A blocking and regularization approach to high dimensional realized covariance estimation

Nikolaus Hautsch, Lada M. Kyj and Roel Oomen

No 2009-049, SFB 649 Discussion Papers from Humboldt University Berlin, Collaborative Research Center 649: Economic Risk

Abstract: 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 'RnB' 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.

Keywords: covariance estimation; blocking; realized kernel; regularization; microstructure; asynchronous trading (search for similar items in EconPapers)
JEL-codes: C14 C22 (search for similar items in EconPapers)
Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.econstor.eu/bitstream/10419/39326/1/612287025.pdf (application/pdf)

Related works:
Journal Article: A blocking and regularization approach to high‐dimensional realized covariance estimation (2012)
Working Paper: A blocking and regularization approach to high dimensional realized covariance estimation (2009)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:zbw:sfb649:sfb649dp2009-049

Access Statistics for this paper

More papers in SFB 649 Discussion Papers from Humboldt University Berlin, Collaborative Research Center 649: Economic Risk Contact information at EDIRC.
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics ().