Multi-objective approaches to portfolio optimization with market impact costs

doi:10.1007/s12293-022-00381-w

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 机器人应用与理论组

	Multi-objective approaches to portfolio optimization with market impact costs
	Wang, Hongze 1,3; Li, Xuerong 2; Hong, Wenjing 4; Tang, Ke 4
刊名	MEMETIC COMPUTING
	2022-10-22
页码	11
关键词	Portfolio optimization Market impact cost Multi-objective optimization Evolutionary computation Memetic algorithm
ISSN号	1865-9284
DOI	10.1007/s12293-022-00381-w
通讯作者	Li, Xuerong(lixuerong@amss.ac.cn)
英文摘要	Market impact costs are important factors to portfolio management, which always lead to adverse price fluctuations in trading. As the practical trading volume becomes increasingly large, the Problem of Portfolio Optimization with Market Impact Costs (MICPOP) has become more important. Traditional MICPOPs involve seeking an optimal allocation of capital to a limited number of assets with respect to either additional constraints or a weighted sum of objectives (net return, investment risk). We suggest solving MICPOPs with Multi-Objective Evolutionary Algorithms (MOEAs). Specifically, we formulate MICPOPs as a bi-objective optimization problem. The advantages of MOEAs over state-of-the-art single objective approaches to MICPOPs will be shown through empirical studies. Our study has revealed that a well-known MOEA, namely Nondominated Sorting Genetic Algorithm II (NSGA-II), fails to provide satisfactory solution quality sometimes. Hence, a memetic MOEA for Portfolio Optimization with Market Impact costs (POMI-MOEA), which inherits the global search capability of NSGA-II while introducing a new local search operator, is proposed and evaluated in this paper. Comprehensive experimental studies on 11 portfolio cases have shown the superiority of POMI-MOEA over NSGA-II and other two MOEAs for MICPOPs.
资助项目	National Natural Science Foundation of China[71901205]
WOS关键词	TRANSACTION COST ; ALGORITHM ; MODEL
WOS研究方向	Computer Science ; Operations Research & Management Science
语种	英语
出版者	SPRINGER HEIDELBERG
WOS记录号	WOS:000870949700001
资助机构	National Natural Science Foundation of China
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/50263]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_机器人应用与理论组
通讯作者	Li, Xuerong
作者单位	1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China 3.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 4.Southern Univ Sci & Technol, Dept Comp Sci & Engn, Guangdong Prov Key Lab Brain Inspired Intelligent, Shenzhen 518055, Peoples R China
推荐引用方式 GB/T 7714	Wang, Hongze,Li, Xuerong,Hong, Wenjing,et al. Multi-objective approaches to portfolio optimization with market impact costs[J]. MEMETIC COMPUTING,2022:11.
APA	Wang, Hongze,Li, Xuerong,Hong, Wenjing,&Tang, Ke.(2022).Multi-objective approaches to portfolio optimization with market impact costs.MEMETIC COMPUTING,11.
MLA	Wang, Hongze,et al."Multi-objective approaches to portfolio optimization with market impact costs".MEMETIC COMPUTING (2022):11.