Two-stage portfolio risk optimisation based on MVO model
by Krassimira Stoyanova; Vassil Guliashki
International Journal of Reasoning-based Intelligent Systems (IJRIS), Vol. 12, No. 1, 2020

Abstract: This paper presents a two-stage portfolio risk optimisation based on Markowitz's mean variance optimisation (MVO) model. Historical return data for six asset classes are used to calculate the optimal proportions of assets, included in a portfolio, so that the expected return of each asset is no less than in advance given target value. Optimisation procedure is performed at the first stage, in order to select a limited number of assets among a large assets sample. At the second stage the optimal proportions of selected assets in the portfolio are calculated, minimising a risk objective function for a given rate of return. Ten optimisation problems are solved for different expected rate of return. The optimisation is performed in MATLAB. The proposed approach is robust and could be used successfully to solve large-scale portfolio optimisation problems.

Online publication date: Thu, 06-Feb-2020

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 Reasoning-based Intelligent Systems (IJRIS):
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