### 抄録

This paper is concerned with a portfolio optimization problem under concave and piecewise constant transaction cost. We formulate the problem as nonconcave maximization problem under linear constraints using absolute deviation as a measure of risk and solve it by a branch and bound algorithm developed in the field of global optimization. Also, we compare it with a more standard 0-1 integer programming approach. We will show that a branch and bound method elaborating the special structure of the problem can solve the problem much faster than the state-of-the integer programming code.

元の言語 | English |
---|---|

ページ（範囲） | 207-219 |

ページ数 | 13 |

ジャーナル | Journal of Global Optimization |

巻 | 32 |

発行部数 | 2 |

DOI | |

出版物ステータス | Published - 2005 6 1 |

外部発表 | Yes |

### Fingerprint

### ASJC Scopus subject areas

- Computer Science Applications
- Control and Optimization
- Management Science and Operations Research
- Applied Mathematics

### これを引用

**Global optimization versus integer programming in portfolio optimization under nonconvex transaction costs.** / Konno, Hiroshi; Yamamoto, Rei.

研究成果: Article

*Journal of Global Optimization*, 巻. 32, 番号 2, pp. 207-219. https://doi.org/10.1007/s10898-004-2703-x

}

TY - JOUR

T1 - Global optimization versus integer programming in portfolio optimization under nonconvex transaction costs

AU - Konno, Hiroshi

AU - Yamamoto, Rei

PY - 2005/6/1

Y1 - 2005/6/1

N2 - This paper is concerned with a portfolio optimization problem under concave and piecewise constant transaction cost. We formulate the problem as nonconcave maximization problem under linear constraints using absolute deviation as a measure of risk and solve it by a branch and bound algorithm developed in the field of global optimization. Also, we compare it with a more standard 0-1 integer programming approach. We will show that a branch and bound method elaborating the special structure of the problem can solve the problem much faster than the state-of-the integer programming code.

AB - This paper is concerned with a portfolio optimization problem under concave and piecewise constant transaction cost. We formulate the problem as nonconcave maximization problem under linear constraints using absolute deviation as a measure of risk and solve it by a branch and bound algorithm developed in the field of global optimization. Also, we compare it with a more standard 0-1 integer programming approach. We will show that a branch and bound method elaborating the special structure of the problem can solve the problem much faster than the state-of-the integer programming code.

KW - 0-1 integer programming

KW - Branch and bound algorithm

KW - Global optimization

KW - Nonconvex transaction cost

KW - Portfolio optimization

UR - http://www.scopus.com/inward/record.url?scp=25444530948&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=25444530948&partnerID=8YFLogxK

U2 - 10.1007/s10898-004-2703-x

DO - 10.1007/s10898-004-2703-x

M3 - Article

AN - SCOPUS:25444530948

VL - 32

SP - 207

EP - 219

JO - Journal of Global Optimization

JF - Journal of Global Optimization

SN - 0925-5001

IS - 2

ER -