A blocking and regularization approach to high dimensional realized covariance estimation
We introduce a regularization and blocking estimator for well-conditioned high-dimensional daily covariances using high-frequency data. Using the Barndorff-Nielsen, Hansen, Lunde, and Shephard (2008a) kernel estimator, we estimate the covariance matrix block-wise and regularize it. A data-driven grouping of assets of similar trading frequency ensures the reduction of data loss due to refresh time sampling. In an extensive simulation study mimicking the empirical features of the S&P 1500 universe we show that the â€™RnBâ€™ estimator yields efficiency gains and outperforms competing kernel estimators for varying liquidity settings, noise-to-signal ratios, and dimensions. An empirical application of forecasting daily covariances of the S&P 500 index confirms the simulation results.
|Date of creation:||Oct 2009|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: http://sfb649.wiwi.hu-berlin.de
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Ole E. Barndorff-Nielsen & Neil Shephard, 2000.
"Econometric analysis of realised volatility and its use in estimating stochastic volatility models,"
2001-W4, Economics Group, Nuffield College, University of Oxford, revised 05 Jul 2001.
- Ole E. Barndorff-Nielsen & Shephard, 2002. "Econometric analysis of realized volatility and its use in estimating stochastic volatility models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 253-280.
- Torben G. Andersen & Tim Bollerslev & Per Frederiksen & Morten �rregaard Nielsen, 2010.
"Continuous-time models, realized volatilities, and testable distributional implications for daily stock returns,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 25(2), pages 233-261.
- Torben G. Andersen & Tim Bollerslev & Per Frederiksen & Morten Ørregaard Nielsen, 2008. "Continuous-Time Models, Realized Volatilities, and Testable Distributional Implications for Daily Stock Returns," Working Papers 1173, Queen's University, Department of Economics.
- Torben G. Andersen & Tim Bollerslev & Per Houmann Frederiksen & Morten Ørregaard Nielsen, 2007. "Continuous-Time Models, Realized Volatilities, and Testable Distributional Implications for Daily Stock Returns," CREATES Research Papers 2007-21, School of Economics and Management, University of Aarhus.
- Griffin, Jim E. & Oomen, Roel C.A., 2011. "Covariance measurement in the presence of non-synchronous trading and market microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 58-68, January.
- Gilles Zumbach, 2009. "The empirical properties of large covariance matrices," Papers 0903.1525, arXiv.org.
- Valeri Voev & Asger Lunde, 2007. "Integrated Covariance Estimation using High-frequency Data in the Presence of Noise," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 5(1), pages 68-104.
- deB. Harris, Frederick H. & McInish, Thomas H. & Shoesmith, Gary L. & Wood, Robert A., 1995. "Cointegration, Error Correction, and Price Discovery on Informationally Linked Security Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 30(04), pages 563-579, December.
- Matteo Bonato & Massimiliano Caporin & Angelo Ranaldo, 2009.
"Forecasting realized (co)variances with a block structure Wishart autoregressive model,"
2009-03, Swiss National Bank.
- Bonato, Matteo & Caporin, Massimiliano & Ranaldo, Angelo, 2012. "Forecasting Realized (Co)Variances with a Bloc Structure Wishart Autoregressive Model," Working Papers on Finance 1211, University of St. Gallen, School of Finance.
- Olivier Ledoit & Michael Wolf, 2001.
"Improved estimation of the covariance matrix of stock returns with an application to portofolio selection,"
Economics Working Papers
586, Department of Economics and Business, Universitat Pompeu Fabra.
- Ledoit, Olivier & Wolf, Michael, 2003. "Improved estimation of the covariance matrix of stock returns with an application to portfolio selection," Journal of Empirical Finance, Elsevier, vol. 10(5), pages 603-621, December.
- Ravi Jagannathan & Tongshu Ma, 2002.
"Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraints Helps,"
NBER Working Papers
8922, National Bureau of Economic Research, Inc.
- Ravi Jagannathan & Tongshu Ma, 2003. "Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraints Helps," Journal of Finance, American Finance Association, vol. 58(4), pages 1651-1684, 08.
- Bandi, Federico M. & Russell, Jeffrey R., 2006. "Separating microstructure noise from volatility," Journal of Financial Economics, Elsevier, vol. 79(3), pages 655-692, March.
- Alexei Onatski, 2009. "Testing Hypotheses About the Number of Factors in Large Factor Models," Econometrica, Econometric Society, vol. 77(5), pages 1447-1479, 09.
- Zhang, Lan & Mykland, Per A. & Ait-Sahalia, Yacine, 2005.
"A Tale of Two Time Scales: Determining Integrated Volatility With Noisy High-Frequency Data,"
Journal of the American Statistical Association,
American Statistical Association, vol. 100, pages 1394-1411, December.
- Lan Zhang & Per A. Mykland & Yacine Ait-Sahalia, 2003. "A Tale of Two Time Scales: Determining Integrated Volatility with Noisy High Frequency Data," NBER Working Papers 10111, National Bureau of Economic Research, Inc.
- Tola, Vincenzo & Lillo, Fabrizio & Gallegati, Mauro & Mantegna, Rosario N., 2008.
"Cluster analysis for portfolio optimization,"
Journal of Economic Dynamics and Control,
Elsevier, vol. 32(1), pages 235-258, January.
When requesting a correction, please mention this item's handle: RePEc:hum:wpaper:sfb649dp2009-049. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (RDC-Team)
If references are entirely missing, you can add them using this form.