<i>The stock market reaction to COVID-19 vaccination in ASEAN</i>

Marizsa Herlina; Ade Yunita Mafruhat; Eti Kurniati; Wildan Wildan; Hilwa Gifty Salsabila

doi:10.12688/f1000research.110341.1

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Research Article

The stock market reaction to COVID-19 vaccination in ASEAN

[version 1; peer review: 1 approved, 1 approved with reservations]

Marizsa Herlina¹, Ade Yunita Mafruhat², Eti Kurniati³, Wildan Wildan¹, Hilwa Gifty Salsabila³

Marizsa Herlina¹, Ade Yunita Mafruhat², [...] Eti Kurniati³, Wildan Wildan¹, Hilwa Gifty Salsabila³

PUBLISHED 29 Mar 2022

Author details Author details

¹ Department of Statistics, Universitas Islam Bandung, Bandung, 40116, Indonesia
² Department of Economic Development, Universitas Islam Bandung, Bandung, 40116, Indonesia
³ Department of Mathematics, Universitas Islam Bandung, Bandung, 40116, Indonesia

Marizsa Herlina
Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Software, Supervision, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing

Ade Yunita Mafruhat
Roles: Formal Analysis, Validation, Writing – Original Draft Preparation, Writing – Review & Editing

Eti Kurniati
Roles: Formal Analysis, Methodology, Project Administration, Writing – Original Draft Preparation

Wildan Wildan
Roles: Data Curation, Project Administration, Software

Hilwa Gifty Salsabila
Roles: Data Curation, Project Administration

OPEN PEER REVIEW

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This article is included in the Research Synergy Foundation gateway.

Abstract

Previous studies have shown that the confirmed cases drive investor sentiment, reflecting the stock's return. Based on this, the vaccination growth is also expected to drive the investor’s sentiment, which can be reflected in the return of the stock market in ASEAN. Therefore, this study explores the vaccination impact on stock returns in ASEAN countries. This study contributes to the gap of taking the COVID-19 vaccination impact to the stock return into account by using the panel regression model with HC and Driscoll and Kraay robust covariance matrix estimator, which addresses the cross-dependency and heterogeneity problems. This study is one of the early studies of the topic, especially in ASEAN. The panel regression model with HC and Driscoll and Kraay robust covariance matrix estimator uses three variables: the daily stocks return, vaccine growth, and cases growth. It is a balanced panel data that includes six countries and 117 daily series data, making 702 observations used in the study. The results show conflicting results where daily vaccination growth negatively affects the stock return. This problem can arise for several reasons, such as the uncertainty in the financial market and cross-dependency and heterogeneity detected in the model. We can see that the investors still have a negative sentiment because COVID-19 has resulted in uncertainty on the financial market in ASEAN. This gives us practical implications that the ASEAN country members’ government needs to push vaccination policy more aggressively.

Keywords

Stock reaction, vaccination, ASEAN, panel regression, heterogeneity, cross-dependence

Corresponding author: Marizsa Herlina

Competing interests: No competing interests were disclosed.

Grant information: The grant for this research is given by the Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung. The grant no. 480/C.01/FMIPA-k/V/2021 is given to Marizsa Herlina as the research lead.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright: © 2022 Herlina M et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Herlina M, Mafruhat AY, Kurniati E et al. The stock market reaction to COVID-19 vaccination in ASEAN [version 1; peer review: 1 approved, 1 approved with reservations]. F1000Research 2022, 11:363 (https://doi.org/10.12688/f1000research.110341.1) First published: 29 Mar 2022, 11:363 (https://doi.org/10.12688/f1000research.110341.1) Latest published: 25 Apr 2023, 11:363 (https://doi.org/10.12688/f1000research.110341.2)

Introduction

No one could predict that the COVID-19 pandemic would be a long-lasting problem facing most of the world. All industries are suffering from the ongoing COVID-19 pandemic, until recently. This was shown from the estimation of the world’s gross output (GO) in 2020, which was −3.5; specifically, all countries also had a negative GO. For Association of Southeast Asian Nations (ASEAN), the economic growth prospect is quite dark due to their strong dependencies on the tourism sector. This sector provided 12% of ASEAN GDP in 2016,¹ and it was predicted to rise had there been no pandemic. The pandemic would make it hard to recover the tourism sector because of the travel limitation and quarantine policies applied differently for each country’s borders.² In the third quartal of 2020, most ASEAN countries suffered from the decrease of GDP except for Vietnam, which increased 2.91% of their GDP.³ While pandemics are still ongoing, ASEAN will face a significant hurdle in its tourism sector, and policymakers should make a new strategy to increase economic growth.

One of the efforts to overcome the rising cases of COVID-19 is the vaccination program. Since the first quarter of 2021, almost all countries have started a COVID-19 vaccination program; however, the impact of the COVID-19 vaccination on economic growth is still rarely explored because the program is still in the early stages and there are not enough data to analyze. Despite that, the vaccination program is indeed an excellent start to cope with the spread of COVID-19. The program’s outcome is to slow down the spread and reduce positive cases of the COVID-19. The increasing number of vaccinated people can stabilize a saturated condition. With the growing number of people vaccinated, people will feel more secure and think positively about the future, which will help raise a reasonable expectation in the stock market.

Moreover, research in Vietnam⁴ about the COVID-19 impact on the stock market shows that when Vietnam announced 0 cases of COVID-19 after the lockdown, the stock market in Vietnam raised significantly and became the best performing stock in April and May 2020. Based on this, the impact of the vaccination program is expected to have a similar outcome which is the increase of the stock market performance in other countries. However, it is not always the case that the positive sentiment will always increase the market’s return; otherwise, it can bring down the return because of the abnormal trading volume in the market.⁵ Especially in a period of uncertainty, the investor’s behavior is hard to predict, reflecting on the stock returns.

Every country has different conditions and policies; this implies a variety of vaccination impacts to their stock market for each country. Therefore, panel data analysis can be used to see the stock reaction to the vaccination program in ASEAN. Panel data can control individual heterogeneity and identify the impact better than pure cross-section or time-series data only.⁶^,⁷ Panel data analysis is often used in analyzing the stock market responses study from the COVID-19 outbreak.⁸^–¹¹ They used the stock return to see the market reaction and positive confirmed cases in the respective countries.

Several researchers had studied the financial market performance response to the COVID-19 vaccination.¹²^–¹⁴ These studies show that vaccination gives a significant effect on the global market. However, the variety of vaccines and each country’s vaccination policies would result in different stock market reactions. Besides, no study considers the vaccination impact in ASEAN countries, to the best of our knowledge.

Based on the previous studies, this study has three significant contributions. First, this study could picture the impact of vaccination on stock returns, and it also shows the benefit or the loss for the future investor. Second, the object of this study is the ASEAN country members. The study’s outcome is expected to help the ASEAN policymakers create a policy that considers the vaccination effect on ASEAN stock returns. Third, this study detected several problems, such as cross-dependency and heterogeneity, potentially leading to biased testing results. Thus, this study used the HC and Driscoll and Kraay robust covariance matrix estimator to address those problems and improve the model results for vaccination on stocks’ return. This paper then explains the whole research process, and it is divided into several sections: introduction, background and literature review, data and methodology, results, discussion, and conclusion.

Background and literature review

The COVID-19 pandemic affects the stock market.⁴ In the USA, COVID-19 impacted the US stock market volatility more than any other pandemic since the 1900s.¹⁵ The stock market itself is strongly interconnected. The pandemic can negatively change investors' sentiment, which will affect the investment decision where it will be reflected in the stock prices.¹⁶ In addition, research involving 64 countries¹⁷ showed a negative impact of the COVID-19 pandemic on the stock return. In other words, stock prices reflect the investor’s expectations. When the downfall of the stock market can be seen as a pause in economic activities, it also means that there is price pressure from people’s expectations and fear of the investor’s.¹⁰ The research conducted in India about the stock market reaction before and after lockdown showed that the stock return reacted positively to the policy after lockdown announcement.¹⁸ The vaccination program and policies may also impact the stock market based on that knowledge.

The COVID-19 vaccination started on February 18^th, 2021, where the high-risk population is the vaccination’s priority target.¹⁹ More than 905 million vaccine doses have already been registered worldwide, which means there are 12 doses available for every 100 people. But, the gap between the available dose and the world population still exists.²⁰

The vaccination program in ASEAN has begun differently in its member countries. The earliest country to start the vaccination program was Indonesia on January 26^th, 2021. From Figure 1A, we can see that the three highest vaccinated countries in ASEAN are Singapore, Cambodia, and Brunei, while the lowest three are Indonesia, Philipines, and Myanmar. We also need to consider the size of the population in this case; in terms of the number of vaccinated people, Indonesia, Vietnam, and Thailand are the three highest countries in ASEAN (Figure 1B). This shows that ASEAN countries have been conducting the vaccination program, and this study explored the stock market reaction to the vaccination program in ASEAN countries using panel data analysis.

Figure 1. The percentage (A) and total number (in a million people) of the COVID-19 vaccinated people (B) in ASEAN countries on October 17^th, 2021.

