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Citations for "Learning and excess volatility"

by James Bullard & John Duffy

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  1. Orlando Gomes, 2010. "Ordinary Least Squares Learning And Nonlinearities In Macroeconomics," Journal of Economic Surveys, Wiley Blackwell, vol. 24(1), pages 52-84, 02.
  2. Klaus Adam & Albert Marcet & Juan Pablo Nicolini, 2011. "Stock Market Volatility and Learning," CEP Discussion Papers dp1077, Centre for Economic Performance, LSE.
  3. 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.
  4. Hommes, C.H. & Zhu, M., 2012. "Behavioral Learning Equilibria," CeNDEF Working Papers 12-09, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  5. Bernard Dumas & Alexander Kurshev & Raman Uppal, 2007. "Equilibrium Portfolio Strategies in the Presence of Sentiment Risk and Excess Volatility," NBER Working Papers 13401, National Bureau of Economic Research, Inc.
  6. repec:dgr:uvatin:20060080 is not listed on IDEAS
  7. Evans, George W. & Honkapohja, Seppo & Mitra, Kaushik, 2007. "Anticipated Fiscal Policy and Adaptive Learning," CEPR Discussion Papers 6216, C.E.P.R. Discussion Papers.
  8. Massimo Guidolin, 2005. "Pessimistic beliefs under rational learning: quantitative implications for the equity premium puzzle," Working Papers 2005-005, Federal Reserve Bank of St. Louis.
  9. Eva Carceles Poveda & Chryssi Giannitsarou, 2006. "Asset pricing with adaptive learning," Computing in Economics and Finance 2006 25, Society for Computational Economics.
  10. Blake LeBaron, 1999. "Evolution and Time Horizons in an Agent-Based Stock Market," Computing in Economics and Finance 1999 1342, Society for Computational Economics.
  11. Liu, Yi-Fang & Zhang, Wei & Xu, Chao & Vitting Andersen, Jørgen & Xu, Hai-Chuan, 2014. "Impact of information cost and switching of trading strategies in an artificial stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 204-215.
  12. Chakraborty, Avik & Evans, George W., 2008. "Can perpetual learning explain the forward-premium puzzle?," Journal of Monetary Economics, Elsevier, vol. 55(3), pages 477-490, April.
  13. Jess Benhabib & Chetan Dave, 2014. "Learning, Large Deviations and Rare Events," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 17(3), pages 367-382, July.
  14. Yi-Fang Liu & Wei Zhang & Chao Xu & J{\o}rgen Vitting Andersen & Hai-Chuan Xu, 2013. "Impact of information cost and switching of trading strategies in an artificial stock market," Papers 1311.4274, arXiv.org, revised Jul 2014.
  15. Ehsan Ahmed & Honggang Li & J. Barkley Rosser, 2006. "Nonlinear bubbles in Chinese Stock Markets in the 1990s," Eastern Economic Journal, Eastern Economic Association, vol. 32(1), pages 1-18, Winter.
  16. Hommes, C.H. & Rosser, B.J., Jr., 2000. "Consistent Expectations Equilibria and Complex Dynamics in Renewable Resource Markets," CeNDEF Working Papers 00-05, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  17. Hommes, C.H., 2007. "Bounded Rationality and Learning in Complex Markets," CeNDEF Working Papers 07-01, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  18. Yi-Fang Liu & Wei Zhang & Chao Xu & Jørgen Vitting Andersen & Hai-Chuan Xu, 2014. "Impact of information cost and switching of trading strategies in an artificial stock market," Documents de travail du Centre d'Economie de la Sorbonne 14031, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  19. Bernard Dumas & Alexander Kurshev & Raman Uppal, 2005. "What Can Rational Investors Do About Excessive Volatility and Sentiment Fluctuations?," NBER Working Papers 11803, National Bureau of Economic Research, Inc.
  20. repec:dgr:uvatin:2013014 is not listed on IDEAS
  21. Florian Wagener & Cars Hommes & William Brock, 2006. "More hedging instruments may destabilize markets," Working Papers wp06-11, Warwick Business School, Finance Group.
  22. Giusto, Andrea, 2014. "Adaptive learning and distributional dynamics in an incomplete markets model," Journal of Economic Dynamics and Control, Elsevier, vol. 40(C), pages 317-333.
  23. Paul McNelis & John Duffy, 1998. "Approximating and Simulating the Stochastic Growth Model: Parameterized Expectations, Neural Networks, and the Genetic Algorithm," GE, Growth, Math methods 9804004, EconWPA, revised 04 May 1998.
  24. Klaus Adam & Albert Marcet, 2011. "Booms and Busts in Asset Prices," CEP Discussion Papers dp1059, Centre for Economic Performance, LSE.
  25. Eva Carceles-Poveda & Chryssi Giannitsarou, 2007. "Online Appendix to Asset Pricing with Adaptive Learning," Technical Appendices carceles08, Review of Economic Dynamics.
  26. Joshua M. Epstein, 2007. "Agent-Based Computational Models and Generative Social Science
    [Generative Social Science Studies in Agent-Based Computational Modeling]
    ," Introductory Chapters, Princeton University Press.
  27. repec:dgr:uvatin:20130014 is not listed on IDEAS
  28. Abbigail Chiodo & Massimo Guidolin & Michael T. Owyang & Makoto Shimoji, 2003. "Subjective probabilities: psychological evidence and economic applications," Working Papers 2003-009, Federal Reserve Bank of St. Louis.
  29. Yi-Fang Liu & Wei Zhang & Chao Xu & Jørgen Vitting Andersen & Hai-Chuan Xu, 2014. "Impact of information cost and switching of trading strategies in an artificial stock market," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00983051, HAL.
  30. LeBaron, Blake, 2006. "Agent-based Computational Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 24, pages 1187-1233 Elsevier.
  31. David Goldbaum, 2013. "Learning and Adaptation as a Source of Market Failure," Working Paper Series 14, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.