Full metadata record
DC FieldValueLanguage
dc.contributor.authorGaleano, Pedro-
dc.contributor.authorWied, Dominik-
dc.date.accessioned2012-03-29T08:11:34Z-
dc.date.available2012-03-29T08:11:34Z-
dc.date.issued2012-03-29-
dc.identifier.urihttp://hdl.handle.net/2003/29399-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-3416-
dc.description.abstractWe propose a monitoring procedure to test for the constancy of the correlation coefficient of a sequence of random variables. The idea of the method is that a historical sample is available and the goal is to monitor for changes in the correlation as new data become available. We introduce a detector which is based on the first hitting time of a CUSUM-type statistic over a suitably constructed threshold function. We derive the asymptotic distribution of the detector and show that the procedure detects a change with probability approaching unity as the length of the historical period increases. The method is illustrated by Monte Carlo experiments and the analysis of a real application with the log-returns of the Standard & Poor's 500 (S&P 500) and IBM stock assets.en
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB 823 ; 12/2012en
dc.subjectcorrelation changesen
dc.subjectGaussian processen
dc.subjectonline detectionen
dc.subjectthreshold functionen
dc.subject.ddc310-
dc.subject.ddc330-
dc.subject.ddc620-
dc.titleMonitoring correlation change in a sequence of random variablesen
dc.typeTextde
dc.type.publicationtypeworkingPaperde
dcterms.accessRightsopen access-
Appears in Collections:Sonderforschungsbereich (SFB) 823

Files in This Item:
File Description SizeFormat 
DP_1212_SFB823_Wied_Galeano.pdfDNB412.75 kBAdobe PDFView/Open


This item is protected by original copyright



This item is protected by original copyright rightsstatements.org