International Journal of Business and Economy (IJBEC) eISSN: 2682-8359 [Vol. 4 No. 1 March 2022]
Journal website: http://myjms.mohe.gov.my/index.php/ijbec
THE EFFECT OF COVID–19 PANDEMICS AND
VACCINATION TOWARDS MALAYSIA STOCK MARKET
Norhasniza Mohd Hasan Abdullah1*, Nur’ Asyiqin Ramdhan2, Nur Liyana Mohamed Yousop3, Shashazrina Roslan4, Zuraidah Ahmad5 and Zuraidah Sipon6
1 3 4 5 6 Fakulti Pengurusan Perniagaan, Universiti Teknologi MARA, Segamat, MALAYSIA
2 Fakulti Pengurusan Perniagaan, Universiti Teknologi MARA, Puncak Alam, MALAYSIA
*Corresponding author: [email protected]
Article Information:
Article history:
Received date : 16 March 2022 Revised date : 19 March 2022 Accepted date : 22 March 2022 Published date : 30 March 2022
To cite this document:
Mohd Hasan Abdullah, N., Ramdhan, N. AMohamed Yousop, N. L., Roslan, S., Ahmad, Z., &Sipon, Z. (2022).
THE EFFECT OF COVID–19 PANDEMICS AND VACCINATION TOWARDS MALAYSIA STOCK MARKET. International Journal of Business and Economy, 4(1), 229-238.
Abstract: World Health Organization (WHO) defines coronavirus disease 2019 (Covid – 19) as an infectious disease caused by a novel coronavirus called severe acute respiratory syndrome coronavirus 2 (SARS-CoV- 2). The latest financial report shows that the Covid – pandemics are severely disrupting the economy and financial markets globally, which includes Malaysia.
Thus, this paper intends to investigate the impact of Covid – 19 pandemics and immunization on the Malaysia stock market over the period from February 28, 2021, to August 31, 2021. The study employs Kuala Lumpur Composite Index (KLCI) as a dependent variable while the number of Covid – 19 confirmed cases, patients recovered from Covid -19, patient death due to Covid – 19, and fully vaccinated people used as independent variables. The results from Ordinary Least Square (OLS) regression showed that Covid – 19 confirmed cases adversely affect the performance of the KLCI index. However, the returns of KLCI increased as the numbers of recovered patients and fully vaccinated people increased.
Keywords: Covid – 19, stock index, recovered cases, death cases, vaccinated people.
1. Introduction
World Health Organization (WHO) defines coronavirus disease 2019 (Covid – 19) as an infectious disease caused by a novel coronavirus called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). WHO temporarily termed the virus as 2019 novel coronavirus (2019-nCoV) on 12 January 2020 and then officially named this infectious disease as coronavirus disease 2019 (Covid -19) on 12 February 2020.
The first case of Covid – 19 was detected in Wuhan City, Hubei Province, China on December 31, 2019. On January 30, 2020, the WHO declared the Covid - 19 outbreak as a global health emergency since 7,818 confirmed cases were reported in 19 countries including China.
However, due to the virus spreading worldwide rapidly, the WHO finally assessed that Covid – 19 can be characterized as the fifth pandemic after the 1918 flu pandemic.
The threat of Covid - 19 became increasingly apparent in Malaysia when their neighbour Singapore reported its first positive case on January 23, 2020. This was an imported case from Wuhan China. From this first case, eight close contacts were identified as being in Johor, Malaysia. While Malaysia reported its first positive case on January 25, 2020. It is also an imported case from Wuhan, China. A total of eight positive cases were reported within six days after starting the first case. As of August 31, 2021, the total confirmed cases of Covid - 19 in Malaysia stand at 1,746,254 cases; with about 1,461,727 recoveries and 16,664 deaths recorded. While statistics showed that the total global confirmed cases of Covid – 19 were 218,562,390 while the global death toll was 4,537,815.
