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Hierarchical Archimedean copulas through multivariate compound distributions

Hélène Cossette, Simon-Pierre Gadoury, Étienne Marceau and Itre Mtalai

Insurance: Mathematics and Economics, 2017, vol. 76, issue C, 1-13

Abstract: In this paper, we propose a new hierarchical Archimedean copula construction based on multivariate compound distributions. This new imbrication technique is derived via the construction of a multivariate exponential mixture distribution through compounding. The absence of nesting and marginal conditions, contrarily to the nested Archimedean copulas approach, leads to major advantages, such as a flexible range of possible combinations in the choice of distributions, the existence of explicit formulas for the distribution of the sum, and computational ease in high dimensions. A balance between flexibility and parsimony is targeted. After presenting the construction technique, properties of the proposed copulas are investigated and illustrative examples are given. A detailed comparison with other construction methodologies of hierarchical Archimedean copulas is provided. Risk aggregation under this newly proposed dependence structure is also examined.

Keywords: Archimedean copulas; Mixing random variables; Compounding; Marshall–Olkin; Hierarchical structure (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:76:y:2017:i:c:p:1-13

DOI: 10.1016/j.insmatheco.2017.06.001

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Insurance: Mathematics and Economics is currently edited by R. Kaas, Hansjoerg Albrecher, M. J. Goovaerts and E. S. W. Shiu

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