Hierarchical copulas with Archimedean blocks and asymmetric between-block pairs

Ihsan Chaoubi, Hélène Cossette, Etienne Marceau and Christian Y. Robert

Computational Statistics & Data Analysis, 2021, vol. 154, issue C

Abstract: A new class of hierarchical copulas is introduced based on joint survival functions of multivariate exponential mixture distributions. The key element of this construction is the mixing random vector defined by convolutions associated to a Lévy subordinator, and leading to hierarchical copulas with Archimedean within-block copulas and asymmetric between-block pair-copulas. For the specific case of two-level trees, dependence properties of pairs are investigated, and a full estimation procedure is proposed for the tree structure and parameters of the hierarchical copulas. The efficiency of the procedure is illustrated through three simulation examples and a study with two real datasets.

Keywords: Hierarchical copulas; Asymmetric pair-copulas; Archimedean copulas; Composite likelihood estimation; Block-exchangeability; Partitioning Around Mdoids (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:154:y:2021:i:c:s0167947320301626

DOI: 10.1016/j.csda.2020.107071

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