A Novel Game-Theoretical Approach for The Possibilistic Mean - Variance Model

Göktaş, Furkan

doi:https://doi.org/10.17093/alphanumeric.1244061

A Novel Game-Theoretical Approach for The Possibilistic Mean - Variance Model

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Furkan Göktaş, Ph.D.

Abstract

Possibility theory is a significant tool to deal with imprecise probability and benefit from expert knowledge. Thus, the possibilistic mean-variance (MV) model is a considerable alternative for the portfolio selection problem. In this study, we propose an extension of the possibilistic MV model to the multiple market strategies where we assume that the possibility distributions of asset returns are given with triangular fuzzy numbers. The proposed extension related to the game theory is provided with a linear optimization problem. Thus, it can be solved with the Simplex algorithm as in this study. After giving the theoretical points, we illustrate it by using a numerical example.

Keywords: Fuzzy Set, Game Theory, Linear Optimization, Portfolio Selection, Possibility Theory

Jel Classification: C61, C72, G11

Suggested citation

Göktaş, F. (2024). A Novel Game-Theoretical Approach for The Possibilistic Mean - Variance Model. Alphanumeric Journal, 12(1), 1-12. https://doi.org/10.17093/alphanumeric.1244061

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2024.12.01.OR.01

alphanumeric journal

Volume 12, Issue 1, 2024

Pages 1-12

Received: Jan. 23, 2023

Accepted: July 1, 2024

Published: July 20, 2024

Full Text [772.7 KB]

2024 Göktaş, F.

This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence, which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.

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A Novel Game-Theoretical Approach for The Possibilistic Mean - Variance Model

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