The panel data analysis has been used often in analyzing the stock market reaction. The research by⁸ used the panel regression to see the effect of uncertainty and confirmed cases on the stock market returns in 43 countries; he found that the higher confirmed cases impact greater with the country which also has a higher level of uncertainty. Similar studies were also done by,⁹ who studied 47 countries on the panel regression to explore the effect of people’s trust in the government and society and also the confirmed cases to the stock market volatility. They found that trust in government and society is significantly crucial to market volatility.

The stock market reaction study in G-20 countries by¹⁰ also used panel data regression and event study to see the impact of the COVID-19 outbreak on the abnormal returns of the stock and found that the COVID-19 outbreak has a negative effect to the stock returns. Moreover, the research of,¹¹ who studied the impact of freedom and growth rate of COVID-19 daily returns, also used a panel regression. He found that the growth of COVID-19 significantly affected the returns negatively, and there is a strong negative relationship between the country’s freedom and the effect of the pandemic in the stock market.

The link between the vaccine program and the stock market is also mentioned in several studies. The study about the response of the global stock market to vaccine availability had been explored by using five main markets indexes such as Dow Jones, Shanghai, S&P, FTSE, and EURONEXT). The results showed that after the vaccine arrival, the stock prices significantly outweighed before the vaccine arrived.¹² Another study using the panel data model of the volatility of the stock market reaction to the vaccination program in the international financial market shows that the stock market volatility significantly dropped by the mass vaccinations.¹³ The vaccine effectivity on the stock market was analyzed using a wavelet coherence approach in the USA. The COVID-19 vaccination, infection rate, and the case fatality ratio significantly influence the S&P-500 returns at the majority business cycle.¹⁴ However, none of them consider the existence of cross-dependency and heterogeneity problems. Therefore, this study incorporated the cases and vaccine of COVID-19 growth to the ASEAN stock returns. We also used the HC estimators to address the issue of heterogeneity and Driscoll and Kraay robust covariance matrix estimator to manage the cross-dependency in the panel data model.

Methods

Ethics

This study used secondary datasets obtained from investing.com and²¹ that are available online. Thus, there are no ethical issues in this study.

Data

The variable used in this study are the daily stock returns,¹⁰ which use equation 1:

(1)

R_{it} = ln [\frac{P_{i, t}}{P_{i, t - 1}}] \times 100

Where $R_{it}$ is the daily return for index i and $P_{i, t}$ is the closing stock price of the i index stock at the time t and $P_{i, t - 1}$ is the closing stock price of the i index stock at the time t−1 (a day before). The return was calculated from the available stock indexes in ASEAN (Table 1) available (among the ASEAN members, only six countries had a country stock index) from investing.com. The other variables are the growth of the confirmed positive COVID-19 cases and the growth of the vaccinated people, which follows equations 2 and 3.⁹ All data are secondary data, originated in the form of total vaccination and confirmed cases of COVID-19 that are gathered from²¹ and are accessed on July 8^th, 2021. All of the analyses on this paper were done using the R software.

(2)

{Case Growth}_{i} = ln [\frac{{Case}_{i, t}}{{Case}_{i, t - 1}}]

(3)

{Vaccine Growth}_{i} = ln [\frac{{Vaccinated}_{i, t}}{{Vaccinated}_{i, t - 1}}]

where

{Case Growth}_{i, t}

is the confirmed case at the i country at period t and

{Vaccine Growth}_{i, t}

is the amount of the vaccinated people in the i country at period t. All of the variables are available in daily series, the period of this study is when the ASEAN country have already started their vaccination program from March 13^th, 2021, until July 7^th, 2021.

Table 1. The stock index list in ASEAN members.

No	ASEAN members	Stock index
1	Indonesia	IHSG or JCI
2	Thailand	SET Index
3	Phillipines	PSE Index
4	Vietnam	VN Index
5	Singapore	Straits Times Index
6	Malaysia	FTSE Bursa Malaysia Index

Methodology

The general model,²² which are estimated in the panel regression and the variables used follow equation 4:

(4)

R_{it} = x_{it} β + c_{i} + ε_{it}

Where $x_{it} = [ln {(Cases Growth)}_{i, t}, ln {(Vaccine Growth)}_{i, t}]'$ ; $c_{i} = z'_{i} α$ is the individual effect which contains group-specific variables. The models consist of²²^,²³:

1. Pooled Model which follows the equation 5.
(5)
$R_{it} = x_{it} β + v_{it}$
where $v_{it} \equiv c_{i} + u_{it}$ as the composite errors; $c_{i}$ is individual effect; $u_{it}$ is the idiosyncratic errors and t=1, …, T.
2. Fixed Effect Model which follows the equation 6.
(6)
$R_{it} = x_{it} β + c_{i} + ε_{it}$
where $c_{i} = z'_{i} α$ and $ε_{it}$ is an error term.
3. Random Effect Model which follows the equation 7.
(7)
$R_{it} = x_{it} β + α + v_{it}$
where $v_{it} = c_{i} j_{T} + u_{i}$ ; $j_{T}$ is the Tx1 vector of ones and $u_{i}$ is a group-spesific random element (for each country). Then, after these models are estimated, several testings were carried out in order to see which model perform best such as i) The Hausman test²⁴ is used for determining the most suitable model between fixed effect and random effect model which the null hypothesis is Random Effect Model is more suitable for the data; ii) The Breusch-Pagan Lagrange Multiplier Test²⁵ in order to see the cross-sectional dependency. In the event of cross-dependency exist, the Driscoll and Kraay robust covariance matrix estimator will be used²⁶; iii) The Breusch-Pagan Test²⁷ in order to see the homoskedasticity assumption. If there is any heteroskedasticity detected, the heteroskedasticity consistent (HC) estimation can be used for the model estimation.²⁸^,²⁹

Results

Descriptive analysis

This study used balanced panel data which includes six countries and 117 daily series so the total is 702 observations. From Figure 2, we can see that the growth of confirmed cases and the vaccinated people fluctuate over time. For confirmed cases growth, it fluctuates mostly in Vietnam, Thailand, Malaysia, and the Philippines. Meanwhile, the vaccination growth decreased over time and sometimes it stays flat because the growth did not change that much. If we see the series on Figure 3, the movement of each country evolved around the 0 line, which confirms that the mean of the daily stock return is near 0.

Figure 2. The positive case growth of COVID-19 (A) and the vaccinated people growth (B) in ASEAN countries from March 13^th, 2021 until July 7^th, 2021.

Figure 3. The daily stock index return in Singapore (A), Vietnam (B), Thailand (C), Philippines (D), Malaysia (E), and Indonesia (F) from March 11^th, 2021 until July 7^th, 2021.

Panel regression model of the stock reaction

The model estimation for Pooled Model, Fixed Effect Model, and Random Effect Models are provided in Table 2. From the estimates, vaccine growth is the only one that significantly affects the return of the stock in ASEAN countries. Moreover, both pooled and random effect models produce similar results in the coefficient. All of the estimations for vaccine growth have negative signs, which means that the vaccine growth negatively influences the return of the stock, which is in contrast to the expectation.

Table 2. Estimation results of panel data regression.

Variables	Statistics	Pooled estimation	Fixed effect estimation	Random effect estimation
Vaccine growth	Coefficient	-0.546	-1.365	-0.546
	Std. Error	0.664	0.742	0.664
	p-value	0.411	0.066*	0.411
Cases growth	Coefficient	-0.002	-3.534	-0.002
	Std. Error	2.102	2.749	2.102
	p-value	0.99	0.199	0.99
Constant	Coefficient	0.038	-	0.038
	Std. Error	0.039	-	0.039
	p-value	0.332	-	0.332
Model summary	Observations	702	702	702
	R²	0.001	0.006	0.001
	Adjusted R²	-0.002	-0.004	-0.002
	F-Statistic	0.3374	1.99723	-

* 10%;

** 5%;

*** 1% significance level.

After the model estimation, several tests are conducted to see the most suitable model among all using the Hausman test and Breusch-Pagan Lagrange Multiplier test (Table 3). The Hausman test shows that the fixed effect model is more ideal than the fixed random effect model, which means there is heterogeneity in vaccine growth and case growth on a daily basis. But then the Breusch-Pagan Lagrange Multiplier test shows that there is a cross-sectional dependence problem. This means that there is a dependence on the stock returns among ASEAN countries.

Table 3. The diagnostic testing of the models.

Test	Statistics value	P-value
Hausman Test	10.812	0.0045***
Breusch-Pagan Lagrange Multiplier Test	65.237	0.000***
Breusch-Pagan Test	127.41	0.00***

* 10%;

** 5%;

*** 1% significance level.

In addition, the Breusch-Pagan test also shows that the variance is not homoskedastic so we estimate the HC estimators for the fixed-effect model which are robust to heteroskedasticity and Driscoll and Kraay robust covariance matrix estimator for cross-dependency problem in Table 4. The HC estimators and the Driscoll and Kraay robust covariance matrix estimators of the fixed effect model shows different results to the previous estimations in Table 2 in terms of the standard error and the p-value. For the HC estimators, all variables significantly affect the daily return of the stock in the ASEAN country. The cases growth indeed negatively influences the return of the stock significantly but the vaccine growth also has a negative coefficient. But, if we use the Driscoll and Kraay robust covariance matrix estimators, all of the variables do not significantly influence the return. The HC and Driscoll and Kraay Robust Covariance Matrix Estimators have different results in testing. Even though we have already addressed each problem, they still have biased results.

