Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/103804
Authors: 
Bormann, Carsten
Schienle, Melanie
Schaumburg, Julia
Year of Publication: 
2014
Series/Report no.: 
SFB 649 Discussion Paper 2014-042
Abstract: 
In practice, multivariate dependencies between extreme risks are often only assessed in a pairwise way. We propose a test to detect when tail dependence is truly high{dimensional and bivariate simpli cations would produce misleading results. This occurs when a signi cant portion of the multivariate dependence structure in the tails is of higher dimension than two. Our test statistic is based on a decomposition of the stable tail dependence function, which is standard in extreme value theory for describing multivariate tail dependence. The asymptotic properties of the test are provided and a bootstrap based nite sample version of the test is suggested. A simulation study documents the good performance of the test for standard sample sizes. In an application to international government bonds, we detect a high tail{risk and low return situation during the last decade which can essentially be attributed to increased higher-order tail risk. We also illustrate the empirical consequences from ignoring higher-dimensional tail risk.
Subjects: 
decomposition of tail dependence
multivariate extreme values
stable tail dependence function
subsample bootstrap
tail correlation
JEL: 
C01
C46
C58
Document Type: 
Working Paper

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