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We construct a spot volatility estimator for high-frequency financial data which contain market microstructure noise. We prove consistency and derive the asymptotic distribution of the estimator. A data-driven method is proposed to select the scale parameter and the bandwidth parameter in the estimator. In Monte Carlo simulations, we compare the finite sample performance of our estimator with some existing estimators. Empirical examples are given to illustrate the potential applications of the estimator.
|Additional Information:||NOTICE: this is the author’s version of a work that was accepted for publication in Journal of Econometrics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Econometrics, Volume 181, Issue 2, Pages 117–135, http://dx.doi.org/10.1016/j.jeconom.2014.04.001|
|Uncontrolled Keywords:||Spot volatility, Market microstructure noise, Subsampling, Scale selection, Bandwidth selection|
|Subjects:||H Social Sciences > HB Economic Theory|
|Divisions:||School of Social Sciences > Department of Economics|
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