A News Sentiment Index and Its Asymmetric Effect on Market Liquidity for the Chinese Stock Market

This paper measured investor sentiment using the News Sentiment Index (NSI) and examined its asymmetric impact on market liquidity, particularly focusing on how these effects changed during the COVID-19 pandemic in the Chinese stock market. Constructed from comprehensive news data sourced from the Global Database on Events, Location, and Tone (GDELT), the NSI encapsulates the sentiment dynamics relevant to the Chinese stock market. We applied the unit root and cointegration tests with time-varying volatilities, which showed that sentiment follows a random walk with time-varying volatility and is cointegrated (co-moved) with liquidity. While the relationship between sentiment and market liquidity has been extensively studied, the asymmetric effects of sentiment on liquidity have remained largely unexplored. Our study fills this gap by applying the vector error correction model (VECM), which revealed that liquidity’s response to sentiment is more pronounced under pessimistic conditions (7.04%) compared to optimistic ones (6.13%). However, this asymmetry appears to have been moderated during the COVID-19 pandemic, indicating a shift in sentiment’s influence on liquidity amid heightened uncertainty. By capturing the dynamics of investor sentiment and its asymmetric effects under different market conditions, this study deepens our understanding of investor sentiment and its relationship with liquidity.