Table 4. The estimation of fixed effects model by using HC estimators and Driscoll and Kraay Robust covariance matrix estimator.

Variables	HC estimators
Variables	Estimate	Std. Error	T-value	P-value
Vaccine growth	-1.365	0.496	-2.7515	0.006***
Cases growth	-3.534	1.348	-2.6218	0.009***

Variables	Driscoll and Kraay Robust covariance matrix estimators
Variables	Estimate	Std. Error	T-value	P-value
Vaccine growth	-1.365	0.864	-1.579	0.1147
Cases growth	-3.534	3.212	-1.1	0.2717

* 10%;

** 5%;

*** 1% significance level.

Discussion

Based on the results above, it is shown that the cases growth negatively impacted the stock returns in ASEAN. This is in line with all of the previous studies.⁸^,⁹^,¹¹ But we found conflicting results in the vaccination growth. The vaccination growth is supposed to impact the stock return positively, but it harms the stock return. This is in line with the theory that the positive sentiment does not necessarily raise the stock returns.⁵^,¹³ This proves that many things happen in trading. They do not move solely on investors’ sentiment, but many factors interfere with the market, such as government interventions, news, abnormal trading, etc. The goal of the vaccination is herd community which makes a certain proportion of the population have the immunity of a disease. Until now, except for the USA, the world is still far behind the herd immunity threshold.³⁰ If the goal of herd immunity had not been achieved, then the stock market is still in a state of extreme uncertainty; that is why the investor behavior would be hard to predict.⁵ Future investors must be aware of the risk if they want to invest in this situation. The practical implication of this study is that ASEAN countries need to create strategies that will outweigh the risk of this uncertainty to attract investors such as strengthening the healthcare system to ease the uncertainty. The more advanced countries’ financial markets are proven to be more robust to the pandemic effect because of their advanced technology, communication, and good citizen’s welfare.³¹ The ASEAN countries should strengthen their citizens’ trust in them to stabilize the situation like The Phillippines did.

Second, the limitation in this study is the existence of either a cross-dependency problem or heterogeneity left in this model. The HC estimators only addressed the heterogeneity problem but not the cross-dependency problem. Reversely, the Driscoll and Kraay Robust Covariance Matrix Estimators is robust to the cross-dependency problem but not heterogeneity. Both cannot solve those problems simultaneously. The cross-dependency itself can be caused by spatial or spillover effect or unobserved common factors.³² This means that every country has a dependency on each other. The spatial effect of the vaccination on the stock returns need to be explored more.

Conclusions

This study explores the vaccination impact on stock returns in ASEAN by using panel regression. It is found that both vaccination growth and the growth cases are impacting the return of stocks in ASEAN. While the growth cases are in line with previous studies, there are conflicting results where the vaccination growth negatively affects the return stock in ASEAN. These results are contrasted with the expectation that vaccination should bring positive sentiment to the investors. The study confirms the research objectives that we found several mixed results in vaccination impact and address the problem of cross-dependency and heterogeneity. These mixed results could be because of the investor’s sentiment, which is in extreme uncertainty because of the non-presence of herd immunity until now. We can see that the investors still have a negative sentiment because COVID-19 has resulted in uncertainty on the financial market in ASEAN. This gives us practical implications that the ASEAN country members’ government needs to push vaccination policy more aggressively. Even though the results showed that the vaccination still negatively influences the stock returns, the vaccination growth has not shown the distribution of the vaccinated people. For example, in Indonesia, only 56,04% of the Indonesian population gets the second vaccination.

Meanwhile, the new variant of COVID-19 keeps evolving and making a new peak on confirmed cases in many countries, including ASEAN. Thus, the economic activities would also be halted if these are not carefully taken care of. So, the ASEAN countries must fasten their second vaccine distribution, and after that, they need to ensure their citizen get the third vaccine. This is a significant move to stabilize the investors’ trust that governments can warranty the citizen’s welfare. This would make the economy slowly recovers, and the investors’ positive sentiment will follow eventually, and next, the financial market can be stabilized in the end.

Second, there is a cross-dependency and heterogeneity problem in the model which can cause biased test results. Therefore, future studies suggest using another estimator or model to address heterogeneity and the cross-dependency problem simultaneously. For example, consider the spatial panel modeling or another model such as the heterogeneous panel data models with cross-sectional dependence³³ that can address this problem to avoid biased test results.

Data availability

Underlying data

Github: Data of The Stock Market Reaction to COVID-19 Vaccination in ASEAN. Dataset created for

https://github.com/owid/covid-19-data/tree/master/public/data/vaccinations²¹

Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).

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Version 2

VERSION 2 PUBLISHED 29 Mar 2022

Author details Author details

Ade Yunita Mafruhat
Roles: Formal Analysis, Validation, Writing – Original Draft Preparation, Writing – Review & Editing

Eti Kurniati
Roles: Formal Analysis, Methodology, Project Administration, Writing – Original Draft Preparation

Wildan Wildan
Roles: Data Curation, Project Administration, Software

Hilwa Gifty Salsabila
Roles: Data Curation, Project Administration

Competing interests

No competing interests were disclosed.

Grant information

The grant for this research is given by the Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung. The grant no. 480/C.01/FMIPA-k/V/2021 is given to Marizsa Herlina as the research lead.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Published: 25 Apr 2023, 11:363

https://doi.org/10.12688/f1000research.110341.2

version 1

Published: 29 Mar 2022, 11:363

https://doi.org/10.12688/f1000research.110341.1

© 2022 Herlina M et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Herlina M, Mafruhat AY, Kurniati E et al. The stock market reaction to COVID-19 vaccination in ASEAN [version 1; peer review: 1 approved, 1 approved with reservations] F1000Research 2022, 11:363 (https://doi.org/10.12688/f1000research.110341.1)

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Key to Reviewer Statuses VIEW HIDE

ApprovedThe paper is scientifically sound in its current form and only minor, if any, improvements are suggested

Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.

Not approvedFundamental flaws in the paper seriously undermine the findings and conclusions

Version 1

VERSION 1

PUBLISHED 29 Mar 2022

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Reviewer Report 30 May 2022

Evan Lau, Faculty of Economics and Business, Universiti Malaysia Sarawak, Kota Samarahan, Malaysia

Approved with Reservations

https://doi.org/10.5256/f1000research.121936.r139087

1. It is a rather interesting proposition of linking the vaccination and stock market. The authors should be able to provide the theoretical link on how these two were related. At the same time, authors could explore using not just specifically COVID, but also pandemics themselves to find the link.

2. Why the selected ASEAN countries? How do these 6 countries represent ASEAN?

3. As the research on the topical issue is on-going, it might be a good idea to expand the sample period at least to 2022. With an expanded sample, I am sure there are more interesting findings. The authors could explore the sub-sample estimation based on the big sampling data.

4. Driscoll and Kraay Robust Covariance Matrix Estimators - I do not see the relevance of adopting this method. Perhaps the authors could consider other methods or other panel estimates. A non-stationary panel time series perhaps?

5. Low R2 and negative adjusted R2.

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Yes
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Economics

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

CITE

Report a concern

Author Response 25 Apr 2023

Marizsa Herlina

25 Apr 2023

Author Response

Thank you for your suggestions. We have accommodated all of your requests in the revised papers as follows:

1. Reviewer: It is a rather interesting proposition of linking the ... Continue reading Thank you for your suggestions. We have accommodated all of your requests in the revised papers as follows:

1. Reviewer: It is a rather interesting proposition of linking the vaccination and stock market. The authors should be able to provide the theoretical link to how these two were related. At the same time, authors could explore using not just specifically COVID, but also pandemics themselves to find the link.

Answer: when the previous pandemic hits such as swine flu or influenza, it has been found that it has link to the stock market when it hits massively, and this has been addressed in the 1st paragraph of the Background and literature review of the revised paper as follows:

“If we learned from the previous pandemic, such as swine flu, the link from influenza to the stock market could be seen when it began to affect the key individuals massively in the stock market, such as traders, market makers, and overall investing behavior directly or indirectly via decreasing in liquidity due to the decline in information flows and production”

2. Reviewer:Why the selected ASEAN countries? How do these 6 countries represent ASEAN?

Answer: The 6 countries, Indonesia, Thailand, Vietnam, Philippines, Singapore, Malaysia are the highest GDP countries in ASEAN, so they significantly drive the ASEAN economies.

We have accommodated this in the 6th paragraph of the revised paper.
“Second, the object of this study is the six biggest ASEAN country members: Indonesia, Thailand, Philipines, Vietnam, Singapore, and Malaysia. The 6 countries are the highest GDP countries in ASEAN, so We consider these countries to significantly influence the ASEAN stock market (1).”

3. Reviewer: As the research on the topical issue is on-going, it might be a good idea to expand the sample period to at least 2022. With an expanded sample, I am sure there are more interesting findings. The authors could explore the sub-sample estimation based on the big sampling data.

