Corporate Financing: An Artificial Agent-Based Analysis

Posted: 24 Jun 2003

See all articles by Thomas H. Noe

Thomas H. Noe

University of Oxford - Said Business School; University of Oxford - Balliol College; Bank of Finland; European Corporate Governance Institute

Michael J. Rebello

University of Texas at Dallas - Naveen Jindal School of Management

Jun Wang

Zicklin School of Business, Baruch College

Multiple version iconThere are 2 versions of this paper

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

Noe, Thomas H. and Rebello, Michael J. and Wang, Jun Jonathan, Corporate Financing: An Artificial Agent-Based Analysis. Available at SSRN: https://ssrn.com/abstract=411133

Thomas H. Noe

University of Oxford - Said Business School ( email )

Park End Street
Oxford, OX1 3BJ
United Kingdom

University of Oxford - Balliol College ( email )

Broad St
Oxford, OX1 3BJ
United Kingdom

Bank of Finland ( email )

P.O. Box 160
FIN-00101 Helsinki
Finland

European Corporate Governance Institute ( email )

c/o the Royal Academies of Belgium
Rue Ducale 1 Hertogsstraat
1000 Brussels
Belgium

Michael J. Rebello (Contact Author)

University of Texas at Dallas - Naveen Jindal School of Management ( email )

P.O. Box 830688
Richardson, TX 75083-0688
United States

Jun Jonathan Wang

Zicklin School of Business, Baruch College ( email )

One Bernard Baruch Way
Box B10-225
New York, NC 10010
United States
646-312-3507 (Phone)
646-312-3451 (Fax)

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Abstract Views
1,064
PlumX Metrics