Lorenzo Trapani
A Randomized Sequential Procedure to Determine the Number of Factors
Trapani, Lorenzo
Authors
Abstract
© 2018, © 2018 American Statistical Association. This article proposes a procedure to estimate the number of common factors k in a static approximate factor model. The building block of the analysis is the fact that the first k eigenvalues of the covariance matrix of the data diverge, while the others stay bounded. On the grounds of this, we propose a test for the null that the ith eigenvalue diverges, using a randomized test statistic based directly on the estimated eigenvalue. The test only requires minimal assumptions on the data, and no assumptions are required on factors, loadings or idiosyncratic errors. The randomized tests are then employed in a sequential procedure to determine k. Supplementary materials for this article are available online.
Citation
Trapani, L. (2018). A Randomized Sequential Procedure to Determine the Number of Factors. Journal of the American Statistical Association, 113(523), 1341-1349. https://doi.org/10.1080/01621459.2017.1328359
Journal Article Type | Article |
---|---|
Acceptance Date | Apr 30, 2017 |
Online Publication Date | Jun 26, 2017 |
Publication Date | Jun 26, 2018 |
Deposit Date | Oct 3, 2017 |
Publicly Available Date | Mar 28, 2024 |
Journal | Journal of the American Statistical Association |
Print ISSN | 0162-1459 |
Electronic ISSN | 1537-274X |
Publisher | Taylor & Francis Open |
Peer Reviewed | Peer Reviewed |
Volume | 113 |
Issue | 523 |
Pages | 1341-1349 |
DOI | https://doi.org/10.1080/01621459.2017.1328359 |
Keywords | Approximate factor models, Randomised tests, Number of factors |
Public URL | https://nottingham-repository.worktribe.com/output/868580 |
Publisher URL | https://www.tandfonline.com/doi/full/10.1080/01621459.2017.1328359 |
Additional Information | This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of the American Statistical Association on 26/06/2017, available online: http://www.tandfonline.com/10.1080/01621459.2017.1328359 |
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