the best of our knowl-

edge,nonehaveexaminedtheimpactofCOVID-19onglobalstockmar-

kets, using an asymmetric exponential EGARCH model with an emphasis

on conditional volatility, conditional skewness and bad state probability.

This allows for not only capturing the dynamic behavior of conditional

variance but also taking into account the asymmetric impact of negative

versus positive return innovations. Second, this study aims to estimate

the impact of COVID-19 recovered cases and deaths on the conditional

mean, conditional volatility and conditional skewness of the returns of

equity market indices. By doing that, we distinguish between the impact

of positive and negative information on stock market behavior to examine

the asymmetric characteristics of stock market behavior. Third, we dem-

onstrate how the COVID-19 pandemic can amplify bad state probability,

whichisimportantinaperiodwhenfinancialmarketsexperienceextreme

uncertainty and investors' behavior is driven by their fear and panic.

Therefore, this study adds not only to the literature on COVID-19's effect

on stock markets but also to the overall literature on financial market

crashes and crises. Fourth, our long analysis period (January 1, 2013 to

December 31, 2020) enables us to compare the stock price behavior

across not only the periods pre- and during the COVID-19 pandemic but

also the first and second quarters during the COVID-19 period. This

allows for better understanding of how stock markets have initially

reacted to the shock of COVID-19, compared to how they are rebounded

after the shock is being absorbed. Moreover, our findings provide impor-

tant implications for investors, practitioners and policy makers. For traders

and investors seeking to invest in international stock markets, the results

indicate which markets are most correlated and risky, which have strong

consequences for portfolio optimizationandimplementationofprofitable

trading strategies. For practitioners, the findings allow to get insights into

the dynamic behavior of stock markets in the countries that are heavily

affected by the pandemic in order to examine the best investment

options. For policy makers, the findings confirm the critical role that the

political leadership and governments can play, via mitigating the spread of

pessimistic views and negative feelings amid citizens, in conveying posi-

tive signals to the investors and thereby decreasing market uncertainty.

2|LITERATURE REVIEW

Following such a huge worldwide crisis, the literature on the economic

effects of COVID-19 has emerged quickly in recent months. For example,

Ramelli and Wagner (2020)andZarembaetal.(2020), among other, have

investigated the adverse impact of COVID 19 on stock returns and vola-

tility. Other studies have examined how the outbreak of COVID-19

affected the financial contagion in financial markets. For example,

Akhtaruzzaman et al. (2020)examinehowtheCOVID-19periodhas

affected the financial contagion between China and G7 countries and

show that stocks listed across China and G7 countries have been associ-

ated with a significant increase in conditional correlations between their

stock returns. Consistently, Just and Echaust (2020) show close depen-

dence between S&P 500 index returns and both implied volatility and

implied correlation during the COVID-19 period.

Other studies focus on exploring how COVID-19 has affected com-

modity markets. Gharib et al. (2021) examine the economic impact of

COVID-19 on the causal relationship between crude oil and gold prices

and find a bilateral contagion effect of bubbles in oil and gold markets

during the recent COVID-19 outbreak. Sharif et al. (2020)analyzethe

connectedness between COVID-19, oil price volatility shock, the stock

market, geopolitical risk and economic policy uncertainty in the

United States. Their finding show that the effect of the COVID-19 on the

geopolitical risk substantially higher than on the US economic uncertainty.

In related context, Conlon and McGee (2020) examine the price behavior

of Bitcoin during the COVID-19 bear market and provide empirical evi-

dence casting doubt on the ability of Bitcointoactasasafe-havenasset.

While other studies focus on assessing the role of governmental policies

in mitigating the negative impact of the pandemic on financial markets.

For instance, Narayan et al. (2020) examine the effect of government

responses of G7 countries to the coronavirus pandemic (COVID-19) on

stock market returns, showing that lockdowns, travel bans, and economic

stimulus packages have exerted a positive effect on the G7 stock markets.

Ma et al. (2020) reveal that countries with more aggressive government

fiscal policy exhibit a superior ability to decrease the adverse impact of

the pandemic on GDP growth, while emerging market are most likely to

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