IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/8692.html
   My bibliography  Save this paper

Decimalization, Realized Volatility, and Market Microstructure Noise

Author

Listed:
  • Vuorenmaa, Tommi A.

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.

Suggested Citation

  • Vuorenmaa, Tommi A., 2008. "Decimalization, Realized Volatility, and Market Microstructure Noise," MPRA Paper 8692, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:8692
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/8692/1/MPRA_paper_8692.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ronen, Tavy & Weaver, Daniel G., 2001. "'Teenies' anyone?," Journal of Financial Markets, Elsevier, vol. 4(3), pages 231-260, June.
    2. 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.
    3. Chakravarty, Sugato & Panchapagesan, Venkatesh & Wood, Robert A., 2005. "Did decimalization hurt institutional investors?," Journal of Financial Markets, Elsevier, vol. 8(4), pages 400-420, November.
    4. Fan, Jianqing & Wang, Yazhen, 2007. "Multi-Scale Jump and Volatility Analysis for High-Frequency Financial Data," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1349-1362, December.
    5. 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.
    6. Glosten, Lawrence R. & Milgrom, Paul R., 1985. "Bid, ask and transaction prices in a specialist market with heterogeneously informed traders," Journal of Financial Economics, Elsevier, vol. 14(1), pages 71-100, March.
    7. Kee H. Chung & Bonnie F. Van Ness & Robert A. Van Ness, 2004. "Trading Costs And Quote Clustering On The Nyse And Nasdaq After Decimalization," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 27(3), pages 309-328, September.
    8. Xin Zhao & Kee H. Chung, 2006. "Decimal Pricing and Information-Based Trading: Tick Size and Informational Efficiency of Asset Price," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 33(5-6), pages 753-766.
    9. Sugato Chakravarty & Robert A. Wood & Robert A. Van Ness, 2004. "Decimals And Liquidity: A Study Of The Nyse," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 27(1), pages 75-94, March.
    10. Ahn, Hee-Joon & Cao, Charles Q. & Choe, Hyuk, 1996. "Tick Size, Spread, and Volume," Journal of Financial Intermediation, Elsevier, vol. 5(1), pages 2-22, January.
    11. Gottlieb, Gary & Kalay, Avner, 1985. "Implications of the Discreteness of Observed Stock Prices," Journal of Finance, American Finance Association, vol. 40(1), pages 135-153, March.
    12. 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.
    13. Xin Zhao & Kee H. Chung, 2006. "Decimal Pricing and Information‐Based Trading: Tick Size and Informational Efficiency of Asset Price," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 33(5‐6), pages 753-766, June.
    14. Madhavan, Ananth & Richardson, Matthew & Roomans, Mark, 1997. "Why Do Security Prices Change? A Transaction-Level Analysis of NYSE Stocks," The Review of Financial Studies, Society for Financial Studies, vol. 10(4), pages 1035-1064.
    15. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    16. Huang, Roger D. & Stoll, Hans R., 2001. "Tick Size, Bid-Ask Spreads, and Market Structure," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 36(4), pages 503-522, December.
    17. Goldstein, Michael A. & A. Kavajecz, Kenneth, 2000. "Eighths, sixteenths, and market depth: changes in tick size and liquidity provision on the NYSE," Journal of Financial Economics, Elsevier, vol. 56(1), pages 125-149, April.
    18. Jim Griffin & Roel Oomen, 2008. "Sampling Returns for Realized Variance Calculations: Tick Time or Transaction Time?," Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 230-253.
    19. 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.
    20. 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.
    21. Amihud, Yakov & Mendelson, Haim, 1987. "Trading Mechanisms and Stock Returns: An Empirical Investigation," Journal of Finance, American Finance Association, vol. 42(3), pages 533-553, July.
    22. Bessembinder, Hendrik, 2003. "Trade Execution Costs and Market Quality after Decimalization," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 38(4), pages 747-777, December.
    23. 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, Wiley Blackwell, vol. 32(5‐6), pages 1063-1081, June.
    24. 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.
    25. 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.
    26. Yan He & Chunchi Wu, 2005. "The Effects Of Decimalization On Return Volatility Components, Serial Correlation, And Trading Costs," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 28(1), pages 77-96, March.
    27. 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, Wiley Blackwell, vol. 32(5-6), pages 1063-1081.
    28. Ole E. Barndorff-Nielsen, 2004. "Power and Bipower Variation with Stochastic Volatility and Jumps," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 1-37.
    29. 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.
    30. Terrence Hendershott & Charles M. Jones & Albert J. Menkveld, 2011. "Does Algorithmic Trading Improve Liquidity?," Journal of Finance, American Finance Association, vol. 66(1), pages 1-33, February.
    31. David C. Porter & Daniel G. Weaver, 1997. "Tick Size and Market Quality," Financial Management, Financial Management Association, vol. 26(4), Winter.
    32. Cho, David Chinhyung & Frees, Edward W, 1988. " Estimating the Volatility of Discrete Stock Prices," Journal of Finance, American Finance Association, vol. 43(2), pages 451-466, June.
    33. Roll, Richard, 1984. "A Simple Implicit Measure of the Effective Bid-Ask Spread in an Efficient Market," Journal of Finance, American Finance Association, vol. 39(4), pages 1127-1139, September.
    34. Harris, Lawrence, 1990. "Estimation of Stock Price Variances and Serial Covariances from Discrete Observations," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 25(3), pages 291-306, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bertrand B. Maillet & Jean-Philippe R. M�decin, 2010. "Extreme Volatilities, Financial Crises and L-moment Estimations of Tail-indexes," Working Papers 2010_10, Department of Economics, University of Venice "Ca' Foscari".

