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On Robust Properties of the SIML Estimation of Volatility under Micro-market noise and Random Sampling

Author

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  • Hiroumi Misaki

    (Research Center for Advanced Science and Technology, University of Tokyo)

  • Naoto Kunitomo

    (Faculty of Economics, University of Tokyo)

Abstract

　　 For estimating the integrated volatility and covariance by using high frequency data, Kunitomo and Sato (2008, 2011) have proposed the Separating Information Maximum Likelihood (SIML) method when there are micro-market noises. The SIML estimator has reasonable finite sample properties and asymptotic properties when the sample size is large under general conditions with non-Gaussian processes or volatility models. We shall show that the SIML estimator has the asymptotic robustness property in the sense that it is consistent and has the stable convergence (i.e. the asymptotic normality in the deterministic case) when there are micro-market noises and the observed high-frequency data are sampled randomly with the underlying (continuous time) stochastic process. The SIML estimation has also reasonable finite sample properties with these effects.

Suggested Citation

  • Hiroumi Misaki & Naoto Kunitomo, 2013. "On Robust Properties of the SIML Estimation of Volatility under Micro-market noise and Random Sampling," CIRJE F-Series CIRJE-F-892, CIRJE, Faculty of Economics, University of Tokyo.
    • Handle: RePEc:tky:fseres:2013cf892
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    References listed on IDEAS

    as
    1. Takaki Hayashi & Nakahiro Yoshida, 2008. "Asymptotic normality of a covariance estimator for nonsynchronously observed diffusion processes," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 60(2), pages 367-406, June.
    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. 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.
    4. Yacine Aït-Sahalia, 2005. "How Often to Sample a Continuous-Time Process in the Presence of Market Microstructure Noise," The Review of Financial Studies, Society for Financial Studies, vol. 18(2), pages 351-416.
    5. Naoto Kunitomo & Seisho Sato, 2008. "Separating Information Maximum Likelihood Estimation of Realized Volatility and Covariance with Micro-Market Noise," CIRJE F-Series CIRJE-F-581, CIRJE, Faculty of Economics, University of Tokyo.
    6. Amihud, Yakov & Mendelson, Haim, 1987. "Trading Mechanisms and Stock Returns: An Empirical Investigation," Journal of Finance, American Finance Association, vol. 42(3), pages 533-553, July.
    7. Seisho Sato & Naoto Kunitomo, 1996. "Some Properties Of The Maximum Likelihood Estimator In The Simultaneous Switching Autoregressive Model," Journal of Time Series Analysis, Wiley Blackwell, vol. 17(3), pages 287-307, May.
    8. Naoto Kunitomo & Seisho Sato, 1999. "Stationary and Non-stationary Simultaneous Switching Autoregressive Models with an Application to Financial Time Series," The Japanese Economic Review, Japanese Economic Association, vol. 50(2), pages 161-190, June.
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