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On evaluation of joint risk for nonnegative multivariate risks under dependence uncertainty

Shuo Gong et al.

ASTIN Bulletin2026https://doi.org/10.1017/asb.2026.10086article
AJG 2ABDC A*
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0.50

Abstract

In this paper, we design a novel axiomatic approach to evaluating the joint risk of multiple insurance risks under dependence uncertainty. To be precise, we first establish a joint risk measure for non-negative multivariate risks, which we refer to as a (scalar) distortion joint risk measure. Then, we characterize it via a new set of axioms. Moreover, we introduce a new class of vector-valued distortion joint risk measures for non-negative multivariate risks and discuss their basic properties. Finally, comparisons with some existing vector-valued multivariate risk measures are made. It turns out that those vector-valued multivariate risk measures have forms of vector-valued distortion joint risk measures, respectively. This paper provides some relevant theoretical results about the evaluation of joint risk under dependence uncertainty.

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https://doi.org/https://doi.org/10.1017/asb.2026.10086

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@article{shuo2026,
  title        = {{On evaluation of joint risk for nonnegative multivariate risks under dependence uncertainty}},
  author       = {Shuo Gong et al.},
  journal      = {ASTIN Bulletin},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1017/asb.2026.10086},
}

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On evaluation of joint risk for nonnegative multivariate risks under dependence uncertainty

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M · momentum0.50 × 0.15 = 0.07
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R · text relevance †0.50 × 0.4 = 0.20

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