The impact of the COVID-19 outbreak on Chinese-listed tourism stocks

Herding behavior and government policy responses: Evidence from COVID-19 effect

The purpose of this study is to investigate the impact of a sudden shock from the COVID-19 epidemic on the behavioral bias of investors in the stock market of Iran as a developing country. The study also examines whether the government response to the COVID-19 pandemic can reduce investor herding behavior. We have used the Cross-sectional absolute deviation (CSAD) to measure securities dispersion from market returns. The studied period includes the cross-sectional data of the top 50 companies listed on the stock exchange during 2381 working days of the market (from March 1, 2012, to March 1, 2022). Furthermore, we use the semi-parametric estimator of the quantile regression for the data on the Iranian government response during the COVID-19 epidemic taken from the Oxford COVID-19 Government Response Tracker (OxCGRT). The main findings are in order. First, results show that the COVID-19 pandemic caused the formation of herding behavior aggravated by market volatility. Second, we document that the government response stringency index is unsuccessful in reducing investor herding behavior in the Iranian stock market. Finally, given the evidence that herding behavior, as a form of behavioral distortion, can drive security prices away from equilibrium values supported by fundamentals and cause price bubbles, our findings have important implications for policymakers and investors to mitigate herding effects and mis valuations.

An impact assessment of the COVID-19 pandemic on Japanese and US hotel stocks

This study proposes two new regime-switching volatility models to empirically analyze the impact of the COVID-19 pandemic on hotel stock prices in Japan compared with the US, taking into account the role of stock markets. The first model is a direct impact model of COVID-19 on hotel stock prices; the analysis finds that infection speed negatively affects Japanese hotel stock prices and shows that the regime continues to switch to high volatility in prices due to COVID-19 until September 2021, unlike US stock prices. The second model is a hybrid model with COVID-19 and stock market impacts on the hotel stock prices, which can remove the market impacts on regime-switching volatility; this analysis demonstrates that COVID-19 negatively affects hotel stock prices regardless of whether they are in Japan or the US. We also observe a transition to a high-volatility regime in hotel stock prices due to COVID-19 until around summer 2021 in both Japan and the US. These results suggest that COVID-19 is likely to affect hotel stock prices in general, except for the influence of the stock market. Considering the market influence, COVID-19 directly and/or indirectly affects Japanese hotel stocks through the Japanese stock market, and US hotel stocks have limited impacts from COVID-19 owing to the offset between the influence on hotel stocks and no effect on the stock market. Based on the results, investors and portfolio managers should be aware that the impact of COVID-19 on hotel stock returns depends on the balance between the direct and indirect effects, and varies from country to country and region to region.

Analysis of an event study using the Fama-French five-factor model: teaching approaches including spreadsheets and the R programming language

The current financial education framework has an increasing need to introduce tools that facilitate the application of theoretical models to real-world data and contexts. However, only a limited number of free tools are available for this purpose. Given this lack of tools, the present study provides two approaches to facilitate the implementation of an event study. The first approach consists of a set of MS Excel files based on the Fama-French five-factor model, which allows the application of the event study methodology in a semi-automatic manner. The second approach is an open-source R-programmed tool through which results can be obtained in the context of an event study without the need for programming knowledge. This tool widens the calculus possibilities provided by the first approach and offers the option to apply not only the Fama-French five-factor model but also other models that are common in the financial literature. It is a user-friendly tool that enables reproducibility of the analysis and ensures that the calculations are free of manipulation errors. Both approaches are freely available and ready-to-use.

COVID-19 and tourism sector stock price in Spain: medium-term relationship through dynamic regression models

The global pandemic, coronavirus disease 2019 (COVID-19), has significantly affected tourism, especially in Spain, as it was among the first countries to be affected by the pandemic and is among the world's biggest tourist destinations. Stock market values are responding to the evolution of the pandemic, especially in the case of tourist companies. Therefore, being able to quantify this relationship allows us to predict the effect of the pandemic on shares in the tourism sector, thereby improving the response to the crisis by policymakers and investors. Accordingly, a dynamic regression model was developed to predict the behavior of shares in the Spanish tourism sector according to the evolution of the COVID-19 pandemic in the medium term. It has been confirmed that both the number of deaths and cases are good predictors of abnormal stock prices in the tourism sector.

