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The Evolution of Security Designs

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  • THOMAS H. NOE
  • MICHAEL J. REBELLO
  • JUN WANG

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.

Suggested Citation

  • Thomas H. Noe & Michael J. Rebello & Jun Wang, 2006. "The Evolution of Security Designs," Journal of Finance, American Finance Association, vol. 61(5), pages 2103-2135, October.
  • Handle: RePEc:bla:jfinan:v:61:y:2006:i:5:p:2103-2135
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    References listed on IDEAS

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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.
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    3. Franklin Allen, Douglas Gale, 1988. "Optimal Security Design," Review of Financial Studies, Society for Financial Studies, pages 229-263.
    4. David Hirshleifer, 2001. "Investor Psychology and Asset Pricing," Journal of Finance, American Finance Association, vol. 56(4), pages 1533-1597, August.
    5. 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.
    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.
    7. repec:cup:macdyn:v:5:y:2001:i:2:p:303-25 is not listed on IDEAS
    8. 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.
    9. Douglas Gale, 1992. "Standard Securities," Review of Economic Studies, Oxford University Press, vol. 59(4), pages 731-755.
    10. 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, June.
    11. H. Peyton Young, 1996. "The Economics of Convention," Journal of Economic Perspectives, American Economic Association, vol. 10(2), pages 105-122, Spring.
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    Cited by:

    1. Lensberg, Terje & Schenk-Hoppé, Klaus Reiner & Ladley, Dan, 2015. "Costs and benefits of financial regulation: Short-selling bans and transaction taxes," Journal of Banking & Finance, Elsevier, vol. 51(C), pages 103-118.
    2. Lensberg, Terje & Schenk-Hoppé, Klaus Reiner & Ladley, Dan, 2012. "Costs and Benefits of Speculation," Discussion Papers 2012/12, Norwegian School of Economics, Department of Business and Management Science.
    3. Noe, Thomas H. & Rebello, Michael & Wang, Jun, 2012. "Learning to bid: The design of auctions under uncertainty and adaptation," Games and Economic Behavior, Elsevier, vol. 74(2), pages 620-636.
    4. Lijian Wei & Wei Zhang & Xue-Zhong He & Yongjie Zhang, 2013. "Learning and Information Dissemination in Limit Order Markets," Research Paper Series 333, Quantitative Finance Research Centre, University of Technology, Sydney.
    5. Ladley, Daniel & Lensberg, Terje & Palczewski, Jan & Schenk-Hoppé, Klaus Reiner, 2015. "Fragmentation and stability of markets," Journal of Economic Behavior & Organization, Elsevier, vol. 119(C), pages 466-481.

    More about this item

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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