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Individual Expectations and Aggregate Behavior in Learning to Forcast Experiments

  • Hommes, C.H.

    ()

    (University of Amsterdam)

  • Lux, T.

    (University of Kiel)

Models with heterogeneous interacting agents explain macro phenomena through interactions at the micro level. We propose genetic algorithms as a model for individual expectations to explain aggregate market phenomena. The model explains all stylized facts observed in aggregate price fluctuations and individual forecasting behaviour in recent learning to forecast laboratory experiments with human subjects (Hommes et al. 2007), simultaneously and across different treatments.

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Paper provided by Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance in its series CeNDEF Working Papers with number 09-03.

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Date of creation: 2009
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Handle: RePEc:ams:ndfwpp:09-03
Contact details of provider: Postal: Dept. of Economics and Econometrics, Universiteit van Amsterdam, Roetersstraat 11, NL - 1018 WB Amsterdam, The Netherlands
Phone: + 31 20 525 52 58
Fax: + 31 20 525 52 83
Web page: http://www.fee.uva.nl/cendef/
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  1. Mankiw, N. Gregory & Reis, Ricardo & Wolfers, Justin, 2003. "Disagreement about Inflation Expectations," Research Papers 1807, Stanford University, Graduate School of Business.
  2. Duffy, John, 2006. "Agent-Based Models and Human Subject Experiments," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 19, pages 949-1011 Elsevier.
  3. Adam, Klaus, 2005. "Experimental evidence on the persistence of output and inflation," Working Paper Series 0492, European Central Bank.
  4. Marimon, Ramon & Sunder, Shyam, 1994. "Expectations and Learning under Alternative Monetary Regimes: An Experimental Approach," Economic Theory, Springer, vol. 4(1), pages 131-62, January.
  5. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers 10368, Iowa State University, Department of Economics.
  6. Cars Hommes & Joep Sonnemans & Jan Tuinstra & Henk van de Velden, 2004. "Coordination of Expectations in Asset Pricing Experiments," DNB Staff Reports (discontinued) 119, Netherlands Central Bank.
  7. Rosen, S. & Murphy, K.M. & Scheinkman, J.A., 1993. "Cattle Cycles," University of Chicago - Economics Research Center 93-2, Chicago - Economics Research Center.
  8. Ricardo Reis, 2005. "Inattentive Producers," 2005 Meeting Papers 290, Society for Economic Dynamics.
  9. repec:att:wimass:9625 is not listed on IDEAS
  10. Lux, Thomas & Schornstein, Sascha, 2002. "Genetic learning as an explanation of stylized facts of foreign exchange markets," Discussion Paper Series 1: Economic Studies 2002,29, Deutsche Bundesbank, Research Centre.
  11. Heemeijer, P. & Hommes, C.H. & Sonnemans, J. & Tuinstra, J., 2006. "Price Stability and Volatility in Markets with Positive and Negative Expectations Feedback: An Experimental Investigation," CeNDEF Working Papers 06-05, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  12. Daniel Kahneman, 2003. "Maps of Bounded Rationality: Psychology for Behavioral Economics," American Economic Review, American Economic Association, vol. 93(5), pages 1449-1475, December.
  13. Lux, T. & M. Marchesi, . "Scaling and Criticality in a Stochastic Multi-Agent Model of a Financial Market," Discussion Paper Serie B 438, University of Bonn, Germany, revised Jul 1998.
  14. Alan Kirman, 2006. "Heterogeneity in Economics," Journal of Economic Interaction and Coordination, Springer, vol. 1(1), pages 89-117, May.
  15. Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-81, September.
  16. LeBaron, Blake & Arthur, W. Brian & Palmer, Richard, 1999. "Time series properties of an artificial stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 23(9-10), pages 1487-1516, September.
  17. Kirman, Alan, 1993. "Ants, Rationality, and Recruitment," The Quarterly Journal of Economics, MIT Press, vol. 108(1), pages 137-56, February.
  18. Hommes, C.H. & Sonnemans, J. & Tuinstra, J. & Velden, H. van de, 2002. "Learning in Coweb Experiments," CeNDEF Working Papers 02-06, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  19. Hommes, C.H., 2001. "Modeling the stylized facts in finance through simple nonlinear adaptive systems," CeNDEF Working Papers 01-06, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  20. Freeman, Richard B, 1975. "Legal "Cobwebs": A Recursive Model of the Market for New Lawyers," The Review of Economics and Statistics, MIT Press, vol. 57(2), pages 171-79, May.
  21. Vriend, Nicolaas J., 2000. "An illustration of the essential difference between individual and social learning, and its consequences for computational analyses," Journal of Economic Dynamics and Control, Elsevier, vol. 24(1), pages 1-19, January.
  22. Arifovic, Jasmina, 1994. "Genetic algorithm learning and the cobweb model," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 3-28, January.
  23. William A. Branch, 2004. "The Theory of Rationally Heterogeneous Expectations: Evidence from Survey Data on Inflation Expectations," Economic Journal, Royal Economic Society, vol. 114(497), pages 592-621, 07.
  24. Marco Casari, 2004. "Can Genetic Algorithms Explain Experimental Anomalies?," Computational Economics, Society for Computational Economics, vol. 24(3), pages 257-275, March.
  25. Chavas, Jean-Paul, 2000. "On information and market dynamics: The case of the U.S. beef market," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 833-853, June.
  26. Richard B. Freeman, 1976. "A cobweb model of the supply and starting salary of new engineers," Industrial and Labor Relations Review, ILR Review, Cornell University, ILR School, vol. 29(2), pages 236-248, January.
  27. 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.
  28. W. Brian Arthur & John H. Holland & Blake LeBaron & Richard Palmer & Paul Taylor, 1996. "Asset Pricing Under Endogenous Expectation in an Artificial Stock Market," Working Papers 96-12-093, Santa Fe Institute.
  29. Arifovic, Jasmina & Gencay, Ramazan, 2000. "Statistical properties of genetic learning in a model of exchange rate," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 981-1005, June.
  30. Zarkin, Gary A, 1985. "Occupational Choice: An Application to the Market for Public School Teachers," The Quarterly Journal of Economics, MIT Press, vol. 100(2), pages 409-46, May.
  31. Anufriev, M. & Hommes, C.H., 2007. "Evolution of Market Heuristics," CeNDEF Working Papers 07-06, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  32. Lux, T. & M. Marchesi, . "Volatility Clustering in Financial Markets: A Micro-Simulation of Interacting Agents," Discussion Paper Serie B 437, University of Bonn, Germany, revised Jul 1998.
  33. Arifovic, Jasmina, 1996. "The Behavior of the Exchange Rate in the Genetic Algorithm and Experimental Economies," Journal of Political Economy, University of Chicago Press, vol. 104(3), pages 510-41, June.
  34. Evans, George W & Ramey, Garey, 1992. "Expectation Calculation and Macroeconomic Dynamics," American Economic Review, American Economic Association, vol. 82(1), pages 207-24, March.
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