Page’s sequential procedure for change-point detection in time series regression

dc.contributor.authorFremdt, Stefan
dc.date.accessioned2013-12-16T12:59:27Z
dc.date.available2013-12-16T12:59:27Z
dc.date.issued2013-12-16
dc.description.abstractIn a variety of different settings cumulative sum (CUSUM) procedures have been applied for the sequential detection of structural breaks in the parameters of stochastic models. Yet their performance depends strongly on the time of change and is best under early-change scenarios. For later changes their finite sample behavior is rather questionable. We therefore propose modified CUSUM procedures for the detection of abrupt changes in the regression parameter of multiple time series regression models, that show a higher stability with respect to the time of change than ordinary CUSUM procedures. The asymptotic distributions of the test statistics and the consistency of the procedures are provided. In a simulation study it is shown that the proposed procedures behave well in finite samples. Finally the procedures are applied to a set of capital asset pricing data related to the Fama-French extension of the capital asset pricing model.en
dc.identifier.urihttp://hdl.handle.net/2003/31546
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-7657
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB 823;47/2013
dc.subjectCUSUMen
dc.subjectFama-French modelen
dc.subjectCAPMen
dc.subjectinvariance principleen
dc.subjectasymptotic distributionen
dc.subjectsequential testen
dc.subjectchange-pointen
dc.subjectlinear modelen
dc.subject.ddc310
dc.subject.ddc330
dc.subject.ddc620
dc.titlePage’s sequential procedure for change-point detection in time series regressionen
dc.typeTextde
dc.type.publicationtypeworkingPaperde
dcterms.accessRightsopen access

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