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Integrated volatility measuring from unevenly sampled observations

Author

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  • Taro Kanatani

    (Graduate School of Economics, Kyoto University)

Abstract

This paper derives the linear interpolation bias of realized volatility. To avoid the bias, the Fourier series estimator has been proposed by Malliavin and Mancino (2002). We examine the theoretical relationship between the Fourier estimator and realized volatility and show that the latter is the most efficient estimator in the class of the former.

Suggested Citation

  • Taro Kanatani, 2004. "Integrated volatility measuring from unevenly sampled observations," Economics Bulletin, AccessEcon, vol. 3(36), pages 1-8.
    • Handle: RePEc:ebl:ecbull:eb-04c10020
    as

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    File URL: http://www.accessecon.com/pubs/EB/2004/Volume3/EB-04C10020A.pdf
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    References listed on IDEAS

    as
    1. Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
    2. Maria Elvira Mancino & Paul Malliavin, 2002. "Fourier series method for measurement of multivariate volatilities," Finance and Stochastics, Springer, vol. 6(1), pages 49-61.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Mancino, M.E. & Sanfelici, S., 2008. "Robustness of Fourier estimator of integrated volatility in the presence of microstructure noise," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2966-2989, February.
    2. Cecilia Mancini & Vanessa Mattiussi & Roberto Renò, 2015. "Spot volatility estimation using delta sequences," Finance and Stochastics, Springer, vol. 19(2), pages 261-293, April.
    3. 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.

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    More about this item

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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