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Martingale approximation of eigenvalues for common factor representation

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  • Bystrov, Victor
  • di Salvatore, Antonietta

Abstract

In this paper a martingale approximation is used to derive an asymptotic distribution of simple positive eigenvalues of the sample covariance matrix for a stationary process. The derived distribution can be used to study stability of the common factor representation based on the principal component analysis of the covariance matrix.

Suggested Citation

  • Bystrov, Victor & di Salvatore, Antonietta, 2013. "Martingale approximation of eigenvalues for common factor representation," Statistics & Probability Letters, Elsevier, vol. 83(1), pages 233-237.
    • Handle: RePEc:eee:stapro:v:83:y:2013:i:1:p:233-237
    DOI: 10.1016/j.spl.2012.09.009
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    References listed on IDEAS

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    1. Alexei Onatski, 2009. "Testing Hypotheses About the Number of Factors in Large Factor Models," Econometrica, Econometric Society, vol. 77(5), pages 1447-1479, September.
    2. Magnus, Jan R., 1985. "On Differentiating Eigenvalues and Eigenvectors," Econometric Theory, Cambridge University Press, vol. 1(2), pages 179-191, August.
    3. Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, vol. 71(1), pages 135-171, January.
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    Cited by:

    1. Elhiwi, Majdi, 2014. "Default barrier intensity model for credit risk evaluation," Statistics & Probability Letters, Elsevier, vol. 95(C), pages 125-131.

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