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Archives › Volume 11, Number 4 (2021)

J. Math. Comput. Sci. 11 (2021), 3829–3850

An interactive approach to multi-objective mean semi-variance model with transaction cost for portfolio optimization

Rahul Chaudhury, Sahidul Islam

Abstract

Portfolio selection may be considered as a complicated decision making under uncertain conditions. Regardless of an unknown future, a fund manager has to make critical financial choices based on the investors’ preferences towards risk and return and perceptions. Since the pioneer work of Markowitz, a lot of studies have been published considering his Mean-Variance (MV) model as a basis. In our proposed model we had considered Semivariance as the risk measure in our proposed portfolio optimization model. We also extend our model to include the effect of transaction cost in portfolio optimization and then the concept of entropy is incorporated as an objective function in our model to obtain a well diversified portfolio within optimal asset allocation.

An interactive approach is used to solve the model. A numerical example is used to illustrate that the model can be efficiently used in practice. Finally the result obtained in interactive method has been compared with the result obtained by Fuzzy Non-Linear Programming (FNLP) and Fuzzy Additive Goal Programming (FAGP) techniques.

Published
19 May 2021
Volume
11 (2021)
License
CC BY 3.0

Copyright © 2021 Rahul Chaudhury, Sahidul Islam. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Cite this article

R. Chaudhury, S. Islam, An interactive approach to multi-objective mean semi-variance model with transaction cost for portfolio optimization, J. Math. Comput. Sci. 11 (2021), 3829–3850. https://doi.org/10.28919/jmcs/5741

BibTeX
@article{Chaudhury2021,
  author  = {Chaudhury, Rahul and Islam, Sahidul},
  title   = {An interactive approach to multi-objective mean semi-variance model with transaction cost for portfolio optimization},
  journal = {J. Math. Comput. Sci.},
  volume  = {11},
  year    = {2021},
  pages   = {3829--3850},
  doi     = {10.28919/jmcs/5741}
}