Dating multiple change points in the correlation matrix

dc.contributor.authorGaleano, Pedro
dc.contributor.authorWied, Dominik
dc.date.accessioned2014-05-12T13:07:00Z
dc.date.available2014-05-12T13:07:00Z
dc.date.issued2014-05-12
dc.description.abstractWe propose a nonparametric procedure for detecting and dating multiple change points in the correlation matrix of a sequence of random variables. The procedure is based on a test for changes in correlation matrices at an unknown point in time recently proposed by Wied (2014). Although the procedure requires constant expectations and variances, only mild assumptions on the serial dependence structure are assumed. We show the validity of the procedure including the convergence rate of the change point estimators. Moreover, we illustrate its performance in finite samples by means of a simulation study and the analysis of a real data example with financial returns. These examples show that the proposed algorithm has large power in finite samples.en
dc.identifier.urihttp://hdl.handle.net/2003/33114
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-15447
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB 823;18/2014en
dc.subjectbinary segmentation algorithmen
dc.subjectnonparametric estimationen
dc.subjectmultiple change point detectionen
dc.subjectfinancial returnsen
dc.subjectCUSUM statisticsen
dc.subjectcorrelation matrixen
dc.subject.ddc310
dc.subject.ddc330
dc.subject.ddc620
dc.titleDating multiple change points in the correlation matrixen
dc.typeTextde
dc.type.publicationtypeworkingPaperde
dcterms.accessRightsopen access

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