key: cord-0789184-hp25c9qo
authors: Ullah, Sabeeh
title: Impact of COVID-19 Pandemic on Financial Markets: a Global Perspective
date: 2022-02-03
journal: J Knowl Econ
DOI: 10.1007/s13132-022-00970-7
sha: 1266afc9bacd16eef2364a1a93e6f30aac3b921f
doc_id: 789184
cord_uid: hp25c9qo

This study aims to examine the influence of the COVID-19 outbreak on daily market returns in most affected developed and emerging markets. For this purpose, panel data of 30 most affected developed and emerging markets over the period January 1, 2020, to December 12, 2020, were analyzed by using panel estimated generalized least square (panel-EGLS) and panel quantile regression approaches. The results confirm that the new COVID-19 daily cases and deaths adversely impact daily market returns around the globe. Also, the positive rate of new COVID-19 cases has also negatively influenced market returns. Further, the number of new COVID-19 daily tests conducted has a positive impact on market returns. Interestingly, the study also found similar impacts for both developed and emerging markets except the news announcement of new COVID-19 daily deaths, which have a positive impact on emerging market returns. The findings of this study present some policy implications for governments to adopt early proactive and control measures to protect financial markets from an adverse decline in future pandemics and to increase investors’ confidence.

On December 31, 2019, the outbreak of coronavirus started in China and spreads to 220 countries and territories around the globe. On March 11, 2020, the World Health Organization (WHO) declare it a global pandemic (Kickbusch et al., 2020; Phillipou et al., 2020) . Coronavirus is a democratic virus that affects Secondly, to the best of available literature, the study considers for the first time both the developed and emerging countries' markets based on the high confirmed cases. The outbreak of the COVID-19 pandemic initially hit the developed economies including the UK, USA, Spain, Germany, and Italy, and its second wave unfolding the emerging market economies (Rakshit & Neog, 2021) . Hevia and Neumeyer (2020) documented that the COVID-19 pandemic arises as to the largest macroeconomic shocks that affect both the developed and emerging markets. Contemporary researchers consider either a single market (Ciner, 2020; Mirza et al., 2020; Tiberiu, 2020) or emerging markets (Czech et al., 2020) , but do not consider both developed and emerging markets. In this line, Machmuddah et al. (2020) suggested that research based on comparative studies is needed by taking more global samples.

Thirdly, to be in line with the most recent studies on the impact of COVID-19 pandemic on market returns (Al-Awadhi et al., 2020; Anh & Gan, 2020; Ashraf, 2020; Zhang et al., 2020) , the study investigated the impact of WHO official announcement regarding the propagation of COVID-19 pandemic, deaths reported, new COVID-19 tests conducted, positive growth rate of COVID-19 virus, poverty index, life expectancy index, and development index on market return in developed and emerging markets. Considering a large set of variables reduces the problem of omitted variable bias and brings more accuracy in explaining the changes in stock market returns (Rakshit & Neog, 2021) .

Finally, from a methodological view, this study adopts the most suitable and robust methods like panel estimated generalized least square (panel-EGLS) and quantile regression approach to estimate the effect of the COVID-19 pandemic on the global financial markets. Contemporary researchers on the relationship between COVID-19 pandemic and market returns either used static panel models (Al-Awadhi et al., 2020; Anh & Gan, 2020; Ashraf, 2020; Tahat & Ahmed, 2020) or classical event-study methods Liu et al., 2020a, b; Machmuddah et al., 2020) . Ciner (2020) suggested that estimating financial market returns during the COVID-19 pandemic through modern penalized regressions could provide robust results. Moreover, for broader application, longitudinal studies are required to accumulate the results of financial markets during the COVID-19 pandemic (Machmuddah et al., 2020) .

In this context, the current study aims to investigate the impact of the COVID-19 pandemic on the global financial markets of the most affected countries and compare the results of two subsamples, developed and emerging markets. To the best of our knowledge, this study is novel and the first to investigate the global financial market returns during the COVID-19 pandemic in both developed and emerging markets.

With this, the study confirms that the new confirmed COVID-19 daily cases, news announcements of confirmed COVID-19 daily deaths, and the positive rate of new COVID-19 cases have negatively affected market returns. In a nutshell, the COVID-19 pandemic has unsurprisingly negatively affected the global markets. Likewise, the study also found similar effects for both developed and emerging markets except the news announcement of new COVID-19 daily deaths, which have a positive effect on emerging markets' returns.

