TUTCRIS - Tampereen teknillinen yliopisto


Investor Reactions to Corporate Merger and Acquisition Announcements



KustantajaTampere University of Technology
ISBN (elektroninen)978-952-15-3318-1
ISBN (painettu)978-952-15-3301-3
TilaJulkaistu - 18 kesäkuuta 2014
OKM-julkaisutyyppiG4 Monografiaväitöskirja


NimiTampere University of Technology. Publication
KustantajaTampere University of Technology
ISSN (painettu)1459-2045


This dissertation examines investor reactions to corporate press and stock exchange releases on mergers and acquisitions (M&A). Investor reactions to corporate announcements are measured in changes in the corporate stock price. The dissertation focuses on a corporate’s acquisition target and its strategic intention to move within its value network, hypothesizing that different types of acquisitions create different cumulative abnormal return. Acquisition types are extended from traditional horizontal vs. vertical and related vs. unrelated acquisitions to cover all types of acquisitions. More detailed acquisition categories are needed to focus on strategic company moves and their impact on the share price. Investor reactions have traditionally been studied by using event study on day-level analysis. Such analysis does not sufficiently reflect current stock trading, whereas algorithmic trading represents most of the total volume. Recently high-frequency trading and the overall speed of the information flow have underscored the importance of transaction-level analysis, which was adopted for this dissertation. The hypotheses in this dissertation were tested with all stock transactions during 2006-2010 in NASDAQ OMX Helsinki. These publicly listed companies published over 30,000 releases, including 548 M&A actions. Consistent with theory, the findings showed a positive compounded abnormal return (CAR) in all M&A actions. Additionally, transaction level analysis revealed a CAR in unrelated acquisitions representing an upstream change in the center of gravity, whereas day-level analysis produced no CAR. Finally, the multiple regression model of transaction-level analysis improved the coefficient of determination significantly over day-level analysis. Whereas day-level analysis is too ambiguous and therefore allows possible misinterpretation of the event time, transaction-level analysis will give additional research topics such as the speed of response to press release and investors’ pre-announcement reactions.


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