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

Hiroshi Konno, Rei Yamamoto

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)207-219
Number of pages13
JournalJournal of Global Optimization
Volume32
Issue number2
DOIs
Publication statusPublished - 2005 Jun 1
Externally publishedYes

Fingerprint

Portfolio Optimization
Transaction Costs
Integer programming
Global optimization
Integer Programming
Global Optimization
Branch and bound method
Costs
0-1 Integer Programming
Branch and Bound Method
Branch and Bound Algorithm
Linear Constraints
Deviation
Optimization Problem
Transaction costs
Portfolio optimization
Optimization problem
Measure of risk
Branch and bound algorithm
Branch-and-bound

Keywords

  • 0-1 integer programming
  • Branch and bound algorithm
  • Global optimization
  • Nonconvex transaction cost
  • Portfolio optimization

ASJC Scopus subject areas

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

Cite this

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

In: Journal of Global Optimization, Vol. 32, No. 2, 01.06.2005, p. 207-219.

Research output: Contribution to journalArticle

@article{33152983a72b4563bf5dad19249ca9c7,
title = "Global optimization versus integer programming in portfolio optimization under nonconvex transaction costs",
abstract = "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.",
keywords = "0-1 integer programming, Branch and bound algorithm, Global optimization, Nonconvex transaction cost, Portfolio optimization",
author = "Hiroshi Konno and Rei Yamamoto",
year = "2005",
month = "6",
day = "1",
doi = "10.1007/s10898-004-2703-x",
language = "English",
volume = "32",
pages = "207--219",
journal = "Journal of Global Optimization",
issn = "0925-5001",
publisher = "Springer Netherlands",
number = "2",

}

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 -