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Ultra high frequency volatility estimation with dependent microstructure noise

Author

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  • Aït-Sahalia, Yacine
  • Mykland, Per A.
  • Zhang, Lan

Abstract

We analyze the impact of time series dependence in market microstructure noise on the properties of estimators of the integrated volatility of an asset price based on data sampled at frequencies high enough for that noise to be a dominant consideration. We show that combining two time scales for that purpose will work even when the noise exhibits time series dependence, analyze in that context a refinement of this approach is based on multiple time scales, and compare empirically our different estimators to the standard realized volatility.

Suggested Citation

  • Aït-Sahalia, Yacine & Mykland, Per A. & Zhang, Lan, 2011. "Ultra high frequency volatility estimation with dependent microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 160-175, January.
    • Handle: RePEc:eee:econom:v:160:y:2011:i:1:p:160-175
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    More about this item

    Keywords

    Market microstructure Serial dependence High frequency data Realized volatility Subsampling Two scales realized volatility Multiple scales realized volatility;

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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