Triple-objective models for portfolio optimisation with symmetric and percentile risk measures
by Bartosz Sawik
International Journal of Logistics Systems and Management (IJLSM), Vol. 25, No. 1, 2016

Abstract: The purpose of this paper is to compare three different triple-criteria portfolio optimisation models. The first model is constructed with the use of percentile risk measure value-at-risk and solved by mixed integer programming. The second one is constructed with the use of percentile risk measure conditional value-at-risk and solved by linear programming. The third one is constructed with the use of a symmetric measure of risk - variance of return - as in the Markowitz portfolio and solved by quadratic programming. Cardinality constraints are formulated in all models that limit the number of assets selected in the portfolio. Computational experiments are conducted for triple-criteria portfolio stock exchange investments. The results obtained prove that the triple-objective portfolio optimisation models with value-at-risk and conditional value-at-risk could be used to shape the distribution of portfolio returns. The decision maker can assess the value of portfolio return, the risk level and number of assets chosen in the portfolio, and can decide how to invest in a real life situation comparing with ideal (optimal) portfolio solutions. The proposed scenario-based portfolio optimisation problems under uncertainty, formulated as a triple-objective linear, mixed integer or quadratic program are solved using commercially available software (AMPL/CPLEX) for mathematical programming.

Online publication date: Mon, 22-Aug-2016

The full text of this article 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 Logistics Systems and Management (IJLSM):
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