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Market microstructure noise,integrated variance estimators,and the accuracy of asymptotic approximations
Authors:Federico M Bandi  Jeffrey R Russell
Institution:1. Carey Business School, Johns Hopkins University, 1133, 100 N. Charles Street, Baltimore, MD 21201, United States;2. Booth School of Business, University of Chicago, 452, 5807 South Woodlawn Avenue, Chicago, IL 60637, United States;3. Edhec-Risk Institute, 393-400 Promenade des Anglais, BP 3116, 06202 Nice Cedex 3, France
Abstract:A growing literature has been advocating consistent kernel estimation of integrated variance in the presence of financial market microstructure noise. We find that, for realistic sample sizes encountered in practice, the asymptotic results derived for the proposed estimators may provide unsatisfactory representations of their finite sample properties. In addition, the existing asymptotic results might not offer sufficient guidance for practical implementations. We show how to optimize the finite sample properties of kernel-based integrated variance estimators. Empirically, we find that their suboptimal implementation can, in some cases, lead to little or no finite sample gains when compared to the classical realized variance estimator. Significant statistical and economic gains can, however, be recovered by using our proposed finite sample methods.
Keywords:C13  C14  C22
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