Monetary Policy, Stock Price and Asymmetry in China: A Comparative Research Based on Econometrics and Artificial Intelligence Methods

Stock price fluctuations are crucial for the healthy and stable development of the stock market. However, the econometrics methods, which have traditionally demonstrated strong performance in addressing nearly all economic issues, exhibit limitations specifically in stock-related analyses-a gap that has only begun to be addressed with the emergence of artificial intelligence methods as cutting-edge applications in this field. Building on this foundation, this study integrates theoretical economic frameworks with empirical methodologies across disciplines to undertake a comparative investigation into the impact of monetary policy on stock prices and its associated asymmetric effects in China. The findings reveal that econometric models (VAR and MS-VAR) yield only partially satisfactory results in analyzing this issue, whereas the artificial intelligence-driven LSTM model demonstrates good explanatory power. Monetary policy exerts asymmetric effects on stock prices: expansionary policies during bear markets show greater efficacy than contractionary measures during bull markets. Additionally, the transmission effect of rising prices on stock price is stronger, and the drag of economic recession on stock price is more pronounced. This study provides insights for the monetary policy interventions and offers practical guidance for the application of interdisciplinary methodological approaches in addressing complex economic issues.