The impact of market sentiment and trading volume on short-term stock volatility—empirical evidence from China’s A-share market

Utilizing monthly data from China’s A-share market from 2007 to 2023, this study employs the number of newly opened investor accounts to measure market sentiment and the number of trades to represent trading volume. Through VAR modelling, Granger causality tests, and impulse response analysis, this study investigate their impact mechanisms on the volatility of the Shanghai Composite Index. Key findings reveal that: (1) Market sentiment acts as a core driver of short-term volatility; (2) Trading volume exhibits a bidirectional short-term effect, establishing a positive feedback loop with volatility; (3) Shanghai Index volatility displays significant autocorrelation, with historical volatility demonstrating strong persistent predictive power for current fluctuations. Based on these behavioural insights, this study proposes establishing a dynamic sentiment monitoring and tiered early-warning system, enhancing high-frequency trading regulation frameworks, optimizing market liquidity supply structures, and strengthening policy coordination with cross-border regulatory cooperation. This integrated approach aims to furnish micro-behavioural evidence and actionable regulatory insights for effective risk prevention in China’s A-share market.