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Asset pricing with adaptive learning

  • Eva Carceles Poveda
  • Chryssi Giannitsarou

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 recursive least squares learning has almost no effects on asset price behavior, for either model, since the algorithm converges fast to rational expectations. At the other end, constant gain learning may sometimes contribute towards explaining the stock price volatility and the predictability of excess returns in the endowment economy. However, in the production economy the effects of constant gain learning are mitigated by the persistence induced by capital accumulation. We conclude that, contrary to popular belief, standard self-referential learning alone cannot resolve the asset pricing puzzles observed in the data

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Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2006 with number 25.

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Date of creation: 04 Jul 2006
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Handle: RePEc:sce:scecfa:25
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  1. Michele Boldrin & Lawrence J. Christiano & Jonas D. M. Fisher, 2000. "Habit persistence, asset returns and the business cycle," Staff Report 280, Federal Reserve Bank of Minneapolis.
  2. Bullard, James & Duffy, John, 2001. "Learning And Excess Volatility," Macroeconomic Dynamics, Cambridge University Press, vol. 5(02), pages 272-302, April.
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  4. Ellen R. McGrattan & Edward C. Prescott, 2003. "Average debt and equity returns: puzzling?," Staff Report 313, Federal Reserve Bank of Minneapolis.
  5. 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.
  6. Campbell, John Y. & Yogo, Motohiro, 2006. "Efficient tests of stock return predictability," Journal of Financial Economics, Elsevier, vol. 81(1), pages 27-60, July.
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  8. 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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  10. Narayana R. Kocherlakota, 1995. "The equity premium: it's still a puzzle," Discussion Paper / Institute for Empirical Macroeconomics 102, Federal Reserve Bank of Minneapolis.
  11. 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.
  12. John Y. Campbell, 2002. "Consumption-Based Asset Pricing," Harvard Institute of Economic Research Working Papers 1974, Harvard - Institute of Economic Research.
  13. Ravi Jagannathan & Ellen R. McGrattan & Anna Scherbina., 2000. "The declining U.S. equity premium," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall, pages 3-19.
  14. 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.
  15. Carceles-Poveda, Eva & Giannitsarou, Chryssi, 2007. "Adaptive learning in practice," Journal of Economic Dynamics and Control, Elsevier, vol. 31(8), pages 2659-2697, August.
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  18. repec:cup:macdyn:v:5:y:2001:i:2:p:272-302 is not listed on IDEAS
  19. repec:att:wimass:9621 is not listed on IDEAS
  20. Martin Lettau, 2003. "Inspecting The Mechanism: Closed-Form Solutions For Asset Prices In Real Business Cycle Models," Economic Journal, Royal Economic Society, vol. 113(489), pages 550-575, 07.
  21. Brennan, Michael J. & Xia, Yihong, 2001. "Stock price volatility and equity premium," Journal of Monetary Economics, Elsevier, vol. 47(2), pages 249-283, April.
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