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Title: The behavior of institutional investors in IPO markets and the decision of going public abroad
Author: Fu, Youyan
ISNI:       0000 0004 6499 8607
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2016
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This thesis comprehensively studies three questions. First of all, I use a unique set of institutional investor bids to examine the impact of personal experience on the behavior of institutional investors in an IPO market. I find that, when deciding to participate in future IPOs, institutions take into account initial returns of past IPOs in which they submitted bids more than IPOs which they merely observed. In addition, initial returns from past IPOs in which institutions’ bids were qualified for share allocation were given more consideration than IPOs for which unqualified bids were submitted. This phenomenon is consistent with reinforcement learning. I also find that institutions do not distinguish the returns that are derived from random events. Furthermore, institutions become more aggressive bidders after experiencing high returns in recent IPOs, conditional on personal participation or being qualified for share allocation in those IPOs. This bidding behavior provides additional evidence of reinforcement learning in IPO markets. Secondly, I merge the dataset of institutional investor bids with post-IPO institutional holdings data to examine whether institutional investors such as fund companies reveal their true valuations through bids in a unique quasi-bookbuilding IPO mechanism. I find that fund companies do truthfully disclose their private information via bids, despite these being without guaranteed compensation. My results contribute to the existing literature by providing new evidence on the information compensation theory and have implications for the IPO mechanism design. Finally, I explore the impact on firm valuation of going public abroad using a sample of 136 Chinese firms that conducted IPOs in the US during the period of 1999-2012. I find that US-listed Chinese firms have higher price multiples and experience less underpricing than their domestic-listed peers. The valuation premium stays consistent when a firm’s characteristics and listing cost are being controlled. These findings are consistent with the theories of foreign listing. Moreover, I find that high-tech Chinese firms with a high growth rate but low profitability are more likely to issue shares in the US, particularly for specific industries such as semiconductors, software and online business services. This industry clustering is interpreted as an incentive to access foreign expertise through listing abroad.
Supervisor: Armitage, Seth ; Gucbilmez, Ufuk Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: IPO ; bookbuilding ; reinforcement learning ; foreign listing ; China