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dc.contributor.authorArnold, Matthiasen_US
dc.contributor.authorWeißbach, Rafaelen_US
dc.date.accessioned2007-07-03en_US
dc.date.accessioned2009-07-23T14:31:32Z-
dc.date.available2009-07-23T14:31:32Z-
dc.date.issued2007en_US
dc.identifier.urihttp://hdl.handle.net/10419/25000-
dc.description.abstractThis paper introduces a test for zero correlation in situations where the correlation matrix is large compared to the sample size. The test statistic is the sum of the squared correlation coefficients in the sample. We derive its limiting null distribution as the number of variables as well as the sample size converge to infinity. A Monte Carlo simulation finds both size and power for finite samples to be suitable. We apply the test to the vector of default rates, a risk factor in portfolio credit risk, in different sectors of the German economy.en_US
dc.language.isoengen_US
dc.publisherUniv., SFB 475 Dortmunden_US
dc.relation.ispartofseriesTechnical Report // Sonderforschungsbereich 475, Komplexitätsreduktion in Multivariaten Datenstrukturen, Universität Dortmund 2007,15en_US
dc.subject.jelC12en_US
dc.subject.jelC52en_US
dc.subject.ddc310en_US
dc.subject.keywordtesting correlationen_US
dc.subject.keywordn-p-asymptoticsen_US
dc.subject.keywordportfolio credit risken_US
dc.subject.stwKorrelationen_US
dc.subject.stwStichprobenverfahrenen_US
dc.subject.stwStatistischer Testen_US
dc.subject.stwTheorieen_US
dc.subject.stwSchätzungen_US
dc.subject.stwKreditrisikoen_US
dc.titleTesting large-dimensional correlationen_US
dc.typeWorking Paperen_US
dc.identifier.ppn534757693en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-
dc.identifier.repecRePEc:zbw:sfb475:200715-
Appears in Collections:Technical Reports, SFB 475: Komplexitätsreduktion in multivariaten Datenstrukturen, TU Dortmund

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