The pandemic of the Covid – 19 not only threatens individuals' lives and wellbeing but also has significant economically costly pandemics in recent history. The synchronously of worldwide lockdowns and financial market trauma make the Covid – 19 pandemics vary from the previous pandemic episodes. As a result, the economy suddenly stops, and because of that Covid – 19 global recession is distinctive (Boissay & Rungcharoenkitkul, 2020). Besides that, according to Ozili (2020) and Tashanova et al. (2020) Covid-19 pandemic not only forced the shutdown of commercial activities, but many companies also suffered liquidity shortage since it affects investors' investment decisions due to uncertainty on the cases of Covid – 19.
Nevertheless, on December 2, 2020, the United Kingdom's Medicines and Healthcare products Regulatory Agency (MHRA) gave temporary regulatory approval for the Pfizer–BioNTech Covid vaccine. While, on February 24, 2021, Malaysia starts its Covid-19 vaccination program, with Muhyiddin Yassin as an eighth Prime Minister as a first-person taking the jab. Currently, Malaysia approved seven types of vaccines to prevent Covid disease by triggering an immune response. As of August 31, 15,032,301 or 47 percent of Malaysia's population fully vaccinated against Covid-19. According to former Health Minister Adham Baba, to achieve the government's target of having 80% of the adult population fully vaccinated against Covid-19 to attain herd immunity, Malaysia has ordered sufficient vaccines to cover 109 percent of its population who qualify for vaccination. Malaysia's government aims to achieve herd immunity by December 2021. Khalfaoui, Nammouri, Labidi, & Ben Jabeur (2021) and Rouatbi, Demir, Kizys, & Zaremba (2021) are the earliest groups of researchers who did a study on the effect of vaccination programs on the stock market. Both of them can provide evidence that the Covid-19 vaccination helps in stabilizing the equity market. They found that mass vaccination significantly lessens the stock market volatility and give a positive effect on stock return.
2. Literature Review
This section reviews the related literature that discussed the impacts of the Covid-19 outbreak.
The figure of Covid – 19 cases has increased rapidly in each country. Therefore, in the purpose to prevent the disease, most countries around the world have implemented several drastic procedures, for instance, enforcing social distancing, restricting their residents from traveling, a ban on gathering, and shut down their business activities (Bahrini and Filfilan, 2020; Toda, 2020). According to Nicola et al. (2020), there are more than a hundred countries around the world had already undertaken several lockdown controls by the end of March 2020. Malaysia also had in forced its first movement control order on March 18, 2020. The lockdown restrictions have given a negative impact on social and economic activities. Besides that, the global supply chain was also affected by the Covid – 19 outbreaks, thus it had disrupted the global economy system (OECD, 2020).
According to Baldwin and Mauro (2020), the economic system was facing three shocks caused by Covid - 19 outbreak. First, household expenditure will be decreased because of unpaid leave and jobless during the pandemic period. Second, the lower aggregate demand tends to disturb the export and import business. Lastly, the "wait and see" approach by individuals and businesses in facing the outbreak was given an effect on manufacturing industries since they had rescheduled their order.
In addition, the study carried out by Boissay and Ruhgcharoenkitkku (2020) states that the pandemic of the Covid – 19 not only threatens individuals' lives and wellbeing but also has significant economically costly pandemics in present history. Covid – 19 pandemics is varying from previous pandemic episodes since it causes worldwide lockdowns and financial market trauma synchronously. As a result, the economy suddenly stops, and because of that Covid – 19 global recession is distinctive.
A study conducted by Albulesco (2020) observed the effects of China's stock market for the 40 days after the global monitoring of Covid-19 commenced. The researcher found that the number of Covid-19 cases reported in China had a negative relationship with stock market volatility but, the number of Covid-19 cases reported outside China tended to shoot up the stock market volatility. However, the results show a positive relationship between financial market volatility and the death ratio inside and outside China. However, contradicting results were found by Sansa (2020) who reported that there is a positive relationship between China's stock indices and the number of Covid – 19 cases.
Meanwhile, Zhou, Wu, Liu, Gao, & Gao (2020) also studied China's market but on several industries found that the number of Covid -19 cases give a positive effect on the healthcare industry. However, the other industries like tourism, transportation, and construction received a negative effect. Nevertheless, Ruiz Estrada, Park, & Lee (2020) do similar research but on four industries (utilities, trading, airlines, and tourism) only. Their results show that trading, airlines, and tourism were badly affected by Covid – 19 cases. The utility industry was not affected since the lockdown and medical services boost the usage of electricity and consequently increased the index of the electricity sector.
