EconPapers    
Economics at your fingertips  
 

Portfolio optimization for wealth-dependent risk preferences

Luis Rios () and Nikolaos Sahinidis ()

Annals of Operations Research, 2010, vol. 177, issue 1, 63-90

Abstract: Empirical and theoretical studies of preference structures of investors have long shown that personal and corporate utility is typically multimodal, implying that the same investor can be risk-averse at certain levels of wealth while risk-seeking at others. In this paper, we consider the problem of optimizing the portfolio of an investor with an indefinite quadratic utility function. The convex and concave segments of this utility reflect the investor’s attitude towards risk, which changes based on deviations from a fixed goal. Uncertainty is modeled via a finite set of scenarios for the returns of securities. A global optimization approach is developed to solve the proposed nonconvex optimization problem. We present computational results which investigate the effect of short sales and demonstrate that the proposed approach systematically produces portfolios with higher values of skewness than the classical expectation-variance approach. Copyright Springer Science+Business Media, LLC 2010

Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://hdl.handle.net/10.1007/s10479-009-0592-6 (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:spr:annopr:v:177:y:2010:i:1:p:63-90:10.1007/s10479-009-0592-6

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1007/s10479-009-0592-6

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:annopr:v:177:y:2010:i:1:p:63-90:10.1007/s10479-009-0592-6