Optimal Asset Allocation: A Worst Scenario Expectation Approach

Fei Lung Yuen () and Hailiang Yang ()
Additional contact information
Fei Lung Yuen: Heriot-Watt University
Hailiang Yang: The University of Hong Kong

Journal of Optimization Theory and Applications, 2012, vol. 153, issue 3, No 15, 794-811

Abstract: Abstract Mean-variance criterion has long been the main stream approach in the optimal portfolio theory. The investors try to balance the risk and the return on their portfolio. In this paper, the deviation of the asset return from the investor’s expectation in the worst scenario is used as the measure of risk for portfolio selection. One important advantage of this approach is that the investors can base on their own knowledge, information, and preference on various risks, in addition to the asset’s volatility, to adjust their exposure to various risks. It also pinpoints one main concern of the investors when they invest, the amount they lose in the worst situation.

Keywords: Asset allocation; Risk measure; Information uncertainty; Worst case scenario; Incomplete market (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1007/s10957-011-9972-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:joptap:v:153:y:2012:i:3:d:10.1007_s10957-011-9972-6

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2

DOI: 10.1007/s10957-011-9972-6

Access Statistics for this article

Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull

More articles in Journal of Optimization Theory and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().