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March 2011 Extreme residual dependence for random vectors and processes
Laurens De Haan, Chen Zhou
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Adv. in Appl. Probab. 43(1): 217-242 (March 2011). DOI: 10.1239/aap/1300198520

Abstract

A two-dimensional random vector in the domain of attraction of an extreme value distribution G is said to be asymptotically independent (i.e. in the tail) if G is the product of its marginal distribution functions. Ledford and Tawn (1996) discussed a form of residual dependence in this case. In this paper we give a characterization of this phenomenon (see also Ramos and Ledford (2009)), and offer extensions to higher-dimensional spaces and stochastic processes. Systemic risk in the banking system is treated in a similar framework.

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Laurens De Haan. Chen Zhou. "Extreme residual dependence for random vectors and processes." Adv. in Appl. Probab. 43 (1) 217 - 242, March 2011. https://doi.org/10.1239/aap/1300198520

Information

Published: March 2011
First available in Project Euclid: 15 March 2011

zbMATH: 1216.62078
MathSciNet: MR2761155
Digital Object Identifier: 10.1239/aap/1300198520

Subjects:
Primary: 62G20

Keywords: Asymptotic independence , extreme residual dependence , spectral measure

Rights: Copyright © 2011 Applied Probability Trust

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Vol.43 • No. 1 • March 2011
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