Adra, S. orcid.org/0000-0002-0187-2607 and Barbopoulos, L.G. (2023) The informational consequences of good and bad mergers. Journal of Corporate Finance, 78. 102310. ISSN 0929-1199
Abstract
We study the information production dynamics in financial markets in response to Mergers and Acquisitions (M&As) announcements. We find that acquirers with low levels of pre-announcement stock price informativeness experience a substantial increase in their corresponding post-announcement stock price informativeness in response to positive Cumulative Abnormal Returns (CAR). We show that this increase is due to the enhanced prospect of deal completion. By contrast, high levels of acquirer pre-announcement stock price informativeness limit traders' incentives to search for, and acquire, new information. We also find that similar dynamics apply to the changes in acquirers' analyst coverage. Emphasizing the important role of information acquisition costs in influencing informed trading, a positive acquirer CAR increases the acquiring firm's post-announcement stock price informativeness in M&As involving public rather than private and subsidiary targets. Overall, we show that M&As have important informational consequences beyond their immediate effects on stock prices.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | Stock price informativeness; Endogenous information production; Mergers and acquisitions; Analyst coverage |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Management School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 30 Nov 2022 10:15 |
Last Modified: | 25 Sep 2024 14:38 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.jcorpfin.2022.102310 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:193206 |