Zaren and Hizarci (2020) had employed the daily data of the total number of Covid-19 cases, the total deaths caused by Covid-19, and the stock markets from January 2020 to March 2020 to examine the impacts of Covid-19 on several stock markets. The results show that the stock market in China, Korea, and Spain have a relationship with a total number of Covid-19 cases, on the other hand, the stock market in France, Germany, and Italy fail to show any relationship with the Covid-19 cases.
Research by using an event study methodology conducted by Liu, Manzoor, Wang, Zhang, &
Manzoor (2020) showed a drop in abnormal return of the stock indices due to investors' pessimistic sentiment. They also reported that the abnormal return of Asian stock markets tended to fall more as compared to other indices during the Covid – 19 outbreaks.
Besides that, Kelvin Yong-Ming Lee, Mohamad Jais, and Chia-Wen Chan (2020) regressed daily data of the number of Covid – 19 cases and the number of deaths due to Covid – 19 in Malaysia, China, and the USA, the volatility index, and the Brent oil price. The study covered from December 31, 2019, to April 18, 2020. They found that the number of Covid – 19 cases give a negative effect on the Malaysian sectorial indices except for the Plantation sector.
Khalfaoui, Nammouri, Labidi, & Ben Jabeur (2021) are the first group of researchers does the study the effect of Covid vaccination on the stock price. They scrutinize four daily sets of data;
namely S&P stock market return as a dependent variable and Covid -19 daily confirmed number of infections, deaths, and vaccinations as independent variables. Their research covers from December 20, 2020, to April 9, 2021. They found that all the variables significantly positively influence the S&P 500. Therefore, they suggest the US government continue with their vaccination plan since it is beneficial for fighting the Covid – 19 pandemics.
The result is supported by a study conducted by Rouatbi, Demir, Kizys, & Zaremba (2021).
The researcher employs data from 66 markets around the world for the period of January 1, 2020, to April 30, 2021, to investigate the effect of vaccination on stock market volatility. By using panel regression their reported that vaccinations aid to lessen market volatility in both emerging and developed markets. They conclude that government health targets to achieve herd immunity within society via vaccinations are encouraging to stabilize the stock market.
2.1 Problem Statement
Currently, the main gap in the existing research is the absence of a comprehensive view on the role of mass Covid-19 vaccination in a Malaysian stock market. Besides that, the pandemic of Covid – 19 give the most significant effect on the stock market as compared to any earlier infectious disease outbreak (Baker et al., 2020). Therefore, the objective of this study is to analyze the effect of the health crisis Covid -19 and the vaccination program on the Malaysian equity market after almost two years the virus attacked. This research contributes to two prime strains of the finance literature. First, this research explores the role of vaccination programs on the Malaysian stock market. Second, this paper adds to the research on the impact of the Covid-19 pandemic on the volatile financial markets. This paper also includes the number of recovered cases from Covid - 19 as one of the variables since there are several times the number of recovered cases shows a higher number as compared to the number of Covid cases. Thus, it triggers a question does the recovered cases will give an impact on a stock index or not.
3. Method 3.1 Samples
This section discusses the data and methodologies applied in this paper. Malaysia starts its vaccination program on February 24, 2021. However, the fully vaccinating individuals are just available four days after that. Therefore, to examine the impact of vaccination and Covid – 19 cases on the Malaysian stock market, this study will employ the daily data of the period February 28, 2021, to August 31, 2021. The data on stock market indices were collected from Yahoo Finance Database (2021) while the data on Covid – 19 were extracted from Worldometer Statistics (2021).
The independent variables used in this study were the number of Covid - 19 confirmed cases, the number of deaths due to Covid – 19, the number of recoveries from Covid – 19, and the number of people fully vaccinating. Whereas, Kuala Lumpur Composite Index (KLCI) will be used as a dependent variable.
3.3 Data Analysis
Three analyses will be conducted in this study after the data collection process is completed.
