Efficiently sampling exchangeable Cuadras-Augé copulas in high dimensions

Authors:
Jan-Frederik Mai;Matthias Scherer
Affiliations:
HVB-Institute for Mathematical Finance, Technische Universität München, Boltzmannstrasse 3, 85748 Garching, Germany;HVB-Institute for Mathematical Finance, Technische Universität München, Boltzmannstrasse 3, 85748 Garching, Germany
Venue:
Information Sciences: an International Journal
Year:
2009

Citing 3
Cited 2

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Lévy-frailty copulas

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Abstract

An n-dimensional random vector is constructed whose survival copula is given by a copula that was first presented in Cuadras and Auge [C.M. Cuadras, J. Auge, A continuous general multivariate distribution and its properties, Communications in Statistics - Theory and Methods 10 (4) (1981) 339-353]. This construction adds a Poisson subordinator as mixing variable to initially independent exponentially distributed random variables. It is shown how the choice of Poisson process relates to the parameter of the induced Cuadras-Auge copula. Based on this construction, a sampling algorithm for this multivariate distribution is presented which has average computational efficiency O(nloglogn).