On the statistical analysis of high-dimensional factor models

Junfan Mao (), Zhigen Gao (), Bing-Yi Jing () and Jianhua Guo ()
Additional contact information
Junfan Mao: Northeast Normal University
Zhigen Gao: Northeast Normal University
Bing-Yi Jing: Southern University of Science and Technology
Jianhua Guo: Beijing Technology and Business University

Statistical Papers, 2024, vol. 65, issue 8, No 8, 5019 pages

Abstract: Abstract High-dimensional factor models have received much attention with the rapid development in big data. We make several contributions to the asymptotic properties of Quasi Maximum Likelihood estimations (QMLE) as both the sample size T and the variable dimension N go to infinity. First we eliminate one of rather unnatural assumptions on the variance estimates which is commonly assumed in the literature. Secondly, we give unified results on the asymptotic properties of the QMLE, which greatly expand the scope of earlier studies. Simulations are given to illustrate these results.

Keywords: High-dimensional factor models; Quasi maximum likelihood estimations; Asymptotic properties; Common factors (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s00362-024-01557-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:stpapr:v:65:y:2024:i:8:d:10.1007_s00362-024-01557-x

Ordering information: This journal article can be ordered from
http://www.springer. ... business/journal/362

DOI: 10.1007/s00362-024-01557-x

Access Statistics for this article

Statistical Papers is currently edited by C. Müller, W. Krämer and W.G. Müller

More articles in Statistical Papers from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().