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On the Possibility of Informationally Efficient Markets

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Author Info
David Goldbaum

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Abstract

In a dynamic asset pricing model informed traders receive a noisy signal of the value of a risky asset while uninformed traders learn to extract the information from the price. The relative popularity of the two strategies depends on past performance. An "intensity of choice" parameter is endogenous, reflecting the traders" confidence in selecting the better of the two strategies. The asymptotic properties of the model depend on the evolutionary process for modeling relative popularity. It also depends on how the treatment of the convergence of the model as the popularity of being informed declines towards zero. It is possible to create prices that are arbitrarily close to perfect efficient

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Publisher Info
Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2004 with number 139.

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Date of creation: 11 Aug 2004
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Handle: RePEc:sce:scecf4:139

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Related research
Keywords: Market Efficiency; Asset Pricing; Learning;

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Find related papers by JEL classification:
G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies
C62 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Existence and Stability Conditions of Equilibrium
D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information

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  1. 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. [Downloadable!] (restricted)
  2. Routledge, Bryan R, 1999. "Adaptive Learning in Financial Markets," Review of Financial Studies, Oxford University Press for Society for Financial Studies, vol. 12(5), pages 1165-1202.
  3. Brock, William A & LeBaron, Blake D, 1996. "A Dynamic Structural Model for Stock Return Volatility and Trading Volume," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 94-110, February. [Downloadable!] (restricted)
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  4. Sethi, Rajiv & Franke, Reiner, 1995. "Behavioural Heterogeneity under Evolutionary Pressure: Macroeconomic Implications of Costly Optimisation," Economic Journal, Royal Economic Society, vol. 105(430), pages 583-600, May. [Downloadable!] (restricted)
  5. Marcet, Albert & Sargent, Thomas J, 1989. "Convergence of Least-Squares Learning in Environments with Hidden State Variables and Private Information," Journal of Political Economy, University of Chicago Press, vol. 97(6), pages 1306-22, December. [Downloadable!] (restricted)
  6. Marcet, Albert & Sargent, Thomas J., 1989. "Convergence of least squares learning mechanisms in self-referential linear stochastic models," Journal of Economic Theory, Elsevier, vol. 48(2), pages 337-368, August. [Downloadable!] (restricted)
  7. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
  8. David Goldbaum, 2001. "Market Efficiency and Learning in an Endogenously Unstable Environment," Computing in Economics and Finance 2001 105, Society for Computational Economics.
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  9. Timmermann, Allan, 1996. "Excess Volatility and Predictability of Stock Prices in Autoregressive Dividend Models with Learning," Review of Economic Studies, Blackwell Publishing, vol. 63(4), pages 523-57, October. [Downloadable!] (restricted)
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  10. Branch, William A. & McGough, Bruce, 2008. "Replicator dynamics in a Cobweb model with rationally heterogeneous expectations," Journal of Economic Behavior & Organization, Elsevier, vol. 65(2), pages 224-244, February. [Downloadable!] (restricted)
  11. Hellwig, Martin F., 1980. "On the aggregation of information in competitive markets," Journal of Economic Theory, Elsevier, vol. 22(3), pages 477-498, June. [Downloadable!] (restricted)
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