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Khalil Dayri & Mathieu Rosenbaum, 2012. "Large tick assets: implicit spread and optimal tick size," Papers 1207.6325, arXiv.org, revised Jan 2013.
    2. Thanos Verousis & Pietro Perotti & Georgios Sermpinis, 2018. "One size fits all? High frequency trading, tick size changes and the implications for exchanges: market quality and market structure considerations," Review of Quantitative Finance and Accounting, Springer, vol. 50(2), pages 353-392, February.
    3. 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.
    4. Xin Zhao & Kee H. Chung, 2006. "Decimal Pricing and Information‐Based Trading: Tick Size and Informational Efficiency of Asset Price," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 33(5‐6), pages 753-766, June.
    5. Murphy Jun Jie Lee, 2013. "The Microstructure of Trading Processes on the Singapore Exchange," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2013.
    6. Michael Fleming & Giang Nguyen & Francisco Ruela, 2024. "Tick Size, Competition for Liquidity Provision, and Price Discovery: Evidence from the U.S. Treasury Market," Management Science, INFORMS, vol. 70(1), pages 332-354, January.
    7. Jiang, George J. & Oomen, Roel C.A., 2008. "Testing for jumps when asset prices are observed with noise-a "swap variance" approach," Journal of Econometrics, Elsevier, vol. 144(2), pages 352-370, June.
    8. Murphy Jun Jie Lee, 2013. "The Microstructure of Trading Processes on the Singapore Exchange," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 4, July-Dece.
    9. Christine Jiang & Jang-Chul Kim & Robert Wood, 2011. "A comparison of volatility and bid-ask spread for NASDAQ and NYSE after decimalization," Applied Economics, Taylor & Francis Journals, vol. 43(10), pages 1227-1239.
    10. Large, Jeremy, 2011. "Estimating quadratic variation when quoted prices change by a constant increment," Journal of Econometrics, Elsevier, vol. 160(1), pages 2-11, January.
    11. Dyl, Edward A. & Yuksel, H. Zafer & Zaynutdinova, Gulnara R., 2019. "Price reversals and price continuations following large price movements," Journal of Business Research, Elsevier, vol. 95(C), pages 1-12.
    12. Li, Z. Merrick & Laeven, Roger J.A. & Vellekoop, Michel H., 2020. "Dependent microstructure noise and integrated volatility estimation from high-frequency data," Journal of Econometrics, Elsevier, vol. 215(2), pages 536-558.
    13. Chaboud, Alain P. & Chiquoine, Benjamin & Hjalmarsson, Erik & Loretan, Mico, 2010. "Frequency of observation and the estimation of integrated volatility in deep and liquid financial markets," Journal of Empirical Finance, Elsevier, vol. 17(2), pages 212-240, March.
    14. Albuquerque, Rui & Song, Shiyun & Yao, Chen, 2017. "The Price Effects of Liquidity Shocks: A Study of SEC’s Tick-Size Experiment," CEPR Discussion Papers 12486, C.E.P.R. Discussion Papers.
    15. Andersen, Torben G. & Archakov, Ilya & Cebiroglu, Gökhan & Hautsch, Nikolaus, 2022. "Local mispricing and microstructural noise: A parametric perspective," Journal of Econometrics, Elsevier, vol. 230(2), pages 510-534.
    16. Craig W. Holden & Stacey Jacobsen & Avanidhar Subrahmanyam, 2014. "The Empirical Analysis of Liquidity," Foundations and Trends(R) in Finance, now publishers, vol. 8(4), pages 263-365, December.
    17. Biais, Bruno & Glosten, Larry & Spatt, Chester, 2005. "Market microstructure: A survey of microfoundations, empirical results, and policy implications," Journal of Financial Markets, Elsevier, vol. 8(2), pages 217-264, May.
    18. Timo Dimitriadis & Roxana Halbleib & Jeannine Polivka & Jasper Rennspies & Sina Streicher & Axel Friedrich Wolter, 2022. "Efficient Sampling for Realized Variance Estimation in Time-Changed Diffusion Models," Papers 2212.11833, arXiv.org, revised Dec 2023.
    19. Albuquerque, Rui & Song, Shiyun & Yao, Chen, 2020. "The price effects of liquidity shocks: A study of the SEC’s tick size experiment," Journal of Financial Economics, Elsevier, vol. 138(3), pages 700-724.
    20. Yacine Aït-Sahalia & Jean Jacod, 2012. "Analyzing the Spectrum of Asset Returns: Jump and Volatility Components in High Frequency Data," Journal of Economic Literature, American Economic Association, vol. 50(4), pages 1007-1050, December.

    More about this item

    Keywords

    Decimalization; Market microstructure noise; Realized volatility; Realized variance; Tick size; Ultra-high-frequency data;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:8692. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.