A new measure of indeterminacy for uncertain variables with application to portfolio selection

Author:

Liu Jin1,Xie Jinsheng2,Ahmadzade Hamed3,Farahikia Mehran4

Affiliation:

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

2. School of Mathematics, Renmin University of China, Beijing, China

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

4. Ayandeh bank, Tehran, Iran

Abstract

Entropy is a measure for characterizing indeterminacy of a random variable or an uncertain variable with respect to probability theory and uncertainty theory, respectively. In order to characterize indeterminacy of uncertain variables, the concept of exponential entropy for uncertain variables is proposed. For computing the exponential entropy for uncertain variables, a formula is derived via inverse uncertainty distribution. As an application of exponential entropy, portfolio selection problems for uncertain returns are optimized via exponential entropy-mean models. For better understanding, several examples are provided.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference12 articles.

1. Partial divergence measure of uncertain random variables and its application;Ahmadzade;Soft Computing,2020

2. Partial entropy of uncertain random variables;Ahmadzade;Journal of Intelligent and Fuzzy Systems,2017

3. Partial quadratic entropy of uncertain random variables;Ahmadzade;Journal of Uncertain Systems,2016

4. Results related to exponential entropy;Amini;International Journal of Information and Coding Theory,2017

5. Cross-entropy measure of uncertain variables;Chen;Information Sciences,2012

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