Structural Breaks in Interactive Effects Panels and the Stock Market Reaction to COVID-19

Dealing with structural breaks is an essential step in most empirical economic research. This is particularly true in panel data comprised of many cross-sectional units, which are all affected by major events. The COVID-19 pandemic has affected most sectors of the global economy;however, its impact on stock markets is still unclear. Most markets seem to have recovered while the pandemic is ongoing, suggesting that the relationship between stock returns and COVID-19 has been subject to structural break. It is therefore important to know if a structural break has occurred and, if it has, to infer the date of the break. Motivated by this last observation, the present article develops a new break detection toolbox that is applicable to different sized panels, easy to implement and robust to general forms of unobserved heterogeneity. The toolbox, which is the first of its kind, includes a structural change test, a break date estimator, and a break date confidence interval. Application to a panel covering 61 countries from January 3 to September 25, 2020, leads to the detection of a structural break that is dated to the first week of April. The effect of COVID-19 is negative before the break and zero thereafter, implying that while markets did react, the reaction was short-lived. A possible explanation is the quantitative easing programs announced by central banks all over the world in the second half of March.

BIST Tourism and BIST Electricity Index Relationship

In this study, which is based on daily data, the relationship between BIST electricity index and BIST tourism index was measured between 2012:M9 – 2022:M9 periods. The aim of the study is to measure the relationship between BIST electricity index and BIST tourism index. VAR Granger causality test was applied to determine whether there is any causal relationship between the variables. It has been determined as a result of the analysis that the BIST electricity index has no effect on the BIST tourism index. Two-way ineffectiveness was determined among the variables. In addition, it was obtained as a result of the analysis that the applied correlation relationship was weak between these variables. The results obtained from the study are important in terms of measuring the effects among BIST indices.

The Bank of Japan's exchange traded fund purchases: a help or hindrance to market efficiency?

We examine the impact of the Bank of Japan's exchange traded fund (ETF) purchases on two aspects of market efficiency—long-range dependence and price delay—of the TOPIX and Nikkei 225 indices. An increase in ETF purchases results in lower long-range dependence for both indices while the impact on the price delay varies according to index and measure. A sub-period analysis shows that the impact on market efficiency varies over time, with the dominant pattern being a delayed harmful effect, followed by a positive impact and thereafter a negative effect. The implications of these findings are discussed.

Asian perspective of capital market performance amid the COVID 19 pandemic

PurposeThe purpose of this research is to investigate the short-term capital markets' reactions to the public announcement first local detection of novel corona virus (COVID 19) cases in 12 major Asian capital markets.Design/methodology/approachUsing the constant mean return model and the market model, an event study methodology has been implied to determine the cumulative abnormal returns (CARs) of 10 pre and post-event trading days. The statistical significance of the data was assessed using both parametric and nonparametric test statistics.FindingsFirst discovery of local COVID 19 cases had a substantial impact on all 12 Asian markets on the event day, as shown by statistically significant negative average abnormal return (AAR) and cumulative average abnormal return (CAAR). The single factor ANOVA result has also demonstrated that there is no variability among 12 regional markets in terms of short-term market responses. Furthermore, there is little evidence that these major Asian stock market indices differ significantly from the FTSE All-World Index which might suggest possible spillover impact and co-integration among the major Asian capital markets. The study further discovers that market capitalization and liquidity did not have any significant impact on market reaction to announcement.Research limitations/implicationsThe study's contribution might have been compromised by the absence of socio-demographic, technical, financial and other significant policy factors from the analysis.Practical implicationsThese findings will be considerably helpful in tackling this unprecedented epidemic issue for personal and institutional investors, industrial and economic experts, government and policymakers in assessing the market in special circumstances, diversifying risk and developing financial and monetary policy proposals.Originality/valueThis paper is the first to examine the effects of local COVID 19 detection announcement on major Asian capital markets. This study will add to the literature by investigating unusual market returns generated by infectious illness outbreaks and the overall market efficiency and investors' behavioral pattern of major Asian capital markets.

