COVID-19, government interventions and emerging capital markets performance

COVID-19 Government restriction policy, COVID-19 vaccination and stock markets: Evidence from a global perspective

We use the COVID-19 stringency index to investigate the relationship among COVID-19 government restriction policy, COVID-19 vaccination and stock markets. We find that the impact of the change rate of COVID-19 stringency index on stock returns turns from significant in the pre-vaccination period to insignificant in the post-vaccination period. Bad news from COVID-19 restriction policy cause more stock volatilities than good news. The advent of COVID-19 vaccination weakens the linkage of COVID-19 stringency index and stock market, while COVID-19 stringency index only plays a partially mediate role in the correlation between COVID-19 cumulative vaccination rate and stock market performance.

An interpretable system for predicting the impact of COVID-19 government interventions on stock market sectors

Evaluating and understanding the financial impacts of COVID-19 has emerged as an urgent research agenda. Nevertheless, the impacts of government interventions on stock markets remain poorly understood. This study explores, for the first time, the impact of COVID-19 related government intervention policies on different stock market sectors using explainable machine learning-based prediction models. The empirical findings suggest that the LightGBM model provides excellent prediction accuracy while preserving computationally efficient and easy explainability of the model. We also find that COVID-19 government interventions are better predictors of stock market volatility than stock market returns. We further show that the observed effects of government intervention on the volatility and returns of ten stock market sectors are heterogeneous and asymmetrical. Our findings have important implications for policymakers and investors in terms of promoting balance and sustaining prosperity across industry sectors through government interventions.

COVID-19 and finance scholarship: A systematic and bibliometric analysis

COVID-19 has posed unprecedented challenges to global finances because of its unparalleled global scope, with both concomitant shocks as well as the likely altering of risk assessments and forecasts for the foreseeable future. As the effects of COVID-19 on financial markets and institutions have been widely addressed by various literature, we systematically synthesize this literature. Through a comprehensive search process, we extract and review 818 articles. Appling bibliometric methods, we explore the trends among various research constituents involved in the field. Using multi-dimensional scaling, we identify the intellectual structure of research in the domain and outline four distinct themes. We also identify the evolution and shifts in research within the short span of three years since the inception of COVID-19. Through detailed content analysis, various future research directions are proposed.

The impact of the COVID-19 outbreak on Japanese shipping industry: An event study approach

This paper examines the stock market response of Japanese shipping firms on the COVID-19 outbreak. We adopt an event study method to investigate the announcement effect of COVID-19-related news such as the incident of largest numbers of cases in a cruise ship, the Princess Diamond on February 3, 2020 and the tight border closing by the Japanese Government on March 9, 2020. Our empirical results show that the negative abnormal returns are significant for both of these pessimistic COVID-19-related events. The negative return on the incident of Princess Diamond persisted for 30 trading days. Moreover, the negative abnormal return of port operations was stronger than maritime transportation after 30 days. Furthermore, we find that the tight border closing policy persisted for only eight trading days. Finally, we find that government policy responses are effective to mitigate negative announcement effects on COVID-related news post the tightened border control.

The sum of all SCARES COVID-19 sentiment and asset return

In this study, I constitute a search based COVID-19 sentiment index using Google search volume. I develop an alternative Scared COVID-19 Attitude Revealed by Eager Search (SCARES) index using the household search volume i.e. "coronavirus pandemic", "coronavirus epidemic", and "coronavirus outbreak" of United States (US) during the COVID-19 pandemic. Using daily data from May 1, 2020 to July 30, 2021, I find that SCARES index negatively explains stock market return and subsequent return reversals, implying that households' increased pandemic sentiment negatively affects equity market return. Furthermore, decile regressions on characteristics-sorted portfolio returns show that SCARES index predicts the return reversals of firms that are small, less profitable, and with low investment. I also report that COVID-19 search shocks of households do not significantly predict any of the Fama-French five-factors except SMB (small-minus-big). Moreover, I use two state Markov switching model and find that structural breaks associated with pandemic phases make SCARES positively related to indices i.e. twitter based uncertainty, volatility index, economic policy uncertainty, and business condition in high volatility regime. Finally, sub-period analysis reports that, in stock market context, people start to react slowly and become relatively less responsive to the COVID-19 search keywords. The findings of this paper can assist key stakeholders in the market to carefully analyze the asset return pattern during pandemic regimes.

COVID-19 government interventions and cryptocurrency market: Is there any optimum portfolio diversification?

