Ultra high frequency volatility estimation with dependent microstructure noise

Yacine At-Sahalia, Per A. Mykland, Lan Zhang

Research output: Contribution to journalArticle

127 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)160-175
Number of pages16
JournalJournal of Econometrics
Volume160
Issue number1
DOIs
StatePublished - Jan 2011

All Science Journal Classification (ASJC) codes

  • Economics and Econometrics

Keywords

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

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