Hedging potentials of green investments against climate and oil market risks

PurposeThis study aims to examine the ability of clean energy stocks to provide cover for investors against market risks related to climate change and disturbances in the oil market.Design/methodology/approachThe study adopts the feasible quasi generalized least squares technique to estimate a predictive model based on Westerlund and Narayan's (2015) approach to evaluating the hedging effectiveness of clean energy stocks. The out-of-sample forecast evaluations of the oil risk-based and climate risk-based clean energy predictive models are explored using Clark and West's model (2007) and a modified Diebold & Mariano forecast evaluation test for nested and non-nested models, respectively.FindingsThe study finds ample evidence that clean energy stocks may hedge against oil market risks. This result is robust to alternative measures of oil risk and holds when applied to data from the COVID-19 pandemic. In contrast, the hedging effectiveness of clean energy against climate risks is limited to 4 of the 6 clean energy indices and restricted to climate risk measured with climate policy uncertainty.Originality/valueThe study contributes to the literature by providing extensive analysis of hedging effectiveness of several clean energy indices (global, the United States (US), Europe and Asia) and sectoral clean energy indices (solar and wind) against oil market and climate risks using various measures of oil risk (WTI (West Texas intermediate) and Brent volatility) and climate risk (climate policy uncertainty and energy and environmental regulation) as predictors. It also conducts forecast evaluations of the clean energy predictive models for nested and non-nested models.

The impact of COVID-19 on the portfolio optimization

PurposeThis article unveils first the lead–lag structure between the confirmed cases of COVID-19 and financial markets, including the stock (DJI), cryptocurrency (Bitcoin) and commodities (crude oil, gold, copper and brent oil) compared to the financial stress index. Second, this paper assesses the role of Bitcoin as a hedge or diversifier by determining the efficient frontier with and without including Bitcoin before and during the COVID-19 pandemic.Design/methodology/approachThe authors examine the lead–lag relationship between COVID-19 and financial market returns compared to the financial stress index and between all markets returns using the thermal optimal path model. Moreover, the authors estimate the efficient frontier of the portfolio with and without Bitcoin using the Bayesian approach.FindingsEmploying thermal optimal path model, the authors find that COVID-19 confirmed cases are leading returns prices of DJI, Bitcoin and crude oil, gold, copper and brent oil. Moreover, the authors find a strong lead–lag relationship between all financial market returns. By relying on the Bayesian approach, findings show when Bitcoin was included in the portfolio optimization before or during COVID-19 period;the Bayesian efficient frontier shifts to the left giving the investor a better risk return trade-off. Consequently, Bitcoin serves as a safe haven asset for the two sub-periods: pre-COVID-19 period and COVID-19 period.Practical implicationsBased on the above research conclusions, investors can use the number of COVID-19 confirmed cases to predict financial market dynamics. Similarly, the work is helpful for decision-makers who search for portfolio diversification opportunities, especially during health crisis. In addition, the results support the fact that Bitcoin is a safe haven asset that should be combined with commodities and stocks for better performance in portfolio optimization and hedging before and during COVID-19 periods.Originality/valueThis research thus adds value to the existing literature along four directions. First, the novelty of this study lies in the analysis of several financial markets (stock, cryptocurrencies and commodities)' response to different pandemics and epidemics events, financial crises and natural disasters (Correia et al., 2020;Ma et al., 2020). Second, to the best of the authors' knowledge, this is the first study that examine the lead–lag relationship between COVID-19 and financial markets compared to financial stress index by employing the Thermal Optimal Path method. Third, it is a first endeavor to analyze the lead–lag interplay between the financial markets within a thermal optimal path method that can provide useful insights for the spillover effect studies in all countries and regions around the world. To check the robustness of our findings, the authors have employed financial stress index compared to COVID-19 confirmed cases. Fourth, this study tests whether Bitcoin is a hedge or diversifier given this current pandemic situation using the Bayesian approach.

Performance Evaluation of Tourism and Hospitality Companies in the Indian Stock Market, A Post-Covid-19 perspective

The Covid-19 pandemic affected the tourism industry's supply chain and reflected its performance and financial market. This paper aims to evaluate the performance of selected tourism-related companies listed in the Indian stock market. This study evaluates the performance of companies share prices and their business performance in post covid perspective. No studies have been conducted before on the performance evaluation of tourism-related companies listed in the Indian Stock Market from a post covid perspective. Fundamental data analysis for the reports from 2018 to 2022 and the share price charts from 2019 to 2022 was undertaken by twenty-five companies in four categorised sectors: Travel Agencies, hotels and resorts, Airlines, and Amusement parks. This study unveils that companies are underperforming in post covid and at the same time, they performed well in the share market after a negative correction due to covid-19. Airline companies are the most affected and least performed in the stock market by their share price growth. The study result helps investors and people interested in the share market assess the influence of a pandemic situation and to help in decision-making related to investment in the tourism and hospitality industry.

