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Tsallis entropy of uncertain random variables and its application

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Abstract

Tsallis entropy is a flexible extension of Shanon (logarithm) entropy. Since entropy measures indeterminacy of an uncertain random variable, this paper proposes the concept of partial Tsallis entropy for uncertain random variables as a flexible devise in chance theory. An approach for calculating partial Tsallis entropy for uncertain random variables, based on Monte Carlo simulation, is provided. As an application in finance, partial Tsallis entropy is invoked to optimize portfolio selection of uncertain random returns via crow search algorithm.

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Authors and Affiliations

  1. School of Information and Statistics, Guangxi University of Finance and Economics, Nanning, 530003, China

    Zhenhua He

  2. Department of Statistics, University of Sistan and Baluchestan, Zahedan, Iran

    Hamed Ahmadzade & Habib Naderi

  3. Department of Computer Science, University of Sistan and Baluchestan, Zahedan, Iran

    Kamran Rezaei & Hassan Rezaei

Authors
  1. Zhenhua He
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  2. Hamed Ahmadzade
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  3. Kamran Rezaei
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  4. Hassan Rezaei
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  5. Habib Naderi
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Contributions

Conceptualization was done by Zhenhua He. Formal analysis was carried out by Hamed Ahmadzade. Methodology and editing were done by Habib Naderi. Resources and editing were done by Hassan Rezaei. Software was done by Kamran Rezaei. Writing original draft and revising were done by Hamed Ahmadzade. Funding acquisition was done by Zhenhua He. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Hamed Ahmadzade.

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He, Z., Ahmadzade, H., Rezaei, K. et al. Tsallis entropy of uncertain random variables and its application. Soft Comput 25, 11735–11743 (2021). https://doi.org/10.1007/s00500-021-06070-z

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