Title
Cutting plane algorithms for mean-CVaR portfolio optimization with nonconvex transaction costs
Abstract
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.
Year
DOI
Venue
2015
10.1007/s10287-014-0209-7
Comput. Manag. Science
Keywords
Field
DocType
portfolio optimization,conditional value at risk,transaction costs
Mathematical optimization,Subgradient method,Portfolio optimization,Integer programming,Minification,Risk measure,Mathematics,Expected shortfall,Special ordered set,CVAR
Journal
Volume
Issue
ISSN
12
2
1619-6988
Citations 
PageRank 
References 
1
0.37
13
Authors
4
Name
Order
Citations
PageRank
Yuichi Takano1416.35
keisuke nanjo210.37
Noriyoshi Sukegawa3286.41
Shinji Mizuno4792153.37