A multiple stochastic goal programming approach for the agent portfolio selection problem

Hatem Masri ()
Additional contact information
Hatem Masri: University of Bahrain

Annals of Operations Research, 2017, vol. 251, issue 1, No 11, 179-192

Abstract: Abstract Stochastic goal programming is a suitable solution approach for multi-objective stochastic programs when a unique goal is settled for each objective function. In this paper, we address the case of multiple stochastic goals for an objective function. We derive results from studying the agent portfolio selection problem. The proposed multiple stochastic goal programming approach allows investors to set different goals for the return objective function. A chance constrained approach is proposed to address the stochastic investors’ minimum acceptable rate of return and a recourse approach to deal with investors’ ideal rate of return. An empirical study from Bahrain stock market is reported.

Keywords: Multi-objective stochastic programming; Stochastic goal programming; Chance constrained approach; Recourse approach; Portfolio selection problem (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://link.springer.com/10.1007/s10479-015-1884-7 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:annopr:v:251:y:2017:i:1:d:10.1007_s10479-015-1884-7

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

DOI: 10.1007/s10479-015-1884-7

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 ().