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MULTIVARIATE TAIL ESTIMATION WITH APPLICATION TO ANALYSIS OF COVAR

Published online by Cambridge University Press:  18 June 2013

Tilo Nguyen
Affiliation:
Center for Applied Math, Cornell University, Ithaca, NY 14853, USA E-Mail: dhn43@cornell.edu
Gennady Samorodnitsky*
Affiliation:
School of Operations Research and Information Engineering, and Department of Statistical Science, Cornell University, Ithaca, NY 14853, USA
*

Abstract

The 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.

Type
Research Article
Copyright
Copyright © ASTIN Bulletin 2013 

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