Ultra High Frequency Volatility Estimation with Dependent Microstructure Noise

Yacine Ait-Sahalia, Per A. Mykland and Lan Zhang

No 11380, NBER Working Papers from National Bureau of Economic Research, Inc

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.

JEL-codes: G12 C22 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-fin
Date: 2005-05
Note: AP
View list of references View citations in EconPapers

Downloads: (external link)
http://www.nber.org/papers/w11380.pdf (application/pdf)
Access to the full text is generally limited to series subscribers, however if the top level domain of the client browser is in a developing country or transition economy free access is provided. More information about subscriptions and free access is available at http://www.nber.org/wwphelp.html.

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: http://EconPapers.repec.org/RePEc:nbr:nberwo:11380

Ordering information: This working paper can be ordered from
http://www.nber.org/papers/w11380
The price is Paper copy available by mail.

Access Statistics for this paper

More papers in NBER Working Papers from National Bureau of Economic Research, Inc
Address: National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.
Contact information at EDIRC.
Series data maintained by ().