Portfolio Optimization with Factors, Scenarios, and Realistic Short Positions
Bruce I. Jacobs (),
Kenneth N. Levy () and
Harry Markowitz
Additional contact information
Bruce I. Jacobs: Jacobs Levy Equity Management, 100 Campus Drive, P.O. Box 650, Florham Park, New Jersey 07932-0650
Kenneth N. Levy: Jacobs Levy Equity Management, 100 Campus Drive, P.O. Box 650, Florham Park, New Jersey 07932-0650
Operations Research, 2005, vol. 53, issue 4, 586-599
Abstract:
This paper presents fast algorithms for calculating mean-variance efficient frontiers when the investor can sell securities short as well as buy long, and when a factor and/or scenario model of covariance is assumed. Currently, fast algorithms for factor, scenario, or mixed (factor and scenario) models exist, but (except for a special case of the results reported here) apply only to portfolios of long positions. Factor and scenario models are used widely in applied portfolio analysis, and short sales have been used increasingly as part of large institutional portfolios. Generally, the critical line algorithm (CLA) traces out mean-variance efficient sets when the investor’s choice is subject to any system of linear equality or inequality constraints. Versions of CLA that take advantage of factor and/or scenario models of covariance gain speed by greatly simplifying the equations for segments of the efficient set. These same algorithms can be used, unchanged, for the long-short portfolio selection problem provided a certain condition on the constraint set holds. This condition usually holds in practice.
Keywords: finance; portfolio:optimization with short sales (search for similar items in EconPapers)
Date: 2005
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (29)
Downloads: (external link)
http://dx.doi.org/10.1287/opre.1050.0212 (application/pdf)
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:inm:oropre:v:53:y:2005:i:4:p:586-599
Access Statistics for this article
More articles in Operations Research from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().