La réputation de l’acquéreur et la réaction des marchés financiers à l’annonce de fusions-acquisitions internationales
Bibliographic record
Abstract
Nous examinons l’influence de la réputation de l’acquéreur sur la réaction des investisseurs suite à l’annonce de fusions-acquisitions internationales. En nous appuyant sur la théorie du signal, nous avançons que la réputation envoie un signal positif aux investisseurs lorsque de telles opérations sont annoncées. Notre étude empirique est fondée sur 134 fusions-acquisitions internationales réalisées par des entreprises multinationales françaises. Nos résultats confirment que la réputation est positivement liée à la création de valeur à court terme des fusions-acquisitions. Toutefois, la réaction positive des investisseurs à l’annonce de fusions-acquisitions est de moindre intensité pour les entreprises les plus réputées. De plus, nous montrons que la relation entre réputation et création de valeur est négativement modérée par la stratégie de diversification sectorielle de l’acquéreur.
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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 | 0.004 | 0.017 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".