Noe, Thomas, Rebello, Michael and Wang, Jun (2003) Corporate Financing: An artificial agent-based analysis. The Journal of Finance, 58 (3). pp. 943-973.
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.
|Keywords:||corporate financing, adaptive learning, genetic algorithm, security choice|
|Centre:||Faculty of Finance|
|Date Deposited:||09 Nov 2011 15:39|
|Last Modified:||23 Oct 2015 14:06|
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