Constrained mean-risk portfolio optimisation: an application of multiobjective simulated annealing
by Georgios Mamanis, Konstantinos P. Anagnostopoulos
International Journal of Financial Markets and Derivatives (IJFMD), Vol. 2, No. 1/2, 2011

Abstract: We solve different constrained mean-risk portfolio optimisation models using a recently developed simulated annealing-based multiobjective optimisation algorithm. We consider practical and widely used constraints in portfolio modelling, i.e., the cardinality constraint which imposes a limit on the number of assets in the portfolio and the quantity constraints which restrict the proportion of each asset in the portfolio to lie between lower and upper bounds. Various risk measures are employed – the classical variance and three risk measures that form the so called downside-risk family, i.e., expected shortfall, value-at-risk and semivariance. The experimental results demonstrate that the algorithm generates a number of efficient portfolios capturing a great range of the trade-offs between mean and risk independently of the risk function used. Comparison with benchmark (when possible) efficient frontiers provides strong evidence that the algorithm effectively solves the discrete constrained mean-risk problems. Furthermore, a computational comparison with a population-based evolutionary algorithm, namely SPEA2, shows that the simulated annealing-based multiobjective optimisation technique achieves almost as good performance in a timely manner.

Online publication date: Sat, 28-Feb-2015

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 Financial Markets and Derivatives (IJFMD):
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