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

• Verfasst von: Christensen, Kim [VerfasserIn]
• Verfasst von: Grawert, Silja [VerfasserIn]
• Verfasst von: Podolskij, Mark [VerfasserIn]
• Titel: Pre-averaging estimators of the ex-post covariance matrix in noisy diffusion models with non-synchronous data
• Verf.angabe: Kim Christensen, Silja Kinnebrock, Mark Podolskij
• Umfang: 18 S.
• Fussnoten: Gesehen am 29.05.2018
• Titel Quelle: Enthalten in: Journal of econometrics
• Jahr Quelle: 2010
• Band/Heft Quelle: 159(2010), 1, S. 116-133
• DOI: doi:10.1016/j.jeconom.2010.05.001
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1575816946

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.