A diagnostic Criterion for approximate factor structure
We build a simple diagnostic criterion for approximate factor structure in large panel datasets. Given observable factors, the criterion checks whether the errors are weakly cross-sectionally correlated or share at least one unobservable common factor (interactive effects). A general version allows determining the number of omitted common factors also for time-varying structures. The empirical analysis runs on ten thousand US stocks from January 1968 to December 2011. For monthly returns, we select time-invariant specifications with at least four financial factors, and a scaled three-factor specification. For quarterly returns, we cannot select macroeconomic models without the market factor.
GAGLIARDINI Patrick;
OSSOLA Elisa;
SCAILLET Olivier;
2019-09-11
ELSEVIER SCIENCE SA
JRC117023
0304-4076 (online),
https://www.sciencedirect.com/science/article/pii/S030440761930137X?via%3Dihub,
https://publications.jrc.ec.europa.eu/repository/handle/JRC117023,
10.1016/j.jeconom.2019.06.001 (online),
Additional supporting files
| File name | Description | File type | |
|---|
