Bias-Correcting the Realized Range-Based Variance in the Presence of Market Microstructure Noise
37 Pages Posted: 11 Oct 2006 Last revised: 6 Sep 2010
Date Written: May 15, 2008
Market microstructure noise is a challenge to high-frequency based estimation of the integrated variance, because the noise accumulates with the sampling frequency. This has lead to widespread use of constructing the realized variance, a sum of squared intraday returns, from sparsely sampled data, for example 5- or 15-minute returns. In this paper, we analyze the impact of microstructure noise on the realized range-based variance and propose a bias-correction to the range-statistic. The new estimator is shown to be consistent for the integrated variance and asymptotically mixed Gaussian under simple forms of microstructure noise. We can select an optimal partition of the high-frequency data in order to minimize its asymptotic conditional variance. The finite sample properties of our estimator are studied with Monte Carlo simulations and we implement it using Microsoft high-frequency data from TAQ. We find that a bias-corrected range-statistic often leads to much smaller confidence intervals for the integrated variance, relative to the realized variance.
Keywords: Bias-correction, Integrated variance, Market microstructure noise, Realized range-based variance, Realized variance
JEL Classification: C10, C80
Suggested Citation: Suggested Citation