Mean-AVaR-Entropy ‎o‎ptimization portfolio selection model in uncertain environments

This paper investigates the complexities surrounding uncertain portfolio selection in cases where security returns are not well-represented by historical data. Uncertainty in security returns is addressed by treating them as uncertain variables. Portfolio selection models are developed using the qua...

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Bibliographic Details
Published in:	Mathematics and Modeling in Finance Vol. 4; no. 1; pp. 127 - 145
Main Authors:	Farahnaz Omidi, Leila Torkzadeh, Kazem Nouri
Format:	Journal Article
Language:	English
Published:	Allameh Tabataba'i University Press 01-07-2024
Subjects:	average value-at-risk mean-avar-entropy portfolio selection quadratic entropy uncertain variables
Online Access:	Get full text
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Summary:	This paper investigates the complexities surrounding uncertain portfolio selection in cases where security returns are not well-represented by historical data. Uncertainty in security returns is addressed by treating them as uncertain variables. Portfolio selection models are developed using the quadratic-entropy of these uncertain variables, with entropy serving as a standard measure of diversification. Additionally, the study underscores the superior risk estimation accuracy of Average Value-at-Risk (AVaR) compared to variance. The research concentrates on the computational challenges of portfolio optimization in uncertain environments, utilizing the Mean-AVaR-Quadratic Entropy paradigm to meet investor requirements and assuage concerns. Two illustrative examples are provided to show the efficiency of the proposed models in this paper.
ISSN:	2783-0578 2783-056X
DOI:	10.22054/jmmf.2024.79078.1129