 Stock return anomalies identification during the Covid-19 with the application of a grouped multiple comparison procedureChiu-Lan Chang and Qingyun Cai Economic Analysis and Policy, 2023, vol. 79, issue C, 168-183 Abstract: This study investigates the impact of COVID-19 pandemic on the Chinese stock market in 2020. Using daily data of three industries, this study addresses the identification of abnormal stock returns as a multiple hypothesis testing problem and proposes to apply a grouped comparison procedure for better detection. By comparing the numbers of daily signals and numbers of stocks with abnormal positive and negative returns, the empirical result shows that the three industries perform differently under the pandemic. Compared to the non-grouped testing procedure, the signals found by the grouped procedure are more prominent, which is advantageous for some situations when there tends to be abnormal performance clustering at the occurrence of major event. This paper on stock return anomalies gives a new perspective on the impact of major events to the stock market, like the global outbreak disease. Keywords: Abnormal stock returns; Major event; COVID-19 pandemic; Multiple hypothesis testing; Hierarchical structure (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ecanpo:v:79:y:2023:i:c:p:168-183 DOI: 10.1016/j.eap.2023.06.017 Access Statistics for this article Economic Analysis and Policy is currently edited by Clevo Wilson More articles in Economic Analysis and Policy from Elsevier |
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