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Subsampling high frequency data

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  • Kalnina, Ilze

Abstract

The main contribution of this paper is to propose a novel way of conducting inference for an important general class of estimators that includes many estimators of integrated volatility. A subsampling scheme is introduced that consistently estimates the asymptotic variance for an estimator, thereby facilitating inference and the construction of valid confidence intervals. The new method does not rely on the exact form of the asymptotic variance, which is useful when the latter is of complicated form. The method is applied to the volatility estimator of Aït-Sahalia et al. (2011) in the presence of autocorrelated and heteroscedastic market microstructure noise.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 161 (2011)
Issue (Month): 2 (April)
Pages: 262-283

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Handle: RePEc:eee:econom:v:161:y:2011:i:2:p:262-283

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Web page: http://www.elsevier.com/locate/jeconom

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Keywords: Subsampling Market microstructure noise High frequency data Realised volatility;

References

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Citations

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Cited by:
  1. Rasmus Tangsgaard Varneskov, 2011. "Flat-Top Realized Kernel Estimation of Quadratic Covariation with Non-Synchronous and Noisy Asset Prices," CREATES Research Papers 2011-35, School of Economics and Management, University of Aarhus.
  2. Rasmus Tangsgaard Varneskov, 2011. "Generalized Flat-Top Realized Kernel Estimation of Ex-Post Variation of Asset Prices Contaminated by Noise," CREATES Research Papers 2011-31, School of Economics and Management, University of Aarhus.

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