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A Test for Dependence and Covariance Estimator of Market Microstructure Noise

Author

Listed:
  • Masato Ubukata

    (Graduate School of Economics, Osaka University)

  • Kosuke Oya

    (Graduate School of Economics, Osaka University)

Abstract

There are many approaches for estimating an integrated variance and covariance in the presence of market microstructure noise. It is important to know a dependence of noise to construct the integrated variance and covariance estimators. We study a time dependence of bivariate noise processes in this paper. We propose a test statistic for the dependence of the noises and an autocovariance estimator of the noises and derive its asymptotic distribution. The asymptotic distribution of the autocovariance estimator provides us to another test statistic which is for significance of the autocovariances and for detection whether the noise exists or not. We obtain good performances of the test statistics and autocovariance estimator of the noises in a finite sample through Monte Carlo simulation. In empirical illustration, we confirm that the proposed statistics and estimators capture various dependence patterns of the market microstructure noises.

Suggested Citation

  • Masato Ubukata & Kosuke Oya, 2008. "A Test for Dependence and Covariance Estimator of Market Microstructure Noise," Discussion Papers in Economics and Business 07-03-Rev.2, Osaka University, Graduate School of Economics.
  • Handle: RePEc:osk:wpaper:0703r2
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    File URL: http://www2.econ.osaka-u.ac.jp/library/global/dp/0703R2.pdf
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    References listed on IDEAS

    as
    1. Zhang, Lan & Mykland, Per A. & Ait-Sahalia, Yacine, 2005. "A Tale of Two Time Scales: Determining Integrated Volatility With Noisy High-Frequency Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1394-1411, December.
    2. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2008. "Designing Realized Kernels to Measure the ex post Variation of Equity Prices in the Presence of Noise," Econometrica, Econometric Society, vol. 76(6), pages 1481-1536, November.
    3. Aït-Sahalia, Yacine & Mykland, Per A. & Zhang, Lan, 2011. "Ultra high frequency volatility estimation with dependent microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 160-175, January.
    4. Politis, D. N. & Romano, Joseph P. & Wolf, Michael, 1997. "Subsampling for heteroskedastic time series," Journal of Econometrics, Elsevier, vol. 81(2), pages 281-317, December.
    5. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2008. "Designing Realized Kernels to Measure the ex post Variation of Equity Prices in the Presence of Noise," Econometrica, Econometric Society, vol. 76(6), pages 1481-1536, November.
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    Cited by:

    1. Hayashi, Takaki & Yoshida, Nakahiro, 2011. "Nonsynchronous covariation process and limit theorems," Stochastic Processes and their Applications, Elsevier, vol. 121(10), pages 2416-2454, October.

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    More about this item

    Keywords

    test statistic; market microstructure noise; time-dependence; nonsynchronous observations; high frequency data.;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • D49 - Microeconomics - - Market Structure, Pricing, and Design - - - Other

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