Acquirer performance: Effect of anticipated and unanticipated acquisitions – Evidence from Europe

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School of Business | Master's thesis

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Mcode

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en

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53

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In recent years, the global M&A markets have seen a significant amount of completed deals due to low interest rates and companies’ growth ambitions. In the previous M&A studies, there have been observations that completed deals generally result in negative shareholder value for the acquiring firm and only benefit the target firm. Regarding this information, the consistent increase in dealmaking activity remains puzzling. This raises the question of what motivates companies to engage in acquisitions, especially when those deals are seen as value-losing for their shareholders. Tunyi (2021) explores this puzzle by categorizing acquirers into five quintiles (Q1–Q5) based on firms’ bid anticipation likelihood. Tunyi (2021) finds that unanticipated acquirers (Q1) earn CARs of 5.2% on a 3-day event window. At the same event window, the most anticipated acquirers (Q5) earn CARs of only 0.4%. Those findings support the notion that companies in the same sector tend to mimic their competitors. This thesis re-evaluates Tunyi’s (2021) findings, focusing on the European stock markets from 2003 to 2021, using an event study approach. By using similar methods in this thesis as Tunyi (2021), this thesis reveals that acquirers in the European market generate mean CARs of 0.8% for a 3-day event window, respectively. The 3-day CAR for Q1 in this thesis is only 0.3%, compared to the previously found CAR of 5.2% by Tunyi (2021). This discrepancy could be partly due to a significantly lower number of deals in Q1 in this thesis compared to Tunyi’s (2021) study. Another unexpected result in this thesis is that companies in the last quintile (Q5) generated the highest 3-day CAR of 0.9%. Still, these first-of-its-kind findings regarding acquirer returns from European markets suggest that acquisitions do generate positive returns for the firm’s shareholders. Importantly, some of the statistical results derived regarding CAR factors do not show explicit statistical significance. This lack of significance implies a need for a cautious interpretation of the data. Even if results hint at certain trends and correlations, these implications are not strong enough to be collectively determined using statistical evidence. Subsequent chapters of this thesis conclude open questions regarding CARs and aim to offer new pathways for future research on acquirer returns. For the proofreading of this thesis, the ChatGPT 4.0 application has been used.

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Keloharju, Matti

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