IDEAS home Printed from https://ideas.repec.org/a/bla/jfinan/v61y2006i5p2103-2135.html

The Evolution of Security Designs

Author

Listed:
  • 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.

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
    DOI: 10.1111/j.1540-6261.2006.01052.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1540-6261.2006.01052.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1540-6261.2006.01052.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dreber, Anna & Rand, David G. & Garcia, Justin R. & Wernerfelt, Nils & Lum, J. Koji & Zeckhauser, Richard, 2010. "Dopamine and Risk Preferences in Different Domains," Working Paper Series rwp10-012, Harvard University, John F. Kennedy School of Government.
    2. 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.
    3. Xinyang Li & Andreas Krause, 2011. "An evolutionary multi‐objective optimization of trading rules in call markets," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 18(1), pages 1-14, January.
    4. 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.
    5. 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.
    6. 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.
    7. Qixuan Luo & Yu Shi & Xuan Zhou & Handong Li, 2021. "Research on the Effects of Institutional Liquidation Strategies on the Market Based on Multi-agent Model," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 1025-1049, December.
    8. Allen, Franklin & Barbalau, Adelina, 2024. "Security design: A review," Journal of Financial Intermediation, Elsevier, vol. 60(C).
    9. Benjamin E. Hermalin & Michael S. Weisbach, 2012. "Information Disclosure and Corporate Governance," Journal of Finance, American Finance Association, vol. 67(1), pages 195-234, February.
    10. Rydqvist, Kristian, 2010. "Tax Arbitrage with Risk and Effort Aversion - Swedish Lottery Bonds 1970-1990," SIFR Research Report Series 70, Institute for Financial Research.
    11. 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.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:jfinan:v:61:y:2006:i:5:p:2103-2135. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/afaaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.