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Martingale approximation of eigenvalues for common factor representation

  • Bystrov, Victor
  • di Salvatore, Antonietta

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.

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Article provided by Elsevier in its journal Statistics & Probability Letters.

Volume (Year): 83 (2013)
Issue (Month): 1 ()
Pages: 233-237

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Handle: RePEc:eee:stapro:v:83:y:2013:i:1:p:233-237
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  1. Anindya Banerjee & Massimiliano Marcellino & Igor Masten, 2008. "Forecasting Macroeconomic Variables Using Diffusion Indexes in Short Samples with Structural Change," Working Papers 334, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  2. Alexei Onatski, 2009. "Testing Hypotheses About the Number of Factors in Large Factor Models," Econometrica, Econometric Society, vol. 77(5), pages 1447-1479, 09.
  3. repec:ner:tilbur:urn:nbn:nl:ui:12-153213 is not listed on IDEAS
  4. Magnus, Jan R., 1985. "On Differentiating Eigenvalues and Eigenvectors," Econometric Theory, Cambridge University Press, vol. 1(02), pages 179-191, August.
  5. Magnus, J.R., 1985. "On differentiating eigenvalues and eigenvectors," Other publications TiSEM f410e3a5-ba9b-4787-b8cc-4, Tilburg University, School of Economics and Management.
  6. 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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