Mean-Variance-CvaR Model of Multiportfolio Optimization via Linear Weighted Sum Method

We propose a new approach to optimizing portfolios to mean-variance-CVaR (MVC) model. Although of several researches have studied the optimal MVC model of portfolio, the linear weighted sum method (LWSM) was not implemented in the area. The aim of this paper is to investigate the optimal portfolio m...

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Main Authors: Younes Elahi, Mohd Ismail Abd Aziz
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2014/104064
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spelling doaj-0850cd7b12ee4db2991d0387656911bf2020-11-24T22:01:07ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472014-01-01201410.1155/2014/104064104064Mean-Variance-CvaR Model of Multiportfolio Optimization via Linear Weighted Sum MethodYounes Elahi0Mohd Ismail Abd Aziz1Faculty of Science, Department of Mathematics, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor, MalaysiaFaculty of Science, Department of Mathematics, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor, MalaysiaWe propose a new approach to optimizing portfolios to mean-variance-CVaR (MVC) model. Although of several researches have studied the optimal MVC model of portfolio, the linear weighted sum method (LWSM) was not implemented in the area. The aim of this paper is to investigate the optimal portfolio model based on MVC via LWSM. With this method, the solution of the MVC model of portfolio as the multiobjective problem is presented. In data analysis section, this approach in investing on two assets is investigated. An MVC model of the multiportfolio was implemented in MATLAB and tested on the presented problem. It is shown that, by using three objective functions, it helps the investors to manage their portfolio better and thereby minimize the risk and maximize the return of the portfolio. The main goal of this study is to modify the current models and simplify it by using LWSM to obtain better results.http://dx.doi.org/10.1155/2014/104064
collection DOAJ
language English
format Article
sources DOAJ
author Younes Elahi
Mohd Ismail Abd Aziz
spellingShingle Younes Elahi
Mohd Ismail Abd Aziz
Mean-Variance-CvaR Model of Multiportfolio Optimization via Linear Weighted Sum Method
Mathematical Problems in Engineering
author_facet Younes Elahi
Mohd Ismail Abd Aziz
author_sort Younes Elahi
title Mean-Variance-CvaR Model of Multiportfolio Optimization via Linear Weighted Sum Method
title_short Mean-Variance-CvaR Model of Multiportfolio Optimization via Linear Weighted Sum Method
title_full Mean-Variance-CvaR Model of Multiportfolio Optimization via Linear Weighted Sum Method
title_fullStr Mean-Variance-CvaR Model of Multiportfolio Optimization via Linear Weighted Sum Method
title_full_unstemmed Mean-Variance-CvaR Model of Multiportfolio Optimization via Linear Weighted Sum Method
title_sort mean-variance-cvar model of multiportfolio optimization via linear weighted sum method
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2014-01-01
description We propose a new approach to optimizing portfolios to mean-variance-CVaR (MVC) model. Although of several researches have studied the optimal MVC model of portfolio, the linear weighted sum method (LWSM) was not implemented in the area. The aim of this paper is to investigate the optimal portfolio model based on MVC via LWSM. With this method, the solution of the MVC model of portfolio as the multiobjective problem is presented. In data analysis section, this approach in investing on two assets is investigated. An MVC model of the multiportfolio was implemented in MATLAB and tested on the presented problem. It is shown that, by using three objective functions, it helps the investors to manage their portfolio better and thereby minimize the risk and maximize the return of the portfolio. The main goal of this study is to modify the current models and simplify it by using LWSM to obtain better results.
url http://dx.doi.org/10.1155/2014/104064
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