Towards an Optimal IPO Mechanism

摘要

Concerns about the negative consequences of the excessive underpricing of the currentarrangement in the initial public offering (IPO) market for the provision of entrepreneurialfinance—book building—have led to research into the viability of auctions for IPO pricing andallocation. IPO firms face a trade-off between the benefit of accurate and reliable IPO price discoveryand the cost of underpricing. The main aim of this paper was to gain new scientific knowledgeabout this trade-off by measuring the impact of two key variables on this trade-off: capacity restraintand discount on the auction clearing price. Using controlled experiment methodology in multi-unituniform price auctions we found that the most capacity-restricted auctions that also offer investorsa discount are likely to produce the most accurate and reliable price discovery and consequently,the most predictable auction outcome. There are indications that a discount of 8% may suffice toincentivize investors to reliably contribute to price discovery. The resulting underpricing (and itsvariability) of these auctions is likely to be significantly lower than if book building would be usedto price and allocate IPOs. Technological innovation in the IPO market through the application ofrecent advances in data science, experimental economics and artificial intelligence allows for theoptimization of IPO mechanisms and crowdfunding platforms which in turn improves the access toequity required for entrepreneurial finance.