The rest of the paper is as follows: "Literature Review" section provides theoretical and empirical literature about Pandemics. "Data and Methodology" section provides the research design. "Empirical Results" section reported the empirical results and "Conclusion and Policy Implications" section concludes the paper.

The speedy propagation of the outbreak of the COVID-19 and declaration as a pandemic by the World Health Organization (WHO) has led to the fear and an interest in other historical pandemics. In the past 300 years, Potter (2001) reported about 10 pandemics and argued that due to the repeated non-regular periodic pattern, I cannot ignore the possibility of new medical disasters in the future. Among those, the pandemics of the Black Death or bubonic plague in the fourteenth century and the 1918 influenza, known as the Spanish flu in 1918-1919, were the more severe, killing approximately 30 to 60 million people (Jonung & Roeger, 2006) . Besides, in the twentieth century, three pandemics arose, namely, the Spanish flu (1918), the Asian flu (1957) , and the Hong Kong flu (1968) (Kilbourne, 2006) . Moreover, the more recent pandemics were severe acute respiratory syndrome ( Prior studies on the microeconomic impact of past pandemics and other diseases are mixed and provide inconclusive results (Bell & Lewis, 2005; Jonung & Roeger, 2006) . For instance, Brainerd and Siegler (2003) found a positive effect of Spanish flu on economic growth. Similarly, Young (2005) documented the positive effect of the AIDS epidemic on net future per capita consumption while Bell et al. (2004) found the negative results. Ismahene (2021) examined the effect of infectious diseases on trade and economic growth in 88 developed and developing countries and found that infectious disease negatively influence economic growth and trade openness. Additionally, studies also found insignificant results of the pandemic on the stock markets, because no one knows by how much and how long the stock prices will fall (Jonung & Roeger, 2006) .

Many analysts and researchers are calling the COVID-19 pandemic a Black Swan event (Lloyd, 2020) , which is very close to the 1918 Spanish flu pandemic (Colvin & McLaughlin, 2020) . Despite the similarities between COVID-19 and the 1918 Spanish flu pandemic, there are also some differences between these two pandemics (Lloyd, 2020) . The global mortality rate of COVID-19 is 4.84%, while initially, WHO estimated a 2% mortality rate and then increase it to 3.4% by March 3, 2020. 1 The global mortality rate of COVID-19 is greater than the mortality rate of swine flu (0.02%) and Spanish flu (0.95%), 2 but less than the mortality rate of SARS (9.6%) and MERS (34.4%). 3

The severity and mortality rate of the COVID-19 pandemic pose a great challenge for policymakers, investors, and individuals at large. The health risks of epidemics and disease outbreaks creating panic and fear lead to various risks to the economy (Ismahene, 2021) . The novelty of the new virus COVID-19 generates fearsome and additional stress on the financial markets around the globe. The new COVID-19 pandemic creates shock waves on financial markets, which resultantly increase price volatility (Albulescu, 2020) . In addition, Ramelli and Wagner (2020) argued that the future economic effect of the COVID-19 pandemic is highly uncertain, as the virus epidemic creates the risk of a financial pandemic (Boot et al., 2020) . Hartwell (2018) reported that different sources like institutional issues, economic conditions, or market uncertainty affect the financial markets. Following this, Onan et al. (2014) and Tiberiu (2020) argued that bad and good macroeconomic announcements also affect financial markets. Some recent prior studies related the economic policy uncertainty (EPU) with financial markets (Kalyvas et al., 2020; Li & Zhong, 2020; Mei et al., 2018; Tiwari et al., 2019) . To maintain liquidity in the markets, different governments apply strategies of the optimized supply chain, cutting interest rates, increasing the purchase of government bonds, and many others (Boot et al., 2020; Lloyd, 2020) .

Despite the heterogeneous responses of different financial markets against the COVID-19 pandemic, to this point, neither of the financial markets around the globe responded strongly to the outbreak of COVID-19. Selmi and Bouoiyour (2020) documented that the impact of the COVID-19 pandemic could be much harmful to investors and the global economy. COVID-19 pandemic crisis leads to market inefficiency and income inequality (Hong et al., 2021) .

