Literature DB >> 35998129

The impacts of the Covid-19 pandemic, policy responses and macroeconomic fundamentals on market risks across sectors in Vietnam.

Hung Quang Bui1, Thao Tran2, Hung Le-Phuc Nguyen2, Duc Hong Vo3.   

Abstract

Vietnam has undergone four waves of the Covid-19 pandemic in 2020 and 2021, which have posed significant market risks to various sectors. Understanding the market risk of Vietnamese sectors and its changes is important for policy implementation to support the economy after the pandemic. This study measures the sectoral market risks and examines the effects of the pandemic, policy responses and macroeconomic fundamentals on the market risks across sectors in Vietnam. We employ the Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) techniques to measure the market risks for 24 sectors from 2012 to 2021. The market risk levels across Vietnamese sectors have changed significantly in response to the pandemic. Oil and Gas and Services sectors show the largest potential loss during the two Covid-19 waves in 2020. The Securities sector is the riskiest sector during the last two Covid-19 waves in 2021. Our results indicate that the new Covid-19 cases reported by the Government increase the market risk levels across Vietnamese sectors. On the other hand, enhancing containment and health policy and reducing economic policy uncertainty result in lower market risk across sectors. We also find that macroeconomic fundamentals such as the exchange rate and interest rate significantly affect the market risks across sectors in Vietnam.

Entities:  

Mesh：

Year:  2022        PMID： 35998129      PMCID： PMC9397878          DOI： 10.1371/journal.pone.0272631

Source DB:  PubMed          Journal:  PLoS One        ISSN： 1932-6203            Impact factor:   3.752


1. Introduction

During the 1970s, companies were exposed to significant risks that emerged from the disappearance of fixed-currency parities, volatility of commodity prices, and natural disasters. These sources of risk, in the form of unprecedented events, revolutionize the concept of risk management in the financial sector [1]. Over nearly half a century, risk management has evolved with unparalleled events, typically the Global Financial Crisis (GFC) of 2007–2008 and the current Covid-19 pandemic. Such events are often associated with the change in market risk, thus making market risk management one of the top priorities for companies and investors worldwide. In acknowledging the necessity of effective market risk management, various modern risk management models have been introduced and adopted to address market risk proactively. Typical models in previous studies include the Maximum Loss [2], Expected Shortfall [3], Value-at-Risk [4-6], and Conditional Value-at-Risk [7, 8]. Generally, the Value-at-Risk (VaR) and the Conditional Value-at-Risk (CVaR) are the most widely used risk measurements to observe risk movements in specified markets, such as the stock markets [3, 9–11], commodity market [12], as well as foreign exchange and cryptocurrency market [6]. Previous studies have focused exclusively on the market risk of industries in Australia [13], Europe [14], and ASEAN members [8] for the pre-and post-GFC period. Vietnam has achieved stable economic growth in the past three decades until the emergence of the pandemic in 2020. The national economy grew steadily in the first two quarters of 2021. Still, it declined significantly in the third quarter of the year when the Covid-19 pandemic severely hit Ho Chi Minh City, the country’s largest economic and financial centre. The services sector is a main contributor to the Vietnamese economy. As such, the downturn in services-related business activities reduced the overall growth of the services sector and the entire economy. The services suffering the largest declines include accommodation and food, transportation and warehousing, and wholesale and retail. Fortunately, growth in the agriculture and industry sectors (agriculture, forestry, fisheries, processing and manufacturing, electricity production and distribution) and other services-related sectors (finance, banking and insurance, information and communication) have saved Vietnam’s economy from recession [15]. Such an unbalanced growth across sectors in Vietnam poses significant risks to entrepreneurs and investors, especially during the unpredictable Covid-19 pandemic, which is still ongoing in 2022. Understanding the market risk, its changes, and the effects of policy responses to the current pandemic and macroeconomic fundamentals are important for policy implementation to support the national economy. This important consideration forms the basis for our study to be conducted. Recently, the Covid-19 emergence has further highlighted the importance of understanding the sectoral market risk, especially for the Vietnamese sectors, which have accumulated limited experience in risk management from significant events. Our literature review indicates that only one study was recently conducted to examine the market risk of the Vietnamese sectors and further examined the relationship between the market risk and the Covid-19 pandemic in Vietnam [16]. Other studies have focused on the connectedness among different markets with the exposure to market risk from the Covid-19 pandemic [17-21]. Meanwhile, previous studies have confirmed significant effects of the Covid-19 pandemic [22-25], policy responses [23-30] and macroeconomic fundamentals [31-34] on stock market return and volatility. Recent studies have mainly focused on the effects of the Covid-19 pandemic and policy responses on stock market return and volatility. The effects of macroeconomic fundamentals have largely been ignored in previous studies. Our study is different from previous analyses. We examine the impacts of the pandemic, relevant policy responses and macroeconomic fundamentals on the market risk of 24 Vietnamese sectors from 2012 to 2021. This study uses VaR and CVaR methods to measure the market risk in Vietnam. Our study makes the following contributions to the existing literature. First, we estimate the market risk at the sectoral level in Vietnam, which has largely been ignored in previous studies. Second, we investigate the changes in market risk in the Vietnamese sectors in the last decade, including 2020 and 2021, with the emergence of the Covid-19 pandemic. Third, we then examine the effects of the pandemic, policy responses to the pandemic and macroeconomic fundamentals on market risk across 24 sectors in Vietnam. The paper is structured as follows. Following this introduction, section 2 discusses and synthesizes related literature. Next, data and methodology are presented and discussed in section 3. Section 4 reports and discusses the empirical results, followed by the concluding remarks and implications in section 5 of the paper.

