Department of Economics and Business Economics

Estimating High-Frequency Based (Co-) Variances: A Unified Approach

Research output: Working paperResearch

  • Valeri Voev, Denmark
  • Ingmar Nolte, University of Konstanz, Germany
  • School of Economics and Management
We propose a unified framework for estimating integrated variances and
covariances based on simple OLS regressions, allowing for a general market
microstructure noise specification. We show that our estimators can outperform,
in terms of the root mean squared error criterion, the most recent and commonly
applied estimators, such as the realized kernels of Barndorff-Nielsen, Hansen,
Lunde & Shephard (2006), the two-scales realized variance of Zhang, Mykland &
Aït-Sahalia (2005), the Hayashi & Yoshida (2005) covariance estimator, and the
realized variance and covariance with the optimal sampling frequency derived in
Bandi & Russell (2005a) and Bandi & Russell (2005b). For a realistic trading
scenario, the efficiency gains resulting from our approach are in the range of
35% to 50%.
Original languageEnglish
Place of publicationÅrhus
PublisherInstitut for Økonomi, Aarhus Universitet
Number of pages80
Publication statusPublished - 2008

    Research areas

  • High frequency data, Realized volatility and covariance, Market microstructure

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