Come Together: The Role of Cognitively Biased Imitators in a Small Scale Agent-Based Financial Market



We analyze the consequences of the presence of imitators in a financial market populated by boundedly rational speculators. We consider imitators that only look at the recent success of the available trading rules. We show that the introduction of this kind of imitators makes the results more complicated but even more realistic. In particular, under some specific circumstances, imitators may stabilize an otherwise unstable market or, at the opposite, make unstable an otherwise stable scenario.


Cognitive biases Bounded rationality Financial markets Agent-based models 


  1. Allais, M. (1953). Le comportement de l’homme rationnel devant le risque: Critique des postulats et axiomes de l’école américaine. Econometrica: Journal of the Econometric Society, 503–546.Google Scholar
  2. Banerjee, A. V. (1992). A simple model of herd behavior. The Quarterly Journal of Economics, 107(3), 797–817.CrossRefGoogle Scholar
  3. Barber, B. M., & Odean, T. (2000). Trading is hazardous to your wealth: The common stock investment performance of individual investors. The Journal of Finance, 55(2), 773–806.CrossRefGoogle Scholar
  4. Barber, B. M., & Odean, T. (2001). Boys will be boys: Gender, overconfidence, and common stock investment. The Quarterly Journal of Economics, 116(1), 261–292.CrossRefGoogle Scholar
  5. Bikhchandani, S., Hirshleifer, D., & Welch, I. (1992). A theory of fads, fashion, custom, and cultural change as informational cascades. Journal of Political Economy, 100(5), 992–1026.CrossRefGoogle Scholar
  6. Bischi, G.-I., Gallegati, M., Gardini, L., Leombruni, R., & Palestrini, A. (2006). Herd behavior and nonfundamental asset price fluctuations in financial markets. Macroeconomic Dynamics, 10(4), 502–528.CrossRefGoogle Scholar
  7. Brianzoni, S., & Campisi, G. (2020). Dynamical analysis of a financial market with fundamentalists, chartists, and imitators. Chaos, Solitons & Fractals, 130, 109434.Google Scholar
  8. Brock, W. A., & Hommes, C. H. (1997). A rational route to randomness. Econometrica: Journal of the Econometric Society, 1059–1095.Google Scholar
  9. Brock, W. A., & Hommes, C. H. (1998). Heterogeneous beliefs and routes to chaos in a simple asset pricing model. Journal of Economic Dynamics and Control, 22(8), 1235–1274.CrossRefGoogle Scholar
  10. Chiarella, C., & He, X.-Z. (2002). Heterogeneous beliefs, risk and learning in a simple asset pricing model. Computational Economics, 19(1), 95–132.CrossRefGoogle Scholar
  11. Chiarella, C., He, X.-Z., et al. (2000). Stability of competitive equilibria with heterogeneous beliefs and learning. Technical report, Quantitative Finance Research Centre, University of Technology, Sydney.Google Scholar
  12. Chiarella, C., Dieci, R., & He, X.-Z. (2009). Heterogeneity, market mechanisms, and asset price dynamics. In Handbook of financial markets: Dynamics and evolution (pp. 277–344). Elsevier.Google Scholar
  13. Day, R. H., & Huang, W. (1990). Bulls, bears and market sheep. Journal of Economic Behavior & Organization, 14(3), 299–329.CrossRefGoogle Scholar
  14. De Long, J. B., Shleifer, A., Summers, L. H., & Waldmann, R. J. (1990). Positive feedback investment strategies and destabilizing rational speculation. The Journal of Finance, 45(2), 379–395.Google Scholar
  15. Fama, E. F. (1965). The behavior of stock-market prices. The Journal of Business, 38(1), 34–105.CrossRefGoogle Scholar
  16. Fama, E. F. (1995). Random walks in stock market prices. Financial Analysts Journal, 51(1), 75–80.CrossRefGoogle Scholar
  17. Farmer, J. D. (2002). Market force, ecology and evolution. Industrial and Corporate Change, 11(5), 895–953.CrossRefGoogle Scholar
