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Global Optimization for the Portfolio Selection Model with High-Order Moments

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成果类型:
期刊论文
作者:
Liu Yang*;Yi Yang;Su-Han Zhong
通讯作者:
Liu Yang
作者机构:
Hunan Key Laboratory for Computation and Simulation in Science and Engineering, Xiangtan University, Xiangtan, China
School of Mathematics and Computational Sciences, Xiangtan University, Xiangtan, China
[Yi Yang] School of Mathematics, Hunan City University, Yiyang, China
[Su-Han Zhong] Department of Mathematics, Texas A &M University, College Station, USA
[Liu Yang] Hunan Key Laboratory for Computation and Simulation in Science and Engineering, Xiangtan University, Xiangtan, China<&wdkj&>School of Mathematics and Computational Sciences, Xiangtan University, Xiangtan, China
通讯机构:
[Liu Yang] H
Hunan Key Laboratory for Computation and Simulation in Science and Engineering, Xiangtan University, Xiangtan, China<&wdkj&>School of Mathematics and Computational Sciences, Xiangtan University, Xiangtan, China
语种:
英文
关键词:
Portfolio selection model;High-order moments;Moment-SOS relaxation;Perturbation sample average approximation
期刊:
中国运筹学学会学报(英文)
ISSN:
2194-668X
年:
2023
页码:
1-22
机构署名:
本校为其他机构
院系归属:
理学院
摘要:
In this paper, we study the global optimality of polynomial portfolio optimization (PPO). The PPO is a kind of portfolio selection model with high-order moments and flexible risk preference parameters. We introduce a perturbation sample average approximation method, which can give a robust approximation of the PPO in form of linear conic optimization. The approximated problem can be solved globally with Moment-SOS relaxations. We summarize a semidefinite algorithm, which can be used to find reliable approximations of the optimal value and optimizer set of the PPO....

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