IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2005.13621.html
   My bibliography  Save this paper

Dynamic Coupling and Market Instability

Author

Listed:
  • Christopher D. Clack
  • Elias Court
  • Dmitrijs Zaparanuks

Abstract

We examine dynamic coupling and feedback effects between High Frequency Traders (HFTs) and how they can destabilize markets. We develop a general framework for modelling dynamic interaction based on recurrence relations, and use this to show how unexpected latency and feedback can trigger oscillatory instability between HFT market makers with inventory constraints. Our analysis suggests that the modelled instability is an unintentional emergent behaviour of the market that does not depend on the complexity of HFT strategies - even apparently stable strategies are vulnerable. Feedback instability can lead to substantial movements in market prices such as price spikes and crashes.

Suggested Citation

  • Christopher D. Clack & Elias Court & Dmitrijs Zaparanuks, 2020. "Dynamic Coupling and Market Instability," Papers 2005.13621, arXiv.org.
    • Handle: RePEc:arx:papers:2005.13621
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2005.13621
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
    2. Frank Westerhoff, 2003. "Market-maker, inventory control and foreign exchange dynamics," Quantitative Finance, Taylor & Francis Journals, vol. 3(5), pages 363-369.
    3. Kan Huang & David Simchi-Levi & Miao Song, 2012. "Optimal Market-Making with Risk Aversion," Operations Research, INFORMS, vol. 60(3), pages 541-565, June.
    4. Gennotte, Gerard & Leland, Hayne, 1990. "Market Liquidity, Hedging, and Crashes," American Economic Review, American Economic Association, vol. 80(5), pages 999-1021, December.
    5. Stefan Thurner & J. Doyne Farmer & John Geanakoplos, 2012. "Leverage causes fat tails and clustered volatility," Quantitative Finance, Taylor & Francis Journals, vol. 12(5), pages 695-707, February.
    6. Albert J. Menkveld & Marius A. Zoican, 2017. "Need for Speed? Exchange Latency and Liquidity," The Review of Financial Studies, Society for Financial Studies, vol. 30(4), pages 1188-1228.
    7. Arthur, W.B. & Holland, J.H. & LeBaron, B. & Palmer, R. & Tayler, P., 1996. "Asset Pricing Under Endogenous Expectations in an Artificial Stock Market," Working papers 9625, Wisconsin Madison - Social Systems.
    8. Jean-Philippe Bouchaud & Rama Cont, 1998. "A Langevin approach to stock market fluctuations and crashes," Science & Finance (CFM) working paper archive 500027, Science & Finance, Capital Fund Management.
    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. Kaizoji, Taisei, 2000. "Speculative bubbles and crashes in stock markets: an interacting-agent model of speculative activity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 493-506.
    11. Iori, Giulia, 2002. "A microsimulation of traders activity in the stock market: the role of heterogeneity, agents' interactions and trade frictions," Journal of Economic Behavior & Organization, Elsevier, vol. 49(2), pages 269-285, October.
    12. Carole Comerton‐Forde & Terrence Hendershott & Charles M. Jones & Pamela C. Moulton & Mark S. Seasholes, 2010. "Time Variation in Liquidity: The Role of Market‐Maker Inventories and Revenues," Journal of Finance, American Finance Association, vol. 65(1), pages 295-331, February.
    13. Giardina, Irene & Bouchaud, Jean-Philippe, 2003. "Volatility clustering in agent based market models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 6-16.
    14. Cont, Rama & Bouchaud, Jean-Philipe, 2000. "Herd Behavior And Aggregate Fluctuations In Financial Markets," Macroeconomic Dynamics, Cambridge University Press, vol. 4(2), pages 170-196, June.
    15. Beja, Avraham & Goldman, M Barry, 1980. "On the Dynamic Behavior of Prices in Disequilibrium," Journal of Finance, American Finance Association, vol. 35(2), pages 235-248, May.
    16. Menkveld, Albert J., 2013. "High frequency trading and the new market makers," Journal of Financial Markets, Elsevier, vol. 16(4), pages 712-740.
    17. G. Caldarelli & M. Marsili & Y. -C. Zhang, 1997. "A Prototype Model of Stock Exchange," Papers cond-mat/9709118, arXiv.org.
    18. Farmer, J. Doyne & Joshi, Shareen, 2002. "The price dynamics of common trading strategies," Journal of Economic Behavior & Organization, Elsevier, vol. 49(2), pages 149-171, October.
    19. Manaster, Steven & Mann, Steven C, 1996. "Life in the Pits: Competitive Market Making and Inventory Control," The Review of Financial Studies, Society for Financial Studies, vol. 9(3), pages 953-975.
    20. Jon Danielsson & Hyun Song Shin & Jean-Pierre Zigrand, 2012. "Endogenous Extreme Events and the Dual Role of Prices," Annual Review of Economics, Annual Reviews, vol. 4(1), pages 111-129, July.
    21. Thomas Lux & Michele Marchesi, 1999. "Scaling and criticality in a stochastic multi-agent model of a financial market," Nature, Nature, vol. 397(6719), pages 498-500, February.
    22. W. Brian Arthur & Paul Tayler, "undated". "Asset Pricing Under Endogenous Expectations in an Artificial Stock Market," Computing in Economics and Finance 1997 57, Society for Computational Economics.
    23. Carl Chiarella, 1992. "The Dynamics of Speculative Behaviour," Working Paper Series 13, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    24. Sethi, Rajiv, 1996. "Endogenous regime switching in speculative markets," Structural Change and Economic Dynamics, Elsevier, vol. 7(1), pages 99-118, March.
    25. Chiarella, Carl & He, Xue-Zhong & Hommes, Cars, 2006. "Moving average rules as a source of market instability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(1), pages 12-17.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Farmer, J. Doyne & Joshi, Shareen, 2002. "The price dynamics of common trading strategies," Journal of Economic Behavior & Organization, Elsevier, vol. 49(2), pages 149-171, October.
    2. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2001. "Microscopic Models of Financial Markets," Papers cond-mat/0110354, arXiv.org.
    3. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186, Elsevier.
    4. Xue-Zhong He, 2003. "Asset Pricing, Volatility and Market Behaviour: A Market Fraction Approach," Research Paper Series 95, Quantitative Finance Research Centre, University of Technology, Sydney.
    5. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2007. "Agent-based Models of Financial Markets," Papers physics/0701140, arXiv.org.
    6. Zhu, Mei & Chiarella, Carl & He, Xue-Zhong & Wang, Duo, 2009. "Does the market maker stabilize the market?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(15), pages 3164-3180.
    7. Rui Carvalho, 2001. "The Dynamics of the Linear Random Farmer Model," Papers cond-mat/0107150, arXiv.org.
    8. 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.
    9. Torsten Trimborn & Philipp Otte & Simon Cramer & Maximilian Beikirch & Emma Pabich & Martin Frank, 2020. "SABCEMM: A Simulator for Agent-Based Computational Economic Market Models," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 707-744, February.
    10. Torsten Trimborn & Philipp Otte & Simon Cramer & Max Beikirch & Emma Pabich & Martin Frank, 2018. "SABCEMM-A Simulator for Agent-Based Computational Economic Market Models," Papers 1801.01811, arXiv.org, revised Oct 2018.
    11. Noemi Schmitt & Ivonne Schwartz & Frank Westerhoff, 2022. "Heterogeneous speculators and stock market dynamics: a simple agent-based computational model," The European Journal of Finance, Taylor & Francis Journals, vol. 28(13-15), pages 1263-1282, October.
    12. Gardini, L. & Radi, D. & Schmitt, N. & Sushko, I. & Westerhoff, F., 2022. "Causes of fragile stock market stability," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 483-498.
    13. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, November.
    14. Youwei Li & Xue-Zhong He, 2005. "Long Memory, Heterogeneity, and Trend Chasing," Computing in Economics and Finance 2005 113, Society for Computational Economics.
    15. Andrea Gaunersdorfer & Cars Hommes, 2007. "A Nonlinear Structural Model for Volatility Clustering," Springer Books, in: Gilles Teyssière & Alan P. Kirman (ed.), Long Memory in Economics, pages 265-288, Springer.
    16. Hommes, C.H., 2005. "Heterogeneous Agents Models: two simple examples, forthcoming In: Lines, M. (ed.) Nonlinear Dynamical Systems in Economics, CISM Courses and Lectures, Springer, 2005, pp.131-164," CeNDEF Working Papers 05-01, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    17. LeBaron, Blake, 2006. "Agent-based Computational Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 24, pages 1187-1233, Elsevier.
    18. Gaunersdorfer, Andrea & Hommes, Cars H. & Wagener, Florian O.O., 2008. "Bifurcation routes to volatility clustering under evolutionary learning," Journal of Economic Behavior & Organization, Elsevier, vol. 67(1), pages 27-47, July.
    19. Cars Hommes & Florian Wagener, 2008. "Complex Evolutionary Systems in Behavioral Finance," Tinbergen Institute Discussion Papers 08-054/1, Tinbergen Institute.
    20. Valentyn Panchenko & Sergiy Gerasymchuk & Oleg V. Pavlov, 2007. "Asset price dynamics with small world interactions under hetereogeneous beliefs," Working Papers 149, Department of Applied Mathematics, Università Ca' Foscari Venezia.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2005.13621. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.