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Test of Unbiasedness of the Integrated Covariance Estimation in the Presence of Noise

Author

Listed:
  • Masato Ubukata

    (Graduate School of Economics, Osaka University)

  • Kosuke Oya

    (Graduate School of Economics, Osaka University)

Abstract

The cumulative covariance estimator in Hayashi and Yoshida (2005b) which suits for non-synchronous observations possibly has a bias in the presence of the observational noise. We propose the test statistic to detect whether the observational noise causes a measurable bias in the estimator of Hayashi and Yoshida (2005b). The test statistic proposed in this paper is asymptotically distributed as standard normal under null hypothesis. The finite sample performance of the test statistic is investigated through Monte Carlo simulation.

Suggested Citation

  • Masato Ubukata & Kosuke Oya, 2007. "Test of Unbiasedness of the Integrated Covariance Estimation in the Presence of Noise," Discussion Papers in Economics and Business 07-03, Osaka University, Graduate School of Economics.
    • Handle: RePEc:osk:wpaper:0703
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    References listed on IDEAS

    as
    1. Andersen T. G & Bollerslev T. & Diebold F. X & Labys P., 2001. "The Distribution of Realized Exchange Rate Volatility," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 42-55, March.
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    4. 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.
    5. repec:ebl:ecbull:v:3:y:2004:i:36:p:1-8 is not listed on IDEAS
    6. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
    7. Valeri Voev & Asger Lunde, 2007. "Integrated Covariance Estimation using High-frequency Data in the Presence of Noise," Journal of Financial Econometrics, Oxford University Press, vol. 5(1), pages 68-104.
    8. Barucci, Emilio & Reno, Roberto, 2002. "On measuring volatility of diffusion processes with high frequency data," Economics Letters, Elsevier, vol. 74(3), pages 371-378, February.
    9. Toshiya Hoshikawa & Keiji Nagai & Taro Kanatani & Yoshihiko Nishiyama, 2008. "Nonparametric Estimation Methods of Integrated Multivariate Volatilities," Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 112-138.
    10. Taro Kanatani, 2004. "Integrated volatility measuring from unevenly sampled observations," Economics Bulletin, AccessEcon, vol. 3(36), pages 1-8.
    11. Maria Elvira Mancino & Paul Malliavin, 2002. "Fourier series method for measurement of multivariate volatilities," Finance and Stochastics, Springer, vol. 6(1), pages 49-61.
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    Cited by:

    1. Taro Kanatani, 2007. "Finite Sample Analysis of Weighted Realized Covariance with Noisy Asynchronous Observations," KIER Working Papers 634, Kyoto University, Institute of Economic Research.

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    More about this item

    Keywords

    test statistic; integrated covariance; non-synchronous observation; observational noise; market microstructure noise;
    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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