Adjusted Rényi entropic Value-at-Risk

Zhenfeng Zou, Qinyu Wu, Zichao Xia and Taizhong Hu

European Journal of Operational Research, 2023, vol. 306, issue 1, 255-268

Abstract: Entropy is a measure of self information or uncertainty. Using different concepts of entropy, we may get different risk measures by dual representation. In this paper, we introduce and study the main properties of a class of convex risk measures, called as adjusted Rényi entropic Value-at-Risk (VaR). The adjusted risk measure quantifies risk as the minimum amount of capital that has to be raised and injected into a financial position to ensure that its Rényi entropic-VaR does not exceed a pre-specified threshold for every probability level. When p∈[1,∞), the adjusted Rényi entropic-VaR of order p is intimately linked to the (p+1)-increasing convex order by choosing the risk threshold to be the Rényi entropic-VaR of a benchmark random loss.

Keywords: Applied probability; Convex risk measure; Coherent risk measure; Risk profile; Increasing convex order (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:306:y:2023:i:1:p:255-268

DOI: 10.1016/j.ejor.2022.08.028

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