Recognizing the possible economic impact of the COVID-19 pandemic on financial market returns, when the COVID-19 pandemic happened, has emerged very sharply in recent years. Recent academic researches around the globe made several attempts to examine the impact of the COVID-19 pandemic on the financial stock market in different countries and found an adverse relationship between the COVID-19 pandemic and market returns (Alfaro et al., 2020; He et al., 2020; Liu et al., 2020a, b; Narayan et al., 2020; Zhang et al., 2020) . Other studies conducted by Al-Awadhi et al. (2020) and Anh and Gan (2020) have reported a negative effect of the COVID-19 pandemic on financial market returns. Consistently, Ashraf (2020) reported that the COVID-19 pandemic has a significantly negative effect on market returns. Hung et al. (2021) analyzed the impact of the COVID-19 pandemic on the Vietnamese stock market and found a significantly negative effect of the COVID-19 pandemic on market returns. Harjoto et al. (2021) showed that the COVID-19 pandemic adversely impacts the financial markets of emerging economies more than developed economies. Similarly, Alexakis et al. (2021) and Basuony et al. (2021) also found an adverse effect of COVID-19 pandemic on stock market returns. Due to consistency in empirical outcomes of recent studies, hypotheses are constructed based on the expected sign of the relationship of COVID-19 pandemic with stock market returns in Table 1 .

The main objective of the study is to estimate how global financial markets react to the growing impact of the COVID-19 pandemic. To accomplish this, a sample of 30 most affected developed and developing countries were used, which consists of 5810 daily observations of COVID-19-related variables and market closing prices. A panel data that range from January 1, 2020, to December 12, 2020, were collected from different secondary sources. The COVID-19 and control variables data were collected from the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University and Global Change Data Labs (GCDL). For market returns, the daily closing prices of each sampled countries' market indexes were collected from the global financial website (www. inves ting. com). A detailed description and source of dependent, independent, and control variables are presented in Table 2 .

To empirically examine the effect of the COVID-19 pandemic on the global financial markets in panel data framework, the study followed the methodology of Aldieri and Vinci (2017), Baker (2016) , Cepoi (2020), and Kuan et al. (2012) and used panel estimated generalized least square (panel-EGLS) and panel quantile regression approach. These methods have several advantages over the other methods used in prior studies.

First, panel data models can have autocorrelation and heteroscedasticity between errors both contemporaneously and over time. In such a situation, it is recommended to use the panel-EGLS method (Mance et al., 2020) . Second, from the panel data framework, the contemporary researches on COVID-19 pandemic and financial markets relationship used either pooled ordinary least square (Albulescu, 2020; Ashraf, 2020; Raifu et al., 2021) , fixed effect (Al-Awadhi et al., 2020; Anh & Gan, 2020), or random effect (Anh & Gan, 2020) . However, these methods only use the central tendency of the data and ignore the view that for a different level of market returns, the effect of the independent variable will be different (Kuan et al., 2012) . Therefore, quantile regression is a non-linear data model (Galvao et al., 2020) and is more successful in finance and economics due to the ability to draw inferences about the data that rank above or below the population conditional mean (Cepoi, 2020). Third, regarding the link between variables, especially for extreme events, the quantile-varying estimates show that ordinary least square methods provide an incomplete picture. While throughout the asset return distributions, quantile regression is more suitable in handling the extreme values and fat tails problems (Du Table 1 Hypotheses with expected signs and source Reproduction rate H3 Negative ( −) (Burdekin & Harrison, 2021; Díaz et al., 2022) New tests H4 Positive ( +) (Anser et al., 2021) Positive rate H5 Negative ( −) (Chatjuthamard et al., 2021; Xu, 2021) Stringency index H6 Negative ( −) (Alexakis et al., 2021; Burdekin & Harrison, 2021; Raifu et al., 2021) Extreme poverty index H7 Negative ( −) (Umar & Nayan, 2018) Life expectancy index H8 Positive ( +) (Umar & Nayan, 2018) Human development index H9 Positive ( +) (Forti et al., 2011; Ranis et al., 2000) Barnes and Hughes (2002) argued that quantile regression also mitigates the problem of non-Gaussian error distribution and sensitivity to outliers. Moreover, most of the developed markets show asymmetric dependencies in COVID-19-related information (Cepoi, 2020). Hence, quantile regression provides a more complete picture of any structure while accounting for asymmetries and nonlinearities (Azimli, 2020) . Finally, a quantile regression also corrects endogenous repressors' biases in panel data (Aldieri & Vinci, 2017) .

Following Ciner (2020), the panel data equations are used to achieve the required objectives as follows.

where Y it is the dependent variable that consists of the stock market returns. These market returns were calculated by taking the logarithmic change of the current closing index price and the previous day's closing price (Anh & Gan, 2020; Ciner, 2020; Haroon & Rizvi, 2020) . Just like Tiberiu (2020), I applied a stepwise procedure for the effect of the COVID-19 pandemic on the global financial markets. In the first step, I implemented a naïve estimation for Eq. (1) at EGLS and quantile regression for 25th, 50th, and 75th quantiles. While in the second step, I included all the control variables in Eq. (2) and estimate them through the EGLS and quantile regression for the same quantiles.

Moreover, to compare the effect of the COVID-19 pandemic on the global financial markets in developed and developing markets, I divided the whole sample into two subsamples based on the markets (i.e., developed and emerging) and re-estimated the Eqs. (1) and (2) for each market separately. Table 3 reports country-wise mean results of the dependent, independent, and control variables. During the study period, the mean return and market volatility for all the markets were positive and negative, respectively. The mean number of COVID-19 new cases and new deaths in all the selected countries were 5544 and 126, respectively. The average number of COVID-19 tests was 89,970 of which 9% were reported positive.

(1) 

For the unit root problem in this study, I used Im et al. (2003) , Levin et al. (2002) , and ADF and PP Fisher chi-square tests proposed by Maddala and Wu (1999) . The results of the four stationarity tests reported in Table 4 reject the null hypothesis of non-stationarity for all the variables. Therefore, it is concluded that all the variables used in this study are stationary at level. Moreover, Table 4 also reports the results of the variance inflation factor (VIF) test. According to Belsley et al. (2005) , the VIF less than 10 indicates no multicollinearity problem. Therefore, based on the VIF results, I concluded that there is no multicollinearity issue in the data. Table 5 indicates the results of Eqs. (1) and (2) for the entire sample based on panel-EGLS and panel quantile regression for 25th, 50th, and 75th quantiles. The panel-EGLS results show a significantly negative relation of COVID-19 new cases with market returns for both the naïve and control models, which confirms H1.

However, COVID-19 new daily death cases, reproduction rate (RR), and positive rate (PR) have no impact on market returns. Moreover, the number of new COVID-19 daily tests conducted has a significantly positive impact on market returns confirming H4.

From quantile regression results, in the naïve model, the coefficient of NC is significantly negative at lower and median quantiles (i.e., 25th and 50th quantiles) with market returns, confirming H1. ND is significantly negative with market returns at lower and median quantiles (H2 confirmed), while positively significant at upper quantile (i.e., 75th quantile), which rejects H2. Further, NT is negatively significant with market returns at all the quantiles, rejecting H4. Moreover, PR and RR are 

Results of the effect of COVID-19 on financial market returns *, **, and *** denote significance at 1%, 5%, and 10%, respectively. t-statistics are reported in parenthesis significantly positive with market returns at lower and median quantiles only, rejecting H3 and H5. The negative relation of NC and ND due to COVID-19 with market returns confirms H1 and H2, respectively. Further, the result of the positive impact of NT on market returns confirms H4. From the control model in quantile regression, the study found almost similar results for the impact of COVID-19 on market returns. Table 6 reports the results of Eqs. (1) and (2) Table 6 reported the results for emerging markets. Likewise developed markets, I found similar results for NC, NT, PR, and RR with market returns. Contrary to developed markets, the coefficients of news announcements of new COVID-19 deaths have a positive impact on emerging markets' returns.

In Table 5 , from the results of panel-EGLS, an adverse impact of COVID-19 new daily cases on market returns is in line with existing studies that predict the negative impact of new cases of COVID-19 on market returns (Al-Awadhi et al., 2020; Anh & Gan, 2020; Ashraf, 2020; Hong et al., 2021) . Similarly, the positive influence of the new daily COVID-19 test conducted on market returns is consistent with the OECD (2020) conclusion that the increasing of COVID-19 daily testing capacity can revitalize the economy and strengthen the health workforce. Likewise, the increasing number of the COVID-19 test will help to reduce new COVID-19 cases (Cirakli et al., 2021) . This leads to reducing the instability in investors' reaction to the COVID-19 pandemic and resultantly causes upward movements in the market. This result is also in line with the findings of Anser et al. (2021) .

