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Statistical Properties of Covariance Estimator of Microstructure Noise: Dependence, Rare Jumps and Endogeneity

In: Recent Advances In Financial Engineering

Author

Listed:
  • Masato Ubukata

    (Graduate School of Economics, Osaka University, Japan)

  • Kosuke Oya

    (Graduate School of Economics, Osaka University, Japan)

Abstract

This paper studies impacts of rare jumps as well as an endogenous microstructure noise on Ubukata and Oya's [16] cross and auto covariance estimators of bivariate microstructure noise processes. The theoretical results show that biases of the noise covariance estimators are asymptotically negligible even when there exist the jump component and the endogeneity in the observed price process. Monte Carlo results are suggestive of robustness of the noise covariance estimators to the jumps and the endogenous noise with an empirically reasonable magnitude of the correlation in finite sample.

Suggested Citation

  • Masato Ubukata & Kosuke Oya, 2009. "Statistical Properties of Covariance Estimator of Microstructure Noise: Dependence, Rare Jumps and Endogeneity," World Scientific Book Chapters, in: Masaaki Kijima & Masahiko Egami & Kei-ichi Tanaka & Yukio Muromachi (ed.), Recent Advances In Financial Engineering, chapter 11, pages 201-218, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789814273473_0011
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