Impact of COVID-19 and economic policy uncertainty on China's stock market returns: evidence from quantile-on-quantile and causality-in-quantiles approaches

COVID-19 unexpectedly ensnared the entire world and wreaked havoc on global economic and financial systems. The stock market is sensitive to black swan events, and the COVID-19 disaster was no exception. Against this backdrop, this study explores the impact of COVID-19 and economic policy uncertainty (EPU) on Chinese stock markets' returns for the period spanning January 23, 2020 to August 04, 2021. The outcomes of the novel quantile-on-quantile regression analysis revealed that both COVID-19 and EPU had a significant negative impact on both Shanghai and Shenzhen stock market returns, while COVID-19 aggravated the level of economic uncertainty in both financial markets. The quantile causality approach of Troster et al. (2018) validates our main estimations. We conclude that COVID-19 and a high level of EPU enervated the returns of China's leading stock markets. Our study provides key insights to policymakers and market participants to determine the behavior of China's stock market returns vis-à-vis COVID-19 during the peak of the pandemic and beyond. Specifically, our findings apprise portfolio investors to augment their portfolio diversification fronts.

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.

Self-restraint, subsidy, and stock market reactions to the coronavirus outbreak: Evidence from the Japanese restaurant industry

This study examined the stock market response of the Japanese restaurant industry to the announcement of the self-restraint request and subsidy for restaurants by the Japanese government during the coronavirus outbreak. Using the event study approach, it was found that the market reacted negatively to the self-restraint request and positively to the subsidy for restaurants. Following the announcement of the self-restraint request, investors in the restaurant industry responded positively to the government's stringent policy responses. Conversely, following the announcement on the "dining-out" subsidy, investors reacted negatively to the stringent government policies. Our findings provide useful information for policy makers and practitioners to mitigate losses in the hospitality industry during the pandemic.

Industries' heterogeneous reactions during the COVID‐19 outbreak: Evidence from Chinese stock markets

This study examines the heterogeneous effects of the COVID‐19 outbreak on stock prices in China. We confirm what is already known, that the pandemic has had a significant negative impact on stock market returns. Additionally, we find, this effect is heterogeneous across industries. Second, fear sentiment can directly cause stock prices to fall and panic exacerbates the negative impact of the pandemic on stock returns. Third, and most importantly, we demonstrate the underlying mechanisms of four firm characteristics and find that those with high asset intensity, low labor intensity, high inventory‐to‐revenue ratio, and small market value are more negatively affected than others. For labor‐intensive state‐owned firms, in particular, stock performance worsened because of higher idle labor costs. Finally, we created an index to measure the relative position of an industry in the supply chain, which shows that downstream companies were more vulnerable to the effects of the pandemic.

A sectoral-level analysis of the short- and long-term impacts of the COVID-19 pandemic on China's stock market volatility

Sampling China’s Shenyin & Wanguo Sectoral Indices for 28 industries and 3272 listed firms included in those indices, and using industry- and firm-level daily data up to December 31, 2020, this paper empirically examined the short- and long-run impacts of the COVID-19 pandemic on stock return volatility. The results of the event study and univariate graphic analysis suggested that the market volatilities of the 28 industries were affected by COVID-19 events at various levels and that the events increased the volatility continuously for up to 6 days. The results of the panel data regression models revealed that the COVID-19-related daily new confirmed cases, daily new deaths, and cumulative cured cases were associated with higher volatility for all industries, although the impact levels were small; the daily deaths impacted volatility more than confirmed and cured cases. Finally, positive and significant effects of firm-specific variables such as total assets, turnover ratio and trading volume were recorded, indicating that fundamental aspects of the company and investors' behaviour also made great sense.

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COVID-19-related new cases, new deaths, and cumulative cured cases were associated with higher stock market volatility.

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COVID-19’s impacts varied across different sectors.

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COVID-19 events increased volatility continuously for up to 6 days.

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COVID-19 daily deaths impacted volatility more than confirmed and cured cases.

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In the long run, the fundamental aspects of the company and investors' behaviour also made great sense.

Determining dependence, centrality, and dynamic networks between green bonds and financial markets

We adopted a network approach to examine the dependence between green bonds and financial markets. We first created a static dependency network for a given set of variables using partial correlations. Secondly, to evaluate the centrality of the variables, we illustrated with-in system connections in a minimum spanning tree (MST). Afterward, rolling-window estimations are applied in both dependency and centrality networks for indicating time variations. Using the data spanning January 3, 2011 to October 30, 2020, we found that green bonds and commodity index had positive dependence on other financial markets and are system-wide net contributors before and after COVID-19. Time-varying dynamics illustrated heightened system integration, particularly during the crisis periods. The centrality networks reiterated the leading role of green bonds and commodity index pre- and post-COVID. Finally, rolling window analysis ascertained system dependence, centrality, and dynamic networks between green bonds and financial markets where green bond sustained their positive dependence all over the sample period. Green bonds' persistent dependence and centrality enticed several implications for policymakers, regulators, investors, and financial market participants.

