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On the Possibility of Informationally Efficient Markets

  • David Goldbaum

    ()

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. The asymptotic properties of the model and the possibility of an informationally efficient market depend on whether the population dynamics determine the level of popularity of the strategies or the direction of innovation in popularity. Allowing all traders to access both types of information introduces a stable fixed point, but also a paradox of inconsistency.

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File URL: http://www.rutgers-newark.rutgers.edu/econnwk/workingpapers/2004-009.pdf
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Paper provided by Department of Economics, Rutgers University, Newark in its series Working Papers Rutgers University, Newark with number 2004-009.

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Length: 29 pages
Date of creation: Oct 2004
Date of revision:
Handle: RePEc:run:wpaper:2004-009
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  1. David Goldbaum, 2004. "Market Efficiency and Learning in an Endogenously Unstable Environment," Working Papers Rutgers University, Newark 2004-002, Department of Economics, Rutgers University, Newark.
  2. Hellwig, Martin F., 1980. "On the aggregation of information in competitive markets," Journal of Economic Theory, Elsevier, vol. 22(3), pages 477-498, June.
  3. 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.
  4. 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.
  5. 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.
  6. William A. Brock & Blake D. LeBaron, 1995. "A Dynamic Structural Model for Stock Return Volatility and Trading Volume," NBER Working Papers 4988, National Bureau of Economic Research, Inc.
  7. Timmermann, Allan, 1996. "Excess Volatility and Predictability of Stock Prices in Autoregressive Dividend Models with Learning," Review of Economic Studies, Wiley Blackwell, vol. 63(4), pages 523-57, October.
  8. 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.
  9. 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.
  10. 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.
  11. Routledge, Bryan R, 1999. "Adaptive Learning in Financial Markets," Review of Financial Studies, Society for Financial Studies, vol. 12(5), pages 1165-1202.
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