Answer: Thank you for the suggestions. This paper limits the time window to 2021 because the sentiment mostly happens when the vaccine is launched. But we will consider your suggestions for future research.

4. Reviewer: Driscoll and Kraay Robust Covariance Matrix Estimators - I do not see the relevance of adopting this method. Perhaps the authors could consider other methods or other panel estimates. A non-stationary panel time series perhaps?

Answer: The Driscoll and Kraay Robust Covariance Matrix Estimators can estimate the model when there is heterogeneity from cross-dependency detected, and it is already stated in the paper result section in the last paragraph:
“In addition, the Breusch-Pagan test also shows that the variance is not homoskedastic so we estimate the HC estimators for the fixed-effect model, which are robust to heteroskedasticity and Driscoll and Kraay robust covariance matrix in Table 4.”

And in the methodology, last paragraph:
“In the event of cross-dependency exist, the Driscoll and Kraay robust covariance matrix estimator will be used; iii) The Breusch-Pagan Test in order to see the homoskedasticity assumption. If there is any heteroskedasticity detected, the heteroskedasticity consistent (HC) estimation can be used for the model estimation.”

And also in the 5^th paragraph on the revised paper we have added more explanation about this:
“However, the Ordinary Least Square (OLS) estimation of the panel regression model requires the assumption of normally distributed and homogenous errors, which are rarely met in many cases in real-life data, especially economic data such as stock prices. If the assumption of homogeneity is violated, the estimator will be biased. Many previous studies used OLS estimation but did not mention diagnostic testing. Hence, we address the issue of where heterogeneity and cross-dependency occur in the panel model error. Therefore, the Heteroskedasticity consistent (HC) estimator can be an alternative estimator to have robustness in heterogeneity. However, heterogeneity can also exist from cross-dependency, and Driscoll and Kraay's robust covariance matrix estimator addresses those problems and improve the model results for vaccination on stocks’ return.”

A non-stationary panel time series such as VECM panel is not used due to the assumption that both vaccination rate and case growth are independent, so the model has no endogeneity or multicollinearity. Hence, we used the panel data regression model. This has been addressed in the last paragraph of the Background and literature review as follows:
“Because the COVID-19 vaccine growth rate and positive cases are unrelated, the panel model regression will be used, considering there is no endogeneity in the variables used.”

5.Reviewer: Low R2 and negative adjusted R2.

Answer: The low R2 mainly causes the negative adjusted R2, which means most of the dependent variability was not explained by the independent variables. So it translates that the vaccination rate and case growth do not explain most of the variability of the stock prices in the initial panel model. And there is also a lack of assumption fulfilments in heterogeneity and cross-dependency in the initial panel model, so the next step is we estimate the model again using the HC estimators for the fixed-effect model, which are robust to heteroskedasticity and Driscoll and Kraay robust covariance matrix estimator for the cross-dependency problem. (This has been addressed in the previous question).
Thank you for your suggestions. We have accommodated all of your requests in the revised papers as follows:

1. Reviewer: It is a rather interesting proposition of linking the vaccination and stock market. The authors should be able to provide the theoretical link to how these two were related. At the same time, authors could explore using not just specifically COVID, but also pandemics themselves to find the link.

Answer: when the previous pandemic hits such as swine flu or influenza, it has been found that it has link to the stock market when it hits massively, and this has been addressed in the 1st paragraph of the Background and literature review of the revised paper as follows:

“If we learned from the previous pandemic, such as swine flu, the link from influenza to the stock market could be seen when it began to affect the key individuals massively in the stock market, such as traders, market makers, and overall investing behavior directly or indirectly via decreasing in liquidity due to the decline in information flows and production”

2. Reviewer:Why the selected ASEAN countries? How do these 6 countries represent ASEAN?

Answer: The 6 countries, Indonesia, Thailand, Vietnam, Philippines, Singapore, Malaysia are the highest GDP countries in ASEAN, so they significantly drive the ASEAN economies.

We have accommodated this in the 6th paragraph of the revised paper.
“Second, the object of this study is the six biggest ASEAN country members: Indonesia, Thailand, Philipines, Vietnam, Singapore, and Malaysia. The 6 countries are the highest GDP countries in ASEAN, so We consider these countries to significantly influence the ASEAN stock market (1).”

3. Reviewer: As the research on the topical issue is on-going, it might be a good idea to expand the sample period to at least 2022. With an expanded sample, I am sure there are more interesting findings. The authors could explore the sub-sample estimation based on the big sampling data.

Answer: Thank you for the suggestions. This paper limits the time window to 2021 because the sentiment mostly happens when the vaccine is launched. But we will consider your suggestions for future research.

4. Reviewer: Driscoll and Kraay Robust Covariance Matrix Estimators - I do not see the relevance of adopting this method. Perhaps the authors could consider other methods or other panel estimates. A non-stationary panel time series perhaps?

Answer: The Driscoll and Kraay Robust Covariance Matrix Estimators can estimate the model when there is heterogeneity from cross-dependency detected, and it is already stated in the paper result section in the last paragraph:
“In addition, the Breusch-Pagan test also shows that the variance is not homoskedastic so we estimate the HC estimators for the fixed-effect model, which are robust to heteroskedasticity and Driscoll and Kraay robust covariance matrix in Table 4.”

And in the methodology, last paragraph:
“In the event of cross-dependency exist, the Driscoll and Kraay robust covariance matrix estimator will be used; iii) The Breusch-Pagan Test in order to see the homoskedasticity assumption. If there is any heteroskedasticity detected, the heteroskedasticity consistent (HC) estimation can be used for the model estimation.”

And also in the 5^th paragraph on the revised paper we have added more explanation about this:
“However, the Ordinary Least Square (OLS) estimation of the panel regression model requires the assumption of normally distributed and homogenous errors, which are rarely met in many cases in real-life data, especially economic data such as stock prices. If the assumption of homogeneity is violated, the estimator will be biased. Many previous studies used OLS estimation but did not mention diagnostic testing. Hence, we address the issue of where heterogeneity and cross-dependency occur in the panel model error. Therefore, the Heteroskedasticity consistent (HC) estimator can be an alternative estimator to have robustness in heterogeneity. However, heterogeneity can also exist from cross-dependency, and Driscoll and Kraay's robust covariance matrix estimator addresses those problems and improve the model results for vaccination on stocks’ return.”

A non-stationary panel time series such as VECM panel is not used due to the assumption that both vaccination rate and case growth are independent, so the model has no endogeneity or multicollinearity. Hence, we used the panel data regression model. This has been addressed in the last paragraph of the Background and literature review as follows:
“Because the COVID-19 vaccine growth rate and positive cases are unrelated, the panel model regression will be used, considering there is no endogeneity in the variables used.”

5.Reviewer: Low R2 and negative adjusted R2.

Answer: The low R2 mainly causes the negative adjusted R2, which means most of the dependent variability was not explained by the independent variables. So it translates that the vaccination rate and case growth do not explain most of the variability of the stock prices in the initial panel model. And there is also a lack of assumption fulfilments in heterogeneity and cross-dependency in the initial panel model, so the next step is we estimate the model again using the HC estimators for the fixed-effect model, which are robust to heteroskedasticity and Driscoll and Kraay robust covariance matrix estimator for the cross-dependency problem. (This has been addressed in the previous question).
Competing Interests: No competing interests were disclosed. Close
Report a concern
Respond or Comment

COMMENTS ON THIS REPORT

Author Response 25 Apr 2023

Marizsa Herlina

25 Apr 2023

Author Response

Thank you for your suggestions. We have accommodated all of your requests in the revised papers as follows:

1. Reviewer: It is a rather interesting proposition of linking the ... Continue reading Thank you for your suggestions. We have accommodated all of your requests in the revised papers as follows:

1. Reviewer: It is a rather interesting proposition of linking the vaccination and stock market. The authors should be able to provide the theoretical link to how these two were related. At the same time, authors could explore using not just specifically COVID, but also pandemics themselves to find the link.

Answer: when the previous pandemic hits such as swine flu or influenza, it has been found that it has link to the stock market when it hits massively, and this has been addressed in the 1st paragraph of the Background and literature review of the revised paper as follows:

“If we learned from the previous pandemic, such as swine flu, the link from influenza to the stock market could be seen when it began to affect the key individuals massively in the stock market, such as traders, market makers, and overall investing behavior directly or indirectly via decreasing in liquidity due to the decline in information flows and production”

2. Reviewer:Why the selected ASEAN countries? How do these 6 countries represent ASEAN?

Answer: The 6 countries, Indonesia, Thailand, Vietnam, Philippines, Singapore, Malaysia are the highest GDP countries in ASEAN, so they significantly drive the ASEAN economies.

We have accommodated this in the 6th paragraph of the revised paper.
“Second, the object of this study is the six biggest ASEAN country members: Indonesia, Thailand, Philipines, Vietnam, Singapore, and Malaysia. The 6 countries are the highest GDP countries in ASEAN, so We consider these countries to significantly influence the ASEAN stock market (1).”

3. Reviewer: As the research on the topical issue is on-going, it might be a good idea to expand the sample period to at least 2022. With an expanded sample, I am sure there are more interesting findings. The authors could explore the sub-sample estimation based on the big sampling data.

