Portfolio Selection by Goal Programming Techniques

Enrique Ballestero, Ana Garcia-Bernabeu () and Adolfo Hilario ()
Additional contact information
Enrique Ballestero: Universitat Politècnica de València
Ana Garcia-Bernabeu: Universitat Politècnica de València
Adolfo Hilario: Universitat Politècnica de València

Chapter Chapter 5 in Socially Responsible Investment, 2015, pp 111-129 from Springer

Abstract: Abstract Goal programming stems from the Simonian paradigm describing decision makers as seekers of satisfying solutions rather than optimal solutions. Weighted Goal Programming (WGP) is usually viewed as a deterministic model, which provides satisfying solutions to multi-objective technological and economic problems in multiple criteria decision making analysis. Deterministic WGP is less appropriated to select securities portfolios because returns on securities are random variables. To accommodate WGP to portfolio selection, some stochastic versions of different strictness had been proposed. In this chapter, we deal with Mean-Variance Stochastic Goal Programming (MV-SGP) model, which relies on classic expected utility maximization theory, also known as Eu(R), Arrow’s risk aversion and Pratt’s approximation to expected utility.

Keywords: Risk Aversion; Portfolio Selection; Portfolio Weight; Absolute Risk Aversion; Portfolio Variance (search for similar items in EconPapers)
Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (1)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:isochp:978-3-319-11836-9_5

Ordering information: This item can be ordered from
http://www.springer.com/9783319118369

DOI: 10.1007/978-3-319-11836-9_5

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().