Herd Behavior Asymmetry During the Tehran Stock Exchange Bubble

Badri, Ahmadi; Osoolian, Mohammad; Karimi, Mahdi

doi:10.48308/jfmp.2024.105023

Herd Behavior Asymmetry During the Tehran Stock Exchange Bubble

Document Type : Original Article

Authors

¹ Associate Prof, Department of Financial Management and Insurance, University of Shahid Beheshti, Tehran, Iran

² Assistant Prof, Department of Financial Management and Insurance, University of Shahid Beheshti, Tehran, Iran.

³ MSc. in Financial Management, University of Shahid Beheshti, Tehran, Iran.

10.48308/jfmp.2024.105023

Abstract

Objective: Herd behavior asymmetry refers to the tendency for herd behavior to manifest with varying frequency depending on whether market returns are positive or negative. This phenomenon is particularly influenced by return jumps, which often arise from impactful information that leads less experienced traders to mimic the trading patterns of others. Considering the significant role that return jumps play in explaining herd behavior and the necessity of understanding this asymmetry within the context of the Tehran Stock Exchange (TSE) bubble, the objective of this research is to thoroughly investigate herd behavior, its asymmetrical nature, and the impact of return jumps on this behavior across different market periods, namely before, during, and after the occurrence of the TSE bubble. This research is designed to offer a comprehensive examination of how herd behavior fluctuates under various market conditions and the specific influence of return jumps, thereby contributing valuable insights into investor behavior, particularly during times of market volatility.
Method: The research covers an extensive dataset of companies listed on the TSE, spanning from February 24, 2015 (the launch date of the equal-weight index), through March 20, 2023. To assess herd behavior on a daily basis, the study utilizes the Cross-Sectional Absolute Deviation (CSAD) method, which is well-suited for capturing the degree to which individual stock returns deviate from the overall index return. Furthermore, to measure and ensure the robustness of return jumps, intraday data at five-minute intervals of the equal-weight index was employed. Realized variance and bipower variance methods were used to accurately quantify return jumps. The analysis compares the frequency of herd behavior under both positive and negative market return conditions, with and without the incorporation of return jumps, thereby rigorously testing the asymmetry of herd behavior. By integrating return jumps into the model, the study aims to determine the extent to which sudden price movements influence herd behavior, particularly in periods marked by significant market fluctuations.
Findings: The findings reveal that, without distinguishing between positive and negative returns, there is no observable herd behavior across the three studied periods on the TSE. However, when examining negative market return conditions (without accounting for return jumps), herd behavior becomes evident in each of the analyzed periods. Upon incorporating return jumps into the analysis, the model's explanatory power is significantly enhanced, as indicated by the notable increase in the adjusted R-squared value. This underscores the importance of return jumps in explaining herd behavior.
Conclusion: The study confirms the presence of herd behavior in negative return markets, while no such behavior is detected in positive return markets, thereby demonstrating an asymmetric pattern in herd behavior on the TSE. This asymmetry can be attributed to the heightened inclination of investors to mimic others during bearish market conditions, driven by stress and increased perceived risks. Conversely, in bullish markets, investors experience lower levels of perceived risk and are less prone to follow the crowd. The results further validate the explanatory power of return jumps, emphasizing their role in influencing herd behavior and highlighting the impact of abrupt price movements on market dynamics.

Keywords

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