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dc.contributor.authorLiu, Kerryen
dc.date.accessioned2020-07-09
dc.date.available2020-07-09
dc.date.issued2020en
dc.identifier.urihttps://hdl.handle.net/2123/22784
dc.description.abstractThe 2019 novel Coronavirus disease (COVID-19) has greatly affected the financial markets, economies and societies around the world. This study is the first of its kind that focuses on the Chinese stock markets. Based on Google Trends data during 1 January – 12 April, 2020 and by using the exponential generalized autoregressive conditional heteroskedastic (EGARCH) model, this study finds that the higher uncertainty resulting from the COVID-19 can cause the significant drop of China’s composite index, but this impact varies by sectors. At the same time, a higher uncertainty towards COVID-19 can cause bigger volatility of stock returns for both composite index and sector indices. Future studies can use data sets from other economies to see whether this pattern is consistent.en
dc.language.isoenen
dc.rightsOtheren
dc.subjectCOVID-19en
dc.subjectCoronavirusen
dc.titleThe Effects of COVID-19 on Chinese Stock Markets: An EGARCH Approachen
dc.typePreprinten
dc.identifier.doi10.1017/s0950268820001065
usyd.facultyThe University of Sydney Business School


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