The Cost of Fragmentation: Lessons from Initial Public Offerings
Bennouri, M., Falconieri, S. ORCID: 0000-0002-7633-562X & Weaver, D. (2023). The Cost of Fragmentation: Lessons from Initial Public Offerings. The European Journal of Finance, 30(2), pp. 205-228. doi: 10.1080/1351847x.2023.2206972
Abstract
This paper investigates both theoretically and empirically the impact of market structure on the price discovery process at the opening of trading of IPOs. Some papers suggest that IPO value uncertainty is not fully resolved at the offering but continues into the aftermarket. Our model predicts that this ex-post uncertainty, i.e., the residual uncertainty about the firm value in the aftermarket, is related to the level of fragmentation in the aftermarket. Our model further predicts that consolidated markets are more efficient in resolving ex-post uncertainty than fragmented markets. Using the introduction of the opening IPO Cross on Nasdaq as a natural experiment, our empirical analysis provides compelling evidence that IPOs in fragmented markets exhibit larger levels of ex-post uncertainty and, consequently, larger underpricing than in consolidated markets.
Publication Type: | Article |
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Additional Information: | © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. |
Publisher Keywords: | trading structure, fragmentation, uncertainty, IPOs |
Subjects: | H Social Sciences > HG Finance |
Departments: | Bayes Business School > Finance |
SWORD Depositor: |
Available under License Creative Commons Attribution Non-commercial No Derivatives.
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