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

Hiroshi Konno, Rei Yamamoto

研究成果: Article

22 引用 (Scopus)

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
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

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

ASJC Scopus subject areas

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

これを引用

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