Answer: Thank you for the suggestions. This paper limits the time window to 2021 because the sentiment mostly happens when the vaccine is launched. But we will consider your suggestions for future research.

4. Reviewer: Driscoll and Kraay Robust Covariance Matrix Estimators - I do not see the relevance of adopting this method. Perhaps the authors could consider other methods or other panel estimates. A non-stationary panel time series perhaps?

Answer: The Driscoll and Kraay Robust Covariance Matrix Estimators can estimate the model when there is heterogeneity from cross-dependency detected, and it is already stated in the paper result section in the last paragraph:
“In addition, the Breusch-Pagan test also shows that the variance is not homoskedastic so we estimate the HC estimators for the fixed-effect model, which are robust to heteroskedasticity and Driscoll and Kraay robust covariance matrix in Table 4.”

And in the methodology, last paragraph:
“In the event of cross-dependency exist, the Driscoll and Kraay robust covariance matrix estimator will be used; iii) The Breusch-Pagan Test in order to see the homoskedasticity assumption. If there is any heteroskedasticity detected, the heteroskedasticity consistent (HC) estimation can be used for the model estimation.”

And also in the 5^th paragraph on the revised paper we have added more explanation about this:
“However, the Ordinary Least Square (OLS) estimation of the panel regression model requires the assumption of normally distributed and homogenous errors, which are rarely met in many cases in real-life data, especially economic data such as stock prices. If the assumption of homogeneity is violated, the estimator will be biased. Many previous studies used OLS estimation but did not mention diagnostic testing. Hence, we address the issue of where heterogeneity and cross-dependency occur in the panel model error. Therefore, the Heteroskedasticity consistent (HC) estimator can be an alternative estimator to have robustness in heterogeneity. However, heterogeneity can also exist from cross-dependency, and Driscoll and Kraay's robust covariance matrix estimator addresses those problems and improve the model results for vaccination on stocks’ return.”

A non-stationary panel time series such as VECM panel is not used due to the assumption that both vaccination rate and case growth are independent, so the model has no endogeneity or multicollinearity. Hence, we used the panel data regression model. This has been addressed in the last paragraph of the Background and literature review as follows:
“Because the COVID-19 vaccine growth rate and positive cases are unrelated, the panel model regression will be used, considering there is no endogeneity in the variables used.”

5.Reviewer: Low R2 and negative adjusted R2.

Answer: The low R2 mainly causes the negative adjusted R2, which means most of the dependent variability was not explained by the independent variables. So it translates that the vaccination rate and case growth do not explain most of the variability of the stock prices in the initial panel model. And there is also a lack of assumption fulfilments in heterogeneity and cross-dependency in the initial panel model, so the next step is we estimate the model again using the HC estimators for the fixed-effect model, which are robust to heteroskedasticity and Driscoll and Kraay robust covariance matrix estimator for the cross-dependency problem. (This has been addressed in the previous question).
Thank you for your suggestions. We have accommodated all of your requests in the revised papers as follows:

1. Reviewer: It is a rather interesting proposition of linking the vaccination and stock market. The authors should be able to provide the theoretical link to how these two were related. At the same time, authors could explore using not just specifically COVID, but also pandemics themselves to find the link.

Answer: when the previous pandemic hits such as swine flu or influenza, it has been found that it has link to the stock market when it hits massively, and this has been addressed in the 1st paragraph of the Background and literature review of the revised paper as follows:

“If we learned from the previous pandemic, such as swine flu, the link from influenza to the stock market could be seen when it began to affect the key individuals massively in the stock market, such as traders, market makers, and overall investing behavior directly or indirectly via decreasing in liquidity due to the decline in information flows and production”

2. Reviewer:Why the selected ASEAN countries? How do these 6 countries represent ASEAN?

Answer: The 6 countries, Indonesia, Thailand, Vietnam, Philippines, Singapore, Malaysia are the highest GDP countries in ASEAN, so they significantly drive the ASEAN economies.

We have accommodated this in the 6th paragraph of the revised paper.
“Second, the object of this study is the six biggest ASEAN country members: Indonesia, Thailand, Philipines, Vietnam, Singapore, and Malaysia. The 6 countries are the highest GDP countries in ASEAN, so We consider these countries to significantly influence the ASEAN stock market (1).”

3. Reviewer: As the research on the topical issue is on-going, it might be a good idea to expand the sample period to at least 2022. With an expanded sample, I am sure there are more interesting findings. The authors could explore the sub-sample estimation based on the big sampling data.

Answer: Thank you for the suggestions. This paper limits the time window to 2021 because the sentiment mostly happens when the vaccine is launched. But we will consider your suggestions for future research.

4. Reviewer: Driscoll and Kraay Robust Covariance Matrix Estimators - I do not see the relevance of adopting this method. Perhaps the authors could consider other methods or other panel estimates. A non-stationary panel time series perhaps?

Answer: The Driscoll and Kraay Robust Covariance Matrix Estimators can estimate the model when there is heterogeneity from cross-dependency detected, and it is already stated in the paper result section in the last paragraph:
“In addition, the Breusch-Pagan test also shows that the variance is not homoskedastic so we estimate the HC estimators for the fixed-effect model, which are robust to heteroskedasticity and Driscoll and Kraay robust covariance matrix in Table 4.”

And in the methodology, last paragraph:
“In the event of cross-dependency exist, the Driscoll and Kraay robust covariance matrix estimator will be used; iii) The Breusch-Pagan Test in order to see the homoskedasticity assumption. If there is any heteroskedasticity detected, the heteroskedasticity consistent (HC) estimation can be used for the model estimation.”

And also in the 5^th paragraph on the revised paper we have added more explanation about this:
“However, the Ordinary Least Square (OLS) estimation of the panel regression model requires the assumption of normally distributed and homogenous errors, which are rarely met in many cases in real-life data, especially economic data such as stock prices. If the assumption of homogeneity is violated, the estimator will be biased. Many previous studies used OLS estimation but did not mention diagnostic testing. Hence, we address the issue of where heterogeneity and cross-dependency occur in the panel model error. Therefore, the Heteroskedasticity consistent (HC) estimator can be an alternative estimator to have robustness in heterogeneity. However, heterogeneity can also exist from cross-dependency, and Driscoll and Kraay's robust covariance matrix estimator addresses those problems and improve the model results for vaccination on stocks’ return.”

A non-stationary panel time series such as VECM panel is not used due to the assumption that both vaccination rate and case growth are independent, so the model has no endogeneity or multicollinearity. Hence, we used the panel data regression model. This has been addressed in the last paragraph of the Background and literature review as follows:
“Because the COVID-19 vaccine growth rate and positive cases are unrelated, the panel model regression will be used, considering there is no endogeneity in the variables used.”

5.Reviewer: Low R2 and negative adjusted R2.

Answer: The low R2 mainly causes the negative adjusted R2, which means most of the dependent variability was not explained by the independent variables. So it translates that the vaccination rate and case growth do not explain most of the variability of the stock prices in the initial panel model. And there is also a lack of assumption fulfilments in heterogeneity and cross-dependency in the initial panel model, so the next step is we estimate the model again using the HC estimators for the fixed-effect model, which are robust to heteroskedasticity and Driscoll and Kraay robust covariance matrix estimator for the cross-dependency problem. (This has been addressed in the previous question).
Competing Interests: No competing interests were disclosed. Close
Report a concern

Views

Reviewer Report 04 May 2022

Robiyanto Robiyanto, Faculty of Economics and Business, Satya Wacana Christian University, Salatiga, Indonesia

Approved

https://doi.org/10.5256/f1000research.121936.r134887

Good manuscript, however some improvements should be made prior to indexing. This manuscript can contribute to the reference regarding the dynamics of financial markets in the pandemic era. Minor changes required.

Major points:

Please explain how vaccination could affect stock return? As you know, some stock markets plummeted in the early pandemic event, but then these stock markets then recovered because the pandemic was priced in already. This is not because of merely vaccination, some robustness checking is needed. The awakening of retail investors (i.e. in Indonesia) etc. should be considered.

Minor points:

Please sharpen the research gaps, which need your contributions, especially the third contribution. Please describe some flaws in previous studies which need this solution and how your method could eliminate these flaws.
Add some recent literature. Some related literature has been published.

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Yes
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests: No competing interests were disclosed.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

CITE

Report a concern

Author Response 25 Apr 2023

Marizsa Herlina

25 Apr 2023

Author Response
Thank you for your suggestions. We have accommodated all of your requests in the revised papers as follows:

1. Major points:
- Reviewer: Please explain how vaccination could
... Continue reading
Thank you for your suggestions. We have accommodated all of your requests in the revised papers as follows:

1. Major points:

Reviewer: Please explain how vaccination could affect stock return? As you know, some stock markets plummeted in the early pandemic event, but then these stock markets then recovered because the pandemic was priced in already. This is not because of merely vaccination, some robustness checking is needed. The awakening of retail investors (i.e. in Indonesia) etc. should be considered.

