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Heterogeneous Gain Learning and Long Swings in Asset Prices

Listed author(s):
  • Blake LeBaron

    ()

    (International Business School, Brandeis University)

This paper considers the impact of heterogeneous gain learning in an asset pricing model. A relatively stylized model is shown to generate persistent swings of asset prices from their fundamental values which replicates long range samples of U.S financial data. The detailed mechanisms of the learning models are then explored. Evidence suggests that agents' perceptions of risk and its dynamics and persistence are important in generating appropriate price/fundamental dynamics. Agents putting large amounts of weight on the recent past in their volatility models control a large fraction of wealth, and are important in perpetuating the volatility magnifying dynamics of the market.

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File URL: http://www.brandeis.edu/economics/RePEc/brd/doc/Brandeis_WP10.pdf
File Function: First version, 2010
Download Restriction: no

File URL: http://www.brandeis.edu/economics/RePEc/brd/doc/Brandeis_WP10R.pdf
File Function: Revised version, 2011
Download Restriction: no

Paper provided by Brandeis University, Department of Economics and International Businesss School in its series Working Papers with number 10.

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Length: 47 pages
Date of creation: Nov 2010
Handle: RePEc:brd:wpaper:10
Contact details of provider: Postal:
MS032, P.O. Box 9110, Waltham, MA 02454-9110

Web page: http://www.brandeis.edu/economics/

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  1. 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.
  2. Lux, Thomas, 1998. "The socio-economic dynamics of speculative markets: interacting agents, chaos, and the fat tails of return distributions," Journal of Economic Behavior & Organization, Elsevier, vol. 33(2), pages 143-165, January.
  3. Day, Richard H. & Huang, Weihong, 1990. "Bulls, bears and market sheep," Journal of Economic Behavior & Organization, Elsevier, vol. 14(3), pages 299-329, December.
  4. Seppo Honkapohja & Kaushik Mitra, 2006. "Learning Stability in Economies with Heterogeneous Agents," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 9(2), pages 284-309, April.
  5. Hommes, Cars, 2011. "The heterogeneous expectations hypothesis: Some evidence from the lab," Journal of Economic Dynamics and Control, Elsevier, vol. 35(1), pages 1-24, January.
  6. Andreas Fuster & David Laibson & Brock Mendel, 2010. "Natural Expectations and Macroeconomic Fluctuations," Journal of Economic Perspectives, American Economic Association, vol. 24(4), pages 67-84, Fall.
  7. LeBaron, Blake, 2001. "Evolution And Time Horizons In An Agent-Based Stock Market," Macroeconomic Dynamics, Cambridge University Press, vol. 5(02), pages 225-254, April.
  8. Carl Chiarella & Roberto Dieci & Xue-Zhong He, 2008. "Heterogeneity, Market Mechanisms, and Asset Price Dynamics," Research Paper Series 231, Quantitative Finance Research Centre, University of Technology, Sydney.
  9. John Y. Campbell & Luis M. Viceira, 1999. "Consumption and Portfolio Decisions when Expected Returns are Time Varying," The Quarterly Journal of Economics, Oxford University Press, vol. 114(2), pages 433-495.
  10. Alberto Giovannini & Philippe Weil, 1989. "Risk Aversion and Intertemporal Substitution in the Capital Asset Pricing Model," NBER Working Papers 2824, National Bureau of Economic Research, Inc.
  11. Robert F. Engle & Jose Gonzalo Rangel, 2008. "The Spline-GARCH Model for Low-Frequency Volatility and Its Global Macroeconomic Causes," Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1187-1222, May.
  12. Campbell, John Y & Shiller, Robert J, 1988. " Stock Prices, Earnings, and Expected Dividends," Journal of Finance, American Finance Association, vol. 43(3), pages 661-676, July.
  13. Georges, Christophre, 2008. "Staggered updating in an artificial financial market," Journal of Economic Dynamics and Control, Elsevier, vol. 32(9), pages 2809-2825, September.
  14. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 7(2), pages 174-196, Spring.
  15. Lubos Pástor & Robert F. Stambaugh, 2009. "Predictive Systems: Living with Imperfect Predictors," Journal of Finance, American Finance Association, vol. 64(4), pages 1583-1628, 08.
  16. Shleifer, Andrei & Vishny, Robert W, 1997. " The Limits of Arbitrage," Journal of Finance, American Finance Association, vol. 52(1), pages 35-55, March.
  17. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, Elsevier.
  18. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
  19. Mitra, Kaushik, 2005. "Is more data better?," Journal of Economic Behavior & Organization, Elsevier, vol. 56(2), pages 263-272, February.
  20. Lucas, Robert E, Jr, 1978. "Asset Prices in an Exchange Economy," Econometrica, Econometric Society, vol. 46(6), pages 1429-1445, November.
  21. Amit Goyal & Ivo Welch, 2003. "Predicting the Equity Premium with Dividend Ratios," Management Science, INFORMS, vol. 49(5), pages 639-654, May.
  22. Gençay, Ramazan & Dacorogna, Michel & Muller, Ulrich A. & Pictet, Olivier & Olsen, Richard, 2001. "An Introduction to High-Frequency Finance," Elsevier Monographs, Elsevier, edition 1, number 9780122796715.
  23. Kenneth L. Fisher & Meir Statman, 2006. "Market Timing In Regressions And Reality," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 29(3), pages 293-304.
  24. repec:fth:harver:1421 is not listed on IDEAS
  25. Klaus Adam & Albert Marcet, 2010. "Booms and Busts in Asset Prices," IMES Discussion Paper Series 10-E-02, Institute for Monetary and Economic Studies, Bank of Japan.
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