This study attempts to find the impact of the COVID-19 government interventions on the cryptocurrency market. Using the daily data over the period 2020 M01 to 2022 M1, this study applied the Markov-Regime-switching and MGARCH-DCC approaches for eight cryptocurrencies. Overall, Markov-Regime-switching models reveal that there is an adverse effect of government interventions on cryptocurrencies. However, MGARCH-DCC models suggest that the best possible diversification opportunity exists between Dogecoin and Oil. For robustness, this study applies the MF-DFA and found a consistent result. The findings of this study would help investors and policymakers to formulate optimal investment decision-making.

Modeling the impact of the COVID‐19 outbreak on environment, health sector and energy market

The global outbreak of COVID‐19 disease had a significant impact on the entire globe. Such a notable public health event can be seen as a “black swan” that brings unpredictable and unusual forces into the economic context and that it could typically lead to a chain of adverse reactions and market disruptions. Hence, the purpose of this study is to examine how COVID‐19 affects the environment, health, and the oil and energy markets. To achieve this objective, we used daily data for several measures that refer to the environment, health, and oil and energy, for the first wave of the COVID‐19 pandemic (December 31, 2019–May 22, 2020). The variable integration mix led to the approach of the ARDL model, and the Granger causality test was also employed. These empirical techniques allowed us to examine the cointegration between variables and causal relationships. The econometric results of the ARDL models exhibited that the global new cases and new deaths of COVID‐19 have short and long‐term effects on the environment, the health sector, the oil, and energy measures. However, no significant causal connection was found between the pandemic and the environment, the health sector, or the oil and energy industry, according to the Granger causality test. The uniqueness of current approach consists in the investigation of pandemic impact on the health, environment, oil, and energy sector by applying the ARDL model that permits the analysis of cointegration both in the long run and in the short term. This study provides important insights for investors and policy makers.

Appeal of word of mouth: Influences of public opinions and sentiment on ports in corporate choice of import and export trade in the post-COVID-19 era

With the advent of the post-COVID-19 era, corporate managers of import and export trade are now more sensitive in their daily work, and their decisions are more likely to be influenced by the emotional bias of public opinions, especially regarding cooperation with trade ports of frequent circulation. Therefore, how to manage public opinion and sentiment in the post-COVID-19 era will be a new opportunity and challenge for the marketing management of ports. For the above considerations, through the same frequency verification between public opinions and sentiment on ports and corporate choice of import and export trade, and through analysis of the influence mechanism, the present study demonstrates the positive effects of public opinions and sentiment on ports in corporate choice of import and export trade in the post-COVID-19 era, verifies the significance of shaping word of mouth in port management, puts forward the great role of public opinions and sentiment in the cognitive and emotional empathy in the choice of import and export trade, and provides theoretical guidance for port managers' strategic choices in the post-COVID-19 era.

Effects of COVID-19 on Global Financial Markets: Evidence from Qualitative Research for Developed and Developing Economies

The research aims to prioritize the pandemic's impact on the financial markets of developed and developing economies using a multi-criteria decision-making approach. The results revealed that COVID-19's pandemic effects on financial markets differ between developed and developing nations. COVID-19 pandemic affects developed countries' financial markets more through supply reduction, demand reduction, and economic instability. Regarding developing nations, confidence and expectations, changes in consumption patterns, and the bandwagon effect are the three most significant impacts of COVID-19 pandemic on financial markets. The best decisions to lower the effect of COVID-19 pandemic on developed nations' financial markets are the declaration of the stimulus package and support of small-and-medium-sized enterprises. Contrastingly, in developing countries, support for vulnerable households and declaration of the stimulus package are the best decisions to combat COVID-19's negative impact on their financial markets. As practical policy implications for lowering COVID-19's negative impact on financial markets, the promotion of new financing instruments, reconstruction of the relationship between public and private sectors, and support of vulnerable households and enterprises are highly recommended.

