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When one stock share is a biological individual: a stylized simulation of the population dynamics in an order-driven market

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  • Hanchao Liu

    (Wilfrid Laurier University)

Abstract

The demand–supply relationship plays an important role in an order-driven stock market. In this paper, we propose a stylized model by defining demand (supply) over a stock at a certain time as how many shares are on the bid (ask) side, which includes all buy (sell) limit orders and buy (sell) market orders. Also, we will treat the two types of shares as two different species with interaction (a single share corresponds to an individual of one species) and will construct and apply generalized Lotka–Volterra equations (Hofbauer and Sigmund in Evolutionary games and population dynamics, Cambridge University Press, Cambridge, 1998) to simulate how their population evolve based on some properties or assumptions of an order-driven market, and also on the heterogenous beliefs among traders. The model suggests that the population of bid and ask shares moves either to a fixed point or periodically without the impact of external information. Also, our model gives a reason, though it is not perfect, explaining why stock prices can behave chaotically.

Suggested Citation

  • Hanchao Liu, 2020. "When one stock share is a biological individual: a stylized simulation of the population dynamics in an order-driven market," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 43(1), pages 373-408, June.
  • Handle: RePEc:spr:decfin:v:43:y:2020:i:1:d:10.1007_s10203-019-00273-8
    DOI: 10.1007/s10203-019-00273-8
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    1. Solomon, Sorin & Richmond, Peter, 2001. "Power laws of wealth, market order volumes and market returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 188-197.
    2. Chiarella, Carl & He, Xue-Zhong, 2002. "Heterogeneous Beliefs, Risk and Learning in a Simple Asset Pricing Model," Computational Economics, Springer;Society for Computational Economics, vol. 19(1), pages 95-132, February.
    3. He Huang & Alec N. Kercheval, 2012. "A generalized birth--death stochastic model for high-frequency order book dynamics," Quantitative Finance, Taylor & Francis Journals, vol. 12(4), pages 547-557, August.
    4. Rama Cont & Adrien de Larrard, 2013. "Price Dynamics in a Markovian Limit Order Market," Post-Print hal-00552252, HAL.
    5. Alan Kirman, 1993. "Ants, Rationality, and Recruitment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(1), pages 137-156.
    6. Agliari, Anna & Naimzada, Ahmad & Pecora, Nicolò, 2018. "Boom-bust dynamics in a stock market participation model with heterogeneous traders," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 458-468.
    7. F. Cavalli & A. Naimzada & M. Pireddu, 2017. "An evolutive financial market model with animal spirits: imitation and endogenous beliefs," Journal of Evolutionary Economics, Springer, vol. 27(5), pages 1007-1040, November.
    8. Chiarella, Carl & Dieci, Roberto & He, Xue-Zhong, 2007. "Heterogeneous expectations and speculative behavior in a dynamic multi-asset framework," Journal of Economic Behavior & Organization, Elsevier, vol. 62(3), pages 408-427, March.
    9. Bak, P. & Paczuski, M. & Shubik, M., 1997. "Price variations in a stock market with many agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 246(3), pages 430-453.
    10. Rama Cont & Sasha Stoikov & Rishi Talreja, 2010. "A Stochastic Model for Order Book Dynamics," Operations Research, INFORMS, vol. 58(3), pages 549-563, June.
    11. Andersen, Torben G. & Bollerslev, Tim, 1997. "Intraday periodicity and volatility persistence in financial markets," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 115-158, June.
    12. P. Toranj Simin & Gholam Reza Jafari & Marcel Ausloos & Cesar Federico Caiafa & Facundo Caram & Adeyemi Sonubi & Alberto Arcagni & Silvana Stefani, 2018. "Dynamical phase diagrams of a love capacity constrained prey–predator model," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 91(2), pages 1-18, February.
    13. Mandelbrot, Benoit B, 1972. "Correction of an Error in "The Variation of Certain Speculative Prices" (1963)," The Journal of Business, University of Chicago Press, vol. 45(4), pages 542-543, October.
    14. De Grauwe, Paul & Rovira Kaltwasser, Pablo, 2012. "Animal spirits in the foreign exchange market," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1176-1192.
    15. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
    Full references (including those not matched with items on IDEAS)

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    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • G1 - Financial Economics - - General Financial Markets

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