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Decimalization, Realized Volatility, and Market Microstructure Noise

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Vuorenmaa, Tommi A.

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Abstract

This paper studies empirically the effect of decimalization on volatility and market microstructure noise. We apply several non-parametric estimators in order to accurately measure volatility and market microstructure noise variance before and after the final stage of decimalization which, on the NYSE, took place in January, 2001. We find that decimalization decreased observed volatility by decreasing noise variance and, consequently, increased the significance of the true signal especially in the trade price data for the high-activity stocks. In general, however, most of the found increase in the signal-to-noise ratio is explainable by confounding and random effects. We also find that although allowing for dependent noise can matter pointwisely, it does not appear to be critical in our case where the estimates are averaged over time and across stocks. For that same reason rare random jumps are not critical either. It is more important to choose a proper data type and prefilter the data carefully.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 8692.

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Date of creation: Apr 2008
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Handle: RePEc:pra:mprapa:8692

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Related research
Keywords: Decimalization Market microstructure noise Realized volatility Realized variance Tick size Ultra-high-frequency data

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Find related papers by JEL classification:
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Other

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    Other versions:
  5. Easley, David & O'Hara, Maureen, 1992. " Time and the Process of Security Price Adjustment," Journal of Finance, American Finance Association, vol. 47(2), pages 576-605, June.
  6. Gibson, Scott & Singh, Rajdeep & Yerramilli, Vijay, 2003. "The effect of decimalization on the components of the bid-ask spread," Journal of Financial Intermediation, Elsevier, vol. 12(2), pages 121-148, April. [Downloadable!] (restricted)
  7. Zhang, Lan & Mykland, Per A. & Ait-Sahalia, Yacine, 2005. "A Tale of Two Time Scales: Determining Integrated Volatility With Noisy High-Frequency Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1394-1411, December. [Downloadable!] (restricted)
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  8. Amihud, Yakov & Mendelson, Haim, 1987. " Trading Mechanisms and Stock Returns: An Empirical Investigation," Journal of Finance, American Finance Association, vol. 42(3), pages 533-53, July. [Downloadable!] (restricted)
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  12. Bacidore, Jeffrey M., 1997. "The Impact of Decimalization on Market Quality: An Empirical Investigation of the Toronto Stock Exchange," Journal of Financial Intermediation, Elsevier, vol. 6(2), pages 92-120, April. [Downloadable!] (restricted)
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  14. Sugato Chakravarty & Bonnie F. Van Ness & Robert A. Van Ness, 2005. "The Effect of Decimalization on Trade Size and Adverse Selection Costs," Journal of Business Finance & Accounting, Blackwell Publishing, vol. 32(5-6), pages 1063-1081. [Downloadable!] (restricted)
  15. Jegadeesh N. & Titman S., 1995. "Short-Horizon Return Reversals and the Bid-Ask Spread," Journal of Financial Intermediation, Elsevier, vol. 4(2), pages 116-132, April. [Downloadable!] (restricted)
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  19. Roel C. A. Oomen, 2005. "Properties of Bias-Corrected Realized Variance Under Alternative Sampling Schemes," Journal of Financial Econometrics, Oxford University Press, vol. 3(4), pages 555-577. [Downloadable!] (restricted)
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