Spotting the Danger Zone: Forecasting Financial Crises With Classification Tree Ensembles and Many Predictors
识别危险区：用分类树集成与众多预测变量预测金融危机
Summary This paper introduces classification tree ensembles (CTEs) to the banking crisis forecasting literature. I show that CTEs substantially improve out‐of‐sample forecasting performance over best‐practice early‐warning systems. CTEs enable policymakers to correctly forecast 80% of crises with a 20% probability of incorrectly forecasting a crisis. These findings are based on a long‐run sample (1870–2011), and two broad post‐1970 samples which together cover almost all…