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Liquidity and Market Microstructure Noise: Evidence from the Pekao Data

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  • Malgorzata Doman

    (Poznan University of Economics)

Abstract

The availability of ultra-high frequency data justifies the use of a continuous-time approach in stock prices modeling. However, this data contain, apart from the information about the price process, a microstructure noise causing a bias in the realized volatility. This noise is connected with all the reality of trade. In the paper we separate the microstructure noise from the price process and determine the noise to signal ratio for the estimates of the realized volatility in the case of the shares of the Polish company Pekao S.A. The results are used to discover the optimal sampling frequency for the realized volatility calculation. Moreover, we check the linkages between the noise and some liquidity measures.

Suggested Citation

  • Malgorzata Doman, 2010. "Liquidity and Market Microstructure Noise: Evidence from the Pekao Data," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 10, pages 5-14.
    • Handle: RePEc:cpn:umkdem:v:10:y:2010:p:5-14
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    References listed on IDEAS

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    Cited by:

    1. Katarzyna Bień-Barkowska, 2014. "“Every move you make, every step you take, I’ll be watching you” – the quest for hidden orders in the interbank FX spot market," Bank i Kredyt, Narodowy Bank Polski, vol. 45(3), pages 197-224.
    2. Seifoddini , Jalal & Rahnamay Roodposhti , Fraydoon & Nikoomaram , Hashem, 2015. "Parametric Estimates of High Frequency Market Microstructure Noise as an Unsystematic Risk," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 10(4), pages 29-50, October.
    3. Joanna Olbrys, 2011. "ARCH Effect in Classical Market-Timing Models with Lagged Market Variable: the Case of Polish Market," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 11, pages 185-202.

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