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Tick size and stock returns

Author

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  • Onnela, Jukka-Pekka
  • Töyli, Juuso
  • Kaski, Kimmo

Abstract

Tick size is an important aspect of the micro-structural level organization of financial markets. It is the smallest institutionally allowed price increment, has a direct bearing on the bid–ask spread, influences the strategy of trading order placement in electronic markets, affects the price formation mechanism, and appears to be related to the long-term memory of volatility clustering. In this paper we investigate the impact of tick size on stock returns. We start with a simple simulation to demonstrate how continuous returns become distorted after confining the price to a discrete grid governed by the tick size. We then move on to a novel experimental set-up that combines decimalization pilot programs and cross-listed stocks in New York and Toronto. This allows us to observe a set of stocks traded simultaneously under two different ticks while holding all security-specific characteristics fixed. We then study the normality of the return distributions and carry out fits to the chosen distribution models. Our empirical findings are somewhat mixed and in some cases appear to challenge the simulation results.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:phsmap:v:388:y:2009:i:4:p:441-454
    DOI: 10.1016/j.physa.2008.10.014
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    Citations

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    Cited by:

    1. Mei-Chen Lin & J. Jimmy Yang, 2023. "Do lottery characteristics matter for analysts’ forecast behavior?," Review of Quantitative Finance and Accounting, Springer, vol. 61(3), pages 1057-1091, October.
    2. Lallouache, Mehdi & Abergel, Frédéric, 2014. "Tick size reduction and price clustering in a FX order book," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 488-498.
    3. 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.
    4. Jörg Rieger & Kirsten Rüchardt & Bodo Vogt, 2011. "Comparing High Frequency Data of Stocks that are Traded Simultaneously in the US and Germany: Simulated Versus Empirical Data," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 1(2), pages 126-142, December.
    5. Gianbiagio Curato & Fabrizio Lillo, 2013. "Modeling the coupled return-spread high frequency dynamics of large tick assets," Papers 1310.4539, arXiv.org.
    6. Gabriele La Spada & J. Doyne Farmer & Fabrizio Lillo, 2010. "Tick size and price diffusion," Papers 1009.2329, arXiv.org, revised Oct 2010.
    7. Münnix, Michael C. & Schäfer, Rudi & Guhr, Thomas, 2010. "Impact of the tick-size on financial returns and correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4828-4843.
    8. Mehdi Lallouache & Frédéric Abergel, 2014. "Tick size reduction and price clustering in a FX order book," Post-Print hal-01006414, HAL.

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