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Sequential parameter nonstationarity in stock market returns
dc.contributor.authorKim, Dongcheolen_US
dc.contributor.authorKon, Stanley J.en_US
dc.date.accessioned2006-09-11T19:31:13Z
dc.date.available2006-09-11T19:31:13Z
dc.date.issued1996-03en_US
dc.identifier.citationKim, Dongcheol; Kon, Stanley J.; (1996). "Sequential parameter nonstationarity in stock market returns." Review of Quantitative Finance and Accounting 6(2): 103-131. <http://hdl.handle.net/2027.42/47893>en_US
dc.identifier.issn0924-865Xen_US
dc.identifier.issn1573-7179en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/47893
dc.description.abstractThis paper provides a Bayesian test of parameter nonstationarity and an estimation procedure for the detection of change points in the time series of stock returns. The empirical results indicate that this procedure can identify the change points in the data without prior knowledge and provide substantially more descriptive validity for the distribution of stock returns than competing models.en_US
dc.format.extent1597985 bytes
dc.format.extent3115 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherKluwer Academic Publishers; Springer Science+Business Mediaen_US
dc.subject.otherEconomics / Management Scienceen_US
dc.subject.otherEconometricsen_US
dc.subject.otherAccounting/Auditingen_US
dc.subject.otherFinance /Bankingen_US
dc.subject.otherOperation Research/Decision Theoryen_US
dc.subject.otherParameter Nonstationarityen_US
dc.subject.otherChange Pointsen_US
dc.subject.otherStock Return Distributionen_US
dc.subject.otherModel Comparisonsen_US
dc.titleSequential parameter nonstationarity in stock market returnsen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelEconomicsen_US
dc.subject.hlbtoplevelBusinessen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Finance, School of Business Administration, University of Michigan, 48109, Ann Arbor, MI, USAen_US
dc.contributor.affiliationotherDepartment of Finance, School of Business, Rutgers University, 08903, New Brunswick, NJ, USAen_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/47893/1/11156_2004_Article_BF00367498.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1007/BF00367498en_US
dc.identifier.sourceReview of Quantitative Finance and Accountingen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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