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Determining the Number of Factors from Empirical Distribution of Eigenvalues
Open accessAbstract
We develop a new estimator of the number of factors in the approximate factor models. The estimator works well even when the idiosyncratic terms are substantially correlated. It is based on the fact, established in the paper, that any finite number of the largest “idiosyncratic” eigenvalues of the sample covariance matrix cluster around a single point. In contrast, all the “systematic” eigenvalues, the number of which equals the number of factors, diverge to infinity. The estimator consistently separates the diverging eigenvalues from the cluster and counts the number of the separated eigenvalues. We consider a macroeconomic and a financial application.
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Cites
The Penn World Table (Mark 5): An Expanded Set of International Comparisons, 1950-1988
Summers, R., & Heston, A. (1991) · The Quarterly Journal of Economics · doi:10.2307/2937941 · Cited by 3,429
Cited by
Forecasting the equity risk premium: the role of technical indicators
Neely, C. J., Rapach, D. E., Tu, J., & Zhou, G. (2014) · Management Science · doi:10.1287/mnsc.2013.1838 · Cited by 1,003
Eigenvalue Ratio Test for the Number of Factors
(2013) · Econometrica · doi:10.3982/ecta8968 · Cited by 936
Onatski, A. (2012) · Journal of Econometrics · doi:10.1016/j.jeconom.2012.01.034 · Cited by 314
Self-citationDetermining the Rank of the Beta Matrix in Linear Asset Pricing Models
Ahn, S. C., Horenstein, A. R., & Wang, N. (2011) · SSRN Electronic Journal · doi:10.2139/ssrn.1784566 · Cited by 2
Metadata
- Authors
- Onatski, A.
- Venue
- Review of Economics and Statistics
- Publisher
- MIT Press - Journals
- Published
- 2010-11
- Volume
- 92
- Issue
- 4
- Pages
- 1004-1016
- ISSN
- 0034-6535 (ISSN-L)
- 1530-9142
- OpenAlex
- W1975395389
- Cited by
- 682
- References
- 1
- FWCI
- 21.28
- Type
- journal article
- Language
- en
- Open access
- green
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