Portfolio optimization under D.C. transaction costs and minimal transaction unit constraints

Authors:
Hiroshi Konno;Annista Wijayanayake
Affiliations:
Department of Industrial Engineering and Management and Center for Research in Advanced Financial Technologies, Tokyo Institute of Technology, Tokyo, Japan (E-mail: konno@indsys.chuo-u.ac. ...;Department of Industrial Engineering and Management, Tokyo Institute of Technology, Tokyo, Japan
Venue:
Journal of Global Optimization
Year:
2002

Citing 2
Cited 8

Mean-absolute deviation portfolio optimization model and its applications to Tokyo stock market

Management Science
Decomposition branch and bound method for globally solving linearly constrained indefinite quadratic minimization problems

Operations Research Letters

Optimal Security Liquidation Algorithms

Computational Optimization and Applications
Global Optimization Versus Integer Programming in Portfolio Optimization under Nonconvex Transaction Costs

Journal of Global Optimization
Models and Simulations for Portfolio Rebalancing

Computational Economics
A branch and reduce approach for solving a class of low rank d.c. programs

Journal of Computational and Applied Mathematics
Possibilistic Approaches to Portfolio Selection Problem with General Transaction Costs and a CLPSO Algorithm

Computational Economics
Dynamic multi-stage resource selection with preference factors in grid economy

GCC'05 Proceedings of the 4th international conference on Grid and Cooperative Computing
Solving a class of low rank d.c. programs via a branch and bound approach: A computational experience

Operations Research Letters
Dynamic objectives aggregation methods for evolutionary portfolio optimisation. A computational study

International Journal of Bio-Inspired Computation

Quantified Score

Hi-index	0.02

Visualization

Abstract

This paper addresses itself to a portfolio optimization problem under nonconvex transaction costs and minimal transaction unit constraints. Associated with portfolio construction is a fee for purchasing assets. Unit transaction fee is larger when the amount of transaction is smaller. Hence the transaction cost is usually a concave function up to certain point. When the amount of transaction increases, the unit price of assets increases due to illiquidity/market impact effects. Hence the transaction cost becomes convex beyond certain bound. Therefore, the net expected return becomes a general d.c. function (difference of two convex functions). We will propose a branch-and-bound algorithm for the resulting d.c. maximization problem subject to a constraint on the level of risk measured in terms of the absolute deviation of the rate of return of a portfolio. Also, we will show that the minimal transaction unit constraints can be incorporated without excessively increasing the amount of computation.