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Ultra high frequency volatility estimation with dependent microstructure noise

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

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.

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File URL: http://www.sciencedirect.com/science/article/B6VC0-4YJ6GKX-G/2/dfcb749c5994e3e24b6e59241bbf4683
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Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 160 (2011)
Issue (Month): 1 (January)
Pages: 160-175

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Handle: RePEc:eee:econom:v:160:y:2011:i:1:p:160-175
Contact details of provider: Web page: http://www.elsevier.com/locate/jeconom

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  4. Yacine Ait-Sahalia & Per A. Mykland, 2003. "How Often to Sample a Continuous-Time Process in the Presence of Market Microstructure Noise," NBER Working Papers 9611, National Bureau of Economic Research, Inc.
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