The foreign market and the national herding behavior during normal and extreme periods: what is the trigger and anti-herding market?
Notice bibliographique
Résumé
Purpose This paper aims to examine not only the herding behavior in developed stock markets but also the role of the foreign market returns in explaining national herding behavior during normal and extreme market movements by extending the cross-sectional absolute deviations (CSADs) model for the period that spans from January 5, 2000, to April 22, 2022. Design/methodology/approach Extending the CSADs model. Findings The authors found that herd behavior in the Canadian market is more pronounced than in the US and French markets, but it is absent in the UK market. Moreover, simultaneity and continuity of herding behavior are detected in these markets. In normal periods, the French market is a UK herding trigger, but the US, UK and Canadian markets are anti-herding. Mainly, downturns in the US market lead Canadian investors to be more pessimistic about their future cash flows, creating a feeling of fear and uncertainty among investors and leading them to flock into herding behavior. Conversely, extreme upturn movements of the UK market explain Canadian herding behavior. These results represent a guide for investors to construct optimal portfolios, an alert for global risk managers and a way for national policymakers to improve regulations to challenge herding risk. Research limitations/implications Investors in global financial markets, global risk managers and local policymakers should put too much emphasis on herding risk in developed-like emerging markets in the era of digitalization and global interconnectedness. This study represents an addition to herding behavior literature. It offers a field for discussion of different explanations suggested by previous studies at the same time. This study also shows that the US market has varying degrees of influence on others. Investors in all markets must pay more attention to US information. Practical implications This helps investors construct optimal portfolios and diversify risk by investing in the UK market. For global risk managers, this clarifies the source of risk and hence helps them to minimize global risk. For Canadian policymakers, this study helps them to improve regulations to challenge herding behavior. This leads UK investors to pay more attention to French market information. Policymakers of the world must take into account US returns in the formulation of new national regulations. The results represent an alert for the Canadian market. Originality/value First, compared to the above-mentioned studies, this work is the first attempt to explain herding behavior across national borders. Second, examining the impact of the foreign market on the national herding behavior for major developed markets takes us away from the usual assumption that herd behavior is particularly significant in emerging markets. Hence, this can offer theoretical and practical implications. Third, this study distinguishes between the trigger and anti-herding markets. This can be a response to several questions. Hence, this offers several practical implications for investors, policymakers, risk managers and future researchers. Fourth, this issue is of great interest to global investors who allocate their assets across developed financial markets because increasing market linkages may reduce the benefits of investment diversification. Fifth, analyzing herding behavior across national borders is important for understanding the mechanisms of financial market operations and developing appropriate policies. Finally, examining whether investors herd around other markets’ consensus can answer questions about the sources of herding behavior and explain its spread to different markets and systemic risk transmission across markets.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».