Bias-correcting the realized range-based variance in the presence of market microstructure noise
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Date
2007-02-21T14:40:51Z
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Abstract
Market microstructure noise is a challenge to high-frequency based estimation of the integrated
variance, because the noise accumulates with the sampling frequency. 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, and 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 on
high-frequency data from TAQ. We find that a bias-corrected range-statistic often has much smaller
confidence intervals than the realized variance.
JEL Classification: C10; C22; C80
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Keywords
Bias-correction, Integrated variance, Market microstructure noise, Realized range-based variance, Realized variance