Abstract: A new theoretical model of optimal innovation decision for enterprises is constructed from the perspective of enterprise value fluctuation theory, based on a stochastic dynamic programming model. Data from A-share listed companies in Shanghai and Shenzhen stock markets are collected to conduct an empirical testing with fixed effect model. The theoretical and empirical results show that: easing monetary policy promotes enterprise innovation; high regional economic policy uncertainty inhibits enterprise innovation, and loose monetary policy can mitigate this effect. Heterogeneity analysis reveals that state-owned enterprises are more stable in innovation input under uncertain environment, and firms with a senior management team rich in R&D and technical expertise better adapt to environmental changes and adjust their innovation behaviors. To strengthen enterprise innovation motivation, financial measures such as lowering market interest rates and expanding money supply should be flexibly combined and adjusted to optimize the corporate financing environment. Local governments should closely align with the direction of central monetary policy when formulating regional economic policies, thus building a stable, transparent, and predictable innovation support system. Enterprises of different ownership types should develop differentiated innovation strategies based on their unique characteristics to fully leverage their advantages and overcome external challenges. When forming senior management teams, enterprises should prioritize candidates with strong technical backgrounds so as to enhance their acuity and responsiveness to market changes and risks.

Key words: monetary policy, regional economic policy uncertainty, enterprise innovation, stochastic dynamic programming