Dependent Microstructure Noise and Integrated Volatility: Estimation from High-Frequency Data
Li, Z. M.
Laeven, R. J. A.
Vellekoop, M. H.
Cambridge Working Papers in Economics
Faculty of Economics, University of Cambridge
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Li, Z. M., Laeven, R. J. A., & Vellekoop, M. H. (2019). Dependent Microstructure Noise and Integrated Volatility: Estimation from High-Frequency Data. https://doi.org/10.17863/CAM.41234
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 n<sup>1/4</sup>. 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.
Dependent microstructure noise, realized volatility, bias correction, integrated volatility, mixing sequences, pre-averaging method
This record's DOI: https://doi.org/10.17863/CAM.41234
This record's URL: https://www.repository.cam.ac.uk/handle/1810/294133
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