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The SIML Estimation of Integrated Covariance and Hedging Coefficient under Micro-market noise and Random Sampling

Author

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  • Naoto Kunitomo

    (Faculty of Economics, University of Tokyo)

  • Hiroumi Misaki

    (Research Center for Advanced Science and Technology, 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 estimation is useful for estimating the integrated covariance and hedging coefficient when we have micro-market noise and financial high frequency data are randomly sampled. The SIML estimation is consistent and has the stable convergence (i.e. the asymptotic normality in the deterministic case) and it has reasonable finite sample properties with these effects.

Suggested Citation

  • Naoto Kunitomo & Hiroumi Misaki, 2013. "The SIML Estimation of Integrated Covariance and Hedging Coefficient under Micro-market noise and Random Sampling," CIRJE F-Series CIRJE-F-893, CIRJE, Faculty of Economics, University of Tokyo.
    • Handle: RePEc:tky:fseres:2013cf893
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    References listed on IDEAS

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    Cited by:

    1. Misaki, Hiroumi & Kunitomo, Naoto, 2015. "On robust properties of the SIML estimation of volatility under micro-market noise and random sampling," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 265-281.

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