COVID-19 full vaccination and blockchain size: empirical evidence from the cryptocurrency market

PurposeThis paper aims to analyse COVID-19 indices and blockchain features on Bitcoin and Ethereum returns, respectively. The authors focus on the most used and owned cryptocurrencies that cover Europe, the US and Asian countries.Design/methodology/approachAn autoregressive distributed lag panel (pooled mean group and mean group) is utilized, and a robustness check is incorporated by using a Random Effect Model and Generalized Method of Moments (GMM).FindingsFour new findings were discovered, including (1) the vaccine confidence index (VCI) pushes economic recovery and increased demand for the Bitcoin market, but the opposite result was interestingly observed from Ethereum;(2) the blockchain features were revealed to be essential to Bitcoin, while they were irrelevant to Ethereum for short-run country-specific results;(3) the hash rate and network difficulty moved inversely during the pandemic;and (4) the government played a significant role in taking action during uncertain times and regarding cryptocurrency policies.Research limitations/implicationsVCI is constructed by the most used vaccine type in our sample countries (i.e. Pfizer), as the data for a specific classification by each type is still unavailable.Practical implicationsProviding an evenly distributed vaccination program primary vaccination series against COVID-19 to the citizens is an essential duty of the government. Bitcoin policymakers and investors should watch the COVID-19 vaccine distributions closely as it will affect its return. Ethereum is emphasized to keep developing its smart contract which appeared to outplay other blockchain features. Cryptocurrency investors should be wise in their investment decisions by analysing the news thoroughly.Social implicationsThis research emphasizes that the success in the roll-out of COVID-19 vaccination requires citizens' willingness to participate and their trust in the vaccine's efficacy. Such self-awareness and self-discipline in society can ultimately empower individuals and stabilise the economy. Nevertheless, the implementation of health protocols is still highly required to prevent the spread of new variants of COVID-19.Originality/valueThis is the first study that attempts to construct a VCI which denotes the confidence derived from the administration of full-dose COVID-19 vaccines (an initial vaccine and a second vaccine). The authors further find the impact on cryptocurrency returns. Next, blockchain size is utilized as a new determinant of cryptocurrencies.

Impact of Covid-19 Pandemic on the Investment Behavior of DIIs and FIIs on Indian Debt and Equity Markets

This paper aims to examine the impact of the Covid-19 pandemic on the investment behaviours of both Domestic Institutional Investors (DIIs) and Foreign Institutional Investors (FIIs) in the Indian debt and equity markets. The study is based on the daily time-series data from January 01,2015, to June 03, 2020. The study has constructed three Structural Vector Auto Regression dynamic models to compare the investment behaviors of FIIs and DIIs in both pre-and post-pandemic periods. The results indicate that the Institutional Investors' activities do not significantly impact the equity returns in the Indian markets, which has remained so in the wake of Covid-19. The debt purchases and sales for the DIIs are relatively more inelastic to market returns and reflect the risk-averse investment attitude of DIIs because of the negligible impact of Covid-19. There is a drop in the risk appetite of the FIIs due to a rise in the share of debt holdings in their portfolio in the wake of the Covid-19 pandemic.

PREDICTIVE ABILITY OF FINANCIAL AND NON-FINANCIAL PERFORMANCE FOR FINANCIAL STATEMENT PUBLICATION TIME FRAME: MODERATING ROLE OF COVID-19 PANDEMIC

