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Extended Gini-type measures of risk and variability

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  • Mohammed Berkhouch
  • Ghizlane Lakhnati
  • Marcelo Brutti Righi

Abstract

The aim of this paper is to introduce a risk measure that extends the Gini-type measures of risk and variability, the Extended Gini Shortfall, by taking risk aversion into consideration. Our risk measure is coherent and catches variability, an important concept for risk management. The analysis is made under the Choquet integral representations framework. We expose results for analytic computation under well-known distribution functions. Furthermore, we provide a practical application.

Suggested Citation

  • Mohammed Berkhouch & Ghizlane Lakhnati & Marcelo Brutti Righi, 2017. "Extended Gini-type measures of risk and variability," Papers 1707.07322, arXiv.org, revised Mar 2018.
    • Handle: RePEc:arx:papers:1707.07322
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    Cited by:

    1. Mohammed Berkhouch & Fernanda Maria Müller & Ghizlane Lakhnati & Marcelo Brutti Righi, 2022. "Deviation-Based Model Risk Measures," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 527-547, February.
    2. Hu, Taizhong & Chen, Ouxiang, 2020. "On a family of coherent measures of variability," Insurance: Mathematics and Economics, Elsevier, vol. 95(C), pages 173-182.
    3. Baishuai Zuo & Chuancun Yin, 2024. "Worst-cases of distortion riskmetrics and weighted entropy with partial information," Papers 2405.19075, arXiv.org.
    4. Fabrizio Maturo & Pierpaolo Angelini, 2023. "Aggregate Bound Choices about Random and Nonrandom Goods Studied via a Nonlinear Analysis," Mathematics, MDPI, vol. 11(11), pages 1-30, May.
    5. Marlon Moresco & Marcelo Righi & Eduardo Horta, 2020. "Minkowski gauges and deviation measures," Papers 2007.01414, arXiv.org, revised Jul 2021.

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