Portfolio selection using mean-risk model and mean-risk diversification model
Akhter Mohiuddin Rather
International Journal of Operational Research, 2012, vol. 14, issue 3, 324-342
Abstract:
With mean-risk and mean-risk diversification models, return distributions are characterised and compared using two statistics: the expected value and the value of a risk measure. This paper uses mean-risk model and risk curve obtained from the same model for portfolio selection problem. Security returns are assumed to be normally distributed. Further, the same mean-risk model is modified by using entropy to diversify the risk; this model can be called as mean-risk diversification model. In both the models, normal distribution is used to calculate the probability of likely losses of portfolio. The idea of mean-risk model is to regard expected return of a portfolio as the investment return and risk curve thus formed as investment risk, and the idea of mean-risk diversification model is to ensure that the portfolio thus formed is well diversified. The objective is to maximise the investor's return at a preset confidence level and minimise the risk. Two numerical examples are presented for the sake of illustration.
Keywords: risk curve; confidence curve; entropy; portfolio selection; mean-risk diversification; investment risks; investment returns. (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=47093 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ids:ijores:v:14:y:2012:i:3:p:324-342
Access Statistics for this article
More articles in International Journal of Operational Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().