4.5 Article

Nordic stock market performance of the travel and leisure industry during the first wave of Covid-19 pandemic

期刊

TOURISM ECONOMICS
卷 28, 期 5, 页码 1240-1257

出版社

SAGE PUBLICATIONS LTD
DOI: 10.1177/1354816621990937

关键词

digital leisure; Markov switching model; Nordic countries; stock market performance; travel and leisure sector

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This study investigates the stock market performance and volatility in the travel and leisure industry for three Nordic countries during the Covid-19 pandemic using the Markov regime switching model. The results show different performance of companies with various compositions during the pandemic, with companies having a large proportion of online gambling firms performing better. This research may provide useful information for policymaking on the impact of the pandemic on tourism and leisure businesses.
This article investigates the performance of the stock market and its volatility in the travel and leisure industry for three Nordic countries using daily data from June 2018 to June 2020, a period that includes the first wave of Covid-19 pandemic. The methodology is based on the Markov regime switching model that allows unobservable regime shifts in the stock return relationship between the travel and leisure industry and the overall market in the period before the outbreak of Covid-19 crisis and during the recovery period at the end of the first wave. The results provide strong evidence of regime switching behaviour in the form of idiosyncratic risk as measured by volatility. The period before Covid-19 corresponds to a low/medium idiosyncratic risk, while the period of the pandemic is characterized by a regime with high idiosyncratic risk. Overall, the timing, likelihood and duration of this crisis regime depend on the composition of the travel and leisure firms. Those with a large proportion of online gambling firms perform better, while those consisting of international transportation firms, hotels and restaurants perform negatively. This study shows that the high-frequency data and the model chosen here can provide timely information on the impact of the pandemic on various tourism and leisure businesses that could be useful for policymaking.

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