Conventional asset pricing theory suggests that stock market moves by rational expectations and homogeneous expectations and rely on the use of quantified information for decision-making. Hence, irrational expectation and components of investors’ behavior are overlooked. The present study tries to investigate herding behavior in six major stock markets across the world using the cross-sectional absolute deviation (CSAD) methodology. The study aims to foster a deeper understanding of irrationality in investment decisions using the established robust framework for analyzing herding behavior in key global markets.
The CSAD developed by Christie and Huang (1995) and Chang et al. (2000) is used to assess market consensus with regression analysis exploring its relationship to market returns. Dummy variables are incorporated to examine herding during extreme market conditions. The analysis encompasses six stock markets across five countries – USA, Europe, China, Japan and India – utilizing daily index data from April 1, 2015, to March 31, 2024. The data capturing the COVID-19 crisis allows for a novel investigation of herding behavior specifically during the pandemic, contributing to the financial literature.
Results show a statistically significant positive correlation between CSAD and extreme market condition dummy variables, but no evidence of herding. Similar results were observed during the COVID-19 period. Another relationship between herding behavior and market returns, for each sampled stock market individually over the entire study period, showed significant negative associations indicating herding behavior in the USA (NASDAQ) and China (Shanghai), while Japan (JPXNIKKEI400) and India’s NIFTY did not show herding. During COVID-19, a significant negative correlation in Euronext suggests herding in Europe, while inconclusive results were found in the USA and India. Overall, the findings illustrate inconsistencies in herding behavior across different markets and conditions, especially during the COVID-19 crisis.
The outcomes of this study have important implications for various stakeholders; investors can tailor their strategy for specific markets as herding varies across different stock exchanges, fund managers and investors could emphasize the need for crisis management in events like COVID-19, especially in markets like Euronext, market regulators in countries like USA and China may need to implement measures to mitigate the potential negative effects of herding behavior on market stability and efficiency, and finally, policymakers can work on information transparency to reduce information asymmetry that leads to herding behavior among less informed investors.
The research has studied the presence of herding in major stock markets to establish the argument of irrationality in investment decision-making. This paper is one of the preliminary attempts to develop a robust framework to examine herding in the top six stock markets, which represent nearly 80% of the global market capitalization, and is an important milestone in behavioral finance literature.
