This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Integrated Covariance Estimation using High-frequency Data in the Presence of Noise

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Valeri Voev
Asger Lunde

Additional information is available for the following registered author(s):

Abstract

We analyze the effects of nonsynchronicity and market microstructure noise on realized covariance type estimators. Hayashi and Yoshida (2005) propose a simple estimator that resolves the problem of nonsynchronicity and is unbiased and consistent for the integrated covariance in the absence of noise. When noise is present, however, we find that this estimator is biased, and show how the bias can be corrected for. Ultimately, we propose a subsampling version of the bias-corrected estimator which improves its efficiency. Empirically, we find that the usual assumption of a martingale price process plus an independently and identically distributed (i.i.d.) noise does not describe the dynamics of the observed price process across stocks, which confirms the practical relevance of our general noise specification and the estimation techniques we propose. Finally, a simulation experiment is carried out to complement the theoretical results. Copyright 2007, Oxford University Press.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help file. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://hdl.handle.net/10.1093/jjfinec/nbl011
File Format: text/html
File Function:
Download Restriction: Access to full text is restricted to subscribers.

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Publisher Info
Article provided by Oxford University Press in its journal Journal of Financial Econometrics.

Volume (Year): 5 (2007)
Issue (Month): 1 ()
Pages: 68-104
Download reference. The following formats are available: HTML, plain text, BibTeX, RIS (EndNote), ReDIF
Handle: RePEc:oup:jfinec:v:5:y:2007:i:1:p:68-104

Contact details of provider:
Postal: Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK
Fax: 01865 267 985
Email:
Web page: http://jfec.oxfordjournals.org/

Order Information:
Web: http://www.oup.co.uk/journals

For technical questions regarding this item, or to correct its listing, contact: (Christopher F. Baum).

Related research
Keywords:

Cited by:
(explanations, 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.)

  1. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2008. "Multivariate realised kernels: consistent positive semin-definite estimators of the covariation of equity prices with noise and non-synchronous trading," Economics Series Working Papers 397, University of Oxford, Department of Economics. [Downloadable!]
  2. Masato Ubukata & Kosuke Oya, 2008. "A Test for Dependence and Covariance Estimator of Market Microstructure Noise," Discussion Papers in Economics and Business 07-03-Rev.2, Osaka University, Graduate School of Economics and Osaka School of International Public Policy (OSIPP). [Downloadable!]
  3. Ingmar Nolte & Valeri Voev, 2007. "Estimating High-Frequency Based (Co-) Variances: A Unified Approach," CoFE Discussion Paper 07-07, Center of Finance and Econometrics, University of Konstanz. [Downloadable!]
    Other versions:
  4. Michiel de Pooter & Martin Martens & Dick van Dijk, 2005. "Predicting the Daily Covariance Matrix for S&P 100 Stocks Using Intraday Data - But Which Frequency to Use?," Tinbergen Institute Discussion Papers 05-089/4, Tinbergen Institute, revised 03 Jan 2006. [Downloadable!]
    Other versions:
  5. Neil Shephard & Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde, 2006. "Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise," Economics Series Working Papers 264, University of Oxford, Department of Economics. [Downloadable!]
    Other versions:
  6. Valeri Voev, 2007. "Dynamic Modeling of Large Dimensional Covariance Matrices," CoFE Discussion Paper 07-01, Center of Finance and Econometrics, University of Konstanz. [Downloadable!]
  7. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2008. "Multivariate realised kernels: consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading," OFRC Working Papers Series 2008fe29, Oxford Financial Research Centre. [Downloadable!]
  8. Masato Ubukata & Kosuke Oya, 2007. "Test of Unbiasedness of the Integrated Covariance Estimation in the Presence of Noise," Discussion Papers in Economics and Business 07-03, Osaka University, Graduate School of Economics and Osaka School of International Public Policy (OSIPP).
  9. Taro Kanatani, 2007. "Finite Sample Analysis of Weighted Realized Covariance with Noisy Asynchronous Observations," Working Papers 634, Kyoto University, Institute of Economic Research. [Downloadable!]
  10. Fulvio Corsi & Francesco Audrino, 2008. "Modeling Tick-by-Tick Realized Correlations," University of St. Gallen Department of Economics working paper series 2008 2008-05, Department of Economics, University of St. Gallen. [Downloadable!]
Statistics
Access and download statistics

Did you know? You too can volunteer with RePEc.

This page was last updated on 2008-8-18.


This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.