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How to predict the consequences of a tick value change? Evidence from the Tokyo Stock Exchange pilot program

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  • Weibing Huang
  • Charles-Albert Lehalle
  • Mathieu Rosenbaum

Abstract

The tick value is a crucial component of market design and is often considered the most suitable tool to mitigate the effects of high frequency trading. The goal of this paper is to demonstrate that the approach introduced in Dayri and Rosenbaum (2015) allows for an ex ante assessment of the consequences of a tick value change on the microstructure of an asset. To that purpose, we analyze the pilot program on tick value modifications started in 2014 by the Tokyo Stock Exchange in light of this methodology. We focus on forecasting the future cost of market and limit orders after a tick value change and show that our predictions are very accurate. Furthermore, for each asset involved in the pilot program, we are able to define (ex ante) an optimal tick value. This enables us to classify the stocks according to the relevance of their tick value, before and after its modification.

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  • Weibing Huang & Charles-Albert Lehalle & Mathieu Rosenbaum, 2015. "How to predict the consequences of a tick value change? Evidence from the Tokyo Stock Exchange pilot program," Papers 1507.07052, arXiv.org.
    • Handle: RePEc:arx:papers:1507.07052
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    References listed on IDEAS

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    2. Chung, Kee H. & Van Ness, Robert A., 2001. "Order handling rules, tick size, and the intraday pattern of bid-ask spreads for Nasdaq stocks," Journal of Financial Markets, Elsevier, vol. 4(2), pages 143-161, April.
    3. David Bourghelle & F. Declerck, 2004. "Why Markets Should not Necessarily Reduce the Tick Size," Post-Print hal-00677711, HAL.
    4. 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.
    5. Bessembinder, Hendrik, 2000. "Tick Size, Spreads, and Liquidity: An Analysis of Nasdaq Securities Trading near Ten Dollars," Journal of Financial Intermediation, Elsevier, vol. 9(3), pages 213-239, July.
    6. Chung, Kee H. & Chuwonganant, Chairat, 2002. "Tick size and quote revisions on the NYSE," Journal of Financial Markets, Elsevier, vol. 5(4), pages 391-410, October.
    7. 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.
    8. 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.
    9. Christian Y. Robert & Mathieu Rosenbaum, 2011. "A New Approach for the Dynamics of Ultra-High-Frequency Data: The Model with Uncertainty Zones," Journal of Financial Econometrics, Oxford University Press, vol. 9(2), pages 344-366, Spring.
    10. Bourghelle, David & Declerck, Fany, 2004. "Why markets should not necessarily reduce the tick size," Journal of Banking & Finance, Elsevier, vol. 28(2), pages 373-398, February.
    11. Matthieu Wyart & Jean-Philippe Bouchaud & Julien Kockelkoren & Marc Potters & Michele Vettorazzo, 2008. "Relation between bid-ask spread, impact and volatility in order-driven markets," Quantitative Finance, Taylor & Francis Journals, vol. 8(1), pages 41-57.
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    Cited by:

    1. Charles-Albert Lehalle & Eyal Neuman, 2019. "Incorporating signals into optimal trading," Finance and Stochastics, Springer, vol. 23(2), pages 275-311, April.
    2. Miko{l}aj Bi'nkowski & Charles-Albert Lehalle, 2018. "Endogeneous Dynamics of Intraday Liquidity," Papers 1811.03766, arXiv.org.
    3. Charles-Albert Lehalle & Othmane Mounjid, 2016. "Limit Order Strategic Placement with Adverse Selection Risk and the Role of Latency," Papers 1610.00261, arXiv.org, revised Mar 2018.

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