Monetary Policy, Investor Sentiment, and Multiscale Jump Behavior of the Chinese Stock Market

We examine the time‐varying jump behavior of the Chinese stock market across various time scales. A novel hybrid model (VMD‐ARJI‐X) is proposed that integrates variational mode decomposition (VMD) with the autoregressive jump intensity model (ARJI), which also incorporates monetary policy and investor sentiment as explicit variables. Results indicate that the interactions between monetary policy and investor sentiment significantly amplify jump risk at the short‐ and medium‐term scales, while the effect is less pronounced over long‐term horizons. The predictive capability of the VMD‐ARJI‐X, which embeds interest rate and investor sentiment into the jump intensity component, outperforms other benchmark models. Our findings provide policymakers with actionable insights for identifying extreme risks triggered by both policy and sentiment and obtaining forward‐looking warnings. The multiscale jump signals offer a practical tool to design dynamic risk management strategies for investors.