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

Ingmar Nolte and Valeri Voev ()

CREATES Research Papers from Department of Economics and Business Economics, Aarhus University

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 (search for similar items in EconPapers)
JEL-codes: C32 F31 G10 (search for similar items in EconPapers)
Pages: 79
Date: 2008-06-10
New Economics Papers: this item is included in nep-cfn, nep-ecm, nep-ets and nep-mst
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:aah:create:2008-31

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