Regional equity market conditions and cross-border mergers and acquisitions (M&A)
Notice bibliographique
Résumé
Purpose – Do regional equity market conditions (bear market) affect the financial performance of firms involved in cross-border mergers and acquisitions (M & A)? If so, is there a clear difference between inward and outward M & A in selected regions? The author addresses these questions using a sample of cross-border M & A between 1990 and 2013 in three major geographical regions of the emerging markets: Brazil, Russia, India, and China (BRIC), Eastern Europe, and Africa. The author finds that regional equity market conditions – such as bear equity conditions – along with direction of the cross-border M & A (inward vs outward), and differences in economic fundamentals among these regions carry valuable information and have real effects on market reactions to the announcement of cross-border M & A transactions. The paper aims to discuss these issues. Design/methodology/approach – Using an empirical approach, the author takes a regional perspective, with emphasis on three regions (BRIC, Eastern Europe, and Africa), and aim to determine the impact of the state of the regional equity market (bear stock market), and direction and duration of the M & A on market reactions to the announcement of cross-border M & A. Findings – The author documents the impact of regional equity market conditions on the financial performance of firms involved in cross-border M & A. The author underlines that differences in economic fundamentals among regions carry valuable information and have real effects on the performance of target firms. Practical implications – On the one hand, merger arbitrage investors are keen to learn how to profit and position their investments accordingly during those periods. Therefore, this study has also put the limelight on the underlying factors that influence the market reaction around the M & A announcement at the regional level and clearly shows the additional benefits of regional market conditions, direction of the transactions, and the timing to highlight the positive gain of those equity investments regarding the emerging markets. On the other hand, as the purpose of the study is to delve into the market reactions to the M & A announcement while taking into consideration some relevant factors such as regional equity market conditions to assist companies’ managers and CEOs to effectively choose the right time. Social implications – By incorporating the result presented in this study, another “family” of mutual funds, beyond just the combination of risky assets and the riskless asset is being introduced. Those investment portfolios which take into account merger and/or any opportunistic strategies are tailored more to the needs of various clienteles. For assisting the analyst and portfolio manager, the intuitive character of the result makes it versatile and easy to use by investment firms as an additional decision tool. Originality/value – To the author knowledge, this is the first study that delves into the market performance of companies involved in cross-border M & A in the emerging markets by taking a regional perspective and aiming to determine the impact of the state of the regional equity market (bear stock market) on the M & A. It offers additional support to those institutional investors who are pursuing international diversification across various countries including emerging markets such that bear equity conditions (recessions in the regional stock markets) have an additional negative impact and a real effect on the performance of target firms.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».