The full text of this article

 

Solving a portfolio optimisation problem via heuristic algorithms
by Xin-Yao Song; Can Cui; Xiao-Shuang Chen; Qi Kang
International Journal of Wireless and Mobile Computing (IJWMC), Vol. 9, No. 2, 2015

 

Abstract: Portfolio investment has become a fashionable investment with the advantage of risk dispersion. In this work, we examine the ability of three heuristic algorithms to distribute capital associated with the standard mean-variance portfolio optimisation with different risks as constraints. Penalty function is used to deal with the constraint conditions. The three methods considered are Differential Evolution (DE), Comprehensive Learning Particle Swarm Optimiser (CLPSO) and Covariance Matrix Adaption Evolution Strategy (CMA-ES). The results demonstrate that CMA-ES is superior in solving investment portfolio problems in comparison to the other two heuristic algorithms.

Online publication date: Mon, 19-Oct-2015

 

is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

 
Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

 
Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Wireless and Mobile Computing (IJWMC):
Login with your Inderscience username and password:

 

    Username:        Password:         

Forgotten your password?


 
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

 
If you still need assistance, please email subs@inderscience.com