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Queuing, Social Interactions, And The Microstructure Of Financial Markets

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  • HORST, ULRICH
  • ROTHE, CHRISTIAN

Abstract

We consider an agent-based model of financial markets with asynchronous order arrival in continuous time. Buying and selling orders arrive in accordance with a Poisson dynamics where the order rates depend both on past prices and on the mood of the market. The agents form their demand for an asset on the basis of their forecasts of future prices and their forecasting rules may change over time as a result of the influence of other traders. Among the possible rules are “chartist” or extrapolatory rules. We prove that when chartists are in the market, and with choice of scaling, the dynamics of asset prices can be approximated by an ordinary delay differential equation. The fluctuations around the first-order approximation follow an Ornstein–Uhlenbeck dynamics with delay in a random environment of investor sentiment.

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  • Horst, Ulrich & Rothe, Christian, 2008. "Queuing, Social Interactions, And The Microstructure Of Financial Markets," Macroeconomic Dynamics, Cambridge University Press, vol. 12(2), pages 211-233, April.
    • Handle: RePEc:cup:macdyn:v:12:y:2008:i:02:p:211-233_07
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    Citations

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    Cited by:

    1. Christof Henkel, 2016. "An agent behavior based model for diffusion price processes with application to phase transition and oscillations," Papers 1606.08269, arXiv.org.
    2. Barucci, Emilio & Tolotti, Marco, 2012. "Social interaction and conformism in a random utility model," Journal of Economic Dynamics and Control, Elsevier, vol. 36(12), pages 1855-1866.
    3. Lux, Thomas & Alfarano, Simone, 2016. "Financial power laws: Empirical evidence, models, and mechanisms," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 3-18.
    4. Lux, Thomas, 2009. "Rational forecasts or social opinion dynamics? Identification of interaction effects in a business climate survey," Journal of Economic Behavior & Organization, Elsevier, vol. 72(2), pages 638-655, November.
    5. Chiarella, Carl & He, Xue-Zhong & Zheng, Min, 2011. "An analysis of the effect of noise in a heterogeneous agent financial market model," Journal of Economic Dynamics and Control, Elsevier, vol. 35(1), pages 148-162, January.
    6. Christof Henkel, 2016. "From quantum mechanics to finance: Microfoundations for jumps, spikes and high volatility phases in diffusion price processes," Papers 1609.05286, arXiv.org, revised Oct 2016.
    7. Lux, Thomas, 2012. "Estimation of an agent-based model of investor sentiment formation in financial markets," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1284-1302.
    8. Gunter M. Schutz & Fernando Pigeard de Almeida Prado & Rosemary J. Harris & Vladimir Belitsky, 2007. "Short-time behaviour of demand and price viewed through an exactly solvable model for heterogeneous interacting market agents," Papers 0801.0003, arXiv.org, revised Jun 2009.
    9. Ulrich Horst & Michael Paulsen, 2017. "A Law of Large Numbers for Limit Order Books," Mathematics of Operations Research, INFORMS, vol. 42(4), pages 1280-1312, November.
    10. Lux, Thomas, 2009. "Mass psychology in action: identification of social interaction effects in the German stock market," Kiel Working Papers 1514, Kiel Institute for the World Economy (IfW Kiel).
    11. Schütz, Gunter M. & de Almeida Prado, Fernando Pigeard & Harris, Rosemary J. & Belitsky, Vladimir, 2009. "Short-time behaviour of demand and price viewed through an exactly solvable model for heterogeneous interacting market agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(19), pages 4126-4144.
    12. Jamol Pender & Richard Rand & Elizabeth Wesson, 2020. "A Stochastic Analysis of Queues with Customer Choice and Delayed Information," Mathematics of Operations Research, INFORMS, vol. 45(3), pages 1104-1126, August.
    13. Ulrich Horst & Michael Paulsen, 2015. "A law of large numbers for limit order books," Papers 1501.00843, arXiv.org.
    14. Henkel, Christof, 2017. "From quantum mechanics to finance: Microfoundations for jumps, spikes and high volatility phases in diffusion price processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 447-458.
    15. Thomas Lux, 2009. "Rational Forecasts or Social Opinion Dynamics? Identification of Interaction Effects in a Business Climate Survey," Post-Print hal-00720175, HAL.
    16. Tae-Seok Jang, 2015. "Identification of Social Interaction Effects in Financial Data," Computational Economics, Springer;Society for Computational Economics, vol. 45(2), pages 207-238, February.
    17. Christian Bayer & Ulrich Horst & Jinniao Qiu, 2014. "A Functional Limit Theorem for Limit Order Books with State Dependent Price Dynamics," Papers 1405.5230, arXiv.org, revised Aug 2016.

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