Global Optimization Versus Integer Programming in Portfolio Optimization under Nonconvex Transaction Costs

  • Authors:
  • Hiroshi Konno;Rei Yamamoto

  • Affiliations:
  • Department of Industrial and Systems Engineering, Chuo University, Bunkyo-Ku, Japan 112-855-1;Department of Industrial and Systems Engineering, Chuo University, Bunkyo-Ku, Japan 112-855-1

  • Venue:
  • Journal of Global Optimization
  • Year:
  • 2005

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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.