Multi-intervals robust mean-conditional value-at-risk portfolio optimisation with conditional scenario reduction technique
by Tahereh Khodamoradi; Maziar Salahi; Ali Reza Najafi
International Journal of Applied Decision Sciences (IJADS), Vol. 16, No. 2, 2023

Abstract: In this paper, we study mean-conditional value at risk (mean-CVaR) portfolio optimisation with cardinality constraints and short selling under uncertainty. To reduce the level of conservatism, instead of single uncertainty interval, multi-intervals uncertainty sets are considered that are obtained by an efficient scenario reduction technique. It is proven that the proposed robust mean-CVaR model with cardinality constraints and short selling is equivalent to a mixed integer linear programming problem. Finally, using historical data on the S&P index for 2018, we evaluate the efficiency of the proposed models using CVX software in MATLAB. The results show that robust model has relatively low conservatism under multi-intervals uncertainties.

Online publication date: Fri, 10-Mar-2023

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 Applied Decision Sciences (IJADS):
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