Modeling portfolio optimization problem by probability-credibility equilibrium risk criterion
type: Item
instance of: scholarly article
title: Modeling portfolio optimization problem by probability-credibility equilibrium risk criterion
zbMATH Open document ID: 1400.91567
DOI: 10.1155/2016/9461021
author: Ye Wang
author: Yanju Chen
author: Yan-Kui Liu
published in: Mathematical Problems in Engineering
publication date: 2018-10-12T00:00:00Z
review text: Summary: This paper studies the portfolio selection problem in hybrid uncertain decision systems. Firstly the return rates are characterized by random fuzzy variables. The objective is to maximize the total expected return rate. For a random fuzzy variable, this paper defines a new equilibrium risk value (ERV) with credibility level beta and probability level alpha. As a result, our portfolio problem is built as a new random fuzzy expected value (EV) model subject to ERV constraint, which is referred to as EV-ERV model. Under mild assumptions, the proposed EV-ERV model is a convex programming problem. Furthermore, when the possibility distributions are triangular, trapezoidal, and normal, the EV-ERV model can be transformed into its equivalent deterministic convex programming models, which can be solved by general purpose optimization software. To demonstrate the effectiveness of the proposed equilibrium optimization method, some numerical experiments are conducted. The computational results and comparison study demonstrate that the developed equilibrium optimization method is effective to model portfolio selection optimization problem with twofold uncertain return rates.
Mathematics Subject Classification ID: 91G10
Mathematics Subject Classification ID: 93E20
zbMATH DE Number: 6953792
Wikidata QID: Q59141076
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2016/9461021
OpenAlex ID: W2295377011
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description: scientific article; zbMATH DE number 6953792