Monetary Policy and Systemic Risk in a Financial Network System Based on Multi-Agent Modeling

Abstract

Global inflation is high, and economic recovery is slow, leading to frequent monetary policy adjustments aimed at maintaining financial stability and accelerating recovery. To study the effects of monetary policies on the systemic risk of financial network systems and their mechanisms of action, this paper constructs a complex financial network system model. The model depicts the behavior of households, firms, banks, and the government (central bank) under the influence of monetary policies and their interactions. The study finds that systemic risk mainly arises from the uncertainty of business operations under market competition regulation. The interest rate policy affects the operation of the financial system by adjusting the operating costs and profits of banks and firms, while the required reserves policy primarily regulates the credit activities of banks and firms. Lower interest rates and higher reserve requirement ratios can mitigate systemic risk, but high reserve requirement ratios can make markets less active. Compared to the two policies, interest rate adjustments impact systemic risk more significantly and have a longer policy action cycle, while reserve requirement ratio adjustments create a strong short-term stimulus to the financial system. Considering the current market conditions, the central bank should adopt a more appropriate monetary policy.

Keywords

• agent-based modeling
• systemic risk
• financial network
• multi-agent
• monetary policy