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Learning Unfair Trading: a Market Manipulation Analysis From the Reinforcement Learning Perspective

Author

Listed:
  • Enrique Mart'inez-Miranda
  • Peter McBurney
  • Matthew J. Howard
Abstract
Market manipulation is a strategy used by traders to alter the price of financial securities. One type of manipulation is based on the process of buying or selling assets by using several trading strategies, among them spoofing is a popular strategy and is considered illegal by market regulators. Some promising tools have been developed to detect manipulation, but cases can still be found in the markets. In this paper we model spoofing and pinging trading, two strategies that differ in the legal background but share the same elemental concept of market manipulation. We use a reinforcement learning framework within the full and partial observability of Markov decision processes and analyse the underlying behaviour of the manipulators by finding the causes of what encourages the traders to perform fraudulent activities. This reveals procedures to counter the problem that may be helpful to market regulators as our model predicts the activity of spoofers.

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  • Enrique Mart'inez-Miranda & Peter McBurney & Matthew J. Howard, 2015. "Learning Unfair Trading: a Market Manipulation Analysis From the Reinforcement Learning Perspective," Papers 1511.00740, arXiv.org.
    • Handle: RePEc:arx:papers:1511.00740
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    File URL: http://arxiv.org/pdf/1511.00740
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    References listed on IDEAS

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    1. Robert A. Jarrow, 2008. "Market Manipulation, Bubbles, Corners, and Short Squeezes," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 6, pages 105-130, World Scientific Publishing Co. Pte. Ltd..
    2. Allen, Franklin & Gale, Douglas, 1992. "Stock-Price Manipulation," The Review of Financial Studies, Society for Financial Studies, vol. 5(3), pages 503-529.
    3. Markus K. Brunnermeier & Lasse Heje Pedersen, 2005. "Predatory Trading," Journal of Finance, American Finance Association, vol. 60(4), pages 1825-1863, August.
    4. Itay Goldstein & Alexander Guembel, 2008. "Manipulation and the Allocational Role of Prices," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 75(1), pages 133-164.
    5. Hillion, Pierre & Suominen, Matti, 2004. "The manipulation of closing prices," Journal of Financial Markets, Elsevier, vol. 7(4), pages 351-375, October.
    6. 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.
    7. Ledgerwood Shaun D. & Carpenter Paul R., 2012. "A Framework for the Analysis of Market Manipulation," Review of Law & Economics, De Gruyter, vol. 8(1), pages 253-295, September.
    8. Craig Pirrong, 2004. "Detecting Manipulation in Futures Markets: The Ferruzzi Soybean Episode," American Law and Economics Review, American Law and Economics Association, vol. 6(1), pages 28-71.
    9. Khwaja, Asim Ijaz & Mian, Atif, 2005. "Unchecked intermediaries: Price manipulation in an emerging stock market," Journal of Financial Economics, Elsevier, vol. 78(1), pages 203-241, October.
    10. Rajesh K. Aggarwal & Guojun Wu, 2006. "Stock Market Manipulations," The Journal of Business, University of Chicago Press, vol. 79(4), pages 1915-1954, July.
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    Cited by:

    1. Viktoria Dalko & Michael H. Wang, 2020. "High-frequency trading: Order-based innovation or manipulation?," Journal of Banking Regulation, Palgrave Macmillan, vol. 21(4), pages 289-298, December.

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