### 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 |
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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 |

### Keywords

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

### ASJC Scopus subject areas

- Management Information Systems
- Information Systems

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## Cite this

Konno, H., & Yamamoto, R. (2005). Integer programming approaches in mean-risk models.

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