2. Literature review

The Value-at-Risk (VaR) is the maximum loss at a certain confidence level in a given holding period. The VaR appears to be the most widely adopted risk measurement technique. Risk managers and investors use the VaR to implement long-term capital management plans and estimate expected losses [4]. However, the most significant limitation of the VaR is that the method does not consider the scenarios where the VaR estimates are exceeded [35, 36]. In other words, VaR may underestimate the risk level because the method ignores all returns worse than the estimated VaR at the given confidence level. Rockafellar et al. [7] introduce the Conditional Value-at-Risk (CVaR), which can capture the expected losses exceeding the estimated VaR at the same confidence level. CVaR provides an average expected loss rather than a wide range offered by VaR that is difficult to account for. Therefore, VaR and CVaR are widely used separately or together to measure and observe risk movements in different areas. Kourouma et al. [3] examine the risk of the French stock market index, S&P 500, wheat, and crude oil during the GFC using VaR and Expected Shortfall. Terinte [11] employs VaR to examine the risk of five stocks in the Romanian financial market from 2011 to 2015. Powell et al. [12] developed ECVaR, a modified CVaR metric, to investigate the tail risk of several commodities relative to the S&P Goldman Sachs Commodity Index (GSCI) for different economic cycles. Uyar et al. [6] employ VaR to analyze the risk of Bitcoin and conventional currencies. In addition, Rout et al. [10] employ VaR and CVaR to measure the national stock market risks across 20 countries (G20) for the 1998–2020 period. The research period is divided into four regimes covering (i) the Asian financial crisis, (ii) the internet bubble bursting, (iii) the GFC, and (iv) the Covid-19 pandemic. Findings from their analysis indicate a significantly high level of market risk across these 20 countries during the GFC and the Covid-19 pandemic. Among the four regimes, risks during the Covid-19 pandemic highlight the most significant magnitude. Li et al. [9] employ VaR and CVaR to investigate whether Covid-19 new cases and deaths magnify the equity market risk in China, the UK, and the US. They conclude that an increase in Covid-19 new cases or deaths is associated with a significant increase in the market risk across the three countries. From the industry perspective, Allen et al. [13] utilised VaR and CVaR to examine risk across 25 Australian industries for 15 years based on equity price movements. In another study, Allen et al. [14] compare the market risk of the European industries before and during the GFC using various VaR and CVaR techniques. Their results show that the riskiest sectors before the GFC are different from those during the GFC. Vo et al. [8] apply CVaR to examine risk, returns, and portfolio optimization at the industry level for four ASEAN nations, during the 2007–2016 period covering the GFC. Their study reveals that Vietnam and Malaysia witness the shift in rankings of the best sectoral performance from the post-GFC to the normal period. The market risk across sectors appears to change significantly with the extreme events. Ho et al. [16] estimate the market risks across ten Vietnamese sectors before and during the Covid-19 pandemic (2012–2020). Their analysis uses VaR and CVaR to measure the market risk. Their study is then extended to examine the effect of the Covid-19 pandemic on the risk of these Vietnamese sectors. The results show that risks across sectors in Vietnam have surged after the Covid-19 outbreak. However, the market risk decreases during the entire lockdown period. No analysis has been conducted concerning the relationship between the pandemic, policy response, macroeconomic fundamentals and the market risk across sectors in Vietnam. Meanwhile, previous studies have found significant effects of the Covid-19 pandemic [22-25], policy responses [23-30], and macroeconomic fundamentals [31-34] on stock market returns and volatility. Specifically, increased Covid-19 new cases are associated with lower stock market returns [22-24], while the effect on stock market volatility is mixed [25]. Regarding the policy responses, an increase in the containment and health index is associated with positive stock market returns [23, 24, 27] and mitigates market volatility [25]. Meanwhile, heightened economic policy uncertainty is related to negative market returns [26, 30] and strengthens volatility in the short run [28, 29]. LIBOR is found to have significant explanatory power for stock returns [34]. Gold returns predetermine stock returns in the short run during the Covid-19 pandemic [32]. Exchange rate fluctuation has a significant causal relationship with stock return for pre-and post-inflation targeting periods [33] and Covid-19 policy responses [31]. Market risk will also be affected by the pandemic, policy responses and macroeconomic fundamentals due to market volatility and changes in market return. However, the current strands of literature only focus extensively on examining the connectedness among different markets with the exposure to market risk from the Covid-19 pandemic, such as energy markets [17, 18], infrastructure markets [20], stock markets [21], and economic indicators [19]. Key findings from these studies suggest that the Covid-19 pandemic intensified the connectedness among the markets. In addition, Akyildirim et al. [17] indicate a strong connectedness between energy markets worldwide with high uncertainty and low economic sentiment. Hernandez et al. [18] find that oil price volatility during the Covid-19 period exerts a causal effect on the connectedness dynamics across US stock sectors. Susantono et al. [20] recommend using the infrastructure assets to hedge against the USD index and USD-denominated assets due to their persistent negative connection. Uddin et al. [21] present a significant predictive power from the world financial index to the regional market indices. Regarding predictability, Qureshi [19] finds that the Covid-19 pandemic significantly affects the long-term predictive economic variables, which can portend the future economic state. Our literature review indicates that only Ho et al. [16] examine the effects of the Covid-19 pandemic on the market risk across sectors in Vietnam. Their analysis, albeit exciting and recent, has primarily ignored relevant and important factors, such as policy responses and macroeconomic fundamentals, which potentially affect the market risks across sectors. Our literature review confirms that our analysis examining the effects of the Covid-19 pandemic, policy responses and macroeconomic fundamentals across 24 sectors in Vietnam during the ten years is warranted.

3 Data and research methodology

3.1. Data

We obtain the daily sector index of 24 sectors in Vietnam to estimate the market risk. Data are collected from Ho Chi Minh City Stock Exchange (HOSE) and Hanoi Stock Exchange (HNX) from 03 January 2012 to 15 September 2021. These 24 sectors include Aquaculture, Aviation, Banking, Building Materials, Business, Construction, Construction Investment, Development Investment, Education, Energy, Fertilizers, Food, Minerals, Oil and Gas, Pharmaceuticals, Plastic, Real Estate, Rubber, Securities, Services, Steel, Technology, Trade, and Transportation. We use VaR and CVaR to measure the market risk across these 24 sectors. We then examine the effect of the pandemic, policy responses and macroeconomic fundamentals on the market risk of these 24 sectors during the ten years. We use the daily new confirmed Covid-19 cases to proxy the pandemic, consistent with previous studies [22-24]. The Containment and Health Index (CHI) and Economic Policy Uncertainty (EPU) index are used to proxy the policy responses to the Covid-19 pandemic [37, 38]. These choices follow recent studies indicating the significant effects of CHI [23–25, 27] and EPU [26, 28–30] on stock market returns and volatility during the Covid-19 pandemic. We finally use the exchange rate (USD/VND), interest rate (LIBOR), and gold prices to capture the effects of macroeconomic fundamentals on the market risks. These macro-level measures have significant relationships with the stock market returns [31-34]. All variables are summarized in Table 1.
Table 1

Selected variables, descriptions, and sources.

VariableDescriptionSource
Dependent variable
Market riskMarket risk across 24 Vietnam sectorsHOSE and HNX
Independent variables
Covid-19 pandemicNew confirmed Covid-19 cases Our World in Data
Policy responsesContainment and Health Index (CHI) Our World in Data
Economic policy uncertainty (EPU)–Equity Market Volatility: Infectious Disease Tracker FRED | St. Louis Fed (stlouisfed.org)
Macroeconomic fundamentalsExchange rate (USD/VND)Thomson Reuters—Refinitiv
LIBOR—Swiss 3-month LIBOR Middle rate (SNB)
Gold price–Gold Bullion LBM $/t oz

3.2. Methodology

The market returns of each sector are calculated using the logarithmic returns of the daily closing prices of the sector indices. Consequently, we adopt VaR and CVaR as our risk measurement methods. For VaR calculation, the following three standard estimation techniques are generally used in the existing literature, including the Variance-Covariance method, Monte Carlo simulation, and historical simulation [39]. The variance-covariance (or the parametric) approach is used in our study. This parametric approach is a widely used method that assumes returns follow a normal distribution. We then calculate the mean and standard deviation of all sectors’ returns before estimating the market risk, as demonstrated by McNeil et al. [40]. where: μ is the mean of all returns from a sector; σ is the standard deviation; is the inverse of the normal distribution of the returns, and 1-α represents the confidence level. We also employ the parametric approach for CVaR estimation: where: r denotes the returns of a particular sector We use VaR and CVaR to estimate the yearly and monthly market risk across 24 sectors in Vietnam. Our yearly VaR and CVaR capture the annual market risk of each sector from 2012 to 2021. Meanwhile, the monthly VaR captures the monthly market risk of each sector between January 2020 and September 2021. We also rank each sector’s market risk based on the yearly VaR and CVaR, together with monthly VaR. We use the fixed-effects estimation to examine the effect of the Covid-19 pandemic, policy responses and macroeconomic fundamentals on the market risk across 24 sectors in Vietnam. The monthly market risk estimated from the VaR technique is used as a dependent variable. We then convert the daily closing indices of all the independent variables, including new confirmed Covid-19 cases, Containment and Health Index, Economic Policy Uncertainty, Gold prices, Exchange rate, and LIBOR, into monthly closing indices. We also use the logarithmic transformation for the monthly value of these variables except for LIBOR. A panel of 24 sectors and 21 months (from January 2020 to September 2021) is used. where: i and t stand for the sector and the month. Cases denote the percentage change in monthly new Covid-19 cases. CHI is the percentage change in the Containment and Health Index. EPU represents the percentage change in the Economic Policy Uncertainty Index. Exchange is the percentage change in the exchange rate (USD/VND). LIBOR is the value of the LIBOR interest rate. Gold is the percentage change in the gold price, and ε represents the error term.

4. Empirical results

4.1. Market risk across sectors in Vietnam

Table 2 presents the descriptive statistics of the daily returns on 24 sector indices in Vietnam from 03 January 2012 to 15 September 2021. We obtain 2,420 daily observations to calculate the market risks yearly and monthly across 24 sectors in Vietnam. Aviation has the highest average daily return of 0.146 per cent. The Minerals sector shows the lowest average daily return of 0.002 per cent. When risks are considered using the standard deviation of the daily returns, Pharmaceutical is the least risky sector. In contrast, Aviation is the riskiest sector among the 24 sectors in Vietnam.
Table 2

Descriptive statistics of the daily return of 24 sectors in Vietnam.

