Forecastability as an Information-Theoretic Limit on Prediction

ArXi:2603.27074v1 Announce Type: cross Forecasting is usually framed as a problem of model choice. This paper starts earlier, asking how much predictive information is available at each horizon. Under logarithmic loss, the answer is exact: the mutual information between the future observation and the declared information set equals the maximum achievable reduction in expected loss. This paper develops the consequences of that identity.