Bibliographic record
Abstract
In this paper we investigate the short term abnormal return to the bidding firm’s shareholders in takeovers made by a Finnish company during the time period from January 2000 to December 2013. Specifically, we study takeover transactions involving publicly traded target companies, and are particularly interested in the relationship between the abnormal return to bidder’s shareholders and the size of the transaction. Specific features of the market for corporate acquisitions in Finland are that almost all transactions are friendly acquisitions and usually aim for 100% of the target company. We estimate the abnormal return around 51 individual takeover announcements and investigate determinants of the abnormal returns. Our results show that the takeover announcement on average yields a positive, but insignificant abnormal return to the bidding firm’s shareholders. The announcement effect on the announcement day is 0.63%, while the cumulative average abnormal return for an eleven day event window is 1.39%. Both pre-event and post-event abnormal returns are statistically insignificant, although there is sign of a price run-up during the last week prior to the announcement. We document a significant negative relationship between the bidder’s abnormal return on the announcement day and the size of the deal, but a positive relationship between the announcement effect and the relative size of the deal. We also document a weak negative relationship between the abnormal returns and the relative size of the target to the bidder. Among the other takeover characteristics we do not find any statistically significant relationship to the announcement effect.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".