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Risk management with Tail Quasi-Linear Means

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  • Bäuerle, Nicole
  • Shushi, Tomer

Abstract

We generalise Quasi-Linear Means by restricting to the tail of the risk distribution and show that this can be a useful quantity in risk management since it comprises in its general form the Value at Risk, the Conditional Tail Expectation and the Entropic Risk Measure in a unified way. We then investigate the fundamental properties of the proposed measure and show its unique features and implications in the risk measurement process. Furthermore, we derive formulas for truncated elliptical models of losses and provide formulas for selected members of such models.

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  • Bäuerle, Nicole & Shushi, Tomer, 2020. "Risk management with Tail Quasi-Linear Means," Annals of Actuarial Science, Cambridge University Press, vol. 14(1), pages 170-187, March.
    • Handle: RePEc:cup:anacsi:v:14:y:2020:i:1:p:170-187_10
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    Cited by:

    1. Mohammed, Nawaf & Furman, Edward & Su, Jianxi, 2021. "Can a regulatory risk measure induce profit-maximizing risk capital allocations? The case of conditional tail expectation," Insurance: Mathematics and Economics, Elsevier, vol. 101(PB), pages 425-436.

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