Statistical models and methods for dependence in insurance data
Document type:
Zeitschriftenaufsatz
Author(s):
Haug, S., Klüppelberg, C. and Peng, L.
Abstract:
Copulas are becoming a quite flexible tool in modeling dependence among the components of a
multivariate vector. In order to predict extreme losses in insurance and finance, extreme value copulas and
tail copulas play a more important role than copulas. In this paper, we review some estimation and testing
procedures for both, extreme value copulas and tail copulas, which received much less attention in the literature
than corresponding studies of copulas.
Keywords:
Copula, dependence modelling, extreme dependence, extreme risk, extreme value copula, inference for copulas, interval estimation, multivariate statistics, point estimation, risk estimation, risk modeling, tail copula, tail dependence coefficient, hypothesis testing.