Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/239351 
Year of Publication: 
2020
Citation: 
[Journal:] Journal of Risk and Financial Management [ISSN:] 1911-8074 [Volume:] 13 [Issue:] 11 [Publisher:] MDPI [Place:] Basel [Year:] 2020 [Pages:] 1-14
Publisher: 
MDPI, Basel
Abstract: 
Due to the lockdown regulations worldwide during the COVID-19 pandemic, the global aviation industry has been severely hit. This study focuses on the volatility estimation of stock indexes in the Chinese Airport Shipping Set (ASS) at industry-enterprise levels and identifies possible business behavior that may cause fluctuating differences. Depending on the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, text mining method and Word Cloud Views, results show that (1) the holistic volatility of Airport Shipping Set Index (ASSI) increases relative to the pre-COVID period; (2) volatility of airport stocks has crucial differences, while the volatility of shipping stocks is similar; (3) there are different responses to the pandemic between Shenzhen Airport and Shanghai Airport shown in their semiannual financial reports. Compared to the latter, the former had a more positive attitude and took various measures to mitigate risks, providing evidence of the volatility differences between firms.
Subjects: 
COVID-19
airline industry
at industry-enterprise levels
financial risk management
stock price returns
stock volatility
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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