Objetivo: Este estudo examinou a capacidade de desempenho financeiro e nao financeiro na previsäo do tempo de publicaçao de relatórios financeiros, moderada pela pandemia da COVID-19. Referenciái teórico: A teoria dos sinais postula que a administraçâo desempenha um papel crucial no fornecimento de informaçöes as partes interessadas sobre as condiçöes da empresa (Brigham & Houston, 2001). De acordo com Spence (1973), as empresas estao motivadas a fornecer informaçöes relevantes as partes interessadas. Se as condiçöes de desempenho sao boas, a empresa tende a acelerar o processo de apresentaçao de demonstraçöes financeiras. Por outro lado, se o desempenho for ruim, há uma tendencia a atrasar a publicaçao dos relatórios financeiros. O longo período de tempo para a publicaçao de relatórios financeiros pode indicar más noticias que a empresa tem, de modo que ela ainda tem que publicar as noticias para o público. Scott (2015) sugere que quando os gerentes souberem que há noticias desfavoráveis sobre a condiçao da empresa no futuro, evitarao publicar estas informaçöes ou pelo menos atrasaräo a apresentaçao das demonstraçöes financeiras. Método: O desempenho financeiro foi medido por quatro indicadores: lucratividade, liquidez e solvencia. Enquanto isso, o desempenho nao financeiro variável foi medido pelo indice de boa governança corporativa (GCG) e pela reputaçao dos auditores. O modelo proposto foi testado com base nos dados quantitativos coletados de 156 empresas de manufatura listadas na Bolsa de Valores da Indonesia (IDX) a partir de 2018 e 2020. A análise de regressao múltipla foi realizada para analisar e interpretar os dados. Resultados e conclusao: O resultado indica que a solvencia, a boa governança corporativa e a reputaçao do auditor foram preditores significativos do período de publicaçao do relatório financeiro. Entretanto, a capacidade preditiva de rentabilidade e liquidez no prazo de publicaçao nao foi considerada significativa. Além disso, os resultados mostram que a pandemia da COVID-19 modera a capacidade de rentabilidade e boa governança corporativa na previsao do prazo de publicaçao. Implicates da pesquisa: O indicador de desempenho financeiro e nao financeiro dá resultados diferentes na previsäo do RWPLK das empresas de manufatura na Indonesia. ROA e CR nao sao capazes de prever o RWPLK, mas DER, GCG, KAP sao capazes de prever o RWPLK. O papel da pandemia COVID-19 foi capaz de moderar a capacidade de ROA e GCG em prever o prazo para publicaçao de relatórios financeiros, mas foi incapaz de moderar a capacidade de CR, DER e KAP em prever o RWPLK. Originalidade/valor: O presente estudo fornece a primeira evidencia empírica sobre o papel moderador da pandemia COVID-19 na capacidade preditiva do desempenho financeiro e nao financeiro para o prazo de publicaçao das demonstraçöes financeiras.Alternate :Purpose: This study examined the ability of financial and non-financial performance in predicting financial reports publication time frame as moderated by the COVID-19 pandemic. Theoretical framework: Signal theory postulates that management serves a crucial role in providing information to stakeholders regarding the condition of the company (Brigham & Houston, 2001). According to Spence (1973), companies are motivated to provide relevant information to stakeholders. If the performance conditions are good, the company tend to speed up the process of presenting financial statements. Conversely, if performance is poor, there is a tendency to delay the financial reports publication. The long span of time for the publication of financial reports can indicate bad news that the company has so that it has yet to publish the news to the public. Scott (2015) suggests that when managers know there is unfavorable news about the condition of the company in the future, they will avoid publishing this information or at least delay the presentation of financial statements. Method/design/approach: Financial performance was measured by four indicators: profita il ty, liquidity and solvency. Meanwhile, variable non-financial performance was measured by the index of good corporate governance (GCG) and auditor reputation. The proposed model was tested based on the quantitative data collected from 156 manufacturing companies listed on the Indonesia Stock Exchange (IDX) from 2018 and 2020. The multiple regression analysis was performed to analyze and interpret the data. Results and conclusion: Result indicates that solvency, good corporate governance, and auditor reputation were significant predictors of the time span of financial report publication. However, the predictive ability of profitability and liquidity on the publication timeframe was found to be not significant. Furthermore, the results show that the COVID-19 pandemic moderates the ability of profitability and good corporate governance in predicting the publication timeframe. Research implications: Financial and non-financial performance indicator gives different results in predicting the RWPLK of manufacturing companies in Indonesia. ROA and CR are not able to predict RWPLK, but DER, GCG, KAP are able to predict RWPLK. The role of the COVID-19 pandemic was able to moderate the ability of ROA and GCG in predicting the timeframe for publication of financial reports, but was unable to moderate the ability of CR, DER and KAP in predicting RWPLK. Originality/value: The present study provides the first empirical evidence on the moderating role of the COVID19 pandemic on the predictive ability of financial and non-financial performance for financial statement publication time frame.

