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Document type:
Zeitschriftenaufsatz 
Author(s):
Klüppelberg, C., Kuhn, G., Peng, L. 
Title:
Semi-parametric models for the multivariate tail dependence function - the asymptotically dependent case 
Abstract:
In general, the risk of joint extreme outcomes in financial markets can be expressed as a function of the tail dependence function of a high-dimensional vector after standardizing marginals. Hence it is of importance to model and estimate tail dependence functions. Even for moderate dimension, nonparametrically estimating a tail dependence function is very inefficient and fitting a parametric model to tail dependence functions is not robust. In this paper we propose a semi-parametric model for (...    »
 
Keywords:
Asymptotic normality, Dependence modeling, Elliptical copula, Elliptical distribution, Regular variation, Semi-parametric model, Tail dependence function 
Journal title:
Scand. J. Stat. 
Year:
2008 
Journal volume:
35 
Journal issue:
Pages contribution:
701-718 
Reviewed:
ja 
Language:
en 
Status:
Verlagsversion / published 
Semester:
SS 08 
Format:
Text