User: Guest  Login
Title:

Semi-parametric models for the multivariate tail dependence function - the asymptotically dependent case

Document type:
Zeitschriftenaufsatz
Author(s):
Klüppelberg, C., Kuhn, G., Peng, L.
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:
4
Pages contribution:
701-718
Reviewed:
ja
Language:
en
Fulltext / DOI:
doi:10.1111/j.1467-9469.2008.00602.x
Status:
Verlagsversion / published
Semester:
SS 08
Format:
Text
 BibTeX