On evaluation of joint risk for nonnegative multivariate risks under dependence uncertainty
Abstract
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.
Fields of Study & Subjects
Risk Management in Financial Firms
Publication details
- Journal / source
- Astin Bulletin
- Publisher
- Cambridge University Press (CUP)
- Volume
- 56
- Issue
- 2
- Pages
- 563–587
- Publication date
- 18 February 2026
- Language
- EN