On the accuracy of alternative approaches for calibrating bank stress test models

Abstract

Multi-year forecasts of bank performance under stressful economic conditions determine large institution regulatory capital requirements and yet the accuracy of these forecasts is undocumented. I compare the accuracies of alternative stress test model forecasts using the financial crisis as the stress scenario. Models include specifications that mimic the Federal Reserve CLASS model and alternatives that use Lasso, the AIC and an abridged set of explanatory variables. A simple single-equation Lasso model has, by far, the best forecast accuracy. Large differences in model forecast accuracy are undetectable from estimation sample statistics. These findings highlight the need for new methods for validating bank stress test models.