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

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 conf...

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Hauptverfasser: Christensen, Kim (VerfasserIn) , Grawert, Silja (VerfasserIn) , Podolskij, Mark (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 19 June 2010
In: Journal of econometrics
Year: 2010, Jahrgang: 159, Heft: 1, Pages: 116-133
DOI:10.1016/j.jeconom.2010.05.001
Online-Zugang:Verlag, Volltext: http://dx.doi.org/10.1016/j.jeconom.2010.05.001
Verlag, Volltext: http://www.sciencedirect.com/science/article/pii/S0304407610001260
Volltext
Verfasserangaben:Kim Christensen, Silja Kinnebrock, Mark Podolskij
Beschreibung
Zusammenfassung: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.
Beschreibung:Gesehen am 29.05.2018
Beschreibung:Online Resource
DOI:10.1016/j.jeconom.2010.05.001