Impact of COVID-19 on G20 countries: analysis of economic recession using data mining approaches

The G20 countries are the locomotives of economic growth, representing 64% of the global population and including 4.7 billion inhabitants. As a monetary and market value index, real gross domestic product (GDP) is affected by several factors and reflects the economic development of countries. This study aimed to reveal the hidden economic patterns of G20 countries, study the complexity of related economic factors, and analyze the economic reactions taken by policymakers during the coronavirus disease of 2019 (COVID-19) pandemic recession (2019-2020). In this respect, this study employed data-mining techniques of nonparametric classification tree and hierarchical clustering approaches to consider factors such as GDP/capita, industrial production, government spending, COVID-19 cases/population, patient recovery, COVID-19 death cases, number of hospital beds/1000 people, and percentage of the vaccinated population to identify clusters for G20 countries. The clustering approach can help policymakers measure economic indices in terms of the factors considered to identify the specific focus of influences on economic development. The results exhibited significant findings for the economic effects of the COVID-19 pandemic on G20 countries, splitting them into three clusters by sharing different measurements and patterns (harmonies and variances across G20 countries). A comprehensive statistical analysis was performed to analyze endogenous and exogenous factors. Similarly, the classification and regression tree method was applied to predict the associations between the response and independent factors to split the G-20 countries into different groups and analyze the economic recession. Variables such as GDP per capita and patient recovery of COVID-19 cases with values of $12,012 and 82.8%, respectively, were the most significant factors for clustering the G20 countries, with a correlation coefficient (R2) of 91.8%. The results and findings offer some crucial recommendations to handle pandemics in terms of the suggested economic systems by identifying the challenges that the G20 countries have experienced.

Did COVID-19 tourism sector supports alleviate investor fear?

The COVID-19 pandemic presented a dynamic black-swan event to which governments implemented support programmes to reduce sectoral probability of default. This research analyses investor response to such assistance, designed to mitigate the effects of the pandemic upon international aviation and tourism. Investor confidence in such support schemes is estimated through short-term abnormal returns. Results indicate significant differential behaviour, with fiscal policy found to be a dominant and largely effective mechanism generating median abnormal returns of 2.17 %. Specific assistance programmes relating to COVID-19 loan facilities, and the provision of pandemic relief packages significantly alleviated short-term investor concerns with median abnormal returns estimated between 2.87 % and 3.89 % respectively. Our empirical results offer investors and policymakers an additional layer of information.

Contagion Effect of Financial Markets in Crisis: An Analysis Based on the DCC–MGARCH Model

Global crises have created unprecedented challenges for communities and economies across the world, triggering turmoil in global finance and economy. This study adopts the dynamic conditional correlation multiple generalized autoregressive conditional heteroskedasticity (DCC–MGARCH) model to explore contagion effects across financial markets in crisis. The main findings are as follows: (1) the financial crisis and COVID-19 pandemic intensified the connection between the Chinese and US stock markets in the short term; (2) the dynamic conditional correlations (DCCs) during the COVID-19 pandemic are higher than those during the 2008 financial crisis owing to the further opening of the Chinese capital market, and financial institutions’ investments in the European market are higher than those in the American markets; (3) a stepwise increase is observed in the dynamic conditional correlation between the returns on the S&P 500 Index and SSEC during and after the onset of a destructive crisis; and (4) a unidirectional contagion effect exists between the Chinese market and US market, and the Hong Kong stock market contributes to the risk spillover. Effective transmission channels of external negative shocks may be investors’ sentiments, financial institutions, and the RMB exchange rate in the stock markets. This study provides useful suggestions to authorities formulating financial regulations and investors diversifying risk investments.

