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

82 Pages Posted: 26 Jul 2007 Last revised: 12 Jun 2008

See all articles by Ingmar Nolte

Ingmar Nolte

Lancaster University - Department of Accounting and Finance

Valeri Voev

Aarhus University - CREATES

Date Written: November 19, 2007

Abstract

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%.

Keywords: High frequency data, Realized volatility and covariance, Market microstructure

JEL Classification: G10, F31,C32

Suggested Citation

Nolte, Ingmar and Voev, Valeri, Estimating High-Frequency Based (Co-) Variances: A Unified Approach (November 19, 2007). Available at SSRN: https://ssrn.com/abstract=1003201 or http://dx.doi.org/10.2139/ssrn.1003201

Ingmar Nolte

Lancaster University - Department of Accounting and Finance ( email )

Lancaster, Lancashire LA1 4YX
United Kingdom

Valeri Voev (Contact Author)

Aarhus University - CREATES ( email )

School of Economics and Management
Building 1322, Bartholins Alle 10
DK-8000 Aarhus C
Denmark

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