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How does the market react to your order flow?

Author

Listed:
  • Bence Toth
  • Zoltan Eisler
  • Fabrizio Lillo
  • Julien Kockelkoren
  • Jean-Philippe Bouchaud
  • J. Doyne Farmer

Abstract

We present an empirical study of the intertwined behaviour of members in a financial market. Exploiting a database where the broker that initiates an order book event can be identified, we decompose the correlation and response functions into contributions coming from different market participants and study how their behaviour is interconnected. We find evidence that (1) brokers are very heterogeneous in liquidity provision -- some are consistently liquidity providers while others are consistently liquidity takers. (2) The behaviour of brokers is strongly conditioned on the actions of {\it other} brokers. In contrast brokers are only weakly influenced by the impact of their own previous orders. (3) The total impact of market orders is the result of a subtle compensation between the same broker pushing the price in one direction and the liquidity provision of other brokers pushing it in the opposite direction. These results enforce the picture of market dynamics being the result of the competition between heterogeneous participants interacting to form a complicated market ecology.

Suggested Citation

  • Bence Toth & Zoltan Eisler & Fabrizio Lillo & Julien Kockelkoren & Jean-Philippe Bouchaud & J. Doyne Farmer, 2011. "How does the market react to your order flow?," Papers 1104.0587, arXiv.org, revised May 2012.
    • Handle: RePEc:arx:papers:1104.0587
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    References listed on IDEAS

