Asset selection based on high frequency Sharpe ratio
文献类型:期刊论文
作者 | Wang, Christina Dan6; Chen, Zhao5; Lian, Yimin4; Chen, Min1,2,3![]() |
刊名 | JOURNAL OF ECONOMETRICS
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出版日期 | 2022-03-01 |
卷号 | 227期号:1页码:168-188 |
关键词 | Asset selection High frequency Sharpe ratio Ultrahigh dimensional Serial correlation Sure screening property |
ISSN号 | 0304-4076 |
DOI | 10.1016/j.jeconom.2020.05.007 |
英文摘要 | In portfolio choice problems, the classical Mean-Variance model in Markowitz (1952) relies heavily on the covariance structure among assets. As the number and types of assets increase rapidly, traditional methods to estimate the covariance matrix and its inverse suffer from the common issues in high or ultra-high dimensional analysis. To avoid the issue of estimating the covariance matrix with high or ultra-high dimensional data, we propose a fast procedure to reduce dimension based on a new risk/return measure constructed from intra-day high frequency data and select assets via Dependent Sure Explained Variability and Independence Screening (D-SEVIS). While most feature screening methods assume i.i.d. samples, by nature of our data, we make contribution to studying D-SEVIS for samples with serial correlation, specifically, for the stationary alpha-mixing processes. Under alpha-mixing condition, we prove that D-SEVIS satisfies sure screening property and ranking consistency property. More importantly, with the assets selected through D-SEVIS, we will build a portfolio that earns more excess return compared with several existing portfolio allocation methods. We illustrate this advantage of our asset selection method with the real data from the stock market. (C) 2020 Elsevier B.V. All rights reserved. |
资助项目 | National Natural Science Foundation of China (NNSFC)[11901395] ; Shanghai Pujiang Program, China[19PJ1400900] ; Shanghai Pujiang Program, China[19PJ1408200] ; NNSFC, China[11690015] ; NNSFC, China[U1811461] ; NNSFC, China[71991475] ; NNSFC, China[11690014/11690010] ; NNSFC, China[11731015] ; Shanghai Municipal Science and Technology Major Project, China[2018SHZDZX01] |
WOS研究方向 | Business & Economics ; Mathematics ; Mathematical Methods In Social Sciences |
语种 | 英语 |
WOS记录号 | WOS:000760554100010 |
出版者 | ELSEVIER SCIENCE SA |
源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/60112] ![]() |
专题 | 应用数学研究所 |
通讯作者 | Chen, Zhao |
作者单位 | 1.Univ Chinese Acad Sci, Beijing, Peoples R China 2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100080, Peoples R China 3.Zhongnan Univ Econ & Law, Wuhan, Hubei, Peoples R China 4.Univ Sci & Technol China, Sch Management, Hefei 230026, Peoples R China 5.Fudan Univ, Sch Data Sci, Shanghai 200433, Peoples R China 6.New York Univ Shanghai, Business Div, Shanghai 200122, Peoples R China |
推荐引用方式 GB/T 7714 | Wang, Christina Dan,Chen, Zhao,Lian, Yimin,et al. Asset selection based on high frequency Sharpe ratio[J]. JOURNAL OF ECONOMETRICS,2022,227(1):168-188. |
APA | Wang, Christina Dan,Chen, Zhao,Lian, Yimin,&Chen, Min.(2022).Asset selection based on high frequency Sharpe ratio.JOURNAL OF ECONOMETRICS,227(1),168-188. |
MLA | Wang, Christina Dan,et al."Asset selection based on high frequency Sharpe ratio".JOURNAL OF ECONOMETRICS 227.1(2022):168-188. |
入库方式: OAI收割
来源:数学与系统科学研究院
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