Inf-convolution and optimal allocations for mixed-VaRs

Zichao Xia, Zhenfeng Zou and Taizhong Hu

Insurance: Mathematics and Economics, 2023, vol. 108, issue C, 156-164

Abstract: A mixed Value-at-Risk (VaR) is a two-parameter quantile-based risk measure, which is a convex combination of left-VaR and right-VaR. In this paper, we investigate optimal allocations in a risk sharing problem where the objectives of agents are mixed-VaRs. Explicit formulas of the inf-convolution and Pareto optimal allocations are obtained. The worst-case mixed VaR under model uncertainty is also presented.

Keywords: Quantile; Risk measure; Risk sharing; Model uncertainty (search for similar items in EconPapers)
JEL-codes: C61 C70 D81 G22 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:108:y:2023:i:c:p:156-164

DOI: 10.1016/j.insmatheco.2022.12.001

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