The Relationship Between Financial Indicators and Financial Intermediaries' Stock Price Volatility Listed on the BM&FBOVESPA Index in the Crisis Period of 2008 and 2020 (Covid-19): GCG

The study goal was to verify the relationship among financial indicators and intermediaries' volatility stock price listed on the BM&FBovespa Index in the crisis period from 2008 and 2020 (COVID-19). The methods used for analysis were Spearman's correlation, multiple linear regression, and Test T. The analyzed period refers to the year 2008, the second semester of 2019 and the first semester of 2020, which include the periods before and during the crises of 2008 and 2020. The results found show that only the indicator of the assets total turnover rate has a significant relationship with the stock price volatility.Alternate :O estudo tem como objetivo verificar a relação entre os indicadores com a volatilidade das ações das intermediadoras financeiras listadas no Índice BM&FBovespa no período das crises de 2008 e 2020 (COVID-19). Os métodos utilizados para análise foram de correlação de Spearman, regressão linear múltipla e Teste T. O período analisado refere-se ao ano de 2008, segundo semestre de 2019 e primeiro semestre de 2020, onde englobam os períodos pré e durante as crises de 2008 e 2020. Os resultados encontrados apontam que apenas o indicador taxa total de rotatividade dos ativos possui relação significativa com a volatilidade do preço das ações.Alternate :El estudio tiene como objetivo verificar la relación entre los indicadores y la volatilidad de las acciones de los intermediarios financieros listados en el Índice BM&FBovespa en el período de las crisis de 2008 y 2020 (COVID-19). Los métodos utilizados para el análisis fueron la correlación de Spearman, la regresión lineal múltiple y la prueba T. El período analizado se refiere al año 2008, la segunda mitad de 2019 y la primera mitad de 2020, que incluyen los períodos antes y durante las crisis de 2008 y 2020. Los resultados encontrados indican que solo el indicador de tasa de rotación de activos totales tiene una relación significativa con la volatilidad del precio de las acciones.

Impact of COVID-19 and government interventions on Bursa Malaysia sectors

PurposeThe purpose of this paper is to examine the influence of the daily growth in confirmed COVID-19 cases in Malaysia and government interventions on the daily returns of financial times stock exchange Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI) and eight selected Bursa Malaysia sectorial indices for the period January 29, 2020 to March 31, 2021.Design/methodology/approachThis paper adopts the multivariate generalized autoregressive conditional heteroscedasticity model to determine the effects for the entire study period and four sub-periods, i.e. pre-government intervention, movement control order (MCO), conditional MCO (CMCO) and recovery MCO phases.FindingsThis paper finds no evidence of the effect of the daily growth in confirmed COVID-19 cases on the returns of FBMKLCI and eight Bursa Malaysia sectorial indices for the full study period. However, the former has exerted different effects over the four sub-periods. Sectors that are positively affected for the MCO period are financial services and real estate investment trust. Yet, these sectors are negatively affected for the CMCO period along with the industrial products and services and technology sectors. Sectors that consistently demonstrate statistically insignificant results are construction, energy, plantation and utilities.Originality/valueThis study makes an initial attempt to investigate the influence of the COVID-19 pandemic on the returns of Bursa Malaysia sectorial indices over different phases of government interventions in Malaysia.

The complex evolution of information quality improvement in competitive market

Information is important market resource. High-quality information is beneficial to increase enterprise's reputation and reduce consumer's verification cost. This paper constructs a two-layer dynamic model, in which enterprises simultaneously conduct price and information game. The goal of profit maximization integrates two types of games into one system. The complex evolution of the two-layer system are studied by equilibrium analysis, stability analysis, bifurcation diagram, entropy and Lyapunov exponent. It is found that improving the information quality through regulations will increase involution and reduce stability of the market. Then, the block chain technology is introduced into the model for improving information quality of the market. It is found that increasing enterprises' willingness to adopt block chain can improve the information quality quickly and effectively, and that is verified by entropy value. Therefore, the application and promotion of new technologies are more effective than exogenous regulations for improving information quality in market.