No.SectorNMean (%)SD (%)Min (%)Max (%)
1Aquaculture2,4200.0941.529-7.1475.622
2Aviation2,4200.1462.700-14.1416.58
3Banking2,4200.0531.536-7.3025.712
4Building Materials2,4200.0771.471-8.7295.096
5Business2,4200.0831.147-9.3977.076
6Construction2,4200.0811.739-8.0907.353
7Construction Investment2,4200.0491.430-7.1695.058
8Development Investment2,4200.0631.991-11.6611.37
9Education2,4200.0611.610-7.8699.422
10Energy2,4200.0841.178-6.5515.031
11Fertilizer2,4200.0541.435-7.8905.786
12Food2,4200.0531.197-7.2914.580
13Mineral2,4200.0021.937-13.2111.36
14Oil & Gas2,4200.0401.920-8.6866.423
15Pharmaceutical2,4200.0721.091-6.2405.643
16Plastic2,4200.0701.284-6.3585.272
17Real Estate2,4200.0491.426-7.0795.557
18Rubber2,4200.0121.458-7.0134.909
19Securities2,4200.0851.880-7.9416.712
20Services2,4200.0651.910-9.5489.081
21Steel2,4200.0911.788-10.667.598
22Technology2,4200.0901.299-7.2525.902
23Trade2,4200.0801.452-7.0495.766
24Transportation2,4200.0631.179-7.1395.228
Table 3 presents the yearly market risks based on VaR (Panel A) and CVaR (Panel B) across 24 sectors in Vietnam. Generally, the market risks calculated by VaR and CVaR at a 95 per cent confidence level have an average of 2.42 per cent and 3.03 per cent, respectively, over the 2012–2021 period. Aviation appears to be the riskiest sector, with a VaR of 3.83 per cent and CVaR of 4.79 per cent. Meanwhile, Pharmaceutical has the lowest risk level among all sectors with a VaR of 1.70 per cent and CVaR of 2.13 per cent.
Table 3

The yearly market risks of 24 sectors in Vietnam, 2012–2021, using VaR (panel A) and CVaR (panel B).

YearAverageAquaAviationBankingBuild MatBusinessConstructCons InvDev InvEduEnergyFertilizerFoodMineralOil & GasPharmaPlasticReal EstateRubberSecuritiesServicesSteelTechTradeTransport
Panel A: VaR at 95 per cent confidence level
Average2.42%2.40%3.83%2.41%2.29%1.76%2.65%2.28%2.89%2.52%1.81%2.22%1.88%3.04%3.06%1.70%2.01%2.26%2.35%2.89%2.97%2.79%2.01%2.26%1.83%
20212.58%2.40%2.39%2.99%2.33%2.65%1.92%2.54%0.94%2.52%1.90%2.85%2.02%2.88%3.49%1.81%1.90%2.67%2.80%4.31%3.25%3.57%2.47%2.88%2.52%
20202.39%2.42%3.43%2.85%2.28%1.72%1.96%2.14%1.02%2.55%1.69%2.45%2.30%2.10%3.43%1.68%1.98%2.63%2.13%2.93%3.70%2.98%2.21%3.28%1.47%
20191.76%1.94%1.73%1.42%1.81%1.01%1.52%1.97%2.43%2.66%1.41%1.72%1.22%2.68%1.96%1.09%1.47%1.62%1.67%1.57%2.51%2.33%1.48%1.66%1.26%
20182.92%3.04%3.21%3.65%3.12%2.21%3.43%2.30%3.82%2.89%2.09%2.31%1.94%4.50%4.44%2.03%2.50%2.56%2.66%3.44%2.86%3.39%2.42%3.27%1.96%
20171.93%2.74%2.12%1.64%1.58%1.17%2.57%1.89%3.36%2.10%1.82%1.93%1.24%2.78%1.94%1.58%1.65%1.38%2.28%1.64%2.44%1.87%1.47%1.91%1.15%
20162.50%2.28%3.66%2.03%1.93%1.60%2.63%1.59%2.52%3.98%1.37%1.26%1.99%4.91%3.21%1.78%1.83%1.85%3.55%2.01%4.90%4.08%1.39%2.01%1.55%
20152.25%2.29%3.18%2.71%2.00%1.37%1.92%2.09%3.87%2.53%1.27%1.69%1.84%2.71%3.36%1.61%1.98%1.87%1.84%2.57%3.34%2.43%1.77%1.87%1.77%
20142.63%2.27%4.19%1.94%2.79%1.92%3.33%2.82%5.44%1.94%1.93%2.64%1.84%3.08%3.27%1.73%2.09%2.59%2.16%3.91%1.83%2.53%2.69%2.06%2.24%
20132.40%2.52%6.40%2.18%2.19%1.50%3.37%2.39%2.64%1.55%2.22%2.22%2.15%2.81%2.40%1.65%2.04%2.45%1.90%2.58%2.63%2.01%1.96%1.79%1.95%
20122.87%2.08%7.98%2.69%2.91%2.42%3.89%3.05%2.91%2.44%2.43%3.15%2.29%1.96%3.08%2.05%2.63%2.98%2.53%3.94%2.26%2.72%2.25%1.84%2.45%
Panel B: CVaR at 95 per cent confidence level
Average3.03%3.00%4.79%3.01%2.87%2.20%3.32%2.84%3.61%3.14%2.27%2.78%2.35%3.78%3.81%2.13%2.51%2.82%2.92%3.61%3.71%3.49%2.52%2.82%2.29%
20213.26%3.04%3.00%3.74%2.94%3.36%2.43%3.18%1.18%3.16%2.37%3.64%2.52%3.67%4.36%2.31%2.39%3.33%3.47%5.46%4.07%4.52%3.16%3.63%3.20%
20202.99%3.07%4.28%3.56%2.86%2.17%2.46%2.70%1.28%3.15%2.12%3.10%2.88%2.65%4.27%2.11%2.49%3.27%2.67%3.72%4.58%3.77%2.77%4.08%1.85%
20192.19%2.41%2.16%1.79%2.25%1.26%1.88%2.46%3.06%3.31%1.76%2.10%1.51%3.32%2.44%1.36%1.82%2.02%2.09%1.93%3.12%2.89%1.87%2.08%1.56%
20183.61%3.81%3.97%4.53%3.84%2.75%4.20%2.84%4.70%3.57%2.60%2.87%2.41%5.57%5.49%2.50%3.06%3.19%3.32%4.26%3.54%4.20%3.01%4.05%2.42%
20172.42%3.39%2.69%2.08%1.99%1.45%3.23%2.35%4.21%2.61%2.27%2.40%1.58%3.48%2.45%2.00%2.05%1.76%2.84%2.09%3.06%2.35%1.85%2.41%1.44%
20163.11%2.83%4.58%2.52%2.42%1.98%3.36%1.98%3.15%4.96%1.71%1.55%2.50%6.10%4.02%2.24%2.31%2.30%4.32%2.48%6.10%5.08%1.74%2.53%1.92%
20152.79%2.84%3.99%3.40%2.51%1.73%2.41%2.61%4.77%3.17%1.59%2.10%2.31%3.30%4.12%1.98%2.49%2.31%2.27%3.19%4.12%3.01%2.21%2.33%2.20%
20143.30%2.88%5.30%2.42%3.55%2.41%4.16%3.52%6.83%2.43%2.43%3.26%2.29%3.83%4.07%2.15%2.60%3.24%2.70%4.89%2.27%3.15%3.36%2.59%2.80%
20133.00%3.13%8.02%2.71%2.74%1.91%4.20%2.97%3.25%1.97%2.81%2.78%2.67%3.45%3.04%2.09%2.59%3.05%2.38%3.21%3.36%2.53%2.45%2.24%2.48%
20123.59%2.61%9.93%3.35%3.61%3.02%4.84%3.78%3.68%3.08%3.06%3.96%2.87%2.42%3.84%2.57%3.29%3.70%3.17%4.90%2.85%3.41%2.78%2.29%3.04%

Note: Aqua–Aquaculture; Build Mat–Building Materials; Construct–Construction; Cons Inv–Construction Investment; Dev Inv–Development Investment; Edu–Education; Tech–Technology; Pharma–Pharmaceutical; Transport–Transportation.

The yearly market risks of 24 sectors in Vietnam, 2012–2021, using VaR (panel A) and CVaR (panel B). Note: Aqua–Aquaculture; Build Mat–Building Materials; Construct–Construction; Cons Inv–Construction Investment; Dev Inv–Development Investment; Edu–Education; Tech–Technology; Pharma–Pharmaceutical; Transport–Transportation. Given Vietnam’s Covid-19 outbreak in February 2020, we consider the change in market risk level across 24 Vietnamese sectors during this pandemic. Table 3 displays that most sectors witness an abrupt increase in market risk from 2019 to 2020, except for Development Investment, Education, and Minerals. Services sector shows the most potential loss in 2020, with a VaR of 3.70 per cent and CVaR of 4.58 per cent. Meanwhile, Development Investment bears the lowest risk level with a VaR of 1.02 per cent and CVaR of 1.28 per cent within the same period. Also, the sector experiencing the most significant change in risk level during 2019–2020 is Aviation, with an increase in VaR by 1.70 per cent and CVaR by 2.12 per cent. We then rank the market risk of 24 sectors by year to further compare the market risk level among sectors from 2012 to 2021 in Table 4. The rankings range from 1 to 24, corresponding to the highest to the lowest risk level using VaR (in panel A) and CVaR (in panel B). These market risk rankings indicate that many sectors are significantly volatile over the 2012–2021 period. Only a few sectors could maintain the risk ranking stability, such as Pharmaceutical.
Table 4

Ranking the yearly market risk of 24 sectors from 2012 to 2021 using VaR (Panel A) and CVaR (Panel B).

YearAquaAviationBankingBuild MatBusinessConstructCons InvDev InvEduEnergyFertilizerFoodMineralOil & GasPharmaPlasticReal EstateRubberSecuritiesServicesSteelTechTradeTransport
Panel A: Risk ranking by VaR at 95 per cent confidence level (1 indicates the riskiest sector, and 24 indicates the least risky sector)
2021161751811201224132281973232110914215614
2020113713201915249211012172221881661514423
2019810199241664220112217231814121535171321
2018119410206193122118241222161514513717823
2017371619234121814102229181521617513201124
2016105111519820942324141718171661323221221
2015104512231411182421186222131617739201519
2014132188214711920102265241611153231291714
2013711413242104231112153922168206517182119
2012211118173691516418235221271321910202414
Panel B: Risk ranking by CVaR at 95 per cent confidence level (1 indicates the riskiest sector, and 24 indicates the least risky sector)
2021161751810201324152271963232111914214812
2020112713201915249211012173221881661514423
2019810199241664220112217231814121535171321
2018119410207193122118241222161514513617823
2017371619234131814112229181721615512201024
2016105121520819942324131718161761423221121
2015104512231411182421166322131718729191520
2014132207214811918102265241611153231291714
2013711413242105231112153922168206417192118
2012211119173681415418235221271321910202416

Note: Aqua–Aquaculture; Build Mat–Building Materials; Construct–Construction; Cons Inv–Construction Investment; Dev Inv–Development Investment; Edu–Education; Tech–Technology; Pharma–Pharmaceutical; Transport–Transportation.

Ranking the yearly market risk of 24 sectors from 2012 to 2021 using VaR (Panel A) and CVaR (Panel B). Note: Aqua–Aquaculture; Build Mat–Building Materials; Construct–Construction; Cons Inv–Construction Investment; Dev Inv–Development Investment; Edu–Education; Tech–Technology; Pharma–Pharmaceutical; Transport–Transportation. Pharmaceutical appears to experience the lowest variation in risk rankings during the ten years. The sector’s risk rankings consistently range from 18 to 24, indicating the lowest market risk level. Further, the pharmaceutical sector maintains a low level of risk. Interestingly, Development Investment and Minerals are often the riskiest sectors in the pre-Covid-19 period from 2014 to 2019. However, this pattern has changed significantly since the pandemic emerged in 2020. Specifically, these two sectors were ranked 24th and 17th out of 24 in 2020. However, before the Covid-19 outbreak, these two sectors were ranked 4th and 1st in 2019. The emergence of Covid-19 appears to change the market risk levels across sectors and their risk rankings in Vietnam. Therefore, we measure the monthly market risk to examine such changes during the pandemic. Tables 5 and 6 provide the monthly market risk and the ranking among 24 sectors in Vietnam. Market risk is measured using the VaR technique.
Table 5

Monthly market risks of 24 sectors in Vietnam from 2020 to 2021 using the VaR technique.

The market risk using VaR at a 95 per cent confidence level
YearMonthAquaAviationBankingBuild MatBusinessConstructCons InvDev InvEduEnergyFertilizerFoodMineralOil & GasPharmaPlasticReal EstateRubberSecuritiesServicesSteelTechTradeTransport
2021Sep1.55%2.04%1.45%2.33%2.15%1.78%2.68%1.00%3.13%1.88%2.46%1.02%2.06%2.17%2.35%1.14%1.13%1.52%1.63%1.19%2.59%1.31%2.02%2.58%
Aug2.40%0.97%2.46%2.15%2.16%1.57%1.83%0.45%1.12%1.28%2.48%1.70%1.96%2.97%1.68%1.43%2.37%1.93%3.14%2.11%2.60%1.62%2.41%3.07%
July3.29%2.78%4.63%2.17%3.22%1.67%3.35%1.12%1.89%1.53%4.18%1.72%2.18%4.63%1.94%2.59%3.53%3.63%6.88%3.42%5.52%3.03%4.80%3.08%
Jun2.79%1.36%2.80%1.96%2.03%1.51%1.48%0.62%2.96%1.11%1.90%0.92%1.65%3.03%1.32%1.57%1.51%1.63%4.81%1.81%3.63%1.56%1.51%1.58%
May1.27%2.37%0.91%1.91%1.30%1.70%1.97%0.55%1.25%1.34%1.56%1.95%2.23%2.68%1.07%1.03%1.32%2.41%2.32%3.55%2.53%1.46%2.46%1.46%
Apr1.53%1.65%2.35%2.36%2.16%1.90%2.61%1.05%2.53%1.81%2.63%1.88%2.57%3.27%0.91%1.52%2.45%2.51%4.07%3.03%3.14%2.29%1.81%2.00%
Mar1.46%1.65%1.71%0.97%1.25%0.81%2.85%0.71%3.09%2.07%2.26%1.31%2.07%2.12%1.45%1.23%0.99%1.87%2.42%3.68%1.75%2.13%1.21%1.01%
Feb2.72%1.66%2.96%2.32%3.39%1.99%2.30%1.11%2.00%1.57%2.61%2.28%2.70%2.69%1.22%1.41%3.83%3.69%3.83%2.43%2.94%2.32%3.71%2.81%
Jan2.95%4.99%5.11%4.12%4.43%3.43%3.42%1.67%3.17%3.64%4.49%4.10%6.35%5.89%3.32%3.74%4.50%4.79%6.52%4.49%5.64%4.68%4.13%4.03%
2020Dec1.55%1.62%1.53%1.53%0.79%1.27%2.53%0.50%3.38%1.06%1.52%0.84%2.81%1.77%0.67%1.14%1.16%1.93%2.15%1.77%2.12%0.78%1.69%1.04%
Nov1.39%1.84%0.93%0.85%0.54%0.93%1.38%0.59%1.02%0.80%2.13%0.97%1.31%1.53%0.64%1.04%1.60%1.01%0.96%1.20%2.44%0.80%1.31%0.54%
Oct1.69%1.93%1.88%1.58%1.16%1.45%3.17%1.22%0.95%1.00%1.98%1.30%3.29%1.37%1.04%1.48%1.67%1.70%2.50%2.64%2.06%1.61%2.09%0.97%
Sep1.09%0.94%1.45%1.08%0.61%0.70%1.41%0.47%2.42%0.76%1.51%0.74%2.31%1.51%0.86%0.73%1.25%0.91%0.83%1.67%1.12%1.46%1.65%0.59%
Aug1.50%1.51%0.98%0.95%0.36%0.64%1.33%0.46%3.14%0.60%1.33%0.79%1.28%0.85%0.95%0.58%0.73%1.48%1.18%1.44%1.73%0.94%1.27%0.51%
July2.87%3.48%3.49%3.43%2.52%2.62%2.61%1.34%1.83%1.97%2.85%3.35%1.41%4.45%1.53%3.62%2.82%3.37%3.85%5.80%3.48%2.72%3.85%2.15%
Jun3.65%3.42%3.17%2.16%1.68%1.96%1.90%0.98%2.76%1.38%3.55%2.59%3.33%3.63%1.59%2.20%3.20%2.81%4.14%4.13%3.69%2.37%3.71%1.62%
May1.81%2.27%1.54%1.58%1.36%1.15%1.32%0.58%1.36%1.79%2.61%1.51%1.06%1.79%0.55%1.65%1.50%1.61%2.17%2.54%2.65%1.60%1.91%1.19%
Apr2.35%3.28%2.69%1.94%1.53%1.72%1.51%0.58%1.18%1.32%1.54%2.20%1.37%4.03%0.88%1.25%2.48%1.48%2.47%2.75%2.24%2.34%3.06%1.53%
Mar3.99%7.28%6.98%5.05%3.89%4.62%3.04%1.98%4.10%3.56%4.08%4.83%2.18%8.07%3.79%3.47%6.88%2.97%5.52%7.30%5.87%4.79%7.78%2.82%
Feb2.93%5.14%2.76%2.45%2.21%2.12%2.74%1.58%4.08%1.82%2.17%2.46%1.25%3.14%2.66%2.58%2.09%2.30%2.64%3.90%2.90%1.90%2.43%1.42%
Jan2.21%3.44%2.78%1.82%1.26%1.32%1.47%0.96%2.12%1.88%2.28%2.87%1.70%3.53%2.19%1.84%1.35%2.33%2.52%2.66%3.09%1.95%2.85%1.55%

