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Extremal cases of distortion risk measures with partial information

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  • Mengshuo Zhao
  • Narayanaswamy Balakrishnan
  • Chuancun Yin

Abstract

This paper considers the best- and worst-case of a general class of distortion risk measures when only partial information regarding the underlying distributions is available. Specifically, explicit sharp lower and upper bounds for a general class of distortion risk measures are derived based on the first two moments along with some shape information, such as symmetry/unimodality property of the underlying distributions. The proposed approach provides a unified framework for extremal problems of distortion risk measures.

Suggested Citation

  • Mengshuo Zhao & Narayanaswamy Balakrishnan & Chuancun Yin, 2024. "Extremal cases of distortion risk measures with partial information," Papers 2404.13637, arXiv.org, revised Oct 2024.
    • Handle: RePEc:arx:papers:2404.13637
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    References listed on IDEAS

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    Cited by:

    1. Baishuai Zuo & Chuancun Yin, 2024. "Worst-cases of distortion riskmetrics and weighted entropy with partial information," Papers 2405.19075, arXiv.org.

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