Dependent microstructure noise and integrated volatility estimation from high-frequency data

Z. Merrick Li, Roger Laeven and Michel H. Vellekoop

Journal of Econometrics, 2020, vol. 215, issue 2, 536-558

Abstract: In this paper, we develop econometric tools to analyze the integrated volatility (IV) of the efficient price and the dynamic properties of microstructure noise in high-frequency data under general dependent noise. We first develop consistent estimators of the variance and autocovariances of noise using a variant of realized volatility. Next, we employ these estimators to adapt the pre-averaging method and derive consistent estimators of the IV, which converge stably to a mixed Gaussian distribution at the optimal rate n1∕4. To improve the finite sample performance, we propose a multi-step approach that corrects the finite sample bias, which turns out to be crucial in applications. Our extensive simulation studies demonstrate the excellent performance of our multi-step estimators. In an empirical study, we analyze the dependence structures of microstructure noise and provide intuitive economic interpretations; we also illustrate the importance of accounting for both the serial dependence in noise and the finite sample bias when estimating IV.

Keywords: Dependent microstructure noise; Realized volatility; Bias correction; Integrated volatility; Pre-averaging method (search for similar items in EconPapers)
JEL-codes: C13 C14 C55 C58 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Working Paper: Dependent Microstructure Noise and Integrated Volatility: Estimation from High-Frequency Data (2019)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:215:y:2020:i:2:p:536-558

DOI: 10.1016/j.jeconom.2019.10.004

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