Determining the number of factors in approximate factor models by twice K-fold cross validation
2020
Wei, Jie | Chen, Hui
We propose a data driven determination method of the number of factors by cross validation (CV) in approximate factor models. A K-fold CV is applied along each of the two directions (individual and time) of a panel dataset. We prove the consistency of the proposed twice K-fold CV under mild conditions. Monte Carlo simulations demonstrate superior and robust performance of our selection method in comparison with existing approaches, especially at small panels with moderate units or time lengths. An empirical application to identify factor numbers in the UK is provided.
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书目信息
Economics letters
卷
191
页码
109149
ISSN
0165-1765
出版者
Elsevier B.V.
其它主题
K-fold cross validation; C55; C52; Approximate factor models; Finite sample performance
语言
英语
类型
Journal Article; Text
2024-02-28
MODS