{"title":"The effects of COVID-19 on Chinese stock markets: an EGARCH approach","authors":"Kerry Liu","doi":"10.1080/20954816.2020.1814548","DOIUrl":null,"url":null,"abstract":"Abstract Coronavirus 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.","PeriodicalId":44280,"journal":{"name":"Economic and Political Studies-EPS","volume":"9 1","pages":"148 - 165"},"PeriodicalIF":1.5000,"publicationDate":"2020-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/20954816.2020.1814548","citationCount":"20","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Economic and Political Studies-EPS","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1080/20954816.2020.1814548","RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"SOCIAL SCIENCES, INTERDISCIPLINARY","Score":null,"Total":0}
引用次数: 20
Abstract
Abstract Coronavirus 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.