The Impact of Single and Multiple Mergers and Acquisitions on Shareholders’ Wealth of UK Bidder Firms
Bibliographic record
Abstract
This study investigates the impact of takeover announcements on UK acquirer shareholders’ wealth during the period 2002-2006. More specifically, it is investigated whether the impact of single acquirers on shareholders’ wealth is significantly different from the impact of multiple acquirers. Findings suggest that acquirer shareholders experience positive abnormal returns during the announcement period. Moreover, the results indicate single acquirers consistently outperform multiple acquirers when testing for deal characteristics such as: payment method (cash or equity), target status (public or private), target location (domestic or cross-border) and industry relatedness (specification or diversification). Performance declines with sequential acquisitions due to merger programme announcement hypothesis. Successful first time acquirers suffer from hubris whilst unsuccessful first time acquirers learn from their experiences suggested by the organisation learning hypothesis but go on to suffer from hubris. Acquisitions of private firms yield significant abnormal returns whereas public acquisitions reduce the value of UK acquirers. The effect of cash and equity, domestic and foreign, related and unrelated takeovers are inconclusive for the short-term windows investigated by this study.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".