Note: Aqua–Aquaculture; Build Mat–Building Materials; Construct–Construction; Cons Inv–Construction Investment; Dev Inv–Development Investment; Edu–Education; Tech–Technology; Pharma–Pharmaceutical; Transport–Transportation.

Table 6

Raking of the monthly market risk for 24 sectors, January 2020 –September 2021.

Ranking of the market risks using VaR at a 95 per cent confidence level (1 indicates the riskiest sector, and 24 indicates the least risky sector)
YearMonthAquaAviationBankingBuild MatBusinessConstructCons InvDev InvEduEnergyFertilizerFoodMineralOil & GasPharmaPlasticReal EstateRubberSecuritiesServicesSteelTechTradeTransport
2021Sep161118791422411352310862122171520319124
Aug823611101915242221516133172091411241872
July111541812221024202362117519168719214313
Jun620587181924422923113211416121102151713
May196231118129242016131082212217571315414
Apr212012111416623819517722422109143131815
Mar141312221723324295168715182110411161920
Feb920614519162418211217101123221421371538
Jan236514121920242218101523211797111481316
2020Dec111012132115324118142028231716647522919
Nov631718241672212192149521114131510120823
Oct118914201621924227181172115121043613523
Sep121481322219241186192516201015173117423
Aug431214241972312081791613211851162151022
July128691816172421201311232225141041715319
Jun581117201819241323714962216101212415321
May741413172119231892152282410161153112620
Apr825121613172422201411191232161874109315
Mar154591612202413181410231171962183711222
Feb517131618822221171224491119151036201423
Jan112617232220241315104181121621987314519
Min (riskiest) 1 4 7 5 12 2 19 1 9 2 4 1 1 6 5 1 4 1 1 1 6 2 2
Max (least risky) 23 23 22 24 23 20 24 24 23 17 23 24 17 24 22 22 21 17 20 21 22 19 23

Note: Aqua–Aquaculture; Build Mat–Building materials; Construct–Construction; Cons Inv–Construction investment; Dev Inv–Development investment; Edu–Education; Tech–Technology; Pharma–Pharmaceutical; Transport–Transportation.

Note: Aqua–Aquaculture; Build Mat–Building Materials; Construct–Construction; Cons Inv–Construction Investment; Dev Inv–Development Investment; Edu–Education; Tech–Technology; Pharma–Pharmaceutical; Transport–Transportation. Note: Aqua–Aquaculture; Build Mat–Building materials; Construct–Construction; Cons Inv–Construction investment; Dev Inv–Development investment; Edu–Education; Tech–Technology; Pharma–Pharmaceutical; Transport–Transportation. Table 5 shows the monthly market risk among 24 sectors in Vietnam. A significant increase in the market risks among all sectors during the February-March 2020 period implies a significant response to the outbreak. However, the extent of response varies differently among sectors. The Trade sector experiences the most significant increase in the market risk by 5.35 per cent, followed by Oil and Gas, Real Estate, and Banking with an increase of 4.93 per cent, 4.79 per cent, and 4.22 per cent, respectively. In contrast, the market risk of Education increases by only 0.02 per cent, which is the lowest increase among all sectors. In summary, we note that most sectors have experienced an increase in the average market risk of about 2 per cent. We also illustrate the results from Table 5 in Fig 1. The market risk increases significantly in March 2020, July 2020, January 2021, and July 2021. These periods coincide with the peaks of the four Covid-19 waves in Vietnam. These findings indicate that Vietnamese sectors respond to the pandemic sensitively. The Oil and Gas sector has exhibited the largest risk level among all sectors during the first Covid-19 wave, while The Services sector exhibits a significant one during the second wave. Such high-risk levels in these two sectors may be due to the Vietnamese government’s social distancing and travel restrictions. During the last two Covid-19 waves, The Securities sector endures the largest potential loss. The income of the Vietnamese and households had been severely affected after the first two Covid-19 waves. In addition, a significant volume of new participants enters the stock market to trade. As a result, the risk to the sector has increased.
Fig 1

Monthly market risk for 24 sectors in Vietnam during Covid-19 pandemic.

This figure presents monthly market risk for 24 Vietnamese sectors during Covid-19 pandemic in 2020 and 2021. 12 pairs of sectors are graphically illustrated. The red line presents the monthly market risks for a Vietnamese sector which appears first in the pair. The black line presents the monthly market risks for a sector which appears second in the pair.

Monthly market risk for 24 sectors in Vietnam during Covid-19 pandemic.

This figure presents monthly market risk for 24 Vietnamese sectors during Covid-19 pandemic in 2020 and 2021. 12 pairs of sectors are graphically illustrated. The red line presents the monthly market risks for a Vietnamese sector which appears first in the pair. The black line presents the monthly market risks for a sector which appears second in the pair.

4.2. Effects of Covid-19, policy responses and macroeconomic fundamentals on market risk

Our analysis indicates a significant increase in market risk across sectors during the four Covid-19 waves from 2020 to 2021. We now examine the effects of the pandemic, policy responses to the pandemic, and macroeconomic fundamentals on market risks across sectors in Vietnam. Table 7 provides the descriptive statistics of all variables. A panel data of 24 sectors for 21 months contains from 480 to 504 observations. Market risk has a mean value of 0.022 and a standard deviation of 0.013.
Table 7

Descriptive statistics of variables used for analysis.

VariableNMeanSDMinMax
Market risk 5040.0220.0130.0040.081
Cases 4805.9332.8731.94612.271
CHI 5043.9610.7320.8074.36
EPU 5042.6410.7030.1783.8
Exchange 50410.0490.00710.03310.064
LIBOR 5040.0230.0080.0140.041
Gold 5047.4850.0627.3517.586
Various estimation techniques, including the pooled OLS, fixed-effects, and random-effects estimators, are used in this analysis. These estimation techniques are consistent with previous studies, such as Ho et al. [16] and Li et al. [9], which examine the impacts of the Covid-19 pandemic on market risk. Table 8 presents empirical results. Various tests, such as the Sargan-Hansen and Breusch-Pagan tests, are conducted to ensure that the estimation methods are appropriate. As presented in Table 8, empirical results are relatively consistent across these estimators. However, the test statistics from the Sargan-Hansen test and Breusch-Pagan test indicate that the fixed-effects estimator is the most appropriate estimation technique for our empirical analysis.
Table 8

Sargan-Hansen test and Breusch and Pagan Lagrangian multiplier test.