Answer: In recent studies, the link between vaccination and stock mostly happens in the news about vaccine announcements, resulting in positive sentiment by investors. We already added this in the revised paper in the 1st paragraph in the background and literature review as follows:

“In addition, a recent study shows that news about covid help equities in general, whether its positive or negative news(3). Moreover, the Covid-19 vaccine announcement also positively impacted the Chinese stock market. Besides, many studies prove that mass campaign about Covid-19 vaccines receives positive sentiments from investors (3–6). Therefore, the approvals of Covid-19 vaccines lighted the hope of humanity and economic recovery, and this phenomenon is reflected in the stock market (5),”

2. Minor points:

Reviewer: Please sharpen the research gaps, which need your contributions, especially the third contribution. Please describe some flaws in previous studies which need this solution and how your method could eliminate these flaws.

Answer: This has been addressed in the fifth paragraph of the Introduction in the revised paper as follows:

"However, the Ordinary Least Square (OLS) estimation of the panel regression model requires the assumption of normally distributed and homogenous errors, which are rarely met in many cases in real-life data, especially economic data such as stock prices. If the assumption of homogeneity is violated, the estimator will be biased. Many previous studies used OLS estimation but did not mention diagnostic testing. Hence, we address the issue of where heterogeneity and cross-dependency occur in the panel model error. Therefore, the Heteroskedasticity consistent (HC) estimator can be an alternative estimator to have robustness in heterogeneity. However, heterogeneity can also exist from cross-dependency, and Driscoll and Kraay's robust covariance matrix estimator addresses those problems and improve the model results for vaccination on stocks’ return."

And in the Background and literature review section, in the last paragraph:

“However, none of them consider the existence of cross-dependency and heterogeneity problems. Therefore, this study incorporated the cases and vaccine of COVID-19 growth to the ASEAN stock returns.”

Reviewer: Add some recent literature. Some related literature has been published.

Answer: We have added recent literatures as you can see in the first point and also from the other reviewer as follows:

1. Yiu MS, Tsang A. Impact of COVID-19 on ASEAN5 stock markets. J Asia Pac Econ. 2021 Aug 21;1–14.
3. Arteaga-Garavito MJ, Croce MM, Farroni P, Wolfskeil I. When the Markets Get CO.V.I.D: Contagion, Viruses, and Information Diffusion. SSRN. 2022;
4. Hartono, Hartono. Covid-19 Vaccine: Global Stock Market “Game Changer.” J Asian Multicult Res Econ Manag Study [Internet]. 2021;2(2). Available from: https://amrsjournals.com/index.php/jamrems/article/view/102
5. Ho KC, Gao Y, Gu Q, Yang D. Covid-19 vaccine approvals and stock market returns: The case of Chinese stocks. Econ Lett. 2022 Jun;215:110466.
6. Oanh TTK. The impact of COVID-19 vaccination on stock market: is there any difference between developed and developing countries? Heliyon [Internet]. 2022 [cited 2023 Apr 2];8(9). Available from: https://linkinghub.elsevier.com/retrieve/pii/S2405844022020060
Thank you for your suggestions. We have accommodated all of your requests in the revised papers as follows:

1. Major points:

Reviewer: Please explain how vaccination could affect stock return? As you know, some stock markets plummeted in the early pandemic event, but then these stock markets then recovered because the pandemic was priced in already. This is not because of merely vaccination, some robustness checking is needed. The awakening of retail investors (i.e. in Indonesia) etc. should be considered.

Answer: In recent studies, the link between vaccination and stock mostly happens in the news about vaccine announcements, resulting in positive sentiment by investors. We already added this in the revised paper in the 1st paragraph in the background and literature review as follows:

“In addition, a recent study shows that news about covid help equities in general, whether its positive or negative news(3). Moreover, the Covid-19 vaccine announcement also positively impacted the Chinese stock market. Besides, many studies prove that mass campaign about Covid-19 vaccines receives positive sentiments from investors (3–6). Therefore, the approvals of Covid-19 vaccines lighted the hope of humanity and economic recovery, and this phenomenon is reflected in the stock market (5),”

2. Minor points:

Reviewer: Please sharpen the research gaps, which need your contributions, especially the third contribution. Please describe some flaws in previous studies which need this solution and how your method could eliminate these flaws.

Answer: This has been addressed in the fifth paragraph of the Introduction in the revised paper as follows:

"However, the Ordinary Least Square (OLS) estimation of the panel regression model requires the assumption of normally distributed and homogenous errors, which are rarely met in many cases in real-life data, especially economic data such as stock prices. If the assumption of homogeneity is violated, the estimator will be biased. Many previous studies used OLS estimation but did not mention diagnostic testing. Hence, we address the issue of where heterogeneity and cross-dependency occur in the panel model error. Therefore, the Heteroskedasticity consistent (HC) estimator can be an alternative estimator to have robustness in heterogeneity. However, heterogeneity can also exist from cross-dependency, and Driscoll and Kraay's robust covariance matrix estimator addresses those problems and improve the model results for vaccination on stocks’ return."

And in the Background and literature review section, in the last paragraph:

“However, none of them consider the existence of cross-dependency and heterogeneity problems. Therefore, this study incorporated the cases and vaccine of COVID-19 growth to the ASEAN stock returns.”

Reviewer: Add some recent literature. Some related literature has been published.

Answer: We have added recent literatures as you can see in the first point and also from the other reviewer as follows:

1. Yiu MS, Tsang A. Impact of COVID-19 on ASEAN5 stock markets. J Asia Pac Econ. 2021 Aug 21;1–14.
3. Arteaga-Garavito MJ, Croce MM, Farroni P, Wolfskeil I. When the Markets Get CO.V.I.D: Contagion, Viruses, and Information Diffusion. SSRN. 2022;
4. Hartono, Hartono. Covid-19 Vaccine: Global Stock Market “Game Changer.” J Asian Multicult Res Econ Manag Study [Internet]. 2021;2(2). Available from: https://amrsjournals.com/index.php/jamrems/article/view/102
5. Ho KC, Gao Y, Gu Q, Yang D. Covid-19 vaccine approvals and stock market returns: The case of Chinese stocks. Econ Lett. 2022 Jun;215:110466.
6. Oanh TTK. The impact of COVID-19 vaccination on stock market: is there any difference between developed and developing countries? Heliyon [Internet]. 2022 [cited 2023 Apr 2];8(9). Available from: https://linkinghub.elsevier.com/retrieve/pii/S2405844022020060
Competing Interests: No competing interests were disclosed. Close
Report a concern
Respond or Comment

COMMENTS ON THIS REPORT

Author Response 25 Apr 2023

Marizsa Herlina

25 Apr 2023

Author Response
Thank you for your suggestions. We have accommodated all of your requests in the revised papers as follows:

1. Major points:
- Reviewer: Please explain how vaccination could
... Continue reading
Thank you for your suggestions. We have accommodated all of your requests in the revised papers as follows:

1. Major points:

Reviewer: Please explain how vaccination could affect stock return? As you know, some stock markets plummeted in the early pandemic event, but then these stock markets then recovered because the pandemic was priced in already. This is not because of merely vaccination, some robustness checking is needed. The awakening of retail investors (i.e. in Indonesia) etc. should be considered.

Answer: In recent studies, the link between vaccination and stock mostly happens in the news about vaccine announcements, resulting in positive sentiment by investors. We already added this in the revised paper in the 1st paragraph in the background and literature review as follows:

“In addition, a recent study shows that news about covid help equities in general, whether its positive or negative news(3). Moreover, the Covid-19 vaccine announcement also positively impacted the Chinese stock market. Besides, many studies prove that mass campaign about Covid-19 vaccines receives positive sentiments from investors (3–6). Therefore, the approvals of Covid-19 vaccines lighted the hope of humanity and economic recovery, and this phenomenon is reflected in the stock market (5),”

2. Minor points:

Reviewer: Please sharpen the research gaps, which need your contributions, especially the third contribution. Please describe some flaws in previous studies which need this solution and how your method could eliminate these flaws.

Answer: This has been addressed in the fifth paragraph of the Introduction in the revised paper as follows:

"However, the Ordinary Least Square (OLS) estimation of the panel regression model requires the assumption of normally distributed and homogenous errors, which are rarely met in many cases in real-life data, especially economic data such as stock prices. If the assumption of homogeneity is violated, the estimator will be biased. Many previous studies used OLS estimation but did not mention diagnostic testing. Hence, we address the issue of where heterogeneity and cross-dependency occur in the panel model error. Therefore, the Heteroskedasticity consistent (HC) estimator can be an alternative estimator to have robustness in heterogeneity. However, heterogeneity can also exist from cross-dependency, and Driscoll and Kraay's robust covariance matrix estimator addresses those problems and improve the model results for vaccination on stocks’ return."

And in the Background and literature review section, in the last paragraph:

“However, none of them consider the existence of cross-dependency and heterogeneity problems. Therefore, this study incorporated the cases and vaccine of COVID-19 growth to the ASEAN stock returns.”

Reviewer: Add some recent literature. Some related literature has been published.

