Compound Archimedean Copulas

Moshe Kelner, Zinoviy Landsman and Udi E. Makov

International Journal of Statistics and Probability, 2021, vol. 10, issue 3, 126

Abstract: The copula function is an effective and elegant tool useful for modeling dependence between random variables. Among the many families of this function, one of the most prominent family of copula is the Archimedean family, which has its unique structure and features. Most of the copula functions in this family have only a single dependence parameter which limits the scope of the dependence structure. In this paper we modify the generator of Archimedean copulas in a way which maintains membership in the family while increasing the number of dependence parameters and, consequently, creating new copulas having more flexible dependence structure.

Date: 2021
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