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Detection and analysis of occurrences of spoofing in the Brazilian capital market

Author

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  • Luisa Mendonça
  • Alan De Genaro

Abstract

Purpose - The purpose of this paper is to analyze a data set from a brokerage firm to find possible spoofing cases in ten stocks from the Ibovespa index. The studies proposed concerned the parameters used in the search for the practice, the frequency of occurrences during the negotiation period, the impact on the price caused by the size of the spoofing order and the correlation between the stock's liquidity and the number of occurrences. Design/methodology/approach - By using intraday orders flows, the authors are able to reassemble the order book and perform an analysis of potential market manipulation. Findings - The authors found six possible cases, all of them happened in the beginning or end of the negotiation period, confirming that there is a window of opportunity for the practice when there is greater uncertainty related to the stock's price. Moreover, they found that in the less liquid stocks, it was necessary to place greater spoofing orders aiming to narrow the wider spread. Practical implications - A methodology for spoofing detection that can be replicated by brokerage firms and other researchers was developed. Social implications - The study contributes to the literature of capital market regulation by suggesting best practices for regulators and self-regulatory entities to avoid a predatory market practice. Originality/value - The authors present an algorithm and parameters for detecting spoofing; other papers are not practical orientated.

Suggested Citation

  • Luisa Mendonça & Alan De Genaro, 2020. "Detection and analysis of occurrences of spoofing in the Brazilian capital market," Journal of Financial Regulation and Compliance, Emerald Group Publishing Limited, vol. 28(3), pages 369-408, March.
    • Handle: RePEc:eme:jfrcpp:jfrc-07-2019-0092
    DOI: 10.1108/JFRC-07-2019-0092
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    References listed on IDEAS

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    1. Harris, Larry, 2002. "Trading and Exchanges: Market Microstructure for Practitioners," OUP Catalogue, Oxford University Press, number 9780195144703, Decembrie.
    2. Michael A. Goldstein & Edith S. Hotchkiss & Erik R. Sirri, 2007. "Transparency and Liquidity: A Controlled Experiment on Corporate Bonds," Review of Financial Studies, Society for Financial Studies, vol. 20(2), pages 235-273.
    3. Kent Daniel & David Hirshleifer, 2015. "Overconfident Investors, Predictable Returns, and Excessive Trading," Journal of Economic Perspectives, American Economic Association, vol. 29(4), pages 61-88, Fall.
    4. Lee, Eun Jung & Eom, Kyong Shik & Park, Kyung Suh, 2013. "Microstructure-based manipulation: Strategic behavior and performance of spoofing traders," Journal of Financial Markets, Elsevier, vol. 16(2), pages 227-252.
    5. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    6. Amy K. Edwards & Lawrence E. Harris & Michael S. Piwowar, 2007. "Corporate Bond Market Transaction Costs and Transparency," Journal of Finance, American Finance Association, vol. 62(3), pages 1421-1451, June.
    7. Bessembinder, Hendrik & Maxwell, William & Venkataraman, Kumar, 2006. "Market transparency, liquidity externalities, and institutional trading costs in corporate bonds," Journal of Financial Economics, Elsevier, vol. 82(2), pages 251-288, November.
    8. Hirshleifer, David & Daniel, Kent, 2015. "Overconfident investors, predictable returns, and excessive trading," MPRA Paper 69002, University Library of Munich, Germany.
    9. Rajesh K. Aggarwal & Guojun Wu, 2006. "Stock Market Manipulations," The Journal of Business, University of Chicago Press, vol. 79(4), pages 1915-1954, July.
    10. Tālis J. Putniņš, 2012. "Market Manipulation: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 26(5), pages 952-967, December.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. David Byrd, 2023. "Learning Not to Spoof," Papers 2306.06087, arXiv.org.
    2. Ramos, Henrique Pinto & Perlin, Marcelo Scherer, 2020. "Does algorithmic trading harm liquidity? Evidence from Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    3. Haochen Li & Maria Polukarova & Carmine Ventre, 2023. "Detecting Financial Market Manipulation with Statistical Physics Tools," Papers 2308.08683, arXiv.org.

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    More about this item

    Keywords

    Surveillance; Spoofing; Market manipulation; G14; G28; C55;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

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