Does US Infectious Disease Equity Market Volatility Index Predict G7 Stock Returns? Evidence Beyond Symmetry

During the COVID-19 pandemic, Baker et al. (2020) [The unprecedented stock market reaction to COVID-19. The Review of Asset Pricing Studies, 10, 742–758.] proposed the infectious disease equity market volatility (ID-EMV) index, which tracks US equity market volatility caused by infectious diseases. We extended the literature by using this newly developed ID-EMV index to examine its asymmetric effect on the share market returns of the G7 countries, which include the United Kingdom, Italy, Japan, Germany, France, Canada, and the United States of America. Moreover, we used novel techniques like the quantile-on-quantile regression test, quantile cointegration test, and quantile unit root test. The quantile cointegration test indicates that the infectious disease EMV index is cointegrated with G7 stock returns. Moreover, the quantile-on-quantile regression technique reveals that the infectious disease index positively affects stock returns during bullish states of the stock markets. In contrast, it negatively affects stock returns during bearish states of the stock market returns. The negative effect of the bearish states implies that investors may discourage investments during the downturns of the economy, whereas they need to boost their investments during economic booms.

The Performance of Top Coronavirus Vaccine Stocks during COVID-19 Pandemic: A Multifractal Analysis

Bu çalışma, 9 Aralık 2019-6 Ocak 2022 arasında beş aşı hissesinin (Pfizer, BioNTech, Moderna, Johnson&Johnson ve AstraZeneca) koronavirüs pandemisinde işgünü haftalık verileri temelinde çoklu fraktal özelliklerinin nasıl etkilendiǧini araştırmaktadır. Çalışmanın temel amacı sürü yatırımının ve piyasa etkinlik düzeyinin aşılama dönemi öncesinde (9 Aralık 2019 - 8 Aralık 2020) ve sonrasında (9 Aralık 2020 - 6 Ocak 2022) deǧişiminin varlıǧını ortaya koymaktır. Genelleştirilmiş Hurst üsleri çoklu fraktal eǧiliminden arındırılmış dalgalanma analizi yoluyla hesaplanmaktadır. Genel olarak, ampirik sonuçlar COVID-19 salgını sırasında her aşı hissesi için çoklu fraktal varlıǧın mevcut olduǧunu göstermektedir. Ayrıca çoklu fraktal özelliklere göre etkinlik düzeyi aşı hisseleri arasında farklılık göstermektedir. Elde edilen sonuçlar aşılama sonrası dönemin BioNTech ve Moderna hisse senetleri için sürü yatırımına daha yatkın olduǧunu göstermektedir. Güncel salgının etkileri göz önüne alındıǧında COVID-19 aşılama sürecinin öncesi ve sonrasında en yüksek MLM (etkinsizlik) indeks deǧerinin BioNTech'e ait olduǧu ortaya konmaktadır.Alternate :This study assesses how the coronavirus pandemic (COVID-19) affects the 5-day week multifractal properties of five vaccine stocks (i.e., Pfizer, BioNTech, Moderna, Johnson & Johnson, and AstraZeneca) using weekday index data ranging from 9 December 2019 to 6 January 2022. The main concern is to document whether the presence of herd investing and the level of market efficiency changed between pre-vaccination (i.e., 9 December 2019 - 8 December 2020) and post-vaccination (i.e., 9 December 2020 - 6 January 2022). The generalised Hurst exponents are calculated through multifractal detrended fluctuation analysis. Overall, the empirical results show multifractality for each vaccine stock during the COVID-19 outbreak. Besides, the efficiency level differs among the vaccine stocks based on multifractal properties. The results indicate that the post-vaccination period is more prone to herd investing in BioNTech and Moderna stocks. Considering the impacts of this far-reaching outbreak, the highest MLM (inefficiency) index value is also attributed to BioNTech before and after the COVID-19 vaccination process.

HERDING BEHAVIOR IN FRONTIER NORDIC COUNTRIES

This paper investigates herding behavior of investors in three frontier Nordic countries from July 1,2002 until July 30, 2021, under different market conditions and during three crises that occurred in this period. As estimation methods, we use both OLS and quantile regression and determine that both up and down market, high and low volatility induce a weak herding behavior for at least one quantile in almost all Nordic countries examined, except for Latvia. At the same time, we find that crises determine a more prominent herding behavior in Nordic countries, but do not influent the behavior of investors from Latvia, that tend to remain rational even in stressful conditions.

