Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This study developed an observation-driven endogenous regime-switching model to observe the relationship between trading volume and return volatility based on a regime-switching perspective. We proposed a maximum likelihood estimation method to estimate the unknown parameters and introduced two likelihood ratio statistics to examine the effects of observable variables on regime shifts. We conducted extensive simulation experiments, confirming that the method performed well regarding finite samples. We applied the proposed model to examine the volume–volatility nexus in China’s stock market. Empirical findings indicate that (1) the relationship between trading volume and volatility is regime specific, (2) the Sequential Information Arrival Hypothesis (SIAH) was more significant in the low-volatility state, and (3) a significant leverage effect can be observed in the Chinese stock market.