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

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  • Masato Ubukata

    ()
    (Graduate School of Economics, Osaka University)

  • Kosuke Oya

    ()
    (Graduate School of Economics, Osaka University)

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    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.

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    Bibliographic Info

    Paper provided by Osaka University, Graduate School of Economics and Osaka School of International Public Policy (OSIPP) in its series Discussion Papers in Economics and Business with number 07-03.

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    Length: 24 pages
    Date of creation: Feb 2007
    Date of revision:
    Handle: RePEc:osk:wpaper:0703

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    Web page: http://www.econ.osaka-u.ac.jp/
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    Related research

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

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    References

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    1. 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.
    2. 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.
    3. Maria Elvira Mancino & Paul Malliavin, 2002. "Fourier series method for measurement of multivariate volatilities," Finance and Stochastics, Springer, vol. 6(1), pages 49-61.
    4. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
    5. Valeri Voev & Asger Lunde, 2007. "Integrated Covariance Estimation using High-frequency Data in the Presence of Noise," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 5(1), pages 68-104.
    6. repec:ebl:ecbull:v:3:y:2004:i:36:p:1-8 is not listed on IDEAS
    7. Nelson, Daniel B., 1990. "ARCH models as diffusion approximations," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 7-38.
    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. 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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    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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