Central bankers’ political discourse as a driver of clean energy markets

We investigate how political language in central bank governors’ speeches affects clean energy market dynamics in both the Chinese and U.S. markets. Using advanced textual analysis (poldis) and a novel lexical matching algorithm, we measure key dimensions of policy discourse—authenticity, urgency, timing, intensity, and commitment. These speech-based indicators are integrated with traditional market and media variables through Extreme Bounds Analysis (EBA) and SHAP value interpretability. We find that speeches with stronger policy commitment and intensity are positively correlated with clean energy stock performance. Conversely, high urgency and shorter timing intervals often predict weaker market outcomes, potentially signaling perceived risks or instability to investors. Our results highlight the significant but nuanced role of central bank communication in shaping investor sentiment within sustainable finance markets. This research therefore contributes to financial economics, behavioral finance, and policy communication studies by quantifying how political discourse can drive asset pricing in emerging sectors like clean energy.