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Equilibrium Stock Return Dynamics Under Alternative Rules of Learning About Hidden States

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  • Michael Brandt, Qi Zeng and Lu Zhang

Abstract

We examine the dynamic properties of equilibrium stock returns in an incomplete information economy in which the agents need to learn the hidden state of the endowment process. We consider both the case of optimal Bayesian learning and suboptimal learning, including near-rational learning, over- or under-confidence, optimism or pessimism, adaptive learning, and limited memory. We find that Bayesian learning can quantitatively explain short-run momentum, long-run mean-reversion, predictability, volatility clustering, and leverage effects in stock returns. Only over-confidence can marginally improve some aspects of the model (add short-run momentum) without substantially deteriorating other aspects. We conclude that the success of the incomplete information model is quite dependent on optimally learning agents.

Suggested Citation

  • Michael Brandt, Qi Zeng and Lu Zhang, 2001. "Equilibrium Stock Return Dynamics Under Alternative Rules of Learning About Hidden States," Computing in Economics and Finance 2001 41, Society for Computational Economics.
  • Handle: RePEc:sce:scecf1:41
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    Cited by:

    1. Rhys Bidder & Ian Dew-Becker, 2016. "Long-Run Risk Is the Worst-Case Scenario," American Economic Review, American Economic Association, vol. 106(9), pages 2494-2527, September.
    2. Hirshleifer, David & Li, Jun & Yu, Jianfeng, 2015. "Asset pricing in production economies with extrapolative expectations," Journal of Monetary Economics, Elsevier, vol. 76(C), pages 87-106.
    3. Cogley, Timothy & Sargent, Thomas J., 2008. "The market price of risk and the equity premium: A legacy of the Great Depression?," Journal of Monetary Economics, Elsevier, vol. 55(3), pages 454-476, April.
    4. Nengjiu Ju & Jianjun Miao, 2012. "Ambiguity, Learning, and Asset Returns," Econometrica, Econometric Society, vol. 80(2), pages 559-591, March.
    5. Guidolin, Massimo & Timmermann, Allan, 2007. "Properties of equilibrium asset prices under alternative learning schemes," Journal of Economic Dynamics and Control, Elsevier, vol. 31(1), pages 161-217, January.
    6. Pakoš, Michal, 2013. "Long-run risk and hidden growth persistence," Journal of Economic Dynamics and Control, Elsevier, vol. 37(9), pages 1911-1928.
    7. Tim W. Cogley & Thomas J. Sargent, 2005. "The Market Price of Risk and the Equity Premium," Working Papers 522, University of California, Davis, Department of Economics.
    8. Michael Johannes & Lars Lochstoer & Pierre Collin-Dufresne, 2015. "Parameter Learning in General Equilibrium: The Asset Pricing Implications," 2015 Meeting Papers 647, Society for Economic Dynamics.
    9. Pierre Collin-Dufresne & Michael Johannes & Lars A. Lochstoer, 2013. "Parameter Learning in General Equilibrium: The Asset Pricing Implications," NBER Working Papers 19705, National Bureau of Economic Research, Inc.
    10. Larry G. Epstein & Martin Schneider, 2007. "Learning Under Ambiguity," Review of Economic Studies, Oxford University Press, vol. 74(4), pages 1275-1303.
    11. Massa, Massimo & Simonov, Andrei, 2005. "Is learning a dimension of risk?," Journal of Banking & Finance, Elsevier, vol. 29(10), pages 2605-2632, October.
    12. Collard, Fabrice & Feve, Patrick & Ghattassi, Imen, 2006. "Predictability and habit persistence," Journal of Economic Dynamics and Control, Elsevier, vol. 30(11), pages 2217-2260, November.
    13. Brevik, Frode & d’Addona, Stefano, 2011. "Information Quality and Stock Returns Revisited," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(06), pages 1419-1446, January.
    14. Pataracchia, B., 2013. "Ambiguity aversion and heterogeneity in financial markets : An empirical and theoretical perspective," Other publications TiSEM bc849a3c-87a4-4718-b049-f, Tilburg University, School of Economics and Management.
    15. Larry G. Epstein & Martin Schneider, 2008. "Ambiguity, Information Quality, and Asset Pricing," Journal of Finance, American Finance Association, vol. 63(1), pages 197-228, February.
    16. Calvet, Laurent E. & Czellar, Veronika, 2015. "Through the looking glass: Indirect inference via simple equilibria," Journal of Econometrics, Elsevier, vol. 185(2), pages 343-358.
    17. repec:eee:dyncon:v:82:y:2017:i:c:p:312-330 is not listed on IDEAS
    18. Myroslav Pidkuyko, 2016. "When the Going Gets Tough: Durable Consumption and the Equity Premium," Centre for Growth and Business Cycle Research Discussion Paper Series 225, Economics, The Univeristy of Manchester.
    19. Bidarkota, Prasad V. & Dupoyet, Brice V. & McCulloch, J. Huston, 2009. "Asset pricing with incomplete information and fat tails," Journal of Economic Dynamics and Control, Elsevier, vol. 33(6), pages 1314-1331, June.
    20. Wen-Lin Wu & Yin-Feng Gau, 2017. "Home bias in portfolio choices: social learning among partially informed agents," Review of Quantitative Finance and Accounting, Springer, vol. 48(2), pages 527-556, February.
    21. Axioglou Christos & Skouras Spyros, 2015. "Asset pricing with flexible beliefs," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(4), pages 415-443, September.
    22. Yiqun Mou & Lars A. Lochstoer & Michael Johannes, 2011. "Learning about Consumption Dynamics," 2011 Meeting Papers 306, Society for Economic Dynamics.

    More about this item

    Keywords

    equilibrium stock return; learning rules; regime switching;

    JEL classification:

    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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