Modeling and forecasting listed tourism firms’ risk in China using a trend asymmetric GARCH-MIDAS model

Author:

Yang Peng1ORCID,Song Haiyan2ORCID,Wen Long3ORCID,Liu Han1ORCID

Affiliation:

1. Jilin University, China

2. The Hong Kong Polytechnic University, Hong Kong SAR

3. University of Nottingham Ningbo China, China

Abstract

This study employs the multivariate trend asymmetric GARCH-MIDAS (TAGM) model, an extension of the GARCH-MIDAS model, to explore the potential asymmetric impact of uncertainty shocks, including oil and infectious disease shocks, on the long-term volatility of China’s listed tourism firms. Furthermore, we test the out-of-sample forecasting accuracy of uncertainty shocks to China’s listed tourism firms’ risk, which is measured by the volatility of tourism stocks after the outbreak of coronavirus disease 2019 (COVID-19). The results show that uncertainty shocks have a significant asymmetric effect on the long-run volatility of tourism stocks. The included uncertainty shocks improved accuracy in forecasting China’s listed tourism firms’ risk after the pandemic outbreak. The empirical results have important implications for tourism investment strategies in unstable environments.

Funder

National Natural Science Foundation of China

Major Project of the Key Research Base of Humanities and Social Sciences of the Ministry of Education

Humanities and Social Science Fund of the Ministry of Education

Hong Kong Research Grant Council

Publisher

SAGE Publications

Subject

Tourism, Leisure and Hospitality Management,Geography, Planning and Development

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