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Asset selection based on high frequency Sharpe ratio
Wang, Christina Dan1; Chen, Zhao2; Lian, Yimin3; Chen, Min4,5,6
AbstractIn 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.
KeywordAsset selection High frequency Sharpe ratio Ultrahigh dimensional Serial correlation Sure screening property
Indexed BySCI
Funding ProjectNational 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 AreaBusiness & Economics ; Mathematics ; Mathematical Methods In Social Sciences
WOS SubjectEconomics ; Mathematics, Interdisciplinary Applications ; Social Sciences, Mathematical Methods
WOS IDWOS:000760554100010
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Document Type期刊论文
Corresponding AuthorChen, Zhao
Affiliation1.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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