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Is high-frequency trading inducing changes in market microstructure and dynamics?

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  • Reginald D. Smith

Abstract

Using high-frequency time series of stock prices and share volumes sizes from January 2002-May 2009, this paper investigates whether the effects of the onset of high-frequency trading, most prominent since 2005, are apparent in the dynamics of the dollar traded volume. Indeed it is found in almost all of 14 heavily traded stocks, that there has been an increase in the Hurst exponent of dollar traded volume from Gaussian noise in the earlier years to more self-similar dynamics in later years. This shift is linked both temporally to the Reg NMS reforms allowing high-frequency trading to flourish as well as to the declining average size of trades with smaller trades showing markedly higher degrees of self-similarity.

Suggested Citation

  • Reginald D. Smith, 2010. "Is high-frequency trading inducing changes in market microstructure and dynamics?," Papers 1006.5490, arXiv.org, revised Sep 2010.
    • Handle: RePEc:arx:papers:1006.5490
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    Cited by:

    1. David Rushing Dewhurst & Michael Vincent Arnold & Colin Michael Van Oort, 2018. "Selection mechanisms affect volatility in evolving markets," Papers 1812.05657, arXiv.org, revised Apr 2019.
    2. Serbera, Jean-Philippe & Paumard, Pascal, 2016. "The fall of high-frequency trading: A survey of competition and profits," Research in International Business and Finance, Elsevier, vol. 36(C), pages 271-287.
    3. Demos, Guilherme & Da Silva, Sergio & Matsushita, Raul, 2015. "Some Statistical Properties of the Mini Flash Crashes," MPRA Paper 65473, University Library of Munich, Germany.
    4. Alfonso Puorro, 2013. "High frequency trading: an overview," Questioni di Economia e Finanza (Occasional Papers) 198, Bank of Italy, Economic Research and International Relations Area.
    5. Sánchez Serrano Antonio, 2020. "High-Frequency Trading and Systemic Risk: A Structured Review of Findings and Policies," Review of Economics, De Gruyter, vol. 71(3), pages 169-195, December.
    6. Chen, Wei-Peng & Chung, Huimin & Lien, Donald, 2016. "Price discovery in the S&P 500 index derivatives markets," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 438-452.
    7. Reginald D. Smith, 2017. "Bitcoin Average Dormancy: A Measure of Turnover and Trading Activity," Papers 1712.10287, arXiv.org, revised Feb 2018.
    8. Bicchetti, David & Maystre, Nicolas Maystre, 2013. "The synchronized and long-lasting structural change on commodity markets: Evidence from high frequency data," Algorithmic Finance, IOS Press, vol. 2(3-4), pages 233-239.
    9. Da Silva, Sergio, 2014. "Why Not Use Robots to Stabilize Stock Markets?," MPRA Paper 60567, University Library of Munich, Germany.
    10. Faisal I Qureshi, 2018. "Investigating Limit Order Book Characteristics for Short Term Price Prediction: a Machine Learning Approach," Papers 1901.10534, arXiv.org.

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