Ultra high frequency volatility estimation with dependent microstructure noise
Yacine Ait-Sahalia,
Per A. Mykland and
Lan Zhang
Journal of Econometrics, 2011, vol. 160, issue 1, 160-175
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.
Keywords: Market; microstructure; Serial; dependence; High; frequency; data; Realized; volatility; Subsampling; Two; scales; realized; volatility; Multiple; scales; realized; volatility (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (148)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304-4076(10)00070-9
Full text for ScienceDirect subscribers only
Related works:
Working Paper: Ultra High Frequency Volatility Estimation with Dependent Microstructure Noise (2005) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:160:y:2011:i:1:p:160-175
Access Statistics for this article
Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson
More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().