  18. Foroni, I., & Agliari, A. (2008). Complex price dynamics in a financial market with imitation. Computational Economics, 32(1–2), 21–36.CrossRefGoogle Scholar
  19. Franke, R., & Westerhoff, F. (2012). Structural stochastic volatility in asset pricing dynamics: Estimation and model contest. Journal of Economic Dynamics and Control, 36(8), 1193–1211.CrossRefGoogle Scholar
  20. Franke, R., & Westerhoff, F. (2016). Why a simple herding model may generate the stylized facts of daily returns: Explanation and estimation. Journal of Economic Interaction and Coordination, 11(1), 1–34.CrossRefGoogle Scholar
  21. Frankel, J. A., Froot, K. A., et al. (1986). Understanding the us dollar in the eighties: The expectations of chartists and fundamentalists. Economic Record, 62(1), 24–38.Google Scholar
  22. Hommes, C. (2011). The heterogeneous expectations hypothesis: Some evidence from the lab. Journal of Economic Dynamics and Control, 35(1), 1–24.CrossRefGoogle Scholar
  23. Hommes, C., & Wagener, F. (2009). Complex evolutionary systems in behavioral finance. In Handbook of financial markets: Dynamics and evolution (pp. 217–276). Elsevier.Google Scholar
  24. Kunda, Z. (1999). Social cognition: Making sense of people. MIT press.Google Scholar
  25. Lux, T. (1995). Herd behaviour, bubbles and crashes. The Economic Journal, 105(431), 881–896.CrossRefGoogle Scholar
  26. Lux, T. (1998). The socio-economic dynamics of speculative markets: Interacting agents, chaos, and the fat tails of return distributions. Journal of Economic Behavior & Organization, 33(2), 143–165.CrossRefGoogle Scholar
  27. Lux, T. (2009). Stochastic behavioral asset-pricing models and the stylized facts. In Handbook of financial markets: Dynamics and evolution (pp. 161–215). Elsevier.Google Scholar
  28. Lux, T., & Marchesi, M. (1998). Volatility clustering in financial markets: A micro-simulation of interacting agents. IFAC Proceedings Volumes, 31(16), 7–10.CrossRefGoogle Scholar
  29. Lux, T., & Marchesi, M. (1999). Scaling and criticality in a stochastic multi-agent model of a financial market. Nature, 397(6719), 498.CrossRefGoogle Scholar
  30. Menkhoff, L., & Taylor, M. P. (2007). The obstinate passion of foreign exchange professionals: Technical analysis. Journal of Economic Literature, 45(4), 936–972.CrossRefGoogle Scholar
  31. Orléan, A. (1995). Bayesian interactions and collective dynamics of opinion: Herd behavior and mimetic contagion. Journal of Economic Behavior & Organization, 28(2), 257–274.CrossRefGoogle Scholar
  32. Shefrin, H. (2001). Behavioral finance. Edward Elgar Publishing.Google Scholar
  33. Shiller, R. J. (2015). Irrational exuberance: Revised and expanded (3rd ed.). Princeton university press.Google Scholar
  34. Tramontana, F., & Westerhoff, F. (2013). One-dimensional discontinuous piecewise-linear maps and the dynamics of financial markets. In Global analysis of dynamic models in economics and finance (pp. 205–227). Springer.Google Scholar
  35. Tversky, A., & Kahneman, D. (1971). Belief in the law of small numbers. Psychological Bulletin, 76(2), 105.CrossRefGoogle Scholar
  36. Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131.Google Scholar
  37. Westerhoff, F. H. (2009). Exchange rate dynamics: A nonlinear survey. In B. Rosser Jr. (Ed.), Handbook of research on complexity. Citeseer.Google Scholar

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© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Department of Economics Marco BiagiUniversity of Modena and Reggio EmiliaModenaItaly
  2. 2.Department of Mathematical Disciplines, Mathematical Finance and EconometricsCatholic University of MilanMilanItaly

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