The foreign market and the national herding behavior during normal and extreme periods: what is the trigger and anti-herding market?
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".