The effect of Cross-border vs. domestic M&A announcements on shareholder wealth: Evidence from UK acquirersTools Henry, Nathan (2020) The effect of Cross-border vs. domestic M&A announcements on shareholder wealth: Evidence from UK acquirers. [Dissertation (University of Nottingham only)]
AbstractThis dissertation investigates the difference between cross-border and domestic M&A announcements effects for UK acquiring firms shareholders from 2012-2018. Specifically, this dissertation will examine the stock market reaction to cross-border and domestic M&A announcements under 4 different windows around the M&A announcement date: 3-day(- 1,+1), 11-day(-5,+5), 21-day(-10,+10) and 81-day(-40,+40) windows. The methodology used event studies to examine whether there was more value creation in cross-border compared to domestic M&A announcements and vice-versa. The total sample includes 99 M&A announcements where 20 were cross-border M&A announcements with continental European targets and 79 were domestic M&A announcements from 2012-2018. Normal returns were calculated from two models: The market and market-adjusted returns model with the use of the FTSE All-Share index for market returns. The main finding displayed domestic M&A announcements were more value-enhancing than cross-border M&A announcements. Additionally, this dissertation examines other deal and acquirers’ characteristics that may affect the abnormal returns to determine if there is a relationship by using OLS regressions. This included relative size, method of payment, listing status of the target (private vs public targets) and industry relatedness between acquirer and target. The results does not display any significant impact of method of payment and industry relatedness on abnormal returns. However, the results display the status of the target had a significant impact on abnormal returns for the domestic and full sample. Lastly, the results display that relative size has a negative significant impact on abnormal returns for the cross-border, domestic and full sample.
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