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

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  • Gong, Shuo
  • Hu, Yijun
  • Wei, Linxiao

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.

Suggested Citation

  • Gong, Shuo & Hu, Yijun & Wei, Linxiao, 2026. "On evaluation of joint risk for nonnegative multivariate risks under dependence uncertainty," ASTIN Bulletin, Cambridge University Press, vol. 56(2), pages 563-587, May.
    • Handle: RePEc:cup:astinb:v:56:y:2026:i:2:p:563-587_11
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