Answer: We have added recent literatures as you can see in the first point and also from the other reviewer as follows:

1. Yiu MS, Tsang A. Impact of COVID-19 on ASEAN5 stock markets. J Asia Pac Econ. 2021 Aug 21;1–14.
3. Arteaga-Garavito MJ, Croce MM, Farroni P, Wolfskeil I. When the Markets Get CO.V.I.D: Contagion, Viruses, and Information Diffusion. SSRN. 2022;
4. Hartono, Hartono. Covid-19 Vaccine: Global Stock Market “Game Changer.” J Asian Multicult Res Econ Manag Study [Internet]. 2021;2(2). Available from: https://amrsjournals.com/index.php/jamrems/article/view/102
5. Ho KC, Gao Y, Gu Q, Yang D. Covid-19 vaccine approvals and stock market returns: The case of Chinese stocks. Econ Lett. 2022 Jun;215:110466.
6. Oanh TTK. The impact of COVID-19 vaccination on stock market: is there any difference between developed and developing countries? Heliyon [Internet]. 2022 [cited 2023 Apr 2];8(9). Available from: https://linkinghub.elsevier.com/retrieve/pii/S2405844022020060
Thank you for your suggestions. We have accommodated all of your requests in the revised papers as follows:

1. Major points:

Reviewer: Please explain how vaccination could affect stock return? As you know, some stock markets plummeted in the early pandemic event, but then these stock markets then recovered because the pandemic was priced in already. This is not because of merely vaccination, some robustness checking is needed. The awakening of retail investors (i.e. in Indonesia) etc. should be considered.

Answer: In recent studies, the link between vaccination and stock mostly happens in the news about vaccine announcements, resulting in positive sentiment by investors. We already added this in the revised paper in the 1st paragraph in the background and literature review as follows:

“In addition, a recent study shows that news about covid help equities in general, whether its positive or negative news(3). Moreover, the Covid-19 vaccine announcement also positively impacted the Chinese stock market. Besides, many studies prove that mass campaign about Covid-19 vaccines receives positive sentiments from investors (3–6). Therefore, the approvals of Covid-19 vaccines lighted the hope of humanity and economic recovery, and this phenomenon is reflected in the stock market (5),”

2. Minor points:

Reviewer: Please sharpen the research gaps, which need your contributions, especially the third contribution. Please describe some flaws in previous studies which need this solution and how your method could eliminate these flaws.

Answer: This has been addressed in the fifth paragraph of the Introduction in the revised paper as follows:

"However, the Ordinary Least Square (OLS) estimation of the panel regression model requires the assumption of normally distributed and homogenous errors, which are rarely met in many cases in real-life data, especially economic data such as stock prices. If the assumption of homogeneity is violated, the estimator will be biased. Many previous studies used OLS estimation but did not mention diagnostic testing. Hence, we address the issue of where heterogeneity and cross-dependency occur in the panel model error. Therefore, the Heteroskedasticity consistent (HC) estimator can be an alternative estimator to have robustness in heterogeneity. However, heterogeneity can also exist from cross-dependency, and Driscoll and Kraay's robust covariance matrix estimator addresses those problems and improve the model results for vaccination on stocks’ return."

And in the Background and literature review section, in the last paragraph:

“However, none of them consider the existence of cross-dependency and heterogeneity problems. Therefore, this study incorporated the cases and vaccine of COVID-19 growth to the ASEAN stock returns.”

Reviewer: Add some recent literature. Some related literature has been published.

Answer: We have added recent literatures as you can see in the first point and also from the other reviewer as follows:

1. Yiu MS, Tsang A. Impact of COVID-19 on ASEAN5 stock markets. J Asia Pac Econ. 2021 Aug 21;1–14.
3. Arteaga-Garavito MJ, Croce MM, Farroni P, Wolfskeil I. When the Markets Get CO.V.I.D: Contagion, Viruses, and Information Diffusion. SSRN. 2022;
4. Hartono, Hartono. Covid-19 Vaccine: Global Stock Market “Game Changer.” J Asian Multicult Res Econ Manag Study [Internet]. 2021;2(2). Available from: https://amrsjournals.com/index.php/jamrems/article/view/102
5. Ho KC, Gao Y, Gu Q, Yang D. Covid-19 vaccine approvals and stock market returns: The case of Chinese stocks. Econ Lett. 2022 Jun;215:110466.
6. Oanh TTK. The impact of COVID-19 vaccination on stock market: is there any difference between developed and developing countries? Heliyon [Internet]. 2022 [cited 2023 Apr 2];8(9). Available from: https://linkinghub.elsevier.com/retrieve/pii/S2405844022020060
Competing Interests: No competing interests were disclosed. Close
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VERSION 2 PUBLISHED 29 Mar 2022

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Version 2 (revision) 25 Apr 23			read
Version 1 29 Mar 22	read	read

Robiyanto Robiyanto, Satya Wacana Christian University, Salatiga, Indonesia
Evan Lau, Universiti Malaysia Sarawak, Kota Samarahan, Malaysia
Walid Bakry, University of Western Sydney, Sydney, Australia

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11 Aug 2023 | for Version 2

Walid Bakry, University of Western Sydney, Sydney, Australia

3 Views Cite this report Responses(0)

Approved With Reservations

I checked the revisions round 1 required and I can see that author(s) did address all of the reviewers’ questions.

The article is interesting, although the topic is not new, however, there are couple of points I would suggest the authors to consider:

1 - The paper did not mention early studies which tested the impact of COVID-19 vaccine on stock return or return volatility, these should be mentioned and included in the literature review section. This includes:

Apergis, N., Mustafa, G., & Malik, S. (2022). COVID-19 pandemic, stock returns, and volatility: the role of the vaccination program in Canada. Applied Economics, 54(42), 4825–4838. https://doi.org/10.1080/00036846.2022.2036688
Bakry, W, Kavalmthara, P, J, Saverimuttu V, Liu Y, Cyril S, (2022). Response of stock market volatility to COVID-19 announcements and stringency measures: A comparison of developed and emerging markets. Finance Research Letters, 46, 102350–102350. https://doi.org/10.1016/j.frl.2021.102350
Behera, J., Pasayat, A. K., & Behera, H. (2022). COVID-19 Vaccination Effect on Stock Market and Death Rate in India. Asia-Pacific Financial Markets, 29(4), 651–673. https://doi.org/10.1007/s10690-022-09364-w
Chan, K. F., Chen, Z., Wen, Y., & Xu, T. (2022). COVID-19 vaccines and global stock markets. Finance Research Letters, 47, 102774–102774. https://doi.org/10.1016/j.frl.2022.102774

2- The second point is the source of stock indices data shown in table 1?

3- The third and final point of concern for me in this article is the use of a panel model with only 2 independent variables which explain little about the change in stock returns. You need to add some other control variables, so you don’t fall in the omitted variable bias issue. That is why your R² is so low and you are not getting much significance in Table 2.

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Partly
Are the conclusions drawn adequately supported by the results?

Yes

References

1. Apergis N, Mustafa G, Malik S: COVID-19 pandemic, stock returns, and volatility: the role of the vaccination program in Canada. Applied Economics. 2022; 54 (42): 4825-4838 Publisher Full Text
2. Bakry W, Kavalmthara PJ, Saverimuttu V, Liu Y, et al.: Response of stock market volatility to COVID-19 announcements and stringency measures: A comparison of developed and emerging markets.Financ Res Lett. 2022; 46: 102350 PubMed Abstract | Publisher Full Text
3. Behera J, Pasayat A, Behera H: COVID-19 Vaccination Effect on Stock Market and Death Rate in India. Asia-Pacific Financial Markets. 2022; 29 (4): 651-673 Publisher Full Text
4. Chan KF, Chen Z, Wen Y, Xu T: COVID-19 vaccines and global stock markets.Financ Res Lett. 2022; 47: 102774 PubMed Abstract | Publisher Full Text

Competing Interests

No competing interests were disclosed.

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25 Views

30 May 2022 | for Version 1

Evan Lau, Faculty of Economics and Business, Universiti Malaysia Sarawak, Kota Samarahan, Malaysia

25 Views Cite this report Responses(1)

Approved With Reservations

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Yes
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Economics

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Author Response

25 Apr 2023

Marizsa Herlina

Thank you for your suggestions. We have accommodated all of your requests in the revised papers as follows:

1. Reviewer: It is a rather interesting proposition of linking the vaccination and stock market. The authors should be able to provide the theoretical link to how these two were related. At the same time, authors could explore using not just specifically COVID, but also pandemics themselves to find the link.

Answer: when the previous pandemic hits such as swine flu or influenza, it has been found that it has link to the stock market when it hits massively, and this has been addressed in the 1st paragraph of the Background and literature review of the revised paper as follows:

“If we learned from the previous pandemic, such as swine flu, the link from influenza to the stock market could be seen when it began to affect the key individuals massively in the stock market, such as traders, market makers, and overall investing behavior directly or indirectly via decreasing in liquidity due to the decline in information flows and production”

2. Reviewer:Why the selected ASEAN countries? How do these 6 countries represent ASEAN?

Answer: The 6 countries, Indonesia, Thailand, Vietnam, Philippines, Singapore, Malaysia are the highest GDP countries in ASEAN, so they significantly drive the ASEAN economies.

We have accommodated this in the 6th paragraph of the revised paper.
“Second, the object of this study is the six biggest ASEAN country members: Indonesia, Thailand, Philipines, Vietnam, Singapore, and Malaysia. The 6 countries are the highest GDP countries in ASEAN, so We consider these countries to significantly influence the ASEAN stock market (1).”

