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Enregistrement W1593236526 · doi:10.1108/ijoem-09-2013-0157

Regional equity market conditions and cross-border mergers and acquisitions (M&A)

2015· article· en· W1593236526 sur OpenAlex

Pourquoi ce travail est dans la base

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Notice bibliographique

RevueInternational Journal of Emerging Markets · 2015
Typearticle
Langueen
DomaineBusiness, Management and Accounting
ThématiqueCorporate Finance and Governance
Établissements canadiensOntario Tech University
Organismes subventionnairesnon disponible
Mots-clésBRICEquity (law)Mergers and acquisitionsArbitrageEconomicsChinaFinancial economicsStock marketBusinessFinanceEmerging marketsGeographyPolitical science

Résumé

récupéré en direct d'OpenAlex

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,128
Score d'incertitude au seuil0,728

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,002
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,046
Tête enseignante GPT0,375
Écart entre enseignants0,329 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle