Literature DB >> 34170989

Stock markets' reaction to COVID-19: Cases or fatalities?

Badar Nadeem Ashraf1.   

Abstract

In this paper, we examine the stock markets' response to the COVID-19 pandemic. Using daily COVID-19 confirmed cases and deaths and stock market returns data from 64 countries over the period January 22, 2020 to April 17, 2020, we find that stock markets responded negatively to the growth in COVID-19 confirmed cases. That is, stock market returns declined as the number of confirmed cases increased. We further find that stock markets reacted more proactively to the growth in number of confirmed cases as compared to the growth in number of deaths. Our analysis also suggests negative market reaction was strong during early days of confirmed cases and then between 40 and 60 days after the initial confirmed cases. Overall, our results suggest that stock markets quickly respond to COVID-19 pandemic and this response varies over time depending on the stage of outbreak.
© 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  COVID-19; Contagious disease; Coronavirus; Financial markets; Pandemic; SARS-CoV-2; Stock market

Year:  2020        PMID: 34170989      PMCID: PMC7244441          DOI: 10.1016/j.ribaf.2020.101249

Source DB:  PubMed          Journal:  Res Int Bus Finance        ISSN: 0275-5319


Introduction

Since its start from the Chinese city of Wuhan in early 2020, the COVID-19, an infectious disease caused by the new type of coronavirus SARS-CoV-2, is causing havoc around the world. World Health Organization declared it a pandemic on March 11. As of April 17, 2020, the number of confirmed patients has exceeded 2 million with around 139,000 already dead globally (WHO, 2020). Countries such as China, Italy, Iran, Spain, France, the United Kingdom and the United Stated have been hit hard so far with severe COVID-19 outbreaks. It is behaving like ‘the once-in-a-century pathogen’ (Gates, 2020). The pandemic is causing huge impact on real economic activity, though the extent of actual impact is yet unknown. By the end of March 2020, more than 100 countries around the world had already instituted the partial or full lockdowns and air and intercity travel was down by 70–90% as compared to figures from March 2019 in major world cities affecting billions of people (Dunford et al., 2020). Major cultural and supporting events have been suspended. National-level responses to the disease are also unprecedented. On the one hand, governments are taking emergency measures, such as shutdowns for social distancing and investments in testing and quarantining the suspected cases and treating the confirmed cases, to contain the disease. On the other hand, governments, from finance ministries to central banks, are rolling out support and stimulus packages to contain the economic damage. In a recent pioneer study, Goodell (2020) presents a comprehensive literature survey regarding the economic impact of natural disasters, such as nuclear wars, climate change or localized disasters, and highlights that COVID-19 pandemic is inflicting unprecedented global destructive economic damage. He points out that the pandemic may have wide ranging impact on financial sector including stock markets, banking and insurance, and is a promising area for future research. In this backdrop, our main objective in this study is to explore how stock markets across the world are responding to the COVID-19 pandemic. Since the disease has brought extreme uncertainty with respect to how deadly disease really is, whether and when can we get a vaccine, what effects government policies will have, how people will respond, and so on (Wagner, 2020), the reaction of stock market investors is also mixed with unprecedented volatility (Baker et al., 2020). Stock markets are moving up and down with the news of COVID-19 and related control measures or stimulus packages such as direct fiscal support or decrease in interest rates, among others. For instance, US stock market observed three of the 15 worst days ever during March 9–16, while one of the top 10 surges ever in the market also took place in this time period (Wagner, 2020). Other international factors are also causing systematic risk and moving stock markets simultaneously with COVID-19. One such important factor which is having confounding impact on stock market volatility together with COVID-19 is the tussle between Saudi Arabia and Russia over oil supply and prices. On 6th March, Russia refused to comply with the oil supply cut decision made by OPEC summit in Vienna on March 5, 2020. In response, Saudi Arabia made announcements on 8th March regarding price discounts ranging from $6 to $8 per barrel for European and Asian customers and oil production increases. The stalemate is still going on to this day and resulting in additional uncertainty. Using the available daily COVID-19 and stock market returns data from 64 countries over the period from January 22, 2020 to April 17, 2020, we examine the impact of growth in COVID-19 confirmed cases and deaths on the stock market returns after controlling for country characteristics and systematic risk due to international factors. Results of our analyses show that stock markets react strongly with negative returns to growth in confirmed cases, however response to the growth in deaths is not that statistically significant. Our results also show that stock markets react strongly during early days of confirmed cases and then between 40 and 60 days after the initial confirmed cases. This study contributes to the literature in at least two important ways: First, we contribute to the studies which have examined the stock market response to different disasters and crises. For example, Gangopadhyay et al. (2010) examined the stock market reaction and share price behaviour around the hurricane Katrina in 2005. Becchetti and Ciciretti (2011) explored the stock market reaction to the global financial crisis of 2007–2009. Kowalewski and Śpiewanowski (2020) examined how stock market reacted to the mine disasters. We complement these studies by examining the stock market reaction to COVID-19 pandemic. Second, we contribute to the recently emerging literature which examines the impact of COVID-19 on financial markets. In this regard, Baker et al. (2020) used textual analysis of news mentions and found that COVID-19 pandemic has resulted in the highest stock market volatility among all recent infectious diseases including the Spanish Flu of 1918. Alfaro et al. (2020) used data from the US and found that equity market value declined in response to pandemics such as Covid-19 and SARS. Al-Awadhi et al. (2020) employed firm-level data from China and examined the early impact of COVID-19 outbreak on share prices in China. Likewise, Zhang et al. (2020) found that COVID-19 has led to increase in global financial market risk. Extending this debate, we examine how stock market returns have responded to COVID-19 using data of major stock indexes from 64 countries. The rest of the paper proceeds as follows: Section 2 outlines our sample construction procedures. Section 3 presents the empirical methodology briefly. Section 4 reports the results of empirical analyses. Final section concludes the study.

Sample construction

We started our sample construction by collecting the data of the number of confirmed cases and deaths from COVID-19 from the website of John Hopkins University (JHU)’ Coronavirus Resource Centre. This data is available on a daily frequency for more than 200 countries and regions, which have been affected by the disease till the day we downloaded data. Data starts from January 22, 2020 and ends at April 17, 2020. Next, we downloaded daily stock market return data from the www.investing.com website over the same period. We included all those countries for which the stock market data was available on the website. To get a consistent sample across countries, we used the data of only one major stock market index from each country. In the next step, we appended the daily COVID-19 data with daily stock market return data. Lastly, we collected data of country-level control variables and added with the daily data. We applied several filters to refine the data. We dropped data of those countries for which the data of daily stock market returns or country-level control variables was not available. We left with the data of 64 countries after applying this filter. Next, from the remaining data, we dropped observations with missing values because although COVID-19 data is available for each day since a country observed first confirmed case, the stock markets data is not available for weekends or national gazetted holidays. After applying the second filter, our final dataset is from 64 countries with 2424 observations over the period from January 22, 2020 to April 17, 2020. Table 1 lists the countries, the stock market index (the data of which was used for a country) and the number of daily data observations from each country. Besides, it also mentions the date when first COVID-19 case was confirmed in a country. The data for any specific country in sample starts from this date.
Table 1

Sample information. This table reports the countries, the stock market index the data of which was used for a country, the date when first COVID-19 case was confirmed in a country and the number of data observations from each country.

CountryStock indexThe day when 1st COVID-19 case was confirmedObservations
ArgentinaS&P MervalMar 03, 202026
AustraliaS&P_ASX 200Jan 26, 202057
AustriaATXFeb 25, 202035
BangladeshDSE 30Mar 08, 202012
BelgiumBEL 20Feb 04, 202050
BrazilBovespaFeb 26, 202034
BulgariaBSE SOFIXMar 08, 202026
CanadaS&P_TSX CompositeJan 26, 202056
ChileS&P CLX IPSAMar 03, 202030
ChinaShanghai CompositeJan 22, 2020a54
ColombiaCOLCAPMar 06, 202026
CroatiaCROBEXFeb 25, 202034
DenmarkOMX Copenhagen 20Feb 27, 202032
EcuadorGuayaquil SelectMar 01, 202031
EgyptEGX 70 EWIFeb 14, 202044
FranceCAC 40Jan 24, 202058
GermanyDAXJan 27, 202056
GreeceAthens General CompositeFeb 26, 202031
HungaryBudapest SEMar 04, 202028
IcelandICEX MainFeb 28, 202032
IndiaBSE Sensex 30Jan 30, 202050
IndonesiaJakarta SECMar 02, 202031
IrelandISEQ OverallFeb 29, 202033
IsraelTA 35Feb 21, 202034
ItalyFTSE MIBJan 31, 202053
JamaicaJSE MarketMar 11, 202020
JapanNikkei 225Jan 22, 202058
KenyaNSE 20Mar 13, 202022
Korea, SouthKOSPJan 22, 202058
LebanonBLOM StockFeb 21, 202034
MalaysiaFTSE KLCIJan 25, 202059
MaltaMSEMar 07, 202024
MexicoS&P_BMV IPCFeb 28, 202031
MoroccoMoroccan All SharesMar 02, 202033
NamibiaFTSE NSX OverallMar 14, 202021
NetherlandsAEXFeb 27, 202033
New ZealandNZX 50Feb 28, 202040
NigeriaNSE 30Feb 28, 202033
NorwayOSE BenchmarkFeb 26, 202033
PakistanKarachi 100Feb 26, 202035
PeruS&P Lima GeneralMar 06, 202027
PhilippinesPSEi CompositeJan 30, 202051
PolandWIG 30Mar 04, 202029
PortugalPSI 20Mar 02, 202031
RomaniaBETFeb 26, 202034
RussiaMOEXJan 31, 202053
Saudi ArabiaTadawul All ShareMar 02, 202032
SerbiaBelex 15Mar 06, 202029
SingaporeFTSE Straits Times SingaporeJan 23, 202060
SloveniaBlue-Chip SBITOPMar 05, 202027
South AfricaTOP 40Mar 05, 202028
SpainIBEX 35Feb 01, 202053
Sri LankaCSE All-ShareJan 27, 202031
SwedenOMX Stockholm 30Jan 31, 202053
SwitzerlandSMIFeb 25, 202035
TanzaniaAll ShareMar 16, 202019
ThailandSET IndexJan 22, 202059
TurkeyBIST 100Mar 11, 202026
UkrainePFTSMar 03, 202021
United Arab EmiratesADX GeneralJan 29, 202054
United KingdomFTSE 100Jan 31, 202053
United StatesS & P 500Jan 22, 202059
VietnamVNJan 23, 202056
ZambiaLSE All ShareMar 18, 202017
Total2424

We start sample from the day the issue caught public eye and databases started reporting information, although China had cases well before Jan 22, 2020.

Sample information. This table reports the countries, the stock market index the data of which was used for a country, the date when first COVID-19 case was confirmed in a country and the number of data observations from each country. We start sample from the day the issue caught public eye and databases started reporting information, although China had cases well before Jan 22, 2020.

Methodology

To examine the impact of change in COVID-19 confirmed cases/deaths on stock market returns, we prefer panel data analysis technique over the classical event study methodology due to several reasons: First, the spread of COVID-19 evolves over a matter of days in a country and is not a one point of time event. Second, panel data regression is better in capturing the time varying relationship between dependent and independent variables (Ashraf, 2017). Third, panel data analysis extracts both cross-sectional and time series variation from the underlying panel data and minimizes the problems such as multicollinearity, heteroscedasticty and estimation bias (Baltagi, 2008; Woolridge, 2010). Primarily, we specify following model.Here, c and t subscripts represent country and day, respectively. α is a constant term. Dependent variable, Y, represents total stock market returns in county c on day t. Stock market return is measured as the daily change in major stock market index of a country. COVID-19 represents (1) the daily growth in COVID-19 confirm patients and (2) the daily growth in the number of deaths of COVID-19 patients. is a vector of country-level control variables including uncertainty avoidance, democratic accountability, investment freedom and log (gross domestic product). Democratic accountability variable is taken from International Country Risk Guide (ICRG) database and represents the quality of political institutions. Uncertainty avoidance index is taken from the Hofstede et al. (2010)’s framework of national culture and measures the cross-country differences in the level of uncertainty aversion in investors. Investment freedom variable measures the stock market liberalization, the data of which is collected from Heritage Foundation database of economic freedom (Heritage_Foundation, 2020). Log (GDP) is taken from World Development Indicators (WDI) of World Bank and measures the level of economic development. Together these variables control for the cross-country variation in stock market returns due to institutional and macroeconomic differences across countries. D is a set of daily fixed-effects dummy variables to control for daily international events which move all stock markets. These dummy variables effectively control for systematic risk due to international factors. Ɛ is an error term. We use heteroskedastic-robust standard errors to estimate p-values in regressions.

Empirical analysis

In this section, we present the results of our empirical analysis. Table 2 reports summary statistics of the main variables. The mean value of stock market returns is −0.00 which shows that on average sample countries experienced zero percent return in stock markets. Minimum and maximum values of −0.11 and 0.08, respectively, show that stock indexes swung between negative 11 percent and positive 8 percent. Likewise, the average daily growth in COVID-19 confirmed cases is 18 percent with a wide standard deviation of 37 percent. Following the similar trend, the average daily growth in deaths is 19 percent with a standard deviation of 33 percent. The number of observations for the growth in deaths variable (i.e., 1390) is lower than the number of observations for the growth in confirmed cases (i.e., 2424) because of the time lag between initial COVID-19 infections and the ultimate first death of any of the infected patient.
Table 2

Summary statistics. This table reports the summary statistics of main variables. Stock market returns is measured as the daily change in major stock index of a country. Growth in confirmed cases is measured as the daily growth in COVID-19 confirmed cases in a country. Growth in deaths is measured as the daily growth in the number of COVID-19 patients died. Democratic accountability is taken from International Country Risk Guide database and represents the quality of political institutions. Uncertainty avoidance index is taken from Hofstede et al. (2010) and controls for cross-country differences in the level of uncertainty aversion in investors. Investment freedom is taken from Freedom House website and controls for stock market liberalization. Log (GDP) is taken for World Development Indicators (WDI) of World Bank and controls for the level of economic development.

VariableObservationsMeanStandard deviationMinimum valueMaximum value
Stock market returns2424−0.000.03−0.110.08
Growth in confirmed cases24240.180.370.007.00
Growth in deaths13900.190.330.005.00
Democratic accountability24244.751.451.506.00
Uncertainty avoidance242463.4123.728.00100.00
Investment freedom242465.7419.4720.0090.00
Log (GDP)242426.921.5323.2730.60
Summary statistics. This table reports the summary statistics of main variables. Stock market returns is measured as the daily change in major stock index of a country. Growth in confirmed cases is measured as the daily growth in COVID-19 confirmed cases in a country. Growth in deaths is measured as the daily growth in the number of COVID-19 patients died. Democratic accountability is taken from International Country Risk Guide database and represents the quality of political institutions. Uncertainty avoidance index is taken from Hofstede et al. (2010) and controls for cross-country differences in the level of uncertainty aversion in investors. Investment freedom is taken from Freedom House website and controls for stock market liberalization. Log (GDP) is taken for World Development Indicators (WDI) of World Bank and controls for the level of economic development. Table 3 reports the Pearson correlations between main variables. Daily growth in COVID-19 confirmed cases has a strong negative correlation with stock market returns.
Table 3

Correlations matrix. This table reports the pairwise Pearson correlations between main variables. Stock market returns is measured as the daily change in major stock index of a country. Growth in confirmed cases is measured as the daily growth in COVID-19 confirmed cases in a country. Growth in deaths is measured as the daily growth in the number of COVID-19 patients died. Democratic accountability is taken from International Country Risk Guide database and represents the quality of political institutions. Uncertainty avoidance index is taken from Hofstede et al. (2010) and controls for cross-country differences in the level of uncertainty aversion in investors. Investment freedom is taken from Freedom House website and controls for stock market liberalization. Log (GDP) is taken for World Development Indicators (WDI) of World Bank and controls for the level of economic development.

Variables(1)(2)(3)(4)(5)(6)(7)
(1)Stock market returns1.00
(2)Growth in confirmed cases−0.15*1.00
(3)Growth in deaths−0.05*0.32*1.00
(4)Democratic accountability−0.010.09*0.07*1.00
(5)Uncertainty avoidance−0.020.05*0.040.16*1.00
(6)Investment freedom−0.010.07*0.08*0.68*0.011.00
(7)Log (GDP)0.01−0.04*0.06*0.07*−0.04*−0.011.00

*Indicates significance level at 10% level.

Correlations matrix. This table reports the pairwise Pearson correlations between main variables. Stock market returns is measured as the daily change in major stock index of a country. Growth in confirmed cases is measured as the daily growth in COVID-19 confirmed cases in a country. Growth in deaths is measured as the daily growth in the number of COVID-19 patients died. Democratic accountability is taken from International Country Risk Guide database and represents the quality of political institutions. Uncertainty avoidance index is taken from Hofstede et al. (2010) and controls for cross-country differences in the level of uncertainty aversion in investors. Investment freedom is taken from Freedom House website and controls for stock market liberalization. Log (GDP) is taken for World Development Indicators (WDI) of World Bank and controls for the level of economic development. *Indicates significance level at 10% level. Table 4 reports the results when we estimate Eq. (1) with panel pooled OLS (i.e. ordinary least squares) regression technique. As shown, growth in confirmed cases variable enters negative and strongly significant in Model 1 suggesting that stock markets respond negatively to the growth in COVID-19 confirmed cases. The results of growth in confirmed cases variable remain similar when we add country-level control variables in Model 2 and daily fixed-effects dummy variables in Model 3.
Table 4

Impact of COVID-19 on stock market returns. This table reports the results of panel pooled ordinary least squares regression results regarding the impact of COVID-19 on stock market returns. Stock market returns is dependent variable in all models and is measured as the daily change in major stock index of a country. Growth in confirmed cases is measured as the daily growth in COVID-19 confirmed cases in a country. Growth in deaths is measured as the daily growth in the number of COVID-19 patients died. Democratic accountability is taken from International Country Risk Guide database and represents the quality of political institutions. Uncertainty avoidance index is taken from Hofstede et al. (2010) and controls for cross-country differences in the level of uncertainty aversion in investors. Investment freedom is taken from Freedom House website and controls for stock market liberalization. Log (GDP) is taken for World Development Indicators (WDI) of World Bank and controls for the level of economic development. The heteroskedasticity robust standard errors are used in estimations. P-values are given in parenthesis.

VariablesStock market returns
(1)(2)(3)(4)(5)(6)
Growth in confirmed cases−0.013***−0.013***−0.003**
(0.000)(0.000)(0.032)
Growth in deaths−0.005*−0.005*−0.001
(0.060)(0.074)(0.526)
Democratic accountability0.0000.000−0.000−0.000
(0.922)(0.834)(0.673)(0.944)
Uncertainty avoidance−0.000−0.0000.0000.000
(0.576)(0.639)(0.806)(0.917)
Investment freedom0.000−0.0000.0000.000
(0.936)(0.596)(0.671)(0.747)
Log (GDP)0.0000.000−0.001*0.001
(0.957)(0.367)(0.099)(0.225)
(0.879)(0.002)
Daily fixed-effects dummy variablesYesYes
(0.047)(0.000)
Constant−0.001*−0.001−0.0100.002**0.027−0.093***
(0.062)(0.899)(0.540)(0.032)(0.103)(0.001)
Observations242424242424139013901390
R-squared0.0220.0220.5220.0030.0050.511

***,**,*Represent statistical significance at 1%, 5%, and 10% levels, respectively.

Impact of COVID-19 on stock market returns. This table reports the results of panel pooled ordinary least squares regression results regarding the impact of COVID-19 on stock market returns. Stock market returns is dependent variable in all models and is measured as the daily change in major stock index of a country. Growth in confirmed cases is measured as the daily growth in COVID-19 confirmed cases in a country. Growth in deaths is measured as the daily growth in the number of COVID-19 patients died. Democratic accountability is taken from International Country Risk Guide database and represents the quality of political institutions. Uncertainty avoidance index is taken from Hofstede et al. (2010) and controls for cross-country differences in the level of uncertainty aversion in investors. Investment freedom is taken from Freedom House website and controls for stock market liberalization. Log (GDP) is taken for World Development Indicators (WDI) of World Bank and controls for the level of economic development. The heteroskedasticity robust standard errors are used in estimations. P-values are given in parenthesis. ***,**,*Represent statistical significance at 1%, 5%, and 10% levels, respectively. The growth in deaths variable also enters negative (Models 4 and 5), however it loses significance when we add daily fixed-effects dummy variables to control for systematic risk due to international factors (Model 6). These results show that stock market response to the number of deaths is not strong. Together these results suggest stock markets respond negatively and overwhelmingly to the growth in the number of confirmed cases while response to the number of deaths is not strong. This is not beyond expectation. Since death is an outcome of a confirmed case and usually occurs several days after one gets COVID-19 infection confirmation, sophisticated stock market investors price in the expected negative impact of COVID-19 early on from the growth in confirmed cases. We perform several robustness tests to further confirm above main results: First, we re-estimate all specifications of Table 4 with panel random-effects regression method. In unreported results1 , we observe that all results are quite similar to that in Table 3. Second, to further confirm that our results are not driven by omitted variables in a cross-country setting, we re-estimate Eq. (1) by including country fixed-effects dummy variables instead of country-level control variables. As shown in Table 5 , growth in confirmed cases enters negative and significant while growth in deaths enters insignificant. These results are qualitatively similar to those reported in Table 4 and confirm that our main results are not biased due to omitted variables.
Table 5

Impact of COVID-19 on stock market returns: robustness tests. This table reports the results of robustness tests regarding the impact of COVID-19 on stock market returns after including country fixed-effect dummy variables in main model. Stock market returns is dependent variable in all models and is measured as the daily change in major stock index of a country. Growth in confirmed cases is measured as the daily growth in COVID-19 confirmed cases in a country. Growth in deaths is measured as the daily growth in the number of COVID-19 patients died. The results are estimated with pooled OLS estimator using heteroskedasticity robust standard errors. P-values are given in parenthesis.

VariablesStock market returns
(1)(2)
Growth in confirmed cases−0.003**
(0.041)
Growth in deaths−0.001
(0.579)
Country fixed-effects dummy variablesYesYes
Daily fixed-effects dummy variablesYesYes
Constant−0.001−0.075***
(0.925)(0.002)
Observations24241390
R-squared0.5280.520

***,**,*Represent statistical significance at 1%, 5%, and 10% levels, respectively.

Impact of COVID-19 on stock market returns: robustness tests. This table reports the results of robustness tests regarding the impact of COVID-19 on stock market returns after including country fixed-effect dummy variables in main model. Stock market returns is dependent variable in all models and is measured as the daily change in major stock index of a country. Growth in confirmed cases is measured as the daily growth in COVID-19 confirmed cases in a country. Growth in deaths is measured as the daily growth in the number of COVID-19 patients died. The results are estimated with pooled OLS estimator using heteroskedasticity robust standard errors. P-values are given in parenthesis. ***,**,*Represent statistical significance at 1%, 5%, and 10% levels, respectively. To get further insights into the specific market reaction over the days as COVID-19 situation evolves across countries, we calculate daily average stock market returns of all stock indexes over the same timeline from the 1st confirmed case of COVID-19. As shown in Fig. 1 , on average, stock market returns go into negative range in first few days (around first 20 days) when first case is confirmed. Then market returns again move into negative range from 40 to 60 days. As COVID-19 takes some time from the first case to result into worst outbreak situation if proper control and containment measures have not been used, this later reaction shows markets again react with negative sentiments to the large number of confirmed cases. This is consistent with the outbreaks in China, Italy, Iran and Spain which reached to their peaks around 30–60 days from initial confirmed cases.
Fig. 1

Stock market returns against the number of days from the date first COVID-19 case was confirmed in a country.

Stock market returns against the number of days from the date first COVID-19 case was confirmed in a country.

Conclusion

In this paper, we examine the stock market response to the COVID-19 pandemic. Using daily COVID-19 confirmed cases and deaths and stock market returns data from 64 countries, we find that stock markets respond negatively to the increase in COVID-19 confirmed cases. That is, stock market returns decline as the number of confirmed cases increase in a country. We further find that stock market response to the growth in number of deaths due to the COVID-19 is weak. Together our findings suggest that stock markets price in COVID-19 pandemic related risks in stock prices early on when the number of confirmed cases increases and react less when some of the confirmed cases die later on. In more detailed analysis, we also observe that stock markets react strongly during early days of confirmed cases and then between 40 and 60 days after the day of initial confirmed cases. Overall, our analysis suggests that stock markets quickly respond to COVID-19 pandemic and this response varies over time depending on the severity of outbreak.

Author statement

Badar Nadeem Ashraf carried out this research.
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