The Evolution of Security Designs
This paper embeds security design in a model of evolutionary learning. We consider a competitive and perfect financial market where agents, as in Allen and Gale (1988), have heterogeneous valuations for cash flows. Our point of departure is that, 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 profoundly affects security design. Securities are mispriced even in the long run and optional designs trade 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, and otherwise produce stable payoffs. These designs are almost the exact opposite of the pure state claims which are optimal in the rational expectations framework but are roughly consistent with what one would expect given the decision making heuristics documented in the behavioural economics literature.
|Date of creation:||15 Sep 2004|
|Contact details of provider:|| Postal: Institute for Financial Research Drottninggatan 89, SE-113 60 Stockholm, Sweden|
Web page: http://www.sifr.org/
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- William A. Brock & Blake D. LeBaron, 1995. "A Dynamic Structural Model for Stock Return Volatility and Trading Volume," NBER Working Papers 4988, National Bureau of Economic Research, Inc.
- Arifovic, Jasmina, 1994. "Genetic algorithm learning and the cobweb model," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 3-28, January.
- Franklin Allen, Douglas Gale, 1988. "Optimal Security Design," Review of Financial Studies, Society for Financial Studies, vol. 1(3), pages 229-263.
- Franklin Allen & Douglas Gale, "undated". "Optimal Security Design," Rodney L. White Center for Financial Research Working Papers 26-87, Wharton School Rodney L. White Center for Financial Research.
- Douglas Gale, 1992. "Standard Securities," Review of Economic Studies, Oxford University Press, vol. 59(4), pages 731-755.
- David Hirshleifer, 2001. "Investor Psychology and Asset Pricing," Journal of Finance, American Finance Association, vol. 56(4), pages 1533-1597, 08.
- Hirshleifer, David, 2001. "Investor Psychology and Asset Pricing," MPRA Paper 5300, University Library of Munich, Germany.
- 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.
- H. Peyton Young, 1996. "The Economics of Convention," Journal of Economic Perspectives, American Economic Association, vol. 10(2), pages 105-122, Spring.
- 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 510-541, June.
- Routledge, Bryan R., 2001. "Genetic Algorithm Learning To Choose And Use Information," Macroeconomic Dynamics, Cambridge University Press, vol. 5(02), pages 303-325, April.
- repec:cup:macdyn:v:5:y:2001:i:2:p:303-25 is not listed on IDEAS
- Allen, Franklin & Karjalainen, Risto, 1999. "Using genetic algorithms to find technical trading rules," Journal of Financial Economics, Elsevier, vol. 51(2), pages 245-271, February. Full references (including those not matched with items on IDEAS)