The dark side of globalization: Evidence from the impact of COVID-19 on multinational companies

The COVID-19 pandemic has led to economic and health crises ("twin crises") worldwide. Using a sample of firms from 73 countries over the period January to December 2020, we examine stock price reactions of multinational corporations (MNCs) and purely domestic companies (DCs) to the crisis. We find that, on average, MNCs suffer a significantly larger decline in firm value relative to DCs during the stock market crisis caused by the pandemic with notable heterogeneity in this underperformance across both industry and region. The evidence of MNC underperformance is robust to using abnormal returns, an alternative crisis window, a matched sample that accounts for differences in characteristics between MNCs and DCs, alternative model specifications, and alternative proxies for multinationality. Further analysis on the effect of government responses on the valuation gap suggests that stringent government responses exacerbate MNCs' underperformance. Finally, we show that a stronger financial system mitigates negative crisis returns, especially under stringent government responses, while real factors, such as the firm's supply chain, investments in human capital, research and development, exacerbate negative crisis returns. Our findings have important implications for managers of MNCs and government policymakers alike and contribute to studies on the international diversification-performance relation by demonstrating a dark side of globalization during a tail-risk event.

How Air Quality Affect Health Industry Stock Returns: New Evidence From the Quantile-on-Quantile Regression

This paper discusses the asymmetric effect of air quality (AQ) on stock returns (SR) in China's health industry through the quantile-on-quantile (QQ) regression method. Compared to prior literature, our study provides the following contributions. Government intervention, especially industrial policy, is considered a fresh and essential component of analyzing frameworks in addition to investors' physiology and psychology. Next, because of the heterogeneous responses from different industries to AQ, industrial heterogeneity is thus considered in this paper. In addition, the QQ method examines the effect of specific quantiles between variables and does not consider structural break and temporal lag effects. We obtain the following empirical results. First, the coefficients between AQ and SR in the health service and health technology industries change from positive to negative as AQ deteriorates. Second, AQ always positively influences the health business industry, but the values of the coefficients are larger in good air. In addition, different from other industries, the coefficients in the health equipment industry are negative, but the values of the coefficients change with AQ. The conclusions provide important references for investors and other market participants to avoid biased decisions due to poor AQ and pay attention to government industrial policies.

COVID-19-related government interventions and travel and leisure stock

COVID-19-related government interventions have significantly affected tourism, while the impact of government interventions on the tourism financial market remains essentially unexplored. This paper comprehensively evaluates how COVID-19-related government interventions affected the travel and leisure stock markets based on a panel quantile regression model. Three government interventions (stringency index, containment and health index and economic support index) and two important stock market features (return and volatility) are discussed. The results reveal that the three government interventions are beneficial to the travel and leisure stock market, especially when the market is under adverse conditions. Specifically, containment and health measures lead to an increase in stock returns. Stringency measures and economic support measures promote stock return and restrain stock market volatility. This study provides significant insights for protecting and recovering the travel and leisure stock market by considering when and which government interventions should be implemented.

A Hybrid Spherical Fuzzy MCDM Approach to Prioritize Governmental Intervention Strategies against the COVID-19 Pandemic: A Case Study from Vietnam

The unprecedented coronavirus pandemic (COVID-19) is fluctuating worldwide. Since the COVID-19 epidemic has a negative impact on all countries and has become a significant threat, it is necessary to determine the most effective strategy for governments by considering a variety of criteria; however, few studies in the literature can assist governments in this topic. Selective governmental intervention during the COVID-19 outbreak is considered a Multi-Criteria Decision-Making (MCDM) problem under a vague and uncertain environment when governments and medical communities adjust their priorities in response to rising issues and the efficacy of interventions applied in various nations. In this study, a novel hybrid Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) and Fuzzy Weighted Aggregated Sum Product Assessment (WASPAS-F) model is proposed to help stakeholders such as governors and policymakers to prioritize governmental interventions for dealing with the COVID-19 outbreak. The SF-AHP is implemented to measure the significance of the criteria, while the WASPAS-F approach is deployed to rank intervention alternatives. An empirical case study is conducted in Vietnam. From the SF-AHP findings, the criteria of “effectiveness in preventing the spread of COVID-19”, “ease of implementation”, and “high acceptability to citizens” were recognized as the most important criteria. As for the ranking of strategies, “vaccinations”, “enhanced control of the country’s health resources”, “common health testing”, “formation of an emergency response team”, and “quarantining patients and those suspected of infection” are the top five strategies. Aside from that, the robustness of the approach was tested by performing a comparative analysis. The results illustrate that the applied methods reach the general best strategy rankings. The applied methodology and its analysis will provide insight to authorities for fighting against the severe pandemic in the long run. It may aid in solving many complicated challenges in government strategy selection and assessment. It is also a flexible design model for considering the evaluation criteria. Finally, this research provides valuable guidance for policymakers in other nations.