From the quantile regression, the positive results of NC, PR, and RR of COVID-19 are in line with the findings of Waheed et al. (2020) , who reported a positive increase in the market index due to the COVID-19 pandemic. Similarly, the negative impact of new deaths due to COVID-19 on market returns is in line with Just and Echaust (2020) , who also found negative relation of new COVID-19 confirmed deaths with the market returns. Further, the result of the positive impact of NT on market returns confirms the findings of OECD (2020). Table 6 reports the results of Eqs. (1) and (2) for developed and emerging markets. In panel A of developed markets, the negative relation of NC with market returns in the naïve model confirms the previous findings of Al-Awadhi et al. (2020) , Anh and Gan (2020) , and Ashraf (2020) . Moreover, the negative relation of PR with market returns in both naïve and control models is consistent with the findings of existing studies (Chatjuthamard et al., 2021; Xu, 2021) . The results of the negative impact of ND on market returns are in line with the results of Just and Echaust (2020) , who documented that the announcement news about new COVID-19 deaths are highly correlated in developed countries and indicates a simultaneous course of events. Similarly, the negative relation of new COVID-19 cases with market returns is supported by the results of Al-Awadhi et al. (2020) and Anh and Gan (2020) . Further, the result of the positive impact of NT on market returns confirms the findings of OECD (2020). The negative impact of the positive rate of COVID-19 infection on market returns is supported by the views of Liu et al. (2020, b) , who argued that the COVID-19 pandemic increases the fear of the investors and creates pessimistic sentiments on future returns. Similarly, this result is also consistent with the findings of Tahat and Ahmed (2020) .

Panel B of Table 6 reported the results for emerging markets. Likewise developed markets, similar results were found for NC, NT, PR, and RR with market returns except for the news announcement of new COVID-19 deaths which has a positive impact on emerging markets' returns. This result is supported by the findings of Hua (2020) , who documented for China that contrary to other financial markets, in response to the spread of COVID-19 at a devastating rate, China's financial market remained more stable. Similarly, for an emerging market, Waheed et al. (2020) reported a positive increase in the Pakistani market index due to the COVID-19 pandemic.

For robustness purposes, almost all relevant estimates in the naïve and control models retain their signs and statistical significance under both the specification of panel-EGLS and quantile regression illustrating in this way their robustness.

The main purpose of the study is to examine the influence of the COVID-19 pandemic on the daily market returns of the 30 most affected developed and emerging economies from January 1, 2020, to December 12, 2020. For this purpose, in the panel data framework, the study employed panel-EGLS and panel quantile regressions techniques. The study confirms that the new confirmed COVID-19 daily cases significantly negative impact on market returns. Similarly, the news announcement Table 6 Results of the effect of COVID-19 on financial market returns of confirmed COVID-19 daily deaths has a significantly negative relationship with market returns. Further, the positive rate of new COVID-19 cases has also negatively influenced market returns. In other words, the COVID-19 pandemic has unsurprisingly negatively affected the global markets. Besides, the number of new COVID-19 daily tests conducted has a positive impact on market returns. Likewise, the study also found similar impacts for both developed and emerging markets except the news announcement of new COVID-19 daily deaths, which have a positive impact on emerging markets' returns. This study presents some policy implications for investors as well as for governments. First, the negative impacts of daily new COVID-19 cases and deaths on market returns suggest that government should adopt early proactive reactions and control measures to protect financial markets from the adverse decline in future pandemics. Second, the positive impact of the increasing number of COVID-19 tests conduction on market returns shows investors' confidence and trust in government reactions to the COVID-19 pandemic. Therefore, governments should increase investors' confidence by enhancing the number of the COVID-19 testing capacity that can help to control and decline the outbreak of the COVID-19 pandemic and to attract more investors in the stock markets. However, it is suggested that this increase in testing capacity may be made through well-developed algorithms rather than an unplanned rise. Third, the impacts of the COVID-19 pandemic on market returns are almost similar for both developed and emerging markets. Therefore, governments and global communities should work together to convey accurate information and implement mutually reinforcing actions in curbing the outbreak of the COVID-19 pandemic, because such actions and information will help the governments to make calm an anxious population, informed choices, and control measures. Lastly, effective public health policies may be implemented in all the countries.

As far as recent researches, this study is original, and it is the first research to examine the influence of the COVID-19 pandemic on the daily market returns of the 30 most affected developed and emerging economies. However, the study has some limitations that need to be addressed by future researchers. First, this study is limited to the top 30 most affected countries, and it is suggested that future studies may consider other demographic, geographical, economic, and social contexts, or even consider other types of larger samples and comparing their differences and similarities would provide more insightful results. Second, this study only considers market returns as dependent variables; other studies would be carried out to contemplate the possibility of using other market variables that may be influenced by the COVID-19 pandemic. Finally, the study did not consider the effect of different waves of the COVID-19 pandemic on the global markets; therefore, it is recommended that future researchers could consider the response of global financial markets in different waves of COVID-19 pandemic.

Author Contribution The author has read and approved the manuscript.

Data used for the analysis in this study are available from on request from the author.

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