COVID-19 Shock, Financial Flexibility, and Hotels' Performance Nexus

This study investigates the nexus of coronavirus disease 2019 (COVID-19) shock, financial flexibility (FF), and firm performance (FP) in Taiwan listed hotel firms. Quantile regression (QR) methods were used to analyze the data from Taiwan Stock Exchange listed hotel firms between 2020 Q1 and 2021 Q2. The results evidence that there is an inversed U-shaped linkage between FF and FP for the hotel industry. Additionally, FF has an inverted U-shaped effect on FP for the asset-light hotel firms for all quantiles except the 50th quantile. In addition, FF also has an inverted U-shaped impact on FP for the asset-heavy hotel firms in the 10th and 90th quantiles. A significant finding in this study is that there is a concave non-linear relationship between FF and FP, consistent with the law of diminishing marginal return. That is, with an increase in FF, the FP is on the rise; when FF exceeds the inflection point level, the FP begins to decline. Thus, a firm must ensure that the FF strategy it adopts must be the most efficient and effective, i.e., it must bring the trade-off between costs and benefits. The empirical results highlight the need for the hotel industry of Taiwan to take the rolling adjustment and optimization of FF after the COVID-19 pandemic for long-term sustainability.

Sail Away to a Safe Harbor? COVID-19 Vaccinations and the Volatility of Travel and Leisure Companies

This paper examines the impact of vaccination programs on the stock market volatility of the travel and leisure sector. Using daily data from 56 countries over the period from January 2020 to March 2021, we find that vaccination leads to a decrease in the investment risk of travel and leisure companies. Vaccination results in a decrease in the volatility of stock prices of travel and leisure companies. The drop in volatility is robust to many alternative estimation techniques, different volatility measures, and various proxies for vaccinations. Moreover, this effect cannot be explained by an array of control variables; this includes the pandemic itself and both the containment and closure policies that followed. Furthermore, the beneficial role of vaccinations is relatively stronger in emerging markets than in developed ones.

Coronavirus Disease 2019 Safety Measures for Sustainable Tourism: The Mediating Effect of Tourist Trust

Coronavirus disease 2019 (COVID-19) pandemic is continuing to have severe effects on tourism-related industries, as safety precautions have become essential to follow. Based on this, this study aims to explore the role of perceptions of the tourist of safety in tourism destination choice with the mediating effect of tourist trust (TT) in the context of the Chinese tourism sector. In addition, this study considers improvements to safety measures for sustainable tourism and the benefits of the technology transformation in the travel industry because of COVID-19. For this study, a quantitative approach was used, and data were collected through convenient sampling. The questionnaire was measured on a 5-point Likert scale, and a cross-sectional approach was adopted for data analysis. The findings of this study show that the effect of the perceived safety of the social environment, perceived safety of facility and equipment elements, perceived safety of human elements, perceived safety of management elements, and perceived safety of natural environments is significant and positive on the tourist destination choice (TDC). In addition, TT is a significant mediator between these elements and TDC. Furthermore, this study concluded that COVID-19 had increased travel anxiety, with particularly negative effects on the Chinese tourism sector, but that the adoption of perceived safety measures could be beneficial in regaining TT for traveling, eventually giving tourists confidence in choosing their traveling destination.

Role and Usage of Social Media in COVID-19- An Analysis of Vaccination Related Conspiracy Theories

There are various misconceptions related to the COVID-19 and the vaccine. This study attempts to identify the role of social media in spreading the misinformation related to COVID-19 and Vaccination. This study will help the agencies to identify the categories of misconceptions and the vaccination-related conspiracy theories dispersed in the social media. In the analysis, seven clusters were found, and the concept map presents seven general misconceptions categories, similarly six subcategories under vaccination related conspiracy theories were found. This study concludes that vaccination related misconception circulated in social media is a serious issue which could affect the vaccination rate severely. Hence a multipronged tactic should be adopted having the components of counter-information strategy, sharing information from authentic sources, educating the general population to go for rigorous review of the information, and improving the health literacy level.

Price and volatility spillovers between global equity, gold, and energy markets prior to and during the COVID-19 pandemic

This study sets out to provide fresh evidence on the dynamic interrelationships, at both return and volatility levels, between global equity, gold, and energy markets prior to and during the outbreak of the novel coronavirus. We undertake our analysis within a bivariate GARCH(p, q) framework, after orthogonalizing raw returns with respect to a rich set of relevant universal factors. Under the COVID-19 regime, we find bidirectional return spillover effects between equity and gold markets, and unidirectional mean spillovers from energy markets to the equity and gold counterparts. The results also suggest the presence of large reciprocal shock spillovers between equity and both of energy and gold markets, and cross-shock spillovers from energy to gold markets. Most probably driven by the recent oil price collapse, energy markets appear to have a substantial cross-volatility spillover impact on the others. Our results offer implications for policymakers and investors.