The analysis begins with descriptive analysis to study the characteristics of variables. Then, followed by correlation analysis to determine the correlation among the variables. Lastly, this study applied the Ordinary Least Square (OLS) regression analysis to investigate the impacts of Covid - 19 disease on the Malaysian stock market. The regression models to be tested in this study were:
SIt = α + β1C19t + β2DEAt + β3RECt + β4VACt (1) SIt = α + β1C19t-1 + β2DEAt-1 + β3RECt-1 + β4VACt-1 (2)
Where SIt is the Kuala Lumpur Composite Index (KLCI) at the day t; C19t is the number of Covid – 19 confirmed cases in Malaysia at day t; DEAt is the number of death cases due to Covid – 19 in Malaysia at day t; RECt is the number of recovered cases from Covid – 19 in Malaysia at day t; VACt is the number of people fully vaccinating in Malaysia at day t. The sign of t-1 refers to the day before day t.
Equation (1) applies to Model 1, in which the KLCI is used as the dependent variable. While Equation (2) is generated because this paper also aims to observe the impact of previous day information on the Malaysia stock indices. Thus, the lagged independent variables will be used to estimate the KLCI.
4. Results and Discussion
This section discusses the results obtained from data and the statistical process. Figure 1 presents a descriptive statistic for all variables used in this study. A standard deviation is calculated to determine the dispersion or fluctuation of a dataset to its mean. Vaccinated people show a highest standard deviation of 4,093,738.50, followed by Covid -19 cases (6,850.22), recovered from Covid -19 cases (5,754.49), death cases due to Covid – 19 and the last one is KLCI (39.65). Thus, this result shows that KLCI is less volatile as compared to other variables.
The maximum value of KLCI is stood at 1,639.83 while the minimum value is 1,489.80.
Whereas, the range numbers of vaccinated people are between 3 and 15,032,301. On average,
Malaysian daily Covid – 19 cases are 7,826.70. However, 82.29 percent (6,440.86) patients are recovered while only 1.07 percent (84.02) patients die. The highest numbers of death cases are 393 and the highest number of Covid – 19 cases are 24,599.
KLCI C19 Cases Death Cases due to C19
Recovered from C19
Vaccinated People
Mean 1,568.66 7,826.70 84.02 6,440.86 3,067,100.18
Median 1,581.37 5,671.00 60.00 4,797.00 1,087,352.00
Mode 1,582.52 941 5 1,247 46
Minimum 1,489.80 941 0 1,052 3
Maximum 1,639.83 24,599 393 22,657 15,032,301
Standard
Deviation 39.65 6,850.22 92.894 5,754.49 4,093,738.50
Skewness -.516 .988 1.32 1.33 1.58
Kurtosis -.984 -.378 1.00 .683 1.36
Figure 1: Descriptive Statistics
Figure 2 presents the outcomes of correlation analysis. The outcome shows that each variable has a significant correlation with other variables. The three strongest correlations were found between the vaccinated people and recovered cases with a correlation of 0.964, followed by the recovered cases and Covid – 19 cases (0.957), and Covid – 19 cases and vaccinated people (0.949). Besides that, the results also reveal that all the independent variables a negatively correlated with the dependent variable. The most independent variable that correlated with KLCI as a dependent variable is death cases with a correlation of 0.659, followed by recovered cases (0.628), vaccinated cases (0.614), and lastly is Covid – 19 cases (0.747).
KLCI C19 Cases Death Cases due to C19
Recovered from C19
Vaccinated People
KLCI 1 -.747
(0.000)
-.659 (0.000)
-.628 (0.000)
-.614 (0.000)
C19 Cases 1 .910
(0.000)
.957 (0.000)
.949 (0.000) Death Cases due to
C19 1 .905
(0.000)
.895 (0.000) Recovered from
C19 1 .964
(0.000)
Vaccinated People 1
Figure 2: Correlation Analysis
Figure 3 presents the results of the regression analysis. The F – tests, measure for the strength of the regression, reveal that both models are significant at five percent (p-value = 0.000).
Therefore, it can be concluded that all variables are vital in determining a Malaysia Stock Index. In terms of the coefficient of variation (R – Square), the second model is slightly better in explaining the variation of KLCI. The explanatory power for Model 2 is 67.4 percent whereas for Model 1 is 67 percent. This indicates that the variation of the dependent variable is explained by more than 65 percent of the independent variables.
