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Wealth Dynamics and a Bias Toward Momentum Trading

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  • Blake LeBaron

    ()
    (International Business School, Brandeis University)

Abstract

Evolutionary metaphors have been prominent in both economics and finance. They are often used as basic foundations for rational behavior and efficient markets. Theoretically, a mechanism which selects for rational investors actually requires many caveats, and is far from generic. This paper tests wealth based evolution in a simple, stylized agent-based financial market. The setup borrows extensively from current research in finance that considers optimal behavior with some amount of return predictability. The results confirm that with a homogeneous world of log utility investors wealth will converge onto optimal adaptive forecasting parameters. However, in the case of utility functions which differ from log, wealth selection alone converges to parameters which are economically far from the optimal forecast parameters. This serves as a strong reminder that wealth selection and utility maximization are not the same thing. Therefore, suboptimal financial forecasting strategies may be difficult to drive out of a market, and may even do quite well for some time.

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File URL: http://www.brandeis.edu/departments/economics/RePEc/brd/doc/Brandeis_WP14.pdf
File Function: First version, 2010
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Bibliographic Info

Paper provided by Brandeis University, Department of Economics and International Businesss School in its series Working Papers with number 14.

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Length: 13 pages
Date of creation: Dec 2010
Date of revision:
Handle: RePEc:brd:wpaper:14

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Postal: MS032, P.O. Box 9110, Waltham, MA 02454-9110
Web page: http://www.brandeis.edu/departments/economics/
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  1. Leonid Kogan & Stephen Ross & Jiang Wang & Mark Westerfield, 2003. "The Price Impact and Survival of Irrational Traders," NBER Working Papers 9434, National Bureau of Economic Research, Inc.
  2. Lawrence Blume & David Easley, 2001. "If You're So Smart, Why Aren't You Rich? Belief Selection in Complete and Incomplete Markets," Working Papers 01-06-031, Santa Fe Institute.
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  7. Armen A. Alchian, 1950. "Uncertainty, Evolution, and Economic Theory," Journal of Political Economy, University of Chicago Press, vol. 58, pages 211.
  8. Lubos Pastor & Robert F. Stambaugh, 2008. "Predictive Systems: Living with Imperfect Predictors," NBER Working Papers 13804, National Bureau of Economic Research, Inc.
  9. Robert R. Bliss & Nikolaos Panigirtzoglou, 2004. "Option-Implied Risk Aversion Estimates," Journal of Finance, American Finance Association, vol. 59(1), pages 407-446, 02.
  10. De Long, J. Bradford & Shleifer, Andrei & Summers, Lawrence H. & Waldmann, Robert J., 1991. "The Survival of Noise Traders in Financial Markets," Scholarly Articles 3725470, Harvard University Department of Economics.
  11. Stambaugh, Robert F., 1999. "Predictive regressions," Journal of Financial Economics, Elsevier, vol. 54(3), pages 375-421, December.
  12. Blake LeBaron, 2011. "Active and Passive Learning in Agent-based Financial Markets," Eastern Economic Journal, Palgrave Macmillan, vol. 37(1), pages 35-43.
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Cited by:
  1. LeBaron, Blake, 2012. "Heterogeneous gain learning and the dynamics of asset prices," Journal of Economic Behavior & Organization, Elsevier, vol. 83(3), pages 424-445.

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