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On estimating market microstructure noise variance

Author

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  • Dong, Yingjie
  • Tse, Yiu-Kuen

Abstract

We study the market microstructure noise-variance estimation of high-frequency stock prices. Based on the Hansen and Lunde (2006) approach, we propose estimates using subsampling method at different time scales. We conduct a Monte Carlo study to compare our method against others in the literature. Our results show that our proposed estimates have lower (absolute) mean error and root mean-squared error, and their performance is quite stable at different time scales.

Suggested Citation

  • Dong, Yingjie & Tse, Yiu-Kuen, 2017. "On estimating market microstructure noise variance," Economics Letters, Elsevier, vol. 150(C), pages 59-62.
    • Handle: RePEc:eee:ecolet:v:150:y:2017:i:c:p:59-62
    DOI: 10.1016/j.econlet.2016.11.009
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    References listed on IDEAS

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    1. Francis X. Diebold & Georg Strasser, 2013. "On the Correlation Structure of Microstructure Noise: A Financial Economic Approach," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 80(4), pages 1304-1337.
    2. Heston, Steven L, 1993. "A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options," The Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 327-343.
    3. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2008. "Designing Realized Kernels to Measure the ex post Variation of Equity Prices in the Presence of Noise," Econometrica, Econometric Society, vol. 76(6), pages 1481-1536, November.
    4. Zhou, Bin, 1996. "High-Frequency Data and Volatility in Foreign-Exchange Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 45-52, January.
    5. Tse, Yiu-Kuen & Dong, Yingjie, 2014. "Intraday periodicity adjustments of transaction duration and their effects on high-frequency volatility estimation," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 352-361.
    6. Ole E. Barndorff‐Nielsen & Neil Shephard, 2002. "Econometric analysis of realized volatility and its use in estimating stochastic volatility models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 253-280, May.
    7. Awartani, Basel & Corradi, Valentina & Distaso, Walter, 2009. "Assessing Market Microstructure Effects via Realized Volatility Measures with an Application to the Dow Jones Industrial Average Stocks," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(2), pages 251-265.
    8. Masato Ubukata & Kosuke Oya, 2009. "Estimation and Testing for Dependence in Market Microstructure Noise," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 106-151, Spring.
    9. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    10. Yiu-kuen Tse & Thomas Tao Yang, 2012. "Estimation of High-Frequency Volatility: An Autoregressive Conditional Duration Approach," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(4), pages 533-545, April.
    11. Hansen, Peter R. & Lunde, Asger, 2006. "Realized Variance and Market Microstructure Noise," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 127-161, April.
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    Cited by:

    1. Yingjie Dong & Yiu-Kuen Tse, 2017. "Business Time Sampling Scheme with Applications to Testing Semi-Martingale Hypothesis and Estimating Integrated Volatility," Econometrics, MDPI, vol. 5(4), pages 1-19, November.

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    More about this item

    Keywords

    Microstructure noise; Noise-to-signal ratio; Realized variance; High-frequency data;
    All these keywords.

    JEL classification:

    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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