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Time endogeneity and an optimal weight function in pre-averaging covariance estimation

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  • Yuta Koike

    (The Institute of Statistical Mathematics
    CREST, JST)

Abstract

We establish a central limit theorem for a class of pre-averaging covariance estimators in a general endogenous time setting. In particular, we show that the time endogeneity has no impact on the asymptotic distribution if certain functionals of observation times are asymptotically well-defined. This contrasts with the case of the realized volatility in a pure diffusion setting. We also discuss an optimal choice of the weight function in the pre-averaging.

Suggested Citation

  • Yuta Koike, 2017. "Time endogeneity and an optimal weight function in pre-averaging covariance estimation," Statistical Inference for Stochastic Processes, Springer, vol. 20(1), pages 15-56, April.
    • Handle: RePEc:spr:sistpr:v:20:y:2017:i:1:d:10.1007_s11203-016-9135-3
    DOI: 10.1007/s11203-016-9135-3
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    References listed on IDEAS

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    Cited by:

    1. Bibinger, Markus & Neely, Christopher & Winkelmann, Lars, 2019. "Estimation of the discontinuous leverage effect: Evidence from the NASDAQ order book," Journal of Econometrics, Elsevier, vol. 209(2), pages 158-184.
    2. Yuta Koike & Zhi Liu, 2019. "Asymptotic properties of the realized skewness and related statistics," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(4), pages 703-741, August.

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