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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
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