KMS Of Academy of mathematics and systems sciences, CAS
Asset selection based on high frequency Sharpe ratio | |
Wang, Christina Dan1; Chen, Zhao2; Lian, Yimin3; Chen, Min4,5,6![]() | |
2022-03-01 | |
Source Publication | JOURNAL OF ECONOMETRICS
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ISSN | 0304-4076 |
Volume | 227Issue:1Pages:168-188 |
Abstract | 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. |
Keyword | Asset selection High frequency Sharpe ratio Ultrahigh dimensional Serial correlation Sure screening property |
DOI | 10.1016/j.jeconom.2020.05.007 |
Indexed By | SCI |
Language | 英语 |
Funding Project | 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 Research Area | Business & Economics ; Mathematics ; Mathematical Methods In Social Sciences |
WOS Subject | Economics ; Mathematics, Interdisciplinary Applications ; Social Sciences, Mathematical Methods |
WOS ID | WOS:000760554100010 |
Publisher | ELSEVIER SCIENCE SA |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | http://ir.amss.ac.cn/handle/2S8OKBNM/60113 |
Collection | 应用数学研究所 |
Corresponding Author | Chen, Zhao |
Affiliation | 1.New York Univ Shanghai, Business Div, Shanghai 200122, Peoples R China 2.Fudan Univ, Sch Data Sci, Shanghai 200433, Peoples R China 3.Univ Sci & Technol China, Sch Management, Hefei 230026, Peoples R China 4.Zhongnan Univ Econ & Law, Wuhan, Hubei, Peoples R China 5.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100080, Peoples R China 6.Univ Chinese Acad Sci, Beijing, Peoples R China |
Recommended Citation 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. |
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