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dc.contributor.authorNguyen, Tilo
dc.contributor.authorSamorodnitsky, Gennady
dc.description.abstractThe quality of estimation of multivariate tails depends significantly on the portion of the sample included in the estimation. A simple approach involving sequential statistical testing is proposed in order to select which observations should be used for estimation of the tail and spectral measures. We prove that the estimator is consistent. We test the proposed method on simulated data, and subsequently apply it to analyze CoVar for stock and index returns.en_US
dc.description.sponsorshipThis research was partially supported by the ARO grants W911NF-07-1-0078 and W911NF-12-10385, NSF grant DMS-1005903 and NSA grant H98230-11-1-0154 at Cornell University.en_US
dc.subjecttail estimationen_US
dc.subjecttail measureen_US
dc.subjectspectral measureen_US
dc.subjecttail regionen_US
dc.titleMultivariate tail measure and the estimation of CoVaren_US
dc.typetechnical reporten_US

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