Pooled OLSFixed effectsRandom effects
Variables Market risk Market risk Market risk
Cases 0.00185***0.00185***0.00185***
(0.000371)(0.000371)(0.000371)
CHI -0.0311***-0.0311***-0.0311***
(0.00285)(0.00285)(0.00285)
EPU 0.0236***0.0236***0.0236***
(0.00194)(0.00194)(0.00194)
Exchange -1.233***-1.233***-1.233***
(0.103)(0.103)(0.103)
LIBOR 0.671***0.671***0.671***
(0.0903)(0.0903)(0.0903)
Gold -0.000861-0.000861-0.000861
(0.00661)(0.00661)(0.00661)
Constant12.46***12.46***12.46***
(1.007)(1.008)(1.007)
Sargan-Hansen test599.435*** (0.0000)
Breusch-Pagan test210.91*** (0.0000)

Standard errors are in parentheses. ***, **, * are significant at 1, 5, and 10 per cent.

Standard errors are in parentheses. ***, **, * are significant at 1, 5, and 10 per cent. Table 9 presents our empirical results concerning these effects in two scenarios: (i) when all sectors are considered together, and (ii) each of these 24 sectors is considered. We use the fixed-effects model for the first scenario and the pooled OLS for the second scenario. Key findings are presented as follows. We report the results when all sectors are considered together from the first column of Table 9. Except for gold prices, the new Covid-19 cases, Economic Policy Uncertainty, Containment and Health, Exchange rate, and LIBOR affect the market risk. An increase in the number of new Covid-19 cases magnifies market risk. For every 1 per cent increase in the number of new Covid-19 cases over a month, the market risk for all sectors on average increases by 0.00185 per cent. This finding aligns with Li et al. [9] but is different from Ho et al. [16]. We note that Li et al. [9] use the number of new cases, whereas Ho et al. [16] use the dummy variable to proxy the pandemic. Enhancing containment and health policy mitigates market risk, whereas reducing economic policy uncertainty also reduces market risk. For every 1 per cent increase in the Containment and Health index over a month, the market risk decreases by 0.0311 per cent.
Table 9

The effects of the Covid-19 pandemic, policy responses and macroeconomic fundamentals on the market risks across 24 Vietnamese sectors.

Variables All sectors Aqua Aviation Banking Build Mat Business Construct Cons Inv Dev Inv Edu Energy Fertilizer Food
Cases 0.00185***0.0020.0030.004*0.0020.0010.0020.0010.000-0.0010.0000.0020.001
(0.000371)(0.001)(0.002)(0.002)(0.001)(0.002)(0.001)(0.001)(0.001)(0.002)(0.001)(0.002)(0.002)
CHI -0.0311***-0.024*-0.059**-0.049**-0.036**-0.026-0.034**-0.022-0.021***-0.022-0.016-0.023-0.032*
(0.00285)(0.013)(0.020)(0.022)(0.015)(0.018)(0.013)(0.013)(0.006)(0.018)(0.012)(0.016)(0.017)
EPU 0.0236***0.017**0.026**0.037***0.027***0.027**0.025***0.0080.010**0.0090.018**0.018*0.027**
(0.00194)(0.007)(0.011)(0.012)(0.009)(0.010)(0.007)(0.007)(0.003)(0.010)(0.007)(0.009)(0.009)
Exchange rate -1.233***-0.928-0.909-1.325-1.763*-2.102*-1.496*-0.576-0.707*-1.754-1.235-0.725-1.426
(0.103)(0.766)(1.144)(1.265)(0.887)(1.009)(0.724)(0.726)(0.352)(1.053)(0.709)(0.919)(0.949)
LIBOR 0.671***0.9461.3610.9331.245*1.0411.007*-0.2300.3990.8480.3590.0170.960
(0.0903)(0.546)(0.816)(0.902)(0.632)(0.720)(0.516)(0.518)(0.251)(0.751)(0.505)(0.656)(0.677)
Gold -0.0008610.0190.0200.0000.0450.0040.030-0.0350.0150.009-0.040-0.0400.014
(0.00661)(0.055)(0.083)(0.091)(0.064)(0.073)(0.052)(0.053)(0.025)(0.076)(0.051)(0.066)(0.069)
Constant12.46***9.2249.13113.39717.431*21.118*14.865*6.1437.055*17.63912.731*7.63614.271
(1.007)(7.505)(11.220)(12.404)(8.693)(9.894)(7.096)(7.120)(3.450)(10.319)(6.947)(9.014)(9.308)
N480202020202020202020202020
R-squared0.3770.5450.7070.6130.5870.5310.6550.4130.6500.3760.5440.4390.582
Variables All sectors Mineral Oil & Gas Pharma Plastic Real Estate Rubber Securities Services Steel Tech Trade Transport
Cases 0.00185***-0.0020.005*0.0010.0020.003*0.0000.0040.0030.005**0.0010.005**0.001
(0.000371)(0.002)(0.002)(0.001)(0.002)(0.002)(0.002)(0.003)(0.002)(0.002)(0.002)(0.002)(0.001)
CHI -0.0311***-0.002-0.040-0.034**-0.036**-0.047**-0.020-0.031-0.045*-0.044*-0.020-0.052**-0.012
(0.00285)(0.021)(0.025)(0.013)(0.017)(0.018)(0.020)(0.032)(0.024)(0.021)(0.017)(0.019)(0.015)
EPU 0.0236***0.0200.034**0.018**0.0150.043***0.020*0.0270.028*0.024*0.026**0.043***0.019**
(0.00194)(0.012)(0.014)(0.007)(0.009)(0.010)(0.011)(0.018)(0.013)(0.012)(0.010)(0.011)(0.008)
Exchange -1.233***-2.141*-0.802-1.533*-0.584-1.809-1.526-0.803-0.681-0.522-1.101-1.477-1.680*
(0.103)(1.202)(1.452)(0.733)(0.955)(1.035)(1.135)(1.849)(1.365)(1.224)(1.005)(1.102)(0.874)
LIBOR 0.671***0.1410.6450.969*0.5221.0340.5330.0460.3970.3830.3981.408*0.743
(0.0903)(0.857)(1.036)(0.523)(0.681)(0.738)(0.810)(1.319)(0.973)(0.873)(0.717)(0.786)(0.623)
Gold -0.0008610.030-0.0610.0200.0200.0110.021-0.061-0.048-0.003-0.0300.047-0.006
(0.00661)(0.087)(0.105)(0.053)(0.069)(0.075)(0.082)(0.134)(0.099)(0.088)(0.073)(0.080)(0.063)
Constant12.46***21.281*8.57315.335*5.81418.152*15.2138.5847.3155.37511.30214.55216.914*
(1.007)(11.784)(14.238)(7.182)(9.364)(10.149)(11.132)(18.126)(13.380)(11.997)(9.856)(10.801)(8.569)
N480202020202020202020202020
R-squared0.3770.3870.5890.6090.4120.7180.2550.3410.5600.4940.5080.7210.543

Note: Aqua–Aquaculture; Build Mat–Building Materials; Construct–Construction; Cons Inv–Construction Investment; Dev Inv–Development Investment; Edu–Education; Tech–Technology; Pharma–Pharmaceutical; Transport–Transportation. Standard errors in parentheses; ***, **, * are significant at 1, 5, and 10 per cent.

Note: Aqua–Aquaculture; Build Mat–Building Materials; Construct–Construction; Cons Inv–Construction Investment; Dev Inv–Development Investment; Edu–Education; Tech–Technology; Pharma–Pharmaceutical; Transport–Transportation. Standard errors in parentheses; ***, **, * are significant at 1, 5, and 10 per cent. Meanwhile, the market risk drops by 0.0236 per cent for every 1 per cent fall in the EPU index over a month. These findings are also consistent with previous studies [25, 28, 29] in which market volatility reduces with improved containment and health policy and decreased economic policy uncertainty during the period. For macroeconomic fundamentals, an increase in the exchange rate (USD/VND), representing a depreciation of the local currency VND against the $ US, is associated with a reduction in market risk. However, we also find that an increased interest rate heightens market risk. For example, when the local currency VND depreciates 1 per cent against the $ US, the market risk will decrease by 1.233 per cent. Also, a one per cent increase in interest rate, proxied by LIBOR, increases the market risk by 0.671 per cent. These findings also align with previous studies [31, 33, 34]. We now report and discuss the empirical results when each of these 24 sectors is considered. The effects on the market risk appear to be as consistent as all sectors are considered together. The market risks from Building Materials, Construction, Pharmaceutical, and Trade sectors exhibit the same effects when all sectors are considered together. The pandemic affects the Oil and Gas, Steel, and Trade sectors the most, followed by Banking and Real Estate sectors. The policy responses to the pandemic affect many sectors in Vietnam. In particular, the containment and health policy significantly reduces the market risk in 13 out of 24 sectors. A reduction in the EPU index reduces market risks across 18 out of 24 sectors. Exchange rates also affect the market risk for 7 out of 24 sectors in Vietnam. Gold price does not appear to affect the market risk from any sector in Vietnam.

