Herding behaviour in the Chinese stock market
Huang, Z., van Dellen, S., Vasileva, K. and Li, X. 2025. Herding behaviour in the Chinese stock market . 18th International Behavioural Finance Conference. London 04 - 06 Jun 2025
Huang, Z., van Dellen, S., Vasileva, K. and Li, X. 2025. Herding behaviour in the Chinese stock market . 18th International Behavioural Finance Conference. London 04 - 06 Jun 2025
| Title | Herding behaviour in the Chinese stock market |
|---|---|
| Authors | Huang, Z., van Dellen, S., Vasileva, K. and Li, X. |
| Type | Conference paper |
| Abstract | This paper employs the non-linear regression model developed by Yao et al. (2014), a generalised form of the Chang et al. (2000) framework suited specifically to examining investor herding in the Chinese stock market at both firm-level and sector level. We apply this model to the period from 2011 to 2024. The method applies Christie and Huang’s (1995) cross-sectional standard deviation (CSSD) measure, which detects herding by analysing return dispersion. Yao et al. (2014) enhance the original model of Chang et al. (2000) by including an additional explanatory term that significantly reduces multicollinearity among the independent variables, alongside the one-day lag of the CSSD measure to further strengthen the statistical power of the regression. This study extends that literature by examining herding in the aggregate market and across all industries in the Chinese stock market. Documenting a decline in herding would contribute to understanding market maturation, since improved information environments and greater institutional participation may reduce the scope for behavioural trading over time. The results from the CCK model and the extended regressions consistently reveal significant herding in both A-share and B-share markets, although its magnitude and persistence vary. The B-share markets show more pronounced herding, suggesting higher information asymmetry and more reactive investor behaviour. The A-share markets, on the other hand, show declining herding intensity in more recent years, particularly since 2017, indicating a gradual transition towards more rational investment behaviour. We also found that the presence and impact of herding differed across industries and firm sizes within the A-share market. For instance, sectors like Pharmaceuticals, Transportation, and Automobiles displayed stronger herding effects than others. This aligns with the understanding that investors reacting to industry-specific news or those trading in popular sectors tend to trade similarly when such information emerges. Additionally, smaller firms and high-growth stocks experienced more significant herding than larger or value-oriented stocks, possibly due to higher speculative interest and uninformed trading activities. These detailed results enrich the existing research by demonstrating that herding is not uniform; its level of magnitude varies according to different market segments and industries, and over time as market conditions evolve. |
| Year | 2025 |
| Conference | 18th International Behavioural Finance Conference |