OIL PRICE AND VIETNAM STOCK MARKET IN THE ERA OF THE COVID-19 OUTBREAK

The interactive association between oil prices and stock market has increasingly captured the attention of researchers. Especially, how does the relationship between oil prices and stock market varies during COVID-19 pandemic? The study's aim is to investigate the time-varying causal effect of the COVID-19 pandemic on the link between the oil prices and Vietnam stock market using the wavelet approach. Daily data about oil prices Vietnam stock prices and returns covers the period of ten years from January 2011 to December 2021 will be gathered, processed and analyzed to examine the influence of pre, first and second waves of COVID-19 pandemic on the relationship between oil prices and stock market.

The impact of simultaneous shocks to financial markets and mortality on pension buy-out prices

In this paper, we determine the fair value of a pension buyout contract under the assumption that changes in mortality can have an impact on financial markets. Our proposed model allows for shocks to occur simultaneously in mortality rates and financial markets, so that strong changes in mortality rates can affect interest rates and asset prices. This approach challenges the common but very strong assumption that mortality and market risk drivers are independent. A simulation-based pricing framework is applied to determine the buyout premium for a hypothetical fully funded pension scheme. The results of an extensive sensitivity analysis show how buyout prices are affected by changes in mortality and financial markets. Surprisingly, we find that the impact of shocks is similar whether or not these shocks occur simultaneously or not, although there are some differences in annuity prices and buyout premiums. We clearly see that the intensity and severity of shocks, and asset price volatility play a dominant role for buyout prices.

The dynamic relationship of cryptocurrencies with supply chain and logistics stocks – the impact of COVID-19

PurposeThe COVID-19 pandemic is known to have affected the logistics and supply chains;however, there is no adequate empirical evidence to prove in which way it has affected the relationship between the stocks related to this field with the corresponding cryptocurrencies. This paper aims to test the dynamic relationship of cryptocurrencies with supply chain and logistics stocks.Design/methodology/approachIn this paper, the author tests the causal and long-run relationship between logistics and supply chain stocks with the corresponding cryptocurrencies related to these fields, or those that are known to exhibit characteristics that can be utilized by these fields, testing also whether the COVID-19 pandemic affected this relationship. To do so, the author performs the variable-lag causality to test the causal relationship, and examines if this relationship changed due to COVID-19. The author then implements the multifractal detrended cross-correlation analysis to investigate the characteristics of a possible long-run relationship, testing also whether they changed due to COVID-19.FindingsThe results indicate that there is a positive long-run relationship between each logistics and supply chain stocks and the corresponding cryptocurrencies, before and also during COVID-19, but during COVID-19 this relationship becomes weaker, in most cases. Moreover, before COVID-19, the majority of the cases indicate a causal direction from cryptocurrencies to the stocks, while during COVID-19, the causal relationships decrease in multitude, and most cases unveil a causal direction from the stocks to cryptocurrencies.Originality/valueThe causal pattern changed during COVID-19, and the long-run relationship became weaker, showing a change in the dynamics in the relationship between logistics and supply chain stocks with cryptocurrencies.

The impact of COVID‐19 pandemic on hospitality stock returns in China

Coronavirus disease (COVID‐19) has already devastated the world, and the economy becomes the most critical challenge for any country worldwide. The increasing uncertainty of the COVID‐19 outbreak has made stock markets in China more turbulent and less predictable. Under the current exceptional circumstances, the hospitality industry suffered the most due to the travel restrictions. This research thus assesses the dynamic relationship among the COVID‐19 outbreak, macroeconomic fluctuations and hospitality stock returns based on a structural VAR framework from 13 January to 11 May 2020, in China. Evidence reveals that macroeconomic fluctuations and hospitality stock returns are significantly affected by shocks from the COVID‐19 outbreak. An unanticipated positive change of the COVID‐19 explosion triggers an addition in exchange rates and causes a reduction in the stock market and hospitality industry returns. For the impacts of the exchange rate, findings reveal that a surprise increase in exchange rates (currency depreciation) exerts a significant negative influence on stock market returns. Additionally, a positive change of stock market returns is linked to a decline in exchange rates and a rise in hospitality industry returns. Therefore, knowledge of these relationships can enable policymakers to evaluate and implement effective policies to stabilize the stock markets and help investors to make appropriate investment strategies.