(1) Department of Industrial and Systems Engineering, Chuo University, 1-13-27 Kasuga, Bunkyo-Ku 112-855-1, Tokyo, Japan
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.