Going Public and the Sale of Shares with Heterogeneous Investors: Agent-Based Computational Modelling and Computer Simulations

Abstract

In this paper we use agent-based computational modelling and computer simulations to examine the interrelationship between different selling strategies for going public. A great deal od recent empirical evidence suggests that to maximise the revenue raised from the shares sold in the public offering, it is fundamental to choose the appropriate design for the sale which, in turn reflects the final ownership structure. This literature establishes that the market for shares is segmented and, particularly, that firms manage the sale of shares with the purpose of discriminating between relatively small and passive investors and applicants for large potentially controlling blocks. One of the key questions in this area, then, is: How and to what extent should this heterogeneity among potential investors influence the firm's strategy for selling shares? Here we attempt to address this question from the standpoint of using agent-based computational modelling and computer simulations. Results show that the design of the sales is an important determinant if the performance of the negotiation process through which the firm is sold. A sequential sale beginning with an initial public offering of dispersed shares, followed by a negotiated sale of a controlling block is in general, more effective than other alternative selling strategies. Changing the negotiation protocol itself cab act as an effective way of impacting upon the revenue raised and the length of the process. The interrelationship between the method of sale and the performance may also depend ont he degree of cognitive accuracy that characterises the negotiating agents' mental representations of their physical and social environment.

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ORCID for Timothy Norman: orcid.org/0000-0002-6387-4034

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