5. Concluding remarks and implications

Vietnam has undergone four waves of the Covid-19 pandemic in the past 24 months, which has dramatically disturbed the risks of various sectors in Vietnam. While empirical studies on the effects of the pandemic have been extensively conducted, the focus on the market risk across sectors has largely been ignored in the current literature, especially in Vietnam. As such, this study examines the effects of the pandemic, policy responses and macroeconomic fundamentals on the market risk among sectors in Vietnam from 2012 to 2021. We employ the VaR and CVaR measures to estimate the market risks for 24 sectors. We first measure the yearly market risk from 2012 to 2021 for each sector in Vietnam to examine how significant the market risks have changed in the past decade for these sectors. We then examine the effects of the pandemic, policy responses, and macroeconomic fundamentals on the market risks. Our results indicate that Aviation is the riskiest sector, whereas Pharmaceutical shows the lowest level of market risk during the 2012–2021 period. Furthermore, the rankings of sectoral market risks have been significantly volatile between 2012 and 2021. Pharmaceutical is the only sector demonstrating the rankings’ stability during the research period. Our results confirm a significant response from all sectors to the Covid-19 outbreaks in Vietnam. Specifically, the market risk increases significantly during the peaks of the four Covid-19 waves in Vietnam. The Oil and Gas sector shows the largest market risk level during the first Covid-19 wave, while The Services sector suffers the most significant potential loss during the second wave. During the last two Covid-19 waves in 2021, The Securities sector suffered the most significant potential loss. Our results indicate that the Vietnamese sectors show a different market risk. Company executives and practitioners should consider this valuable information when making decisions. Companies in the riskiest sectors such as Aviation, Oil and Gas, and Services should focus on their risk management strategies, including product diversification. For example, airlines may need to design an appropriate hybrid model to diversify the revenue streams from passengers and cargo, particularly during an extreme event such as the Covid-19 pandemic. In addition to improving reserves, oil and gas companies should invest in refining and petrochemicals that concentrate on deep processing and the quality of petroleum products. Service companies should leverage online platforms instead of in-person operations disrupted by the pandemic. For example, digital tourism can become an alternative to traditional tourism. In addition, lower-risk sectors such as Pharmaceutical will also need to initiate and implement business strategies to deal with the worst possible scenarios from market risks in the future. Our empirical analysis confirms a significant relationship between the sectoral market risk and the new Covid-19 cases, economic policy uncertainty, containment and health, exchange rate, and interest rate (LIBOR). We find that increasing the number of new Covid-19 cases increases sectoral market risk in Vietnam. Decreased market risks are associated with improved economic policy uncertainty and improved containment and health policy. Our results also indicate that market risks across sectors in Vietnam increase when the Vietnam Dong (VND) appreciates against the $ US. In addition, an increased interest rate leads to increased sectoral market risks. In conclusion, the Covid-19 pandemic affects the market risks for all sectors in Vietnam. Oil and Gas, Steel, and Trade, followed by Banking and Real estate, are the most affected sectors. These findings provide important policy implications for the Vietnamese government, policymakers, and investors. The Vietnamese government should provide the necessary financial and non-financial support to affected sectors to help them recover from the pandemic. Stabilizing domestic gasoline prices should be implemented as gasoline is a significant cost component of the affected sectors. Maintaining this stability will support the performance of these sectors and the entire market. Domestic trade and consumption should be promoted to support the sectors. The government should continue supporting small-medium enterprises in joining industrial clusters and value chains and creating value. For example, the government can implement an interest rate support package for enterprises facing difficulties due to the Covid-19 pandemic. The support package is particularly of help for those that are genuinely struggling but have the potential to recover and grow. Innovative entrepreneurship should also be promoted to create breakthrough business models and market approaches, thereby overcoming the limitations of old models in the context of escalated market risk from the Covid-19 crisis. The government should implement containment and health policies more assertively. Clear plans for several scenarios should be implemented to minimize uncertainty, decreasing market risk for the entire market and sectors. In addition, the State Bank of Vietnam should flexibly manage the exchange rate to effectively affect the foreign exchange market, such as stabilizing exchange rates and enhancing liquidity while still ensuring the international competitive advantage. Investors should know the high-risk sectors for appropriate portfolio diversification strategies, thereby delivering expected returns. Risk-averse investors should adopt hedging strategies to protect their portfolios against significant market risk. Investment decisions in the stock market should consider exchange rates and interest rates. Our study has potential limitations that offer possible directions for further research. First, market risk can be estimated using measures such as expected shortfall and others. Using various measures for market risk provides robustness to the estimates. Second, a nonlinear relationship between market risk and the pandemic, policy responses and macroeconomic fundamentals may also exist. A mechanism for this nonlinear relationship can be initiated and tested. Third, previous studies have examined the connectedness among several markets with the exposure to market risk. However, the connectedness of market risk across sectors remains unaddressed. These limitations and gaps should be thoroughly examined in future studies. (RAR) Click here for additional data file. 20 Apr 2022
PONE-D-22-08126
The Impacts of Covid-19 Pandemic, Policy Responses and Macroeconomic Fundamentals on Market Risks across Sectors in Vietnam
PLOS ONE Dear Dr. Vo, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.
The manuscript requires further refinements with reference to study rationale, review of literature, variables’ selection, empirical outcomes’ discussion, as well as concluding remarks and future research avenues.
Please submit your revised manuscript by Jun 04 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript:
A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols. We look forward to receiving your revised manuscript. Kind regards, Stefan Cristian Gherghina, PhD. Habil. Academic Editor PLOS ONE Journal Requirements: When submitting your revision, we need you to address these additional requirements. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf 2. We note that the grant information you provided in the ‘Funding Information’ and ‘Financial Disclosure’ sections do not match. When you resubmit, please ensure that you provide the correct grant numbers for the awards you received for your study in the ‘Funding Information’ section. 3. We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For more information on unacceptable data access restrictions, please see http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions. In your revised cover letter, please address the following prompts: a) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially sensitive information, data are owned by a third-party organization, etc.) and who has imposed them (e.g., an ethics committee). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent. b) If there are no restrictions, please upload the minimal anonymized data set necessary to replicate your study findings as either Supporting Information files or to a stable, public repository and provide us with the relevant URLs, DOIs, or accession numbers. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories. We will update your Data Availability statement on your behalf to reflect the information you provide. [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes Reviewer #2: Yes Reviewer #3: Yes ********** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes Reviewer #3: Yes ********** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: No Reviewer #2: Yes Reviewer #3: Yes ********** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: No Reviewer #2: Yes Reviewer #3: Yes ********** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: Decision: Accepted with minor revision This study measures the sectoral market risks and examines the effects of the current Covid-19 pandemic, policy responses, and macroeconomic fundamentals on the market risks across sectors in Vietnam. This is a very well written paper in terms of language, robust measures of econometrics analysis is properly executed. Results have also been analyzed critically and reflect policy implication. Therefore, I recommend minor revision as follows: The length of the paper should be reduced. Stress on the most important contribution of your study. Update the recent literature on covid. Akyildirim, E., Cepni, O., Molnar, P., & Uddin, G. S. (2022). Connectedness of energy markets around the world during the COVID-19 pandemic. Energy Economics, 105900. Hernandez, J. A., Shahzad, S. J. H., Sadorsky, P., Uddin, G. S., Bouri, E., & Kang, S. H. (2022). Regime specific spillovers across US sectors and the role of oil price volatility. Energy Economics, 105834. Uddin, G. S., Yahya, M., Goswami, G. G., Lucey, B., & Ahmed, A. (2022). Stock market contagion during the COVID-19 pandemic in emerging economies. International Review of Economics & Finance, 79, 302-309. Susantono, Bambang, Gazi Salah Uddin, Donghyun Park, and Shu Tian. "On Hedging Properties of Infrastructure Assets during the Pandemic: What We Learn from Global and Emerging Markets?." Sustainability 14, no. 5 (2022): 2987. Reviewer #2: Overall Comments The theme of the paper is very interesting and has a lot of practical implications. However, following are some suggestions to improve the paper 1. The study offers an original idea and novel contribution to the existing field of research. There are research gaps explicitly stated but the rationale of study got to be established. 2. The authors should explain that the choice of variables and macroeconomic indicators in detail. What is economic justification of analyzing relationship between sectoral market risk, COVID-19 pandemic effect, policy response and macroeconomic indicators in Vietnam. Explain 3. Please enrich the literature with some recent studies other than research conducted in context of Vietnam for wider readership. There are many studies conducted in given context at international level. How your study is different from existing literature? Explain. See and cite recent research work on COVID-19 pandemic and economy by Qureshi. F (2021). 4. Are the empirical findings similar or different to the findings by earlier studies in the current research framework? Explain 5. The conclusion section should be rewritten. Provide clear and precise information in the conclusion section with focus on policy implications References: Qureshi, F. (2021). COVID-19 pandemic, economic indicators and sectoral returns: evidence from US and China. Economic Research-Ekonomska Istraživanja, 1-31. Reviewer #3: Please present the descriptive statistics for all variables. There is no EPU data for Vietnam (see https://www.policyuncertainty.com/ ). Did you use GLOBAL EPU? It is not clear which method you used to obtain the findings in Table 7. Please also present the test statistics of the assumptions of the method you used. The author(s) should discuss possible directions for further research. ********** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: Yes: Fiza Qureshi Reviewer #3: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. Submitted filename: PONE-D-22-08126.docx Click here for additional data file. 29 May 2022 Dear the Office, Please be advised that we have included responses to reviewers comments in a separate document with this revision. Thank you very much and all the best. Cheers Duc Submitted filename: Response to Reviewers.docx Click here for additional data file. 20 Jun 2022
PONE-D-22-08126R1
The impacts of the Covid-19 pandemic, policy responses and macroeconomic fundamentals on market risks across sectors in Vietnam
PLOS ONE Dear Dr. Vo, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. The manuscript requires further refinements with reference to the quantitative analysis. Please submit your revised manuscript by Aug 04 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript:
If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols. We look forward to receiving your revised manuscript. Kind regards, Stefan Cristian Gherghina, PhD. Habil. Academic Editor PLOS ONE Journal Requirements: Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice. [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #2: All comments have been addressed Reviewer #4: (No Response) Reviewer #5: All comments have been addressed Reviewer #6: All comments have been addressed ********** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #2: Yes Reviewer #4: Yes Reviewer #5: Yes Reviewer #6: Yes ********** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #2: Yes Reviewer #4: Yes Reviewer #5: Yes Reviewer #6: Yes ********** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #2: Yes Reviewer #4: Yes Reviewer #5: Yes Reviewer #6: Yes ********** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #2: Yes Reviewer #4: Yes Reviewer #5: Yes Reviewer #6: Yes ********** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #2: no comments. I am satisfied with the comments addressed ease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) (Limit 100 to 20000 Characters) Reviewer #4: The main purpose of this study is to analyse market risks of Vietnamese sectors and determine the driving factors of market risk. I enjoyed reading the paper and found the results quite interesting. I suppose the paper has been reviewed before and it seems the authors have carefully addressed the reviewers' comments. I have two minor suggestions/comments though: - The paper has potential implications and insights for investors and policy makers alike. However, as it stands, it lacks these implications. The authors could expand more on what their results offer for different stakeholders. - How do the authors make sure their regression models are well-specified? I suggest the authors conduct some diagnostics tests and verify their regression results are reliable. -Finally, what do the results from this study add to our understanding? The authors should compare their findings with previous studies to position their work in the existing literature. Reviewer #5: Authors have addressed all comments from the first-round review. However, authors can strengthen their contribution section when proofreading the article for publication. Reviewer #6: The authors have addressed all the necessary comments for the earlier version of the manuscript. The readability of the paper now is much better. ********** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #2: Yes: Fiza Qureshi Reviewer #4: No Reviewer #5: No Reviewer #6: Yes: Evan Lau ********** [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.
13 Jul 2022 Dear Editor-in-Chief, the Academic Editor and the Reviewers, Thank you very much for the opportunity to revise and resubmit our paper in Round 2. We are very happy to learn that the other five reviewers are satisfied with our revision in Round 1. Nevertheless, comments from Reviewer # 4 in this second-round review are very constructive and insightful. The responses to each of the comments are incorporated into the revised paper. We consider that all comments are very constructive and insightful. Therefore, the response to each comment is incorporated into the revised version of the paper. Our corrections and additional discussions in response to your comments are highlighted in yellow for your convenience. Thank you very much, and all the very best. Submitted filename: Response to Reviewers R&R2.docx Click here for additional data file. 25 Jul 2022 The impacts of the Covid-19 pandemic, policy responses and macroeconomic fundamentals on market risks across sectors in Vietnam PONE-D-22-08126R2 Dear Dr. Vo, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Stefan Cristian Gherghina, PhD. Habil. Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #2: All comments have been addressed Reviewer #4: All comments have been addressed Reviewer #6: All comments have been addressed ********** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #2: Yes Reviewer #4: Yes Reviewer #6: Yes ********** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #2: Yes Reviewer #4: Yes Reviewer #6: Yes ********** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #2: Yes Reviewer #4: Yes Reviewer #6: Yes ********** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #2: Yes Reviewer #4: Yes Reviewer #6: Yes ********** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #2: I am satisfied with the comments incorporated. No comments required. I am satisfied with the comments incorporated. Reviewer #4: The authors have addressed all my comments. I believe that the manuscript has improved significantly after the second round. Therefore, I advise acceptance Reviewer #6: Thanks for the second revision of the paper. All comments been addressed well by the authors. The readability of the paper is now is much enhanced. ********** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #2: Yes: Fiza Qureshi Reviewer #4: No Reviewer #6: Yes: Evan Lau ********** 11 Aug 2022 PONE-D-22-08126R2 The impacts of the Covid-19 pandemic, policy responses and macroeconomic fundamentals on market risks across sectors in Vietnam Dear Dr. Vo: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Stefan Cristian Gherghina Academic Editor PLOS ONE
  8 in total

