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dc.contributor.authorLiu, Kerryen_AU
dc.date.accessioned2021-07-06T23:34:23Z
dc.date.available2021-07-06T23:34:23Z
dc.date.issued2021
dc.identifier.urihttps://hdl.handle.net/2123/25609
dc.description.abstractCoronavirus disease 2019 (COVID-19), the disease caused by the novel coronavirus SARS-CoV-2, has greatly affected financial markets, economies and societies worldwide. This study focusses on the Chinese stock markets. Based on Google Trends data during the period from 1 January 2020 to 12 April 2020, and using the exponential generalised autoregressive conditional heteroskedastic (EGARCH) model, this study finds that the higher uncertainty resulting from the COVID-19 pandemic is significantly associated with the drop in China’s composite index, but this impact varies by sectors. Simultaneously, the higher uncertainty due to COVID-19 is significantly associated with greater volatility in stock returns for both the composite index and sector indices.en_AU
dc.language.isoenen_AU
dc.subjectCOVID-19en_AU
dc.subjectCoronavirusen_AU
dc.titleThe effects of COVID-19 on Chinese stock markets: an EGARCH approachen_AU
dc.typeArticleen_AU
dc.identifier.doi10.1080/20954816.2020.1814548


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