A Transmission of Beta Herding during Subprime Crisis in Taiwan’s Market: DCC-MIDAS Approach

Abstract

The aim of this study is to investigate the herding of beta transmission between return and volatility. We have used the dynamic conditional correlation model with the mixed-data sampling (DCC-MIDAS) model for the analysis. The evidence demonstrates that herding is a key transmitter in Taiwan’s stock market. The significant estimation of DCC-MIDAS explains that the herding phenomenon is highly dynamic and time-varying in herding behavior. By means of time-varying beta of herding based on our rolling forecasting method and robustness check of the Markov-switching regression approach using four types of portfolios, the evidence indicates that there are conditional correlations between betas and herding. In addition, it also reveals that herding forms in Taiwan’s markets during the subprime crisis period.

Examining Herding Behaviour and Its Impact on Stock Market Volatility: Insights from Asian Economies

“…This contradicts the findings in China and Singapore, where lower CSAD values (indicating increased herding) lead to higher volatility. This aligns with Chen et al's (2021) research, which asserts that herding is a key transmitter in the Taiwan stock market and correlates with betas, causing volatility. Tan et al (2008) also state that foreign investors engage in herding, following positive feedback and causing an increase in stock prices in Taiwan.…”

“…Chen (2016) asserts that herding is evident in Taiwan due to a lack of experience and access to various sources of information. Shinn-Juh Lin (2017) and Y.-C. Chen et al (2021) also state that herding in Taiwan varies over time and is present during the post-2008 period or after the 2008 financial crisis. There is also a conditional correlation between beta and herding.…”