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This article examines dynamic volatility spillovers between stock index returns of four main hospitality sub-sectors in US during the coronavirus disease 2019 (COVID-19) pandemic. These are tourism and travel, hotel and lodging, recreational services and food and beverages. Volatility spillovers are explicitly used as accurate and informative proxies for risk contagion between sectors during turbulent times.

The authors employ dynamic conditional correlation-generalized autoregression heteroskedasticity (DCC-GARCH) and wavelet coherence analysis (WCA) to analyze the phenomenon. The authors’ timeframe is divided into three main sub-periods, namely the pre-pandemic, the first wave and the second wave periods.

This study’s results reveal immense negative shocks in returns of all four sub-sectors on the Black Monday (8th March 2020). Moreover, high volatility persistence was observed during both waves with an exception of tourism and travel which exhibited lower volatility persistence during the second wave. The authors discovered magnified contagion effects between tourism and travel, hotel and lodgment and recreational services during the first wave of the pandemic with tourism and travel being the main volatility transmitter. Lower magnitudes of spillovers were observed between food and beverages and other sub-sectors with a decoupling effect being evident during the second wave.

This study’s findings contribute to the contagion theory by providing evidence of disproportional volatility spillover among hospitality sub-sectors despite being exposed to similar turbulent economic conditions.

Crucial implications can be drawn from this study’s findings to assist in risk management, asset valuation and portfolio management. The importance of close monitoring, safety measures, international diversification and adequacy of liquid assets during health crises cannot be stresses enough for hospitality firms. Retail investors, speculators and asset managers can take advantage of this study’s findings to design trading strategies and hedge against risk.

A body of knowledge pertaining to effects of crises such as COVID-19 on hospitality stocks has been proliferating. Nonetheless, there is still a relative dearth of empirical literature on volatility spillover between hospitality sub-sectors especially during periods of rising economic uncertainties.

This article examines the susceptibility of cryptocurrencies to coronavirus disease 2019 (COVID-19) induced panic in comparison with major stock indices.

The author employs the Bayesian structural vector autoregression to examine the phenomenon in Bitcoin, Ethereum and Litecoin from 2nd January 2020 to 30th June 2021. A similar analysis is conducted for major stock indices, namely S&P 500, FTSE 100 and SSE Composite for comparison purposes.

The results suggest that cryptocurrencies returns suffered immensely in the early days of the COVID-19 outbreak following declarations of the disease as a global health emergency and eventually a pandemic in March 2020. However, the returns for all three cryptocurrencies recovered by April 2020 and remained resistant to further COVID-19 panic shocks. The results are dissimilar to those of S&P 500, FTSE 100 and SSE Composite values which were vulnerable to COVID-19 panic throughout the timeframe to June 2021. The results further reveal strong predictive power of Bitcoin on prices of other cryptocurrencies.

The article provides evidence to support the cryptocurrency as a safe haven during COVID-19 school of thought given their resistance to subsequent shocks during COVID-19. Thus, the author stresses the need for diversification of investment portfolios by including cryptocurrencies given their uniqueness and resistance to shocks during crises.

The author makes use of the novel corona virus panic index to examine the magnitude of shocks in prices of cryptocurrencies during COVID-19.

Following the COVID-19 outbreak, various economies imposed different financial interventions as part of initiatives to cushion their stock markets from deteriorating performance. Our article examines the effectiveness of these interventions in protecting stock markets during the pandemic.

The authors employ Panel Vector Autoregression to model the magnitude and timing of shocks from COVID-19 to stock markets. The fixed effects regression is then utilized to assess the role of financial interventions in protecting stock markets during COVID-19. The study uses daily stock index returns as well COVID-19 containment measures stringency index data from 39 countries ranging from 2nd January 2020 to 30th September 2021.

Our findings firstly reveal a significant positive stock market reaction to country-level containment measures stringency but only during the first wave of COVID-19. We secondly show that stock market functioning interventions that include short selling bans and circuit breakers amplify the positive effects of COVID-19 containment measures stringency on stock market performance.

The authors stress the need for policymakers and regulators to timely intervene in protecting economies and stock markets during crises such as COVID-19 in order to reduce panic among investors. Moreover, investors should adjust their portfolios by investing in stocks from countries that have proper financial market interventions in place.

Despite growing body of literature on COVID-19 and stock market performance, there is limited evidence on the role of financial sector interventions to cushion stock markets during tumultuous conditions caused by the pandemic.

The purpose of this article is to examine the impact of panic and hysteria news on the volatility of microchip stocks during Covid-19.

The authors use the P-GARCH (1,1) and random effects regression to model/examine the impact of Covid-19 panic and hysteria news on the overall microchip sector and individual firms. They further utilize the SVAR model to examine volatility spill-over from the microchip sector to the automobile and main technology sectors. Their time frame ranges from 6th January 2020 to 30th June 2021 to capture the effects of both waves of Covid-19.

The study results firstly reveal that Covid-19 panic and hysteria news have tremendous potential to model the volatility of microchip sector stock thus confirming the information discovery hypothesis. The authors secondly demonstrate the influence of Covid-19 cases, deaths and policy stringency on stock returns of individual microchip companies in different countries. Finally the authors confirm the presence of volatility spill-over from the microchip sector to other technology sectors.

The authors provide evidence to support the profundity of bad news in predicting stock behavior. The study results depict how Covid-19 has affected microchip stocks so that policy initiatives can be taken to protect the industry. The presence of volatility spill-over signifies the importance of diversifying portfolios by mixing technology and non-technology stocks.

The research strand on Covid-19 and individual sectoral stocks has received limited scholarly attention despite unparallel effects of the pandemic on different sectors.

Despite the popularity of the entrepreneurial ecosystem (EE) concept, research on its value-adding activities receives less attention. Thus, in this article, the authors investigate the role of EEs in supporting global value chain (GVC) activities.

The authors employ the fuzzy-set qualitative comparative analysis (fsQCA) technique to identify practical configurations of EE’s framework and systemic conditions spurring GVC activities in 80 countries.

The findings suggest different configurations of EE`s framework and systemic conditions necessary for various GVC activities regarding input-output structure, geographical scope, upgrading, and forward and backward participation.

This study contributes to the extant literature by pioneering the EE approach to explaining GVC development. Moreover, the findings provide novel insights for understanding the EE – GVC interplay. As a result, the study offers a more nuanced understanding of how the EE supports GVC activities.

The purpose of this study is to examine the impact of the corona virus (COVID-19) pandemic on stock returns of listed cargo shipping companies.

The author employs the events study methodology to examine this phenomenon. A sample of 49 listed cargo shipping companies in the container, dry bulk and tanker sub-sectors from Asia, North America, and Europe was selected and their daily closing stock prices from 1st January 2020 to 31st December 2020 were utilized.

The results reveal that there was an overall negative overreaction to the announcement by World Health Organization (WHO) that declared COVID-19 a pandemic. The approvals of USD 857 billion stimulus package by the European Union (EU) and Pfizer vaccine by Food and Drug Administration (FDA) in USA received slight positive reactions. The Greek, Singaporean and Taiwanese shipping stocks were the least affected stocks as their respective shipping industries remained resilient during 2020.

This study provides evidence to confirm the fact that COVID-19 has affected stock markets; however the impact is un parallel among cargo shipping stocks of different countries.

The majority of studies have conducted country level analyses of the COVID-19 and stock market performance phenomenon. However, there have been sectoral disparities in terms of their susceptibility to economic shocks from COVID-19. This study's focal point is on the cargo shipping sector which synonymous with other sectors has not been immune to the current pandemic. The study also extends the timeline of events to incorporate those from June to December 2020.