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

Peng Yang, Haiyan Song, Long Wen, Han Liu

• 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.