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Accepted version

Publication date

2019-07

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cc-by-nc-nd (c) Elsevier, 2019
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/134030

Partially Schur-constant models

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Abstract

In this paper, we introduce a new multivariate dependence model that generalizes the standard Schur-constant model. The difference is that the random vector considered is partially exchangeable, instead of exchangeable, whence the term partially Schur-constant. Its advantage is to allow some heterogeneity of marginal distributions and a more flexible dependence structure, which broadens the scope of potential applications. We first show that the associated joint survival function is a monotonic multivariate function. Next, we derive two distributional representations that provide an intuitive understanding of the underlying dependence. Several other properties are obtained, including correlations within and between subvectors. As an illustration, we explain how such a model could be applied to risk management for insurance networks.

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Models matemàtics, Risc (Assegurances), Risc (Economia)

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Mathematical models, Risk (Insurance), Risk

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Articles publicats en revistes (Matemàtica Econòmica, Financera i Actuarial)

Citation

CASTAÑER, Anna, et al. Partially Schur-constant models. Journal of Multivariate Analysis. 2019. Vol. 172, num. July, pags. 47-58. ISSN 0047-259X. [consulted: 8 of August of 2026]. Available at: https://hdl.handle.net/2445/134030

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