Integer programming approaches in mean-risk models

Hiroshi Konno, Rei Yamamoto

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

This paper is concerned with porfolio optimization problems with integer constraints. Such problems include, among others mean-risk problems with nonconvex transaction cost, minimal transaction unit constraints and cardinality constraints on the number of assets in a portfolio. These problems, though practically very important have been considered intractable because we have to solve nonlinear integer programming problems for which there exists no efficient algorithms. We will show that these problems can now be solved by the state-of-the-art integer programming methodologies if we use absolute deviation as the measure of risk.

Original languageEnglish
Pages (from-to)339-351
Number of pages13
JournalComputational Management Science
Volume2
Issue number4
DOIs
Publication statusPublished - 2005 Nov 1
Externally publishedYes

Fingerprint

Integer programming
Costs
Risk model
Optimization problem
Deviation
Transaction costs
Methodology
Assets
Measure of risk
Integer

Keywords

  • Integer constraints
  • Integer programming
  • Mean-absolute deviation model
  • Portfolio optimization

ASJC Scopus subject areas

  • Business, Management and Accounting (miscellaneous)

Cite this

Integer programming approaches in mean-risk models. / Konno, Hiroshi; Yamamoto, Rei.

In: Computational Management Science, Vol. 2, No. 4, 01.11.2005, p. 339-351.

Research output: Contribution to journalArticle

Konno, Hiroshi ; Yamamoto, Rei. / Integer programming approaches in mean-risk models. In: Computational Management Science. 2005 ; Vol. 2, No. 4. pp. 339-351.
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