The T-tests show that all variables give similar results for both models. All the variables except death cases were significantly related to Malaysia Composite Index. It discloses that either the current information or the previous day information will influence the performance of KLCI.
The number of Covid – 19 confirmed cases in Malaysia, on the same day or earlier day, had a significant negative effect on KLCI. On the other hand, either the same day or the earlier day, the number of recovered cases and the number of vaccinated people in Malaysia were positively and significantly influencing KLCI. This indicates that a worsening outbreak of Covid – 19 tend to decrease the performance of KLCI whereas the increasing number of recovered cases and immunization program will help to incline the KLCI performance. This empirical result confirms that the Malaysian stock market is also disrupted by Covid -19 cases.
The uncertainty about the Covid -19 cases influences investors' decisions in entering the stock market. These findings are supported by Al-Awadhi, Alsaifi, Al-Awadhi, & Alhammadi (2020), Harjoto, Rossi, & Paglia (2020) and Liu, Manzoor, Wang, Zhang, & Manzoor (2020).
All of them provide evidence of a significant negative effect on stock returns. They also agreed that the pandemic has led to excessive risk and uncertainty in the global financial market.
On the other hand, the positive and significant effect of the vaccine shows that the immunization program is not only beneficial in protecting people against disease but also gives some confidence for the investors to trade back. Malaysia had launched its immunization program in February 2021 to curb and end the Covid – 19 pandemics. A similar result was found by Khalfaoui, Nammouri, Labidi, & Ben Jabeur (2021) and Rouatbi, Demir, Kizys, &
Zaremba (2021). They give a recommendation for investors to closely follow the development of vaccination policies of countries and alter their portfolios based on the vaccination policies.
Further, even the number of death cases has a negative coefficient, the critical value is insignificant for both models. Therefore, it shows that KLCI does not have any significant relationship with Malaysia's number of death cases either on a similar day or the previous day.
Model 1 Model 2
Intercept 453.916
(0.000)
449.439 (0.000)
C19 Cases -11.235
(0.000)
-11.640 (0.000) Death Cases due to C19 -1.092
(0.276)
-1.081 (0.281)
Recovered from C19 3.581
(0.000)
4.083 (0.000)
Vaccinated People 3.440
(0.001)
3.241 (0.001)
R-Square 0.670 0.674
F - Statistic 91.529
(0.000)
92.348 (0.000) Figure 3: Regression Analysis
5. Conclusion
The outbreaks of Covid – 19 diseases have caused a major impact on the socio-economic situation of most countries including Malaysia. However, a Covid -19 vaccine can develop immunity in human bodies to the virus that causes Covid - 19. This study attempts to contribute to this emerging literature by including the effect of the vaccination program and the numbers of people recovered from Covid – 19.
Therefore, this study conducts an OLS regression analysis to investigate the impact of Covid – 19 pandemics and vaccination programs on the Malaysia stock market index. A daily number of Covid – 19 confirmed cases, deaths, recovered, and fully vaccinated people are used as independent variables while daily data of KLCI is used as a dependent variable over a period of February 28, 2021, to August 31, 2021.
The results of the analysis demonstrate that during this period of coronavirus outbreak the KLCI stock markets responded negatively and in a significant manner to the increase in Covid – 19 confirmed cases. However, the numbers of recovered cases from Covid - 19 and fully vaccinated people influence positively and significantly the KLCI stock market. This study fails to find any significant response of the KLCI stock market to the increase in Covid – 19 confirmed deaths. These findings suggest that the investors in the KLCI stock market are more anxious by information about Covid – 19 confirmed cases, the patient recovered from Covid – 19, and the numbers of public immunized from Covid - 19 as compared to deaths caused by the Covid – 19.
Further studies on the topics discussed in this research may continue the analysis by using longer data set since the main limitation of this study is the fresh and relatively short sample period. Future researchers also may explore more proxies for the Covid – 19 outbreaks. Besides that, this paper had revealed that the vaccination program has given a positive impact on the equity market. Thus, future researchers can investigate the impact of immunizations on other asset classes such as properties, currencies, or the debt market.
6. Acknowledgement
We thank the Universiti Teknologi MARA for supporting this research project.
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