Stationary bootstrapping realized volatility under market microstructure noise

Eunju Hwang, Dong Wan Shin

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Large-sample validity is proved for stationary bootstrapping of a bias-corrected realized volatility under market microstructure noise, which enables us to construct a bootstrap confidence interval of integrated volatility. A finite-sample simulation shows that the stationary bootstrapping confidence interval outperforms existing ones which are constructed ignoring market microstructure noise or using asymptotic normality for the bias-corrected realized volatility.

Original languageEnglish
Pages (from-to)2032-2053
Number of pages22
JournalElectronic Journal of Statistics
Volume7
Issue number1
DOIs
StatePublished - 2013

Keywords

  • Confidence interval
  • Market microstructure noise
  • Stationary bootstrap

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