### 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 language | English |
---|---|

Pages (from-to) | 339-351 |

Number of pages | 13 |

Journal | Computational Management Science |

Volume | 2 |

Issue number | 4 |

DOIs | |

Publication status | Published - 2005 Nov 1 |

Externally published | Yes |

### Fingerprint

### Keywords

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

### ASJC Scopus subject areas

- Business, Management and Accounting (miscellaneous)

### Cite this

*Computational Management Science*,

*2*(4), 339-351. https://doi.org/10.1007/s10287-005-0038-9

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

Research output: Contribution to journal › Article

*Computational Management Science*, vol. 2, no. 4, pp. 339-351. https://doi.org/10.1007/s10287-005-0038-9

}

TY - JOUR

T1 - Integer programming approaches in mean-risk models

AU - Konno, Hiroshi

AU - Yamamoto, Rei

PY - 2005/11/1

Y1 - 2005/11/1

N2 - 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.

AB - 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.

KW - Integer constraints

KW - Integer programming

KW - Mean-absolute deviation model

KW - Portfolio optimization

UR - http://www.scopus.com/inward/record.url?scp=27644465300&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=27644465300&partnerID=8YFLogxK

U2 - 10.1007/s10287-005-0038-9

DO - 10.1007/s10287-005-0038-9

M3 - Article

AN - SCOPUS:27644465300

VL - 2

SP - 339

EP - 351

JO - Computational Management Science

JF - Computational Management Science

SN - 1619-697X

IS - 4

ER -