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Two parameter generalized entropy of uncertain random variables and its application

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Abstract

Generalized entropy is a flexible risk measure to characterize indeterminacy of uncertain random variables. As important roles of risk measures in finance, this paper proposes the concept of generalized entropy for uncertain random variables. Also, an approach for computing generalized entropy is derived based on inverse uncertainty distributions. As an application in finance, portfolio selection problems of uncertain random returns are solved by minimizing generalized entropy in mean-entropy models. Finally, for better understanding, some examples and tables are provided.

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Author notes

  1. Xingxing Liang, Jinsheng Xie, Zhiqiang Miao, Yue Xu and Yanghe Feng contributed equally to this work.

Authors and Affiliations

  1. College of Systems Engineering, National University of Defense Technology, Changsha, 410073, China

    Xingxing Liang & Yanghe Feng

  2. Department of Mathematical Sciences, Tsinghua University, Beijing, 100084, China

    Jinsheng Xie

  3. College of Electrical and Information Engineering, Hunan University, Changsha, 100000, China

    Zhiqiang Miao

  4. The No. 31102 Troop of PLA, Nanjing, 210016, China

    Yue Xu

Authors
  1. Xingxing Liang
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  2. Jinsheng Xie
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  3. Zhiqiang Miao
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  4. Yue Xu
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  5. Yanghe Feng
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Correspondence to Jinsheng Xie.

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Liang, X., Xie, J., Miao, Z. et al. Two parameter generalized entropy of uncertain random variables and its application. J Ambient Intell Human Comput 14, 16337–16346 (2023). https://doi.org/10.1007/s12652-022-03855-4

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  • DOI: https://doi.org/10.1007/s12652-022-03855-4

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