Ultra High Frequency Volatility Estimation with Dependent Microstructure Noise

43 Pages Posted: 4 Jul 2005 Last revised: 7 Aug 2022

See all articles by Yacine Ait-Sahalia

Yacine Ait-Sahalia

Princeton University - Department of Economics

Per A. Mykland

University of Chicago - Department of Statistics

Lan Zhang

University of Illinois at Chicago - Department of Finance

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Date Written: May 2005

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 based on multiple time scales, and compare empirically our different estimators to the standard realized volatility.

Suggested Citation

Ait-Sahalia, Yacine and Mykland, Per A. and Zhang, Lan, Ultra High Frequency Volatility Estimation with Dependent Microstructure Noise (May 2005). NBER Working Paper No. w11380, Available at SSRN: https://ssrn.com/abstract=731035

Yacine Ait-Sahalia (Contact Author)

Princeton University - Department of Economics ( email )

Fisher Hall
Princeton, NJ 08544
United States
609-258-4015 (Phone)
609-258-5398 (Fax)

Per A. Mykland

University of Chicago - Department of Statistics ( email )

Chicago, IL 60637-1514
United States
773-702-8044 (Phone)

Lan Zhang

University of Illinois at Chicago - Department of Finance ( email )

601 South Morgan Street
Chicago, IL 60607
United States

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