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

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.

Do non-pharmaceutical policies in response to COVID-19 affect stock performance? Evidence from Malaysia stock market return and volatility

This paper examines the impact of non-pharmaceutical intervention by government on stock market return as well as volatility. Using daily Malaysian equity data from January 28, 2020 to May 31, 2022, the regression analysis with bootstrapping technique reveals that the government's response in combating the deadly virus through Stringency index has shown a positive direct effect on both stock market returns and volatility, and indirect negative effect on stock market returns. The study revealed that international travel restriction and cancelling public events are the major contributors to the growth of volatility when estimated for Malaysia stock market index. On the one hand, heterogenous impact is expected from the perspective of different sectors when the individual social distancing measures were taken into account in determining stock return and volatility. Apart from that, the robustness check for the main findings remains intact in majority of the regression models after incorporating daily COVID-19 death rate, log (daily vaccination) and day-of-the-week effect as additional control variable in alternative.

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.

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.

Can wastewater surveillance assist China to cost-effectively prevent the nationwide outbreak of COVID-19?

China has controlled the nationwide spread of COVID-19 since April 2020, but it is still facing an enormous threat of disease resurgence originating from infected international travelers. Taking the rapid transmission and the mutation of SARS-CoV-2 into consideration, the current status would be easily jeopardized if sporadic locally-transmitted individuals are not identified at an early stage. Clinical diagnosis is the gold standard for COVID-19 surveillance, but it is hard to screen presymptomatic or asymptomatic cases in those who have not exhibited symptoms. Since presymptomatic or asymptomatic individuals are infectious, it is urgent to establish a surveillance system based on other tools that can profile the entire population. Infected people including those who are symptomatic, presymptomatic, and asymptomatic shed SARS-CoV-2 RNA in feces and thereby endow wastewater-based epidemiology (WBE) with an early-warning ability for mass COVID-19 surveillance. In the context of China's "COVID-zero" strategy, this work intends to discuss the practical feasibility of WBE applications as an early warning and disease surveillance system in hopes that WBE together with clinical testing would cost-effectively restrain sporadic COVID-19 outbreaks in China.

Exploring home-based accommodation operators' responses to Covid-19: Implications of untact hospitality adoption

Unlike the mainstream research conducted on the COVID-19 pandemic and its impacts on both large-scale tourism and hospitality firms, and also at the destination level, the current study focused on home-based accommodations in Iran which have experienced rapid development throughout the country. In-depth interviews with a number (n = 45) of such accommodation operators revealed that due to their perceived high vulnerability to the pandemic and self-protection, they adopted "untact hospitality", thereby decreasing their direct interaction with guests. Looking through the lens of Protection Motivation Theory, four main themes were explored: motivations to work in the hospitality industry; local accommodation operators' perception of threat; coping appraisal; and protection behavior intention. The results revealed that many local ventures were unable to survive, leading to the bankruptcy of such units throughout the country. With few exceptions, the public sector's responses to the pandemic, and the hospitality sector's measures, were generally unsuccessful in managing the health crisis. The current study contributes to the risk, crisis preparation and crisis management of hospitality organizations at the local level in the context of their health protection motivation behavior.

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.

Effects of the COVID-19 Pandemic on the Spot Price of Colombian Electricity

COVID-19 disease shocked global economic activity and affected the electricity markets due to lockdown and work-from-home policies. Therefore, this study proposes an empirical analysis to identify the electricity spot price response during the preventive and mandatory insulation in Colombia, where the economic contraction caused the largest decrease in the electricity demand, especially in the industrial sector. The methodology applied was quantile regression to quantify the non-linear effect on the spot price returns, and two sample periods were selected to contrast the results: 2018 and 2019. The main findings showed that regulated demand variation caused the highest variability on the spot price dynamic during the strict quarantine. However, the price could not fully capture the effects of the demand change due to the short duration of the shock and, also, the price variability in 2019 was higher than 2020 by an El Niño shock.