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Online Appendix to Asset Pricing with Adaptive Learning

  • Eva Carceles-Poveda

    (SUNY Stony Brook)

  • Chryssi Giannitsarou

    (University of Cambridge)

We study the extent to which self-referential adaptive learning can explain stylized asset pricing facts in a general equilibrium framework. In particular, we analyze the effects of recursive least squares and constant gain algorithms in a production economy and a Lucas type endowment economy. We find that (a) recursive least squares learning has almost no effects on asset price behavior, since the algorithm converges relatively fast to rational expectations, (b) constant gain learning may contribute towards explaining the stock price and return volatility as well as the predictability of excess returns in the endowment economy but (c) in the production economy the effects of constant gain learning are mitigated by the persistence induced by capital accumulation. We conclude that in the context of these two commonly used models, standard linear self-referential learning does not resolve the asset pricing puzzles observed in the data. (Copyright: Elsevier)

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Paper provided by Review of Economic Dynamics in its series Technical Appendices with number carceles08.

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Length: 7 pages
Date of creation: Oct 2007
Date of revision:
Handle: RePEc:red:append:carceles08
Note: The original article was published in the Review of Economic Dynamics, forthcoming
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  1. repec:cup:macdyn:v:5:y:2001:i:2:p:272-302 is not listed on IDEAS
  2. 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.
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  4. Brock, W.A. & Hommes, C.H., 1996. "Hetergeneous Beliefs and Routes to Chaos in a Simple Asset Pricing Model," Working papers 9621, Wisconsin Madison - Social Systems.
  5. Timmermann, Allan G, 1993. "How Learning in Financial Markets Generates Excess Volatility and Predictability in Stock Prices," The Quarterly Journal of Economics, MIT Press, vol. 108(4), pages 1135-45, November.
  6. James Bullard & John Duffy, 1999. "Learning and Excess Volatility," Computing in Economics and Finance 1999 224, Society for Computational Economics.
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  8. Campbell, John & Shiller, Robert, 1988. "Stock Prices, Earnings, and Expected Dividends," Scholarly Articles 3224293, Harvard University Department of Economics.
  9. Carceles-Poveda, Eva & Giannitsarou, Chryssi, 2006. "Adaptive Learning in Practice," CEPR Discussion Papers 5627, C.E.P.R. Discussion Papers.
  10. Honkapohja, S. & Mitra, K., 1999. "Learning with Bounded Memory in Stochastic Models," University of Helsinki, Department of Economics 456, Department of Economics.
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  14. William A. Brock, 1982. "Asset Prices in a Production Economy," NBER Chapters, in: The Economics of Information and Uncertainty, pages 1-46 National Bureau of Economic Research, Inc.
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  16. Bacon, Robert W, 1980. "A Note on the Properties of Products of Random Variables with Reference to Economic Applications," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 42(4), pages 337-44, November.
  17. Campbell, John Y. & Yogo, Motohiro, 2006. "Efficient tests of stock return predictability," Journal of Financial Economics, Elsevier, vol. 81(1), pages 27-60, July.
  18. Stephen G. Cecchetti & Pok-sang Lam & Nelson C. Mark, 1998. "Asset Pricing with Distorted Beliefs: Are Equity Returns Too Good To Be True?," NBER Working Papers 6354, National Bureau of Economic Research, Inc.
  19. Brennan, Michael J. & Xia, Yihong, 2001. "Stock price volatility and equity premium," Journal of Monetary Economics, Elsevier, vol. 47(2), pages 249-283, April.
  20. Ravi Jagannathan & Ellen R. McGrattan & Anna Scherbina, 2001. "The Declining U.S. Equity Premium," NBER Working Papers 8172, National Bureau of Economic Research, Inc.
  21. Fama, Eugene F. & French, Kenneth R., 1988. "Dividend yields and expected stock returns," Journal of Financial Economics, Elsevier, vol. 22(1), pages 3-25, October.
  22. Giannitsarou, Chryssi, 2005. "E-Stability Does Not Imply Learnability," Macroeconomic Dynamics, Cambridge University Press, vol. 9(02), pages 276-287, April.
  23. Klaus Adam & Albert Marcet & Juan Pablo Nicolini, 2006. "Learning and Stock Market Volatility," Computing in Economics and Finance 2006 15, Society for Computational Economics.
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