Mean-Entropy model for portfolio selection with type-2 fuzzy returns

Authors:
Ying Liu;Yanju Chen
Affiliations:
College of Mathematics & Computer Science, Hebei University, Baoding, Hebei, China;College of Mathematics & Computer Science, Hebei University, Baoding, Hebei, China
Venue:
ICIC'11 Proceedings of the 7th international conference on Intelligent Computing: bio-inspired computing and applications
Year:
2011

Citing 6
Cited 0

Type-2 fuzzy variables and their arithmetic

Soft Computing - A Fusion of Foundations, Methodologies and Applications
Methods of critical value reduction for type-2 fuzzy variables and their applications

Journal of Computational and Applied Mathematics
Modeling fuzzy data envelopment analysis by parametric programming method

Expert Systems with Applications: An International Journal
Expected value of fuzzy variable and fuzzy expected value models

IEEE Transactions on Fuzzy Systems
Entropy of Credibility Distributions for Fuzzy Variables

IEEE Transactions on Fuzzy Systems
Mean-Entropy Models for Fuzzy Portfolio Selection

IEEE Transactions on Fuzzy Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

Entropy is a measurement of the degree of uncertainty. Mean-entropy method can be used for modeling the choice among uncertain outcomes. In this paper, we consider the portfolio selection problem under the assumption that security returns are characterized by type-2 fuzzy variables. Since the expectation and entropy of type-2 fuzzy variables haven't been well defined, type-2 fuzzy variables need to be reduced firstly. Then we propose a mean-entropy model with reduced variables. To solve the proposed model, we use the entropy formula of reduced fuzzy variable and transform the mean-entropy model to its equivalent parametric form, which can be solved by standard optimization solver.