Analysis of stock market efficiency during crisis periods in the US stock market: Differences between the global financial crisis and COVID-19 pandemic
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Choi, Sun-Yong | - |
dc.date.accessioned | 2021-07-04T03:41:47Z | - |
dc.date.available | 2021-07-04T03:41:47Z | - |
dc.date.created | 2021-04-20 | - |
dc.date.issued | 2021-07-15 | - |
dc.identifier.issn | 0378-4371 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/81495 | - |
dc.description.abstract | In this study, we test the efficient market hypothesis for a number of sectors in the US stock market during the COVID-19 pandemic to identify its effects on individual sectors. To test this hypothesis, we define the average price for 11 sectors within the S&P 500 and apply multifractal detrended fluctuation analysis to the average return series. Furthermore, we also investigate these sectors’ efficiency and multifractality during the global financial crisis (GFC) to analyze the features of the COVID-19 pandemic. Our findings can be summarized as follows. First, the average return series show non-persistent and persistent features during the GFC and the COVID-19 pandemic, respectively. Second, during each of these crisis periods, the consumer discretionary and utilities sectors had the highest and lowest levels of efficiency, respectively. Third, while both long-range correlations and fat-tailed distribution contributed to the multifractal properties, the latter of these was the chief contributor. Furthermore, the lower the efficiency ranking, the greater the impact of the fat-tailed distribution on multifractality. Finally, we classify sectors with low market efficiency for the two crisis periods. These findings have several important implications for asset allocations by investors in US stock markets. © 2021 Elsevier B.V. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER | - |
dc.relation.isPartOf | PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS | - |
dc.title | Analysis of stock market efficiency during crisis periods in the US stock market: Differences between the global financial crisis and COVID-19 pandemic | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.identifier.wosid | 000652083100015 | - |
dc.identifier.doi | 10.1016/j.physa.2021.125988 | - |
dc.identifier.bibliographicCitation | PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, v.574 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.scopusid | 2-s2.0-85104052135 | - |
dc.citation.title | PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS | - |
dc.citation.volume | 574 | - |
dc.contributor.affiliatedAuthor | Choi, Sun-Yong | - |
dc.type.docType | Article | - |
dc.subject.keywordAuthor | COVID-19 pandemic | - |
dc.subject.keywordAuthor | Efficient market hypothesis | - |
dc.subject.keywordAuthor | Global financial crisis | - |
dc.subject.keywordAuthor | MF-DFA | - |
dc.subject.keywordPlus | Commerce | - |
dc.subject.keywordPlus | Financial markets | - |
dc.subject.keywordPlus | Fractals | - |
dc.subject.keywordPlus | Investments | - |
dc.subject.keywordPlus | COVID-19 pandemic | - |
dc.subject.keywordPlus | Efficient market hypothesis | - |
dc.subject.keywordPlus | Fat-tailed distributions | - |
dc.subject.keywordPlus | Global financial crisis | - |
dc.subject.keywordPlus | Market efficiency | - |
dc.subject.keywordPlus | MF-DFA | - |
dc.subject.keywordPlus | Multifractal detrended fluctuation analysis | - |
dc.subject.keywordPlus | Multifractality | - |
dc.subject.keywordPlus | Persistent feature | - |
dc.subject.keywordPlus | Utility sector | - |
dc.subject.keywordPlus | Efficiency | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
1342, Seongnam-daero, Sujeong-gu, Seongnam-si, Gyeonggi-do, Republic of Korea(13120)031-750-5114
COPYRIGHT 2020 Gachon University All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.