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.
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