Η απόδοση των αγοραστών σε συγχωνεύσεις & εξαγορές στον κλάδο υψηλής τεχνολογίας στην αγορά των ΗΠΑ

View/ Open
Keywords
Συγχωνεύσεις ; Εξαγορές ; Αγοραστές ; Υψηλή τεχνολογία ; Ανάλυση γεγονότων ; Μη κανονικές αποδόσεις ; Market Index Model ; Χρηματιστηριακή αντίδρασηAbstract
This thesis examines the short-term stock market performance of acquiring firms involved in mergers and acquisitions (M&As) in the high-technology sector in the United States over the period 2010–2024. The primary objective of the study is to investigate whether the technological nature of a transaction affects the cumulative abnormal returns (CARs) of acquirers around the announcement date.
The final sample consists of 270 completed transactions in which both acquirers and targets are publicly listed companies in the United States. The transactions are classified into three categories: (i) non-technological transactions, allowing for a comparative analysis across groups, (ii) deals in which only the acquirer belongs to the high-technology sector, and (iii) deals in which both the acquirer and the target belong to the high-technology sector
The empirical analysis is based on the event study methodology. Abnormal Returns (ARs) are estimated using the Market Index Model with the S&P 500 as the market benchmark. Multiple event windows are examined around the announcement date, namely (-30,+30), (-5,+5), (-1,+1), and (0), in order to capture the short-term market reaction. In addition, a multivariate regression framework is employed to assess the impact of transaction-specific characteristics on cumulative abnormal returns.
With the limitation of the small sample used, our findings indicate that no systematic statistically significant abnormal returns are observed for acquiring firms across the examined event windows. Furthermore, the technological nature of the transaction does not appear to function as an independent determinant of short-term stock market outperformance. These results suggest that value creation for acquirers is not solely driven by the high-technology classification of a transaction, but is likely influenced by broader strategic and organizational factors.