The impact of COVID-19 outbreak on hotels' value compared to previous diseases: the role of ALFO strategy

By using the Event Study Method (ESM), this paper aims to examine the effect of new coronavirus (SARS-CoV-2) disease (COVID-19) outbreak on the market performance of the hotel industry in the U.S. We also compare the impact of COVID-19 outbreak with three previous diseases outbreaks. The results show that there is a negative influence of the diseases outbreaks on stock returns of hotels in the U.S. However, the impact of COVID-19 is incomparably higher in magnitude compared to previous diseases. Furthermore, given the importance of following flexible corporate strategies to adapt to new and unpredicted situations, it is found that the ALFO (assets-light, fee-orientated) strategy acts as a mitigator for the predicted market value drop due to the pandemic.

Has COVID-19 Changed the Hedge Effectiveness of Bitcoin?

The Bitcoin market has become a research hotspot after the outbreak of Covid-19. In this paper, we focus on the relationships between the Bitcoin spot and futures. Specifically, we adopt the vector autoregression-dynamic correlation coefficient-generalized autoregressive conditional heteroskedasticity (VAR-DCC-GARCH) model and vector autoregression-Baba, Engle, Kraft, and Kroner-generalized autoregressive conditional heteroskedasticity (VAR-BEKK-GARCH) models and calculate the hedging effectiveness (HE) value to investigate the dynamic correlation and volatility spillover and assess the risk reduction of the Bitcoin futures to spot. The empirical results show that the Bitcoin spot and futures markets are highly connected; second, there exists a bi-directional volatility spillover between the spot and futures market; third, the HE value is equal to 0.6446, which indicates that Bitcoin futures can indeed hedge the risks in the Bitcoin spot market. Furthermore, we update the data to the post-Covid-19 period to do the robustness checks. The results do not change our conclusion that Bitcoin futures can hedge the risks in the Bitcoin spot market, and besides, the post-Covid-19 results indicate that the hedging ability of Bitcoin futures increased. Finally, we test whether the gold futures can be used as a Bitcoin spot market hedge, and we further control other cryptocurrencies to illustrate the hedging ability of the Bitcoin futures to the Bitcoin spot. Overall, the empirical results in this paper will surely benefit the related investors in the Bitcoin market.

Impact of Perceived Organizational Support on OCB in the Time of COVID-19 Pandemic in Hungary: Employee Engagement and Affective Commitment as Mediators

The performance of the employees and productivity of each individual, in general, have been badly affected because of the COVID-19 pandemic. Organizational citizenship behavior is regarded as an interpretation of the performance of the employee which is essential to contribute more to the organization’s processes and success. Therefore, to increase the organizational effectiveness and achieve its goals, it is crucial to understand the factors affecting the organizational citizenship behavior of the employees. This study aims to examine the impact of perceived organizational support on organizational citizenship behavior with the mediating role of employee engagement and affective commitment. To collect the data for this study, a linear snowball sampling method was used, and 380 foreign employees working in different service companies in Hungary participated in the survey. Structural equation modeling (SEM) was used to test the proposed hypothesis. The results of the study revealed that perceived organizational support positively associated with organizational citizenship behavior and this relationship is also strongly mediated by employee engagement. On the other hand, employee engagement and affective commitment pose a direct positive influence on organizational citizenship behavior. This study has theoretical and practical implications as it will provide a comprehensive framework to better understand the factors influencing the organizational citizenship behavior of the employees.

The impacts of ICTs on tourism development: International evidence based on a panel quantile approach

Information and communication technologies (ICTs) have transformed the travel and leisure sector worldwide, yet until now there are no studies presenting international evidence of the different impacts of ICTs (i.e., Internet usage, secure Internet servers, mobile cellular subscriptions, high-technology export, communications as well as computer, and fixed broadband subscriptions) on tourism development (i.e., international traveler arrivals, increased international tourism receipts, and travel and leisure sector returns) by considering countries with different tourism development processes (e.g., high or low tourism development quantile). It is possible that ICTs have diverse or non-linear impacts on countries undergoing varying tourism development processes. Using international data based on a new panel quantile approach, this research thus aims to explore whether ICTs affect tourism development and looks into the possible asymmetric and non-linear relationships among the many variables. Results show that increasing mobile cellular subscriptions, secure Internet servers, and fixed broadband subscriptions have greater positive effects on traveler arrivals. ICTs also asymmetrically and non-linearly influence tourism across different quantiles. Non-global financial sub-periods and developing nations gain benefits from ICTs’ establishment. Lastly, there are geographic differences in the ICTs-tourism nexus.