Perez, Marcos and Ahn, Seung Chan (2007): GMM Estimation of the Number of Latent Factors.

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Abstract
We propose a generalized method of moment (GMM) estimator of the number of latent factors in linear factor models. The method is appropriate for panels a large (small) number of crosssection observations and a small (large) number of timeseries observations. It is robust to heteroskedasticity and time series autocorrelation of the idiosyncratic components. All necessary procedures are similar to three stage least squares, so they are computationally easy to use. In addition, the method can be used to determine what observable variables are correlated with the latent factors without estimating them. Our Monte Carlo experiments show that the proposed estimator has good finitesample properties. As an application of the method, we estimate the number of factors in the US stock market. Our results indicate that the US stock returns are explained by three factors. One of the three latent factors is not captured by the factors proposed by Chen Roll and Ross 1986 and Fama and French 1996.
Item Type:  MPRA Paper 

Institution:  Arizona State UNiversity 
Original Title:  GMM Estimation of the Number of Latent Factors 
Language:  English 
Keywords:  Factor models; GMM; number of factors; asset pricing 
Subjects:  C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C10  General G  Financial Economics > G1  General Financial Markets > G12  Asset Pricing ; Trading Volume ; Bond Interest Rates C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C13  Estimation: General C  Mathematical and Quantitative Methods > C3  Multiple or Simultaneous Equation Models ; Multiple Variables > C33  Panel Data Models ; Spatiotemporal Models 
Item ID:  4862 
Depositing User:  PEREZ MARCOS 
Date Deposited:  12. Sep 2007 
Last Modified:  19. Feb 2013 04:52 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/4862 