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Realized Variance and IID Market Microstructure Noise

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Author Info
Asger Lunde
Peter Reinhard Hansen

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Abstract

We analyze the properties of a bias-corrected realized variance (RV) in the presence of iid market microstructure noise. The bias correction is based on the first-order autocorrelation of intraday returns and we derive the optimal sampling frequency as defined by the mean squared error (MSE) criterion. The bias-corrected RV is benchmarked to the standard measure of RV and an empirical analysis shows that the former can reduce the MSE by 50%-90%. Our empirical analysis also shows that the iid noise assumption does not hold in practice. While this need not affect the RVs that are based on low-frequency intraday returns, it has important implications for those based on high-frequency returns

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Paper provided by Econometric Society in its series Econometric Society 2004 North American Summer Meetings with number 526.

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Date of creation: 11 Aug 2004
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Handle: RePEc:ecm:nasm04:526

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Related research
Keywords: Realized Variance; High-Frequency Data; Integrated Variance.;

Find related papers by JEL classification:
C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - General
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General

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  3. Bollen, Bernard & Inder, Brett, 2002. "Estimating daily volatility in financial markets utilizing intraday data," Journal of Empirical Finance, Elsevier, vol. 9(5), pages 551-562, December. [Downloadable!] (restricted)
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  6. Lan Zhang & Per A. Mykland & Yacine Ait-Sahalia, 2003. "A Tale of Two Time Scales: Determining Integrated Volatility with Noisy High Frequency Data," NBER Working Papers 10111, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  7. Nour Meddahi, 2002. "A theoretical comparison between integrated and realized volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 479-508. [Downloadable!]
  8. Yacine Ait-Sahalia & Per A. Mykland, 2003. "How Often to Sample a Continuous-Time Process in the Presence of Market Microstructure Noise," NBER Working Papers 9611, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  9. Fulvio Corsi & Gilles Zumbach & Ulrich Müller & Michel Dacorogna, 2004. "Consistent high-precision volatility from high-frequency data," Finance 0407005, EconWPA. [Downloadable!]
  10. Roel C.A. Oomen, 2004. "Statistical Models for High Frequency Security Prices," Econometric Society 2004 North American Winter Meetings 77, Econometric Society. [Downloadable!]
  11. Ole E. Barndorff-Nielsen & Neil Shephard, 2000. "Econometric analysis of realised volatility and its use in estimating stochastic volatility models," Economics Papers 2001-W4, Economics Group, Nuffield College, University of Oxford, revised 05 Jul 2001. [Downloadable!]
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  12. Andreou, Elena & Ghysels, Eric, 2002. "Rolling-Sample Volatility Estimators: Some New Theoretical, Simulation, and Empirical Results," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 363-76, July.
    Other versions:
  13. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Ebens, Heiko, 2001. "The distribution of realized stock return volatility," Journal of Financial Economics, Elsevier, vol. 61(1), pages 43-76, July. [Downloadable!] (restricted)
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