An M-estimator for tail dependence in arbitrary dimensions

Details An M-estimator for tail dependence in arbitrary dimensions An M-estimator for tail dependence in arbitrary dimensions

2011-12-05

arxiv.org/abs/1112.0905v2

Mathematics

Statistics Theory

26 pages, 6 figures

Scientific paper

Consider a random sample in the max-domain of attraction of a multivariate extreme value distribution such that the dependence structure of the attractor belongs to a parametric model. A new estimator for the unknown parameter is defined as the value that minimises the distance between a vector of weighted integrals of the tail dependence function and their empirical counterparts. The minimisation problem has, with probability tending to one, a unique, global solution. The estimator is consistent and asymptotically normal. The spectral measures of the tail dependence models to which the method applies can be discrete or continuous. Examples demonstrate the applicability and the performance of the method.

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