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Original Articles

Copulas checker-type approximations: Application to quantiles estimation of sums of dependent random variables

, &
Pages 3044-3062
Received 22 Jul 2018
Accepted 18 Feb 2019
Published online: 12 Mar 2019
 

Abstract

Several approximations of copulas have been proposed in the literature. By using empirical versions of checker-type copulas approximations, we propose non parametric estimators of the copula. Under some conditions, the proposed estimators are copulas and their main advantage is that they can be sampled from easily. One possible application is the estimation of quantiles of sums of dependent random variables from a small sample of the multivariate law and a full knowledge of the marginal laws. We show that estimations may be improved by including in an easy way in the approximated copula some additional information on the law of a sub-vector for example. Our approach is illustrated by numerical examples.

Acknowledgements

We are grateful to anonymous referees for many interesting remarks on a previous version who helped to improve the article. This work has been partially supported by the MultiRisk LEFE-MANU project and the research chair Actuariat responsable sponsored by Generali.