Tripti Singh

Type of the article: Research Article

Herding behavior often emerges in uncertain market conditions, when investors, confronted with limited or ambiguous information, tend to imitate their peers’ actions instead of relying on their own analytical assessments. This follow-on herd mentality phenomenon engenders analogous trading behavior among market participants, potentially undermining market efficiency. During times of increased volatility, such behavioral patterns become more noticeable, which has a substantial impact on asset values and skews the efficiency of financial markets. This study explores herding in the UAE stock markets during the COVID-19 outbreak, focusing on the Dubai Financial Market (DFM) and the Abu Dhabi Securities Exchange (ADX). Using daily data from January 1, 2019 through December 31, 2021, the Cross-Sectional Absolute Deviation (CSAD) model is implemented in static and dynamic forms to explore nonlinear and evolving aspects of investor behavior. The analysis indicates that during the initial months of the pandemic, clear evidence of herding emerged in the Dubai Financial Market (γ₃ = –3.087; p < 0.05), whereas the Abu Dhabi Exchange did not display statistically meaningful signs of such behavior. This contrast highlights how herding behaviors are not uniform across markets; they are shaped by factors such as institutional structures, liquidity levels, and the overall composition of traders. The results offer valuable implications for regulators, policymakers, and large investors, providing insights into how behavioral patterns can affect market resilience in emerging markets. Moreover, the study’s findings highlight the importance of timely disclosure and targeted investor awareness initiatives in reducing irrational reactions during periods of distress or crisis.

Acknowledgment
We are grateful to our co-authors for their invaluable contributions and collaboration in this research. A special thanks to the young independent researchers who are also the co-authors for their dedication and efforts in data collection and analysis, which have significantly enriched this study. We also appreciate the support provided by our institutions and the insightful feedback from our peers and reviewers.