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    1. B. Tóth & F. Lillo & J. D. Farmer, 2010. "Segmentation algorithm for non-stationary compound Poisson processes," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 78(2), pages 235-243, November.
    2. Jean-Philippe Bouchaud & Yuval Gefen & Marc Potters & Matthieu Wyart, 2003. "Fluctuations and response in financial markets: the subtle nature of `random' price changes," Papers cond-mat/0307332, arXiv.org, revised Aug 2003.
    3. Hasbrouck, Joel, 1991. "Measuring the Information Content of Stock Trades," Journal of Finance, American Finance Association, vol. 46(1), pages 179-207, March.
    4. Madhavan, Ananth, 2000. "Market microstructure: A survey," Journal of Financial Markets, Elsevier, vol. 3(3), pages 205-258, August.
    5. Jean-Philippe Bouchaud & Yuval Gefen & Marc Potters & Matthieu Wyart, 2004. "Fluctuations and response in financial markets: the subtle nature of 'random' price changes," Quantitative Finance, Taylor & Francis Journals, vol. 4(2), pages 176-190.
    6. J. Doyne Farmer, 2002. "Market force, ecology and evolution," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 11(5), pages 895-953, November.
    7. Handa, Puneet & Schwartz, Robert A, 1996. "Limit Order Trading," Journal of Finance, American Finance Association, vol. 51(5), pages 1835-1861, December.
    8. Jean-Philippe Bouchaud & Julien Kockelkoren & Marc Potters, 2006. "Random walks, liquidity molasses and critical response in financial markets," Quantitative Finance, Taylor & Francis Journals, vol. 6(2), pages 115-123.
    9. Amihud, Yakov & Mendelson, Haim, 1980. "Dealership market : Market-making with inventory," Journal of Financial Economics, Elsevier, vol. 8(1), pages 31-53, March.
    10. F. Lillo & Szabolcs Mike & J. Doyne Farmer, 2004. "A theory for long-memory in supply and demand," Papers cond-mat/0412708, arXiv.org, revised Mar 2005.
    11. Lillo Fabrizio & Farmer J. Doyne, 2004. "The Long Memory of the Efficient Market," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(3), pages 1-35, September.
    12. Jean-Philippe Bouchaud & J. Doyne Farmer & Fabrizio Lillo, 2008. "How markets slowly digest changes in supply and demand," Papers 0809.0822, arXiv.org.
    13. Menkveld, Albert J., 2013. "High frequency trading and the new market makers," Journal of Financial Markets, Elsevier, vol. 16(4), pages 712-740.
    14. J. Doyne Farmer & Austin Gerig & Fabrizio Lillo & Szabolcs Mike, 2006. "Market efficiency and the long-memory of supply and demand: is price impact variable and permanent or fixed and temporary?," Quantitative Finance, Taylor & Francis Journals, vol. 6(2), pages 107-112.
    15. Glosten, Lawrence R. & Milgrom, Paul R., 1985. "Bid, ask and transaction prices in a specialist market with heterogeneously informed traders," Journal of Financial Economics, Elsevier, vol. 14(1), pages 71-100, March.
    16. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    17. Esteban Moro & Javier Vicente & Luis G. Moyano & Austin Gerig & J. Doyne Farmer & Gabriella Vaglica & Fabrizio Lillo & Rosario N. Mantegna, 2009. "Market impact and trading profile of large trading orders in stock markets," Papers 0908.0202, arXiv.org.
    18. Armand Joulin & Augustin Lefevre & Daniel Grunberg & Jean-Philippe Bouchaud, 2008. "Stock price jumps: news and volume play a minor role," Papers 0803.1769, arXiv.org.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Emilio Said, 2019. "How Option Hedging Shapes Market Impact," Papers 1910.05056, arXiv.org, revised Nov 2019.
    2. Zhong, Li-Xin & Xu, Wen-Juan & Ren, Fei & Shi, Yong-Dong, 2013. "Coupled effects of market impact and asymmetric sensitivity in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2139-2149.
    3. Gregoire Loeper, 2013. "Option pricing with linear market impact and non-linear Black and Scholes equations," Papers 1301.6252, arXiv.org, revised Aug 2016.
    4. Bence Toth & Imon Palit & Fabrizio Lillo & J. Doyne Farmer, 2011. "Why is order flow so persistent?," Papers 1108.1632, arXiv.org, revised Nov 2014.
    5. Hiroyuki Moriya, 2017. "Quantized price volatility model for transaction data," Evolutionary and Institutional Economics Review, Springer, vol. 14(2), pages 397-408, December.
    6. Bence Toth & Zoltan Eisler & Jean-Philippe Bouchaud, 2017. "The short-term price impact of trades is universal," Papers 1702.08029, arXiv.org, revised Jan 2018.
    7. Damien Challet & Nikita Gourianov, 2018. "Dynamical regularities of US equities opening and closing auctions," Papers 1802.01921, arXiv.org, revised Oct 2018.
    8. Pankaj Kumar, 2021. "Deep Hawkes Process for High-Frequency Market Making," Papers 2109.15110, arXiv.org.
    9. Tóth, Bence & Palit, Imon & Lillo, Fabrizio & Farmer, J. Doyne, 2015. "Why is equity order flow so persistent?," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 218-239.
    10. Kyle Bechler & Michael Ludkovski, 2017. "Order Flows and Limit Order Book Resiliency on the Meso-Scale," Papers 1708.02715, arXiv.org.
    11. 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.
    12. Sandro Claudio Lera & Didier Sornette, 2015. "Currency target zone modeling: An interplay between physics and economics," Papers 1508.04754, arXiv.org, revised Oct 2015.
    13. Damian Eduardo Taranto & Giacomo Bormetti & Jean-Philippe Bouchaud & Fabrizio Lillo & Bence Toth, 2016. "Linear models for the impact of order flow on prices II. The Mixture Transition Distribution model," Papers 1604.07556, arXiv.org.
    14. Emilio Said, 2019. "How Option Hedging Shapes Market Impact," Working Papers hal-02310080, HAL.
    15. A. Gareche & G. Disdier & J. Kockelkoren & J. -P. Bouchaud, 2013. "A Fokker-Planck description for the queue dynamics of large tick stocks," Papers 1304.6819, arXiv.org.
    16. Li-Xin Zhong & Wen-Juan Xu & Fei Ren & Yong-Dong Shi, 2012. "Coupled effects of market impact and asymmetric sensitivity in financial markets," Papers 1209.3399, arXiv.org, revised Jan 2013.
    17. Damian Eduardo Taranto & Giacomo Bormetti & Jean-Philippe Bouchaud & Fabrizio Lillo & Bence Toth, 2016. "Linear models for the impact of order flow on prices I. Propagators: Transient vs. History Dependent Impact," Papers 1602.02735, arXiv.org.

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