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The Evolution of Security Designs

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Author Info
THOMAS H. NOE
MICHAEL J. REBELLO
JUN WANG

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Abstract

We consider a competitive and perfect financial market in which agents have heterogeneous cash flow valuations. Instead of assuming that agents are endowed with rational expectations, we model their behavior as the product of adaptive learning. Our results demonstrate that adaptive learning affects security design profoundly, with securities mispriced even in the long run and optimal designs trading off underpricing against intrinsic value maximization. The evolutionary dominant security design calls for issuing securities that engender large losses with a small but positive probability, but that otherwise produce stable payoffs, almost the exact opposite of the pure state claims that are optimal in the rational expectations framework. Copyright 2006 by The American Finance Association.

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File URL: http://www.blackwell-synergy.com/doi/abs/10.1111/j.1540-6261.2006.01052.x
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Publisher Info
Article provided by American Finance Association in its journal The Journal of Finance.

Volume (Year): 61 (2006)
Issue (Month): 5 (October)
Pages: 2103-2135
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Handle: RePEc:bla:jfinan:v:61:y:2006:i:5:p:2103-2135

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  1. Brock, William A & LeBaron, Blake D, 1996. "A Dynamic Structural Model for Stock Return Volatility and Trading Volume," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 94-110, February. [Downloadable!] (restricted)
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  2. David Hirshleifer, 2001. "Investor Psychology and Asset Pricing," Journal of Finance, American Finance Association, vol. 56(4), pages 1533-1597, 08. [Downloadable!] (restricted)
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  3. Arifovic, Jasmina, 1996. "The Behavior of the Exchange Rate in the Genetic Algorithm and Experimental Economies," Journal of Political Economy, University of Chicago Press, vol. 104(3), pages 510-41, June. [Downloadable!] (restricted)
  4. Franklin Allen, Douglas Gale, 1988. "Optimal Security Design," Review of Financial Studies, Oxford University Press for Society for Financial Studies, vol. 1(3), pages 229-263. [Downloadable!] (restricted)
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  5. Allen, Franklin & Karjalainen, Risto, 1999. "Using genetic algorithms to find technical trading rules1," Journal of Financial Economics, Elsevier, vol. 51(2), pages 245-271, February. [Downloadable!] (restricted)
  6. Routledge, Bryan R., 2001. "Genetic Algorithm Learning To Choose And Use Information," Macroeconomic Dynamics, Cambridge University Press, vol. 5(02), pages 303-325, April. [Downloadable!]
  7. Arifovic, Jasmina, 1994. "Genetic algorithm learning and the cobweb model," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 3-28, January. [Downloadable!] (restricted)
  8. Gale, Douglas, 1992. "Standard Securities," Review of Economic Studies, Blackwell Publishing, vol. 59(4), pages 731-55, October. [Downloadable!] (restricted)
  9. Thomas H. Noe & Michael J. Rebello & Jun Wang, 2003. "Corporate Financing: An Artificial Agent-based Analysis," Journal of Finance, American Finance Association, vol. 58(3), pages 943-973, 06. [Downloadable!] (restricted)
  10. repec:cup:macdyn:v:5:y:2001:i:2:p:303-25 is not listed on IDEAS
  11. Young, H Peyton, 1996. "The Economics of Convention," Journal of Economic Perspectives, American Economic Association, vol. 10(2), pages 105-22, Spring. [Downloadable!] (restricted)
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