UM
Residential Collegefalse
Status已發表Published
Improving Minimum Variance Portfolios by Alleviating Over-Dispersion of Eigenvalues
Fangquan Shi1; Lianjie Shu1; Aijun Yang2; Fangyi He3
2019-10
Source PublicationJournal of Financial and Quantitative Analysis
ABS Journal Level4
ISSN0022-1090
Pages1-62
Abstract

In portfolio risk minimization, the inverse covariance matrix of returns is often unknown and has to be estimated in practice. Yet the eigenvalues of the sample covariance matrix are often over-dispersed, leading to severe estimation errors in the inverse covariance matrix. To deal with this problem, we propose a general framework by shrinking the sample eigenvalues based on Schatten norm. The proposed framework has the advantage to be computationally efficient as well as structure free. The comparative studies show that our approach behaves reasonably well in terms of reducing out-of-sample portfolio risk and turnover.

DOIhttps://doi.org/10.1017/S0022109019000899
Language英語English
Fulltext Access
Citation statistics
Document TypeJournal article
CollectionUniversity of Macau
Corresponding AuthorLianjie Shu
Affiliation1.University of Macau Faculty of Business Administration
2.Southwestern University of Finance and Economics School of Finance
3.Nanjing Forest University College of Economics and Management
First Author AffilicationFaculty of Business Administration
Corresponding Author AffilicationFaculty of Business Administration
Recommended Citation
GB/T 7714
Fangquan Shi,Lianjie Shu,Aijun Yang,et al. Improving Minimum Variance Portfolios by Alleviating Over-Dispersion of Eigenvalues[J]. Journal of Financial and Quantitative Analysis,2019:1-62.
APA Fangquan Shi,Lianjie Shu,Aijun Yang,&Fangyi He.(2019).Improving Minimum Variance Portfolios by Alleviating Over-Dispersion of Eigenvalues.Journal of Financial and Quantitative Analysis,1-62.
MLA Fangquan Shi,et al."Improving Minimum Variance Portfolios by Alleviating Over-Dispersion of Eigenvalues".Journal of Financial and Quantitative Analysis (2019):1-62.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Fangquan Shi]'s Articles
[Lianjie Shu]'s Articles
[Aijun Yang]'s Articles
Baidu academic
Similar articles in Baidu academic
[Fangquan Shi]'s Articles
[Lianjie Shu]'s Articles
[Aijun Yang]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Fangquan Shi]'s Articles
[Lianjie Shu]'s Articles
[Aijun Yang]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.