3. Reviewer: As the research on the topical issue is on-going, it might be a good idea to expand the sample period to at least 2022. With an expanded sample, I am sure there are more interesting findings. The authors could explore the sub-sample estimation based on the big sampling data.

Answer: Thank you for the suggestions. This paper limits the time window to 2021 because the sentiment mostly happens when the vaccine is launched. But we will consider your suggestions for future research.

4. Reviewer: Driscoll and Kraay Robust Covariance Matrix Estimators - I do not see the relevance of adopting this method. Perhaps the authors could consider other methods or other panel estimates. A non-stationary panel time series perhaps?

Answer: The Driscoll and Kraay Robust Covariance Matrix Estimators can estimate the model when there is heterogeneity from cross-dependency detected, and it is already stated in the paper result section in the last paragraph:
“In addition, the Breusch-Pagan test also shows that the variance is not homoskedastic so we estimate the HC estimators for the fixed-effect model, which are robust to heteroskedasticity and Driscoll and Kraay robust covariance matrix in Table 4.”

And in the methodology, last paragraph:
“In the event of cross-dependency exist, the Driscoll and Kraay robust covariance matrix estimator will be used; iii) The Breusch-Pagan Test in order to see the homoskedasticity assumption. If there is any heteroskedasticity detected, the heteroskedasticity consistent (HC) estimation can be used for the model estimation.”

And also in the 5^th paragraph on the revised paper we have added more explanation about this:
“However, the Ordinary Least Square (OLS) estimation of the panel regression model requires the assumption of normally distributed and homogenous errors, which are rarely met in many cases in real-life data, especially economic data such as stock prices. If the assumption of homogeneity is violated, the estimator will be biased. Many previous studies used OLS estimation but did not mention diagnostic testing. Hence, we address the issue of where heterogeneity and cross-dependency occur in the panel model error. Therefore, the Heteroskedasticity consistent (HC) estimator can be an alternative estimator to have robustness in heterogeneity. However, heterogeneity can also exist from cross-dependency, and Driscoll and Kraay's robust covariance matrix estimator addresses those problems and improve the model results for vaccination on stocks’ return.”

A non-stationary panel time series such as VECM panel is not used due to the assumption that both vaccination rate and case growth are independent, so the model has no endogeneity or multicollinearity. Hence, we used the panel data regression model. This has been addressed in the last paragraph of the Background and literature review as follows:
“Because the COVID-19 vaccine growth rate and positive cases are unrelated, the panel model regression will be used, considering there is no endogeneity in the variables used.”

5.Reviewer: Low R2 and negative adjusted R2.

Answer: The low R2 mainly causes the negative adjusted R2, which means most of the dependent variability was not explained by the independent variables. So it translates that the vaccination rate and case growth do not explain most of the variability of the stock prices in the initial panel model. And there is also a lack of assumption fulfilments in heterogeneity and cross-dependency in the initial panel model, so the next step is we estimate the model again using the HC estimators for the fixed-effect model, which are robust to heteroskedasticity and Driscoll and Kraay robust covariance matrix estimator for the cross-dependency problem. (This has been addressed in the previous question).

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25 Views

04 May 2022 | for Version 1

Robiyanto Robiyanto, Faculty of Economics and Business, Satya Wacana Christian University, Salatiga, Indonesia

25 Views Cite this report Responses(1)

Approved

Please explain how vaccination could affect stock return? As you know, some stock markets plummeted in the early pandemic event, but then these stock markets then recovered because the pandemic was priced in already. This is not because of merely vaccination, some robustness checking is needed. The awakening of retail investors (i.e. in Indonesia) etc. should be considered.

Minor points:

Please sharpen the research gaps, which need your contributions, especially the third contribution. Please describe some flaws in previous studies which need this solution and how your method could eliminate these flaws.
Add some recent literature. Some related literature has been published.

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Yes
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests

No competing interests were disclosed.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Respond to this report

Responses (1)

Author Response

25 Apr 2023

Marizsa Herlina

Thank you for your suggestions. We have accommodated all of your requests in the revised papers as follows:

1. Major points:

Reviewer: Please explain how vaccination could affect stock return? As you know, some stock markets plummeted in the early pandemic event, but then these stock markets then recovered because the pandemic was priced in already. This is not because of merely vaccination, some robustness checking is needed. The awakening of retail investors (i.e. in Indonesia) etc. should be considered.

Answer: In recent studies, the link between vaccination and stock mostly happens in the news about vaccine announcements, resulting in positive sentiment by investors. We already added this in the revised paper in the 1st paragraph in the background and literature review as follows:

“In addition, a recent study shows that news about covid help equities in general, whether its positive or negative news(3). Moreover, the Covid-19 vaccine announcement also positively impacted the Chinese stock market. Besides, many studies prove that mass campaign about Covid-19 vaccines receives positive sentiments from investors (3–6). Therefore, the approvals of Covid-19 vaccines lighted the hope of humanity and economic recovery, and this phenomenon is reflected in the stock market (5),”

2. Minor points:

Reviewer: Please sharpen the research gaps, which need your contributions, especially the third contribution. Please describe some flaws in previous studies which need this solution and how your method could eliminate these flaws.

Answer: This has been addressed in the fifth paragraph of the Introduction in the revised paper as follows:

"However, the Ordinary Least Square (OLS) estimation of the panel regression model requires the assumption of normally distributed and homogenous errors, which are rarely met in many cases in real-life data, especially economic data such as stock prices. If the assumption of homogeneity is violated, the estimator will be biased. Many previous studies used OLS estimation but did not mention diagnostic testing. Hence, we address the issue of where heterogeneity and cross-dependency occur in the panel model error. Therefore, the Heteroskedasticity consistent (HC) estimator can be an alternative estimator to have robustness in heterogeneity. However, heterogeneity can also exist from cross-dependency, and Driscoll and Kraay's robust covariance matrix estimator addresses those problems and improve the model results for vaccination on stocks’ return."

And in the Background and literature review section, in the last paragraph:

“However, none of them consider the existence of cross-dependency and heterogeneity problems. Therefore, this study incorporated the cases and vaccine of COVID-19 growth to the ASEAN stock returns.”

Reviewer: Add some recent literature. Some related literature has been published.

Answer: We have added recent literatures as you can see in the first point and also from the other reviewer as follows:

1. Yiu MS, Tsang A. Impact of COVID-19 on ASEAN5 stock markets. J Asia Pac Econ. 2021 Aug 21;1–14.
3. Arteaga-Garavito MJ, Croce MM, Farroni P, Wolfskeil I. When the Markets Get CO.V.I.D: Contagion, Viruses, and Information Diffusion. SSRN. 2022;
4. Hartono, Hartono. Covid-19 Vaccine: Global Stock Market “Game Changer.” J Asian Multicult Res Econ Manag Study [Internet]. 2021;2(2). Available from: https://amrsjournals.com/index.php/jamrems/article/view/102
5. Ho KC, Gao Y, Gu Q, Yang D. Covid-19 vaccine approvals and stock market returns: The case of Chinese stocks. Econ Lett. 2022 Jun;215:110466.
6. Oanh TTK. The impact of COVID-19 vaccination on stock market: is there any difference between developed and developing countries? Heliyon [Internet]. 2022 [cited 2023 Apr 2];8(9). Available from: https://linkinghub.elsevier.com/retrieve/pii/S2405844022020060

View more View less

Competing Interests

No competing interests were disclosed.

Alongside their report, reviewers assign a status to the article:

Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested

Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.

Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions

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The stock market reaction to COVID-19 vaccination in ASEAN

Abstract

Keywords

Introduction

Background and literature review

Figure 1. The percentage (A) and total number (in a million people) of the COVID-19 vaccinated people (B) in ASEAN countries on October 17th, 2021.

Methods

Ethics

Data

(1)

(2)

(3)

Table 1. The stock index list in ASEAN members.

Methodology

(4)

(5)

(6)

(7)

Results

Descriptive analysis

Figure 2. The positive case growth of COVID-19 (A) and the vaccinated people growth (B) in ASEAN countries from March 13th, 2021 until July 7th, 2021.

Figure 3. The daily stock index return in Singapore (A), Vietnam (B), Thailand (C), Philippines (D), Malaysia (E), and Indonesia (F) from March 11th, 2021 until July 7th, 2021.

Panel regression model of the stock reaction

Table 2. Estimation results of panel data regression.

Table 3. The diagnostic testing of the models.

Table 4. The estimation of fixed effects model by using HC estimators and Driscoll and Kraay Robust covariance matrix estimator.

Discussion

Conclusions

Data availability

Underlying data

References

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Figure 1. The percentage (A) and total number (in a million people) of the COVID-19 vaccinated people (B) in ASEAN countries on October 17^th, 2021.

Figure 2. The positive case growth of COVID-19 (A) and the vaccinated people growth (B) in ASEAN countries from March 13^th, 2021 until July 7^th, 2021.

Figure 3. The daily stock index return in Singapore (A), Vietnam (B), Thailand (C), Philippines (D), Malaysia (E), and Indonesia (F) from March 11^th, 2021 until July 7^th, 2021.