1.  The effects of daily growth in COVID-19 deaths, cases, and governments' response policies on stock markets of emerging economies.

Authors:  Murat Guven; Basak Cetinguc; Bulent Guloglu; Fethi Calisir
Journal:  Res Int Bus Finance       Date:  2022-04-14

2.  Exchange rate expectation, abnormal returns, and the COVID-19 pandemic.

Authors:  Joscha Beckmann; Robert L Czudaj
Journal:  J Econ Behav Organ       Date:  2022-02-07

3.  The gold-stock market relationship during COVID-19.

Authors:  Pamela Peterson Drake
Journal:  Financ Res Lett       Date:  2021-05-08

4.  Connectedness of energy markets around the world during the COVID-19 pandemic.

Authors:  Erdinc Akyildirim; Oguzhan Cepni; Peter Molnár; Gazi Salah Uddin
Journal:  Energy Econ       Date:  2022-03-04

5.  Death and contagious infectious diseases: Impact of the COVID-19 virus on stock market returns.

Authors:  Abdullah M Al-Awadhi; Khaled Al-Saifi; Ahmad Al-Awadhi; Salah Alhamadi
Journal:  J Behav Exp Finance       Date:  2020-04-08

6.  COVID-19 and market risk: An assessment of the G-20 nations.

Authors:  Bhabani Sankar Rout; Nupur Moni Das; Mohd Merajuddin Inamdar
Journal:  J Public Aff       Date:  2020-12-21
  8 in total

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