This paper proposes a framework for deriving early-warning models with optimal out-of-sample forecasting properties and applies it to predicting distress in European banks. The main contributions of the paper are threefold. First, the paper introduces a conceptual framework to guide the process...

Early-warning models most commonly optimize signaling thresholds on crisis probabilities. The expost threshold optimization is based upon a loss function accounting for preferences between forecast errors, but comes with two crucial drawbacks: unstable thresholds in recursive estimations and an...

This paper introduces a new loss function and Usefulness measure for evaluating early warning systems (EWSs) that incorporate policymakers' preferences between issuing false alarms and missing crises, as well as individual observations. The novelty derives from three enhancements: i) accounting...