Central bank signals, behavioral biases, and information flow

How central bank communications reshape market uncertainty is a fundamental question for monetary policy, yet existing tools, such as volatility proxies, event studies, and structural models, do not quantify directional information flow or account for behavioral distortions. This paper develops an information-theoretic framework to measure aggregate uncertainty using market entropy and to quantify directional information flows among assets using simulated and market data around Federal Reserve announcements. Results show that behavioral biases amplify short-term reactions to central bank signals, but these distortions fade as markets converge toward efficiency. Anticipated announcements reduce uncertainty, while unanticipated ones increase it, and such communications alter cross-asset dependence, weakening safe haven equity comovement while strengthening within-sector dependence. These findings reveal an information-transmission channel through which monetary policy signals reshape market dynamics beyond standard rational expectations benchmarks.