A comparative study of heuristic methods for cardinality constrained portfolio optimization
作者机构:Bank of JiangsuNanjing 210001China School of EconomicsFudan UniversityShanghai 200433China School of Information Management and EngineeringShanghai University of Finance and EconomicsShanghai 200433China
出 版 物:《高置信计算(英文)》 (High-Confidence Computing)
年 卷 期:2023年第3卷第1期
页 面:23-30页
核心收录:
学科分类:0711[理学-系统科学] 07[理学] 0701[理学-数学] 070101[理学-基础数学]
主 题:Acceleration Mean-variance portfolio optimization Cardinality constraint Mixed-integer programming
摘 要:The cardinality constrained mean–variance(CCMV)portfolio selection model aims to identify a subset of the candidate assets such that the constructed portfolio has a guaranteed expected return and minimum *** formulating this model as the mixed-integer quadratic program(MIQP),the exact solution can be solved by a branch-and-bound ***,computational efficiency is the central issue in the time-sensitive portfolio investment due to its NP-hardness *** accelerate the solution speeds to CCMV portfolio optimization problems,we develop various heuristic methods based on techniques such as continuous relaxation,l1-norm approximation,integer optimization,and relaxation of semi-definite programming(SDP).We evaluate our heuristic methods by applying them to the US equity market *** experimental results show that our SDP-based method is effective in terms of the computation time and the approximation *** SDP-based method performs even better than a commercial MIQP solver when the computational time is *** addition,several investment companies in China have adopted our methods,gaining good *** paper sheds light on the computation optimization for financial investments.