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Pre-averaging estimators of the ex-post covariance matrix in noisy diffusion models with non-synchronous data

Kim Christensen (), Silja Kinnebrock () and Mark Podolskij ()
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Silja Kinnebrock: AOPP - Department of Atmospheric, Oceanic and Planetary Physics [Oxford] - University of Oxford

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Abstract: We show how pre-averaging can be applied to the problem of measuring the ex-post covariance of financial asset returns under microstructure noise and non-synchronous trading. A pre-averaged realised covariance is proposed, and we present an asymptotic theory for this new estimator, which can be configured to possess an optimal convergence rate or to ensure positive semi-definite covariance matrix estimates. We also derive a noise-robust Hayashi-Yoshida estimator that can be implemented on the original data without prior alignment of prices. We uncover the finite sample properties of our estimators with simulations and illustrate their practical use on high-frequency equity data.

Keywords: C10; C22; C80; Central limit theorem; Diffusion models; High-frequency data; Market microstructure noise; Non-synchronous trading; Pre-averaging; Realised covariance (search for similar items in EconPapers)
Date: 2010-09-15
Note: View the original document on HAL open archive server: https://hal.science/hal-00732537
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Citations: View citations in EconPapers (134)

Published in Econometrics, 2010, 159 (1), pp.116. ⟨10.1016/j.jeconom.2010.05.001⟩

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Journal Article: Pre-averaging estimators of the ex-post covariance matrix in noisy diffusion models with non-synchronous data (2010) Downloads
Working Paper: Pre-averaging estimators of the ex-post covariance matrix in noisy diffusion models with non-synchronous data (2009) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-00732537

DOI: 10.1016/j.jeconom.2010.05.001

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