2009
DOI: 10.1016/j.spa.2008.11.004
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Microstructure noise in the continuous case: The pre-averaging approach

Abstract: This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues. Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their pe… Show more

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Cited by 657 publications
(673 citation statements)
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“…This has motivated the development of alternative estimators. One popular method is the pre-averaging approach first introduced by Podolskij and Vetter (2009) and further studied by Jacod et al (2009)…”
Section: Introductionmentioning
confidence: 99%
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“…This has motivated the development of alternative estimators. One popular method is the pre-averaging approach first introduced by Podolskij and Vetter (2009) and further studied by Jacod et al (2009)…”
Section: Introductionmentioning
confidence: 99%
“…In this paper, we propose a bootstrap method that can be used to estimate the distribution and the variance of the pre-averaged realized volatility estimator of Jacod et al (2009). Our proposal is to resample the pre-averaged returns instead of resampling the original noisy returns.…”
Section: Introductionmentioning
confidence: 99%
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“…150 (3) To deal with the combination of both problems, methods such as subsampling , pre-averaging (Jacod et al, 2009) and the two-and multi-scales estimators (Zhang, 2011) have been proposed to restore consistency of the estimators. Voev and Lunde (2007) proposed a bias correction method for the Hayashi and Yoshida estimator in the presence of dependent microstructure noise while Nolte and Voev (2009) propose a least squares approach to obtain the unbiased integrated volatility or co-volatility.…”
Section: Introductionmentioning
confidence: 99%