IDEAS home Printed from https://ideas.repec.org/a/bla/jfinan/v58y2003i3p943-973.html
   My bibliography  Save this article

Corporate Financing: An Artificial Agent‐based Analysis

Author

Listed:
  • Thomas H. Noe
  • Michael J. Rebello
  • Jun Wang

Abstract

We examine corporate security choice by simulating an economy populated by adaptive agents who learn about the structure of security returns and prices through experience. Through a process of evolutionary selection, each agent gravitates toward strategies that generate the highest payoffs. Despite the fact that markets are perfect and agents maximize value, a financing hierarchy emerges in which straight debt dominates other financing choices. Equity and convertible debt display significant underpricing. In general, the smaller the probability of loss to outside investors, the more likely the firm is to issue the security and the smaller the security's underpricing.

Suggested Citation

  • 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.
  • Handle: RePEc:bla:jfinan:v:58:y:2003:i:3:p:943-973
    DOI: 10.1111/1540-6261.00554
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/1540-6261.00554
    Download Restriction: no

    File URL: https://libkey.io/10.1111/1540-6261.00554?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
    ---><---

    Citations

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


    Cited by:

    1. Albert Banal-Estañol & Augusto Rupérez Micola, 2010. "Are Agent-based Simulations Robust? The Wholesale Electricity Trading Case," Working Papers 443, Barcelona School of Economics.
    2. International Monetary Fund, 2005. "Mauritius: Selected Issues and Statistical Appendix," IMF Staff Country Reports 2005/280, International Monetary Fund.
    3. Peter Wirtz, 2006. "Compétences, conflits et création de valeur:vers une approche intégrée de la gouvernance," Revue Finance Contrôle Stratégie, revues.org, vol. 9(2), pages 187-201, June.
    4. 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.
    5. Andrikopoulos, Andreas, 2015. "Truth and financial economics: A review and assessment," International Review of Financial Analysis, Elsevier, vol. 39(C), pages 186-195.
    6. 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.
    7. 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.
    8. 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.
    9. Daniel Arce & Douglas Cook & Robert Kieschnick, 2015. "On the evolution of corporate capital structures," Journal of Evolutionary Economics, Springer, vol. 25(3), pages 561-583, July.
    10. Nunez-Letamendia, Laura, 2007. "Fitting the control parameters of a genetic algorithm: An application to technical trading systems design," European Journal of Operational Research, Elsevier, vol. 179(3), pages 847-868, June.
    11. Ines Chaabouni & Anis Jarboui, 2016. "Effect of board`s skills on stakeholder value," Asian Journal of Empirical Research, Asian Economic and Social Society, vol. 6(4), pages 84-100, April.
    12. Marc Goergen & Christine A. Mallin & Eve Mitleton-Kelly & Ahmed Al-Hawamdeh & Iris H-Y Chiu, 2010. "Corporate Governance and Complexity Theory," Books, Edward Elgar Publishing, number 13927.
    13. 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.
    14. Duca, Eric, 2016. "Do investors learn from the past? Evidence from follow-on equity issues," Journal of Corporate Finance, Elsevier, vol. 39(C), pages 36-52.
    15. Banal-Estañol, Albert & Rupérez Micola, Augusto, 2011. "Behavioural simulations in spot electricity markets," European Journal of Operational Research, Elsevier, vol. 214(1), pages 147-159, October.

    More about this item

    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:58:y:2003:i:3:p:943-973. 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.