Integer and combinatorial optimization
Integer and combinatorial optimization
Portfolio optimization under D.C. transaction costs and minimal transaction unit constraints
Journal of Global Optimization
Hi-index | 0.00 |
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.