caa a22 4500 606233105 CHVBK 20210128101230.0 cr unu---uuuuu 210128e20150401xx s 000 0 eng 10.1007/s10287-014-0209-7 doi (NATIONALLICENCE)springer-10.1007/s10287-014-0209-7 Cutting plane algorithms for mean-CVaR portfolio optimization with nonconvex transaction costs [Elektronische Daten] [Yuichi Takano, Keisuke Nanjo, Noriyoshi Sukegawa, Shinji Mizuno] This paper studies the mean-risk portfolio optimization problem with nonconvex transaction costs. We employ the conditional value-at-risk (CVaR) as a risk measure. There are a number of studies that aim at efficiently solving large-scale CVaR minimization problems. None of these studies, however, take into account nonconvex transaction costs, which are present in practical situations. To make a piecewise linear approximation of the transaction cost function, we utilized special ordered set type two constraints. Moreover, we devised a subgradient-based cutting plane algorithm to handle a large number of scenarios. This cutting plane algorithm needs to solve a mixed integer linear programming problem in each iteration, and this requires a substantial computation time. Thus, we also devised a two-phase cutting plane algorithm that is even more efficient. Numerical experiments demonstrated that our algorithms can attain near-optimal solutions to large-scale problems in a reasonable amount of time. Especially when rebalancing a current portfolio that is close to an optimal one, our algorithms considerably outperform other solution methods. Springer-Verlag Berlin Heidelberg, 2014 Portfolio optimization nationallicence Conditional value-at-risk nationallicence Cutting plane algorithm nationallicence Transaction costs nationallicence Mixed integer linear programming nationallicence Takano Yuichi School of Network and Information, Senshu University, 2-1-1 Higashimita, Tama-ku, 214-8580, Kawasaki-shi, Kanagawa, Japan aut Nanjo Keisuke Department of Industrial Engineering and Management, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, 152-8552, Tokyo, Japan aut Sukegawa Noriyoshi Department of Industrial Engineering and Management, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, 152-8552, Tokyo, Japan aut Mizuno Shinji Department of Industrial Engineering and Management, Tokyo Institute of Technology, 2-12-1-W9-58 Ookayama, Meguro-ku, 152-8552, Tokyo, Japan aut Computational Management Science Springer Berlin Heidelberg 12/2(2015-04-01), 319-340 1619-697X 12:2<319 2015 12 10287 https://doi.org/10.1007/s10287-014-0209-7 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10287-014-0209-7 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Takano Yuichi School of Network and Information, Senshu University, 2-1-1 Higashimita, Tama-ku, 214-8580, Kawasaki-shi, Kanagawa, Japan aut NATIONALLICENCE 700 1- Nanjo Keisuke Department of Industrial Engineering and Management, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, 152-8552, Tokyo, Japan aut NATIONALLICENCE 700 1- Sukegawa Noriyoshi Department of Industrial Engineering and Management, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, 152-8552, Tokyo, Japan aut NATIONALLICENCE 700 1- Mizuno Shinji Department of Industrial Engineering and Management, Tokyo Institute of Technology, 2-12-1-W9-58 Ookayama, Meguro-ku, 152-8552, Tokyo, Japan aut NATIONALLICENCE 773 0- Computational Management Science Springer Berlin Heidelberg 12/2(2015-04-01), 319-340 1619-697X 12:2<319 2015 12 10287