We analyze the information embedded in forecasts by examining the moments of subjective probability distributions. Specifically, we propose that a forecast conveys a strong upward signal when the median exceeds a target, such as a central bank's 2% inflation threshold, coupled with positive skewness. Conversely, a median below the target with negative skewness signals strong downward expectations. In cases where the median and skewness diverge, the signal weakens, indicating mixed expectations. To formalize these insights, we develop a Signal Strength Indicator (SSI) that quantifies the consistency and directional alignment of forecast signals, assessing its predictive power within a Growth-at-Risk framework. Importantly, the SSI can be estimated without relying on parametric assumptions. Our findings indicate that the SSI offers valuable insights, suggesting it could serve as a practical tool for central banks to monitor expectations in real time.