Sectoral Herding During Global Rare Events: Evidence from the Indonesian Capital Market

Abstract

Research Aims: This research aims to examine the effects of increased levels of herding on abnormal returns during rare events.Design/Methodology/Approach: Time series regression including all stocks across 9 sectors in the Indonesia Stock Exchange from 1997 to 2020, totaling 5,615 observations is used. The primary model is predicated on three factors derived from Fama-French and prospect theory to incorporate herding as a primary risk factor in assessing the impact of on abnormal returns during rare events.Research Results: The results show that various events produce impacts on herding behavior across different sectors. During bearish market conditions, this behavior manifests significant negative effect leading to greater abnormal returns. Conversely, positive and significant anti-herding behavior is observed in bullish market conditions. Rare events do not necessarily induce herding behavior but may lead to anti-herding behavior.Theoretical Contribution/Originality: In this research, the variables are developed from the Efficient Market Hypothesis, Capital Asset Pricing Model, prospect theory, and market integration theory. The estimation model is grounded in prospect theory and the contribution addresses the research gaps.Practitioners/Policy Implications: The provision of insights to stakeholders in the capital market regarding the impact of rare events on financial behaviors influences investors' decision-making processes in stock investments.Research Limitations/Implications: The measurement of herding refers to Chang et al. (2000) due to the availability of aggregate data from the Indonesian Stock Exchange. Comprehensive micro-level data is not unavailable and the accessibility of complete micro-level data can be conducted. The presence of these data in the capital markets of other countries should be investigated.