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Smart Agents and Sentiment in the Heterogeneous Agent Model


  • Lukáš Vácha
  • Jozef Barunik
  • Miloslav Vošvrda


In this paper we extend the original heterogeneous agent model by introducing smart traders and changes in agents' sentiment. The idea of smart traders is based on the endeavor of market agents to estimate future price movements. By adding smart traders and changes in sentiment we try to improve the original heterogeneous agents model so that it provides a closer description of real markets. The main result of the simulations is that the probability distribution functions of the price deviations change significantly when smart traders are added to the model, and they also change significantly when changes in sentiment are introduced. We also use the Hurst exponent to measure the persistence of the price deviations and we find that the Hurst exponent is significantly increasing with the number of smart traders in the simulations. This means that the introduction of the smart traders concept into the model results in significantly higher persistence of the simulated price deviations. On the other hand, the introduction of changing sentiment in the proposed form does not change the persistence of the simulated prices significantly.

Suggested Citation

  • Lukáš Vácha & Jozef Barunik & Miloslav Vošvrda, 2009. "Smart Agents and Sentiment in the Heterogeneous Agent Model," Prague Economic Papers, University of Economics, Prague, vol. 2009(3), pages 209-219.
  • Handle: RePEc:prg:jnlpep:v:2009:y:2009:i:3:id:350:p:209-219

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    References listed on IDEAS

    1. Miloslav Vošvrda & Lukáš Vácha, 2003. "Heterogeneous agent model with memory and asset price behaviour," Prague Economic Papers, University of Economics, Prague, vol. 2003(2).
    2. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
    3. Chiarella, Carl & He, Xue-Zhong, 2003. "Heterogeneous Beliefs, Risk, And Learning In A Simple Asset-Pricing Model With A Market Maker," Macroeconomic Dynamics, Cambridge University Press, vol. 7(04), pages 503-536, September.
    4. 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.
    5. 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.
    6. 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.
    7. Miloslav Vošvrda & Lukáš Vácha, 2002. "Heterogeneous Agent Model And Numerical Analysis Of Learning," Bulletin of the Czech Econometric Society, The Czech Econometric Society, vol. 9(17).
    8. Lukáš Vácha & Miloslav Vošvrda, 2007. "Wavelet Decomposition of the Financial Market," Prague Economic Papers, University of Economics, Prague, vol. 2007(1), pages 38-54.
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    Cited by:

    1. Kukacka, Jiri & Barunik, Jozef, 2013. "Behavioural breaks in the heterogeneous agent model: The impact of herding, overconfidence, and market sentiment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 5920-5938.

    More about this item


    market structure; Hurst exponent; heterogeneous agent model; smart traders;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading


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