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Can Agents Learn to Form Rational Expectations? Some Results on Convergence and Stability of Learning in the UK Stock Market

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  • Timmermann, Allan

Abstract

Rational expectations are frequently justified as the point of convergence of agents' learning process. When agents' learning feeds back on the actual law of motion of the economy convergence of their rule to a rational expectations equilibrium (REE) is not guaranteed however. Applying new methods to analyze the convergence of learning in a model of U.K. stock prices we find evidence that agents could not have learned to form rational expectations if they had attempted to estimate the long-run dynamics of the model. If, however, agents have strong priors and impose a unit root on the model, thus confining their learning to the short run dynamics, there is evidence that recursive learning may eventually lead them to a REE. The learning process on the path to this equilibrium is highly volatile, suggesting that learning may help to explain excess volatility in U.K. stock prices. Copyright 1994 by Royal Economic Society.

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  • Timmermann, Allan, 1994. "Can Agents Learn to Form Rational Expectations? Some Results on Convergence and Stability of Learning in the UK Stock Market," Economic Journal, Royal Economic Society, vol. 104(425), pages 777-797, July.
  • Handle: RePEc:ecj:econjl:v:104:y:1994:i:425:p:777-97
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    Cited by:

    1. George W. Evans, 2011. "Comment on "Natural Expectations, Macroeconomic Dynamics, and Asset Pricing"," NBER Chapters,in: NBER Macroeconomics Annual 2011, Volume 26, pages 61-71 National Bureau of Economic Research, Inc.
    2. Basdevant, Olivier, 2005. "Learning process and rational expectations: An analysis using a small macro-economic model for New Zealand," Economic Modelling, Elsevier, vol. 22(6), pages 1074-1089, December.
    3. Kapetanios, George & Mitchell, James & Shin, Yongcheol, 2014. "A nonlinear panel data model of cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 179(2), pages 134-157.
    4. Shively, Philip A., 2007. "Asymmetric temporary and permanent stock-price innovations," Journal of Empirical Finance, Elsevier, vol. 14(1), pages 120-130, January.
    5. Barucci, Emilio & Landi, Leonardo, 1996. "Speculative dynamics with bounded rationality learning," European Journal of Operational Research, Elsevier, vol. 91(2), pages 284-300, June.
    6. Massimo Guidolin, 2013. "Markov switching models in asset pricing research," Chapters,in: Handbook of Research Methods and Applications in Empirical Finance, chapter 1, pages 3-44 Edward Elgar Publishing.
    7. William A. Branch & George W. Evans, 2011. "Learning about Risk and Return: A Simple Model of Bubbles and Crashes," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(3), pages 159-191, July.
    8. Sampson, Michael, 2003. "New Eras and Stock Market Bubbles," Structural Change and Economic Dynamics, Elsevier, vol. 14(3), pages 297-315, September.
    9. Rotheli, Tobias F., 2001. "Acquisition of costly information: an experimental study," Journal of Economic Behavior & Organization, Elsevier, vol. 46(2), pages 193-208, October.

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