Evolutionary Switching between Forecasting Heuristics: An Explanation of an Asset-Pricing Experiment

  • Mikhail Anufriev
  • Cars Hommes
Part of the Lecture Notes in Economics and Mathematical Systems book series (LNE, volume 614)


In this paper we propose an explanation of the findings of a recent laboratory market forecasting experiment. In the experiment the participants were asked to predict prices for 50 periods on the basis of past realizations. Three different aggregate outcomes were observed in an identical environment: slow monotonic price convergence, persistent price oscillations, and oscillatory dampened price fluctuations. Individual predictions exhibited a high degree of coordination, although the individual forecasts were not commonly known. To explain these findings we propose an evolutionary model of reinforcement learning over a set of simple forecasting heuristics. The key element of our model is the switching between heuristics on the basis of their past performance. Simulations show that such evolutionary learning can reproduce the qualitative patterns observed in the experiment.


Pension Fund Rational Expectation Risky Asset Price Dynamic Past Performance 
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  1. W. A. Brock and C. H. Hommes. A rational route to randomness. Econometrica, 65(5):1059-1095, 1997.CrossRefGoogle Scholar
  2. W. A. Brock and C. H. Hommes. Heterogeneous beliefs and routes to chaos in a simple asset pricing model. Journal of Economic Dynamics and Control, 22:1235-1274, 1998.CrossRefGoogle Scholar
  3. J. Duffy. Experimental macroeconomics. In S. Durlauf and L. Blume, editors, New Palgrave Dictionary of Economics. Palgrave Macmillan, New York, 2008. forthcoming.Google Scholar
  4. E.F. Fama. Efficient capital markets: a review of theory and empirical work. Journal of Finance, 25:383-417, 1970.CrossRefGoogle Scholar
  5. C. Hommes. Heterogeneous agent models in economics and finance. In K. Judd and L. Tesfatsion, editors, Handbook of Computational Economics Vol. 2: Agent-Based Computational Economics. Elsevier, North-Holland, 2006.Google Scholar
  6. C. Hommes, J. Sonnemans, J. Tuinstra, and H. v. d. Velden. Coordination of expectations in asset pricing experiments. Review of Financial Studies, 18(3):955-980, 2005.CrossRefGoogle Scholar
  7. D. Kahneman. Maps of bounded rationality: Psychology for behavioral economics. American Economic Review, 93:1449-1475, 2003.CrossRefGoogle Scholar
  8. R. E. Lucas and E. C. Prescott. Investment under uncertainty. Econometrica, 39(5):659-681, 1971.CrossRefGoogle Scholar
  9. J. F. Muth. Rational expectations and the theory of price movements. Econometrica, 29(3):315-335,1961.CrossRefGoogle Scholar
  10. T. J. Sargent. Bounded Rationality in Macroeconomics. Oxford University Press, 1993.Google Scholar
  11. H. A. Simon. Models of Man: Social and Rational. John Wiley, New York, 1957.Google Scholar
  12. V. L. Smith. An experimental study of competitive market behavior. Journal of Political Economy, 70 (2):111-137, 1962.CrossRefGoogle Scholar
  13. V. L. Smith, G. L. Suchanek, and A. W. Williams. Bubbles, crashes, and endogenous expectations in experimental spot asset markets. Econometrica, 56(5):1119-1151, 1988.CrossRefGoogle Scholar
  14. A. Tversky and D. Kahneman. Judgement under uncertainty: Heuristics and biases. Science, 185: 1124-1130, 1974.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Mikhail Anufriev
    • 1
  • Cars Hommes
    • 1
  1. 1.CeNDEFUniversity of AmsterdamAmsterdamThe Netherlands

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