Detailed Information

Cited 53 time in webofscience Cited 56 time in scopus
Metadata Downloads

Significance testing in empirical finance: A critical review and assessment

Full metadata record
DC Field Value Language
dc.contributor.authorKim, Jae H.-
dc.contributor.authorJi, Philip Inyeob-
dc.date.accessioned2024-08-08T04:00:57Z-
dc.date.available2024-08-08T04:00:57Z-
dc.date.issued2015-12-
dc.identifier.issn0927-5398-
dc.identifier.issn1879-1727-
dc.identifier.urihttps://scholarworks.dongguk.edu/handle/sw.dongguk/17436-
dc.description.abstractThis paper critically reviews the practice of significance testing in modern finance research. Employing a survey of recently published articles in four top-tier finance journals, we find that the conventional significance levels are exclusively used with little consideration of the key factors such as the sample size, power of the test, and expected losses. We also find that statistically significant results reported in many surveyed papers become questionable, if Bayesian method or revised standards for evidence were instead used. We observe strong evidence of publication bias in favour of statistical significance. We propose that substantial changes be made to the current practice of significance testing in finance research, in order to improve research credibility and integrity. (C) 2015 Elsevier B.V. All rights reserved.-
dc.format.extent14-
dc.language영어-
dc.language.isoENG-
dc.publisherELSEVIER SCIENCE BV-
dc.titleSignificance testing in empirical finance: A critical review and assessment-
dc.typeArticle-
dc.publisher.location네델란드-
dc.identifier.doi10.1016/j.jempfin.2015.08.006-
dc.identifier.scopusid2-s2.0-84942608702-
dc.identifier.wosid000366231500001-
dc.identifier.bibliographicCitationJOURNAL OF EMPIRICAL FINANCE, v.34, pp 1 - 14-
dc.citation.titleJOURNAL OF EMPIRICAL FINANCE-
dc.citation.volume34-
dc.citation.startPage1-
dc.citation.endPage14-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassssci-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaBusiness & Economics-
dc.relation.journalWebOfScienceCategoryBusiness, Finance-
dc.relation.journalWebOfScienceCategoryEconomics-
dc.subject.keywordPlusSTATISTICS MISLEAD EXPERTS-
dc.subject.keywordPlusSOFT PSYCHOLOGY-
dc.subject.keywordPlusREGRESSION-
dc.subject.keywordPlusPREDICTABILITY-
dc.subject.keywordPlusCRISIS-
dc.subject.keywordPlusUNCERTAINTY-
dc.subject.keywordPlusINFORMATION-
dc.subject.keywordPlusHYPOTHESES-
dc.subject.keywordPlusSTANDARD-
dc.subject.keywordPlusILLUSION-
dc.subject.keywordAuthorLevel of significance-
dc.subject.keywordAuthorLindley paradox-
dc.subject.keywordAuthorMassive sample size-
dc.subject.keywordAuthorMeehl's conjecture-
dc.subject.keywordAuthorPublication bias-
dc.subject.keywordAuthorSpurious statistical significance-
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of the Social Science > Department of Economics > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Ji, In Yeob photo

Ji, In Yeob
College of the Social Science (Department of Economics)
Read more

Altmetrics

Total Views & Downloads

BROWSE