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Realized volatility, price informativeness, and tick size: A market microstructure approach

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  • Xiao, Xijuan
  • Yamamoto, Ryuichi

Abstract

This study examines the effects of tick size reduction on price volatility and microstructure noise terms embedded in stock prices. Comparing the realized variances and microstructure noise autocovariance before and after the tick size reduction and stock split, it is found that a smaller tick size induces a significant decline in price fluctuations at a 1-min frequency. Regressing the realized variances and microstructure noise autocovariance against trading activities, it is found that the decrease in the execution of large trades due to tick size reduction is primarily accountable for the shrinkage in price volatility. This effect exceeds the increase in the number of small trades that introduce higher price volatility. A less tick-constrained environment encourages order splitting, alleviates order clustering, weakens microstructure noise contamination, lowers its role in price variation, and thus improves price informativeness.

Suggested Citation

  • Xiao, Xijuan & Yamamoto, Ryuichi, 2024. "Realized volatility, price informativeness, and tick size: A market microstructure approach," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 410-426.
    • Handle: RePEc:eee:reveco:v:89:y:2024:i:pa:p:410-426
    DOI: 10.1016/j.iref.2023.07.109
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    1. Huang, Roger D. & Masulis, Ronald W., 2003. "Trading activity and stock price volatility: evidence from the London Stock Exchange," Journal of Empirical Finance, Elsevier, vol. 10(3), pages 249-269, May.
    2. Z. Merrick Li & Oliver Linton, 2022. "A ReMeDI for Microstructure Noise," Econometrica, Econometric Society, vol. 90(1), pages 367-389, January.
    3. Onnela, Jukka-Pekka & Töyli, Juuso & Kaski, Kimmo, 2009. "Tick size and stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(4), pages 441-454.
    4. Jones, Charles M & Kaul, Gautam & Lipson, Marc L, 1994. "Transactions, Volume, and Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 7(4), pages 631-651.
    5. 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.
    6. Andersen, Torben G. & Bollerslev, Tim & Meddahi, Nour, 2011. "Realized volatility forecasting and market microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 220-234, January.
    7. Andersen, Torben G. & Dobrev, Dobrislav & Schaumburg, Ernst, 2012. "Jump-robust volatility estimation using nearest neighbor truncation," Journal of Econometrics, Elsevier, vol. 169(1), pages 75-93.
    8. Bacidore, Jeffrey & Battalio, Robert H. & Jennings, Robert H., 2003. "Order submission strategies, liquidity supply, and trading in pennies on the New York Stock Exchange," Journal of Financial Markets, Elsevier, vol. 6(3), pages 337-362, May.
    9. Ingrid M. Werner & Barbara Rindi & Sabrina Buti & Yuanji Wen, 2022. "Tick Size, Trading Strategies and Market Quality," Post-Print hal-03591205, HAL.
    10. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
    11. Griffith, Todd G. & Roseman, Brian S., 2019. "Making cents of tick sizes: The effect of the 2016 U.S. SEC tick size pilot on limit order book liquidity," Journal of Banking & Finance, Elsevier, vol. 101(C), pages 104-121.
    12. Kamara, Avraham & Koski, Jennifer Lynch, 2001. "Volatility, autocorrelations, and trading activity after stock splits," Journal of Financial Markets, Elsevier, vol. 4(2), pages 163-184, April.
    13. 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.
    14. Van Ness, Bonnie F & Van Ness, Robert A & Pruitt, Stephen W, 2000. "The Impact of the Reduction in Tick Increments in Major U.S. Markets on Spreads, Depth, and Volatility," Review of Quantitative Finance and Accounting, Springer, vol. 15(2), pages 153-167, September.
    15. F. M. Bandi & J. R. Russell, 2008. "Microstructure Noise, Realized Variance, and Optimal Sampling," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 75(2), pages 339-369.
    16. Jacod, Jean & Li, Yingying & Mykland, Per A. & Podolskij, Mark & Vetter, Mathias, 2009. "Microstructure noise in the continuous case: The pre-averaging approach," Stochastic Processes and their Applications, Elsevier, vol. 119(7), pages 2249-2276, July.
    17. 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.
    18. Easley, David & O'Hara, Maureen, 1987. "Price, trade size, and information in securities markets," Journal of Financial Economics, Elsevier, vol. 19(1), pages 69-90, September.
    19. Bandi, Federico M. & Russell, Jeffrey R., 2006. "Separating microstructure noise from volatility," Journal of Financial Economics, Elsevier, vol. 79(3), pages 655-692, March.
    20. Liu, Lily Y. & Patton, Andrew J. & Sheppard, Kevin, 2015. "Does anything beat 5-minute RV? A comparison of realized measures across multiple asset classes," Journal of Econometrics, Elsevier, vol. 187(1), pages 293-311.
    21. Mehdi Lallouache & Fr'ed'eric Abergel, 2013. "Tick Size Reduction and Price Clustering in a FX Order Book," Papers 1307.5440, arXiv.org, revised Sep 2014.
    22. Chung, Dennis & Hrazdil, Karel, 2010. "Liquidity and market efficiency: A large sample study," Journal of Banking & Finance, Elsevier, vol. 34(10), pages 2346-2357, October.
    23. Jean Jacod & Yingying Li & Xinghua Zheng, 2017. "Statistical Properties of Microstructure Noise," Econometrica, Econometric Society, vol. 85, pages 1133-1174, July.
    24. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    25. 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.
    26. 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.
    27. 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.
    28. Chan, Choon Chat & Fong, Wai Mun, 2006. "Realized volatility and transactions," Journal of Banking & Finance, Elsevier, vol. 30(7), pages 2063-2085, July.
    29. Ruey S. Tsay, 2009. "Autoregressive Conditional Duration Models," Palgrave Macmillan Books, in: Terence C. Mills & Kerry Patterson (ed.), Palgrave Handbook of Econometrics, chapter 21, pages 1004-1024, Palgrave Macmillan.
    30. 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.
    31. Aït-Sahalia, Yacine & Mykland, Per A. & Zhang, Lan, 2011. "Ultra high frequency volatility estimation with dependent microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 160-175, January.
    32. Easley, David & O'Hara, Maureen & Saar, Gideon, 2001. "How Stock Splits Affect Trading: A Microstructure Approach," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 36(1), pages 25-51, March.
    33. Lin, Ji-Chai & Sanger, Gary C & Booth, G Geoffrey, 1995. "Trade Size and Components of the Bid-Ask Spread," The Review of Financial Studies, Society for Financial Studies, vol. 8(4), pages 1153-1183.
    34. Lipson, Marc L. & Mortal, Sandra, 2006. "The effect of stock splits on clientele: Is tick size relevant?," Journal of Corporate Finance, Elsevier, vol. 12(5), pages 878-896, December.
    35. Giot, Pierre & Laurent, Sébastien & Petitjean, Mikael, 2010. "Trading activity, realized volatility and jumps," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 168-175, January.
    36. Eaton, Gregory W. & Irvine, Paul J. & Liu, Tingting, 2021. "Measuring institutional trading costs and the implications for finance research: The case of tick size reductions," Journal of Financial Economics, Elsevier, vol. 139(3), pages 832-851.
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    More about this item

    Keywords

    Realized volatility; Price informativeness; Microstructure noise; Tick size reduction; Stock split;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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