1,012
Views
3
CrossRef citations to date
0
Altmetric
Theory and Methods

Factor and Idiosyncratic Empirical Processes

, , , &
Pages 1138-1146 | Received 01 Aug 2017, Published online: 07 Aug 2018

References

  • Aït-Sahalia, Y., and Xiu, D. (2017), “Using Principal Component Analysis to Estimate a High Dimensional Factor Model With High-Frequency Data,” Journal of Econometrics, 201, 384–399.
  • ——— (2018), “Principal Component Analysis of High Frequency Data,” Journal of the American Statistical Association.
  • Alessi, L., Barigozzi, M., and Capasso, M. (2010), “Improved Penalization for Determining the Number of Factors in Approximate Factor Models,” Statistics and Probability Letters, 80, 1806–1813.
  • Bai, J. (2003), “Inferential Theory for Factor Models of Large Dimensions,” Econometrica 71, 135–171.
  • Bai, J., and Ng, S. (2002), “Determining the Number of Factors in Approximate Factor Models,” Econometrica, 70, 191–221.
  • Cai, L., and Yang, L. (2015), “A Smooth Simultaneous Confidence Band for Conditional Variance Function,” TEST, 24, 632–655.
  • Chamberlain, G. (1983), “Funds, Factors, and Diversification in Arbitrage Pricing Models,” Econometrica, 51, 1305–1323.
  • Chamberlain, G., and Rothschild, M. (1983), “Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets,” Econometrica, 51, 1281–1304.
  • Chan, N. H., and Ling, S. (2008), “Residual Empirical Processes for Long and Short Memory Time Series,” Annals of Statistics, 36, 2453–2470.
  • Fan, J., Liao, Y., and Mincheva, M. (2013), “Large Covariance Estimation by Thresholding Principal Orthogonal Complements,” Journal of the Royal Statistical Society, Series B, 75, 603–680.
  • Forni, M., Hallin, M., Lippi, M., and Reichlin, L. (2000), “The Generalized Dynamic-Factor Model: Identification and Estimation,” Review of Economics and Statistics, 82, 540–554.
  • ——— (2004), “The Generalized Dynamic-Factor Model: Consistency and Rates,” Journal of Econometrics, 119, 231–255.
  • ——— (2005), “The Generalized Dynamic-Factor Model: One-Sided Estimation and Forecasting,” Journal of the American Statistical Association, 100, 830–840.
  • Forni, M., Hallin, M., Lippi, M., and Zaffaroni, P. (2015), “Dynamic Factor Models With Infinite-Dimensional Factor Space: One-Sided Representations,” Journal of Econometrics, 185, 359–371.
  • ——— (2017), “Dynamic Factor Models With Infinite-Dimensional Factor Space: Asymptotic Analysis,” Journal of the American Statistical Association, 199, 74–92.
  • Gu, L., and Yang, L. (2015), “Oracally Efficient Estimation for Single-Index Link Function with Confidence Band,” Electronic Journal of Statistics, 9, 1540–1561.
  • Hallin, M., and Lippi, M. (2013), “Factor Models in High-Dimensional Time Series: A Time-Domain Approach,” Stochastic Processes and Their Applications, 123, 2678–2695.
  • Hallin, M., and Lis̆ka, R. (2007), “Determining the Number of Factors in the General Dynamic Factor Model,” Journal of the American Statistical Association, 102, 603–617.
  • Ho, H. C., and Hsing, T. (1996), “On the Asymptotic Expansion of the Empirical Process of Long-Memory Moving Averages,” Annals of Statistics, 24, 992–1024.
  • Lee, S., and Wei, C. Z. (1999), “On Residual Empirical Processes of Stochastic Regression Models With Applications to Time Series,” Annals of Statistics, 27, 237–261.
  • Ling, S. (1998), “Weak Convergence of the Sequential Empirical Processes of Residuals in Nonstationary Autoregressive Models,” Annals of Statistics, 26, 741–754.
  • Pelger, M. (2018), “Large-Dimensional Factor Modeling Based on High-Frequency Observations,” available at SSRN 2584172.
  • Shao, Q., and Yang, L. (2011), “Autoregressive Coefficient Estimation in Nonparametric Analysis,” Journal of Time Series Analysis, 32, 587–597.
  • ——— (2017), “Oracally Efficient Estimation and Consistent Model Selection for Auto-Regressive Moving Average Time Series With Trend,” Journal of the Royal Statistical Society, Series B, 79, 507–524.
  • Stock, J. H., and Watson, M. W. (2002a), “Macroeconomic Forecasting Using Diffusion Indexes,” Journal of Business and Economic Statistics, 20, 147–162.
  • ——— (2002b), “Forecasting Using Principal Components From a Large Number of Predictors,” Journal of the American Statistical Association, 97, 1167–1179.
  • Wang, Q. Y., and Wang, Y. X. (2013), “Non-Parametric Cointegrating Regression With NNH Errors,” Econometric Theory, 29, 1–27.
  • Wu, W. B. (2003), “Empirical Processes of Long-Memory Sequences,” Bernoulli, 9, 809–831.
  • Zheng, S., Yang, L., and Härdle, W. (2014), “A Smooth Simultaneous Confidence Corridor for the Mean of Sparse Functional Data,” Journal of the American Statistical Association, 109, 661–673.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.