Using a large panel of US banks over the period 2008-2013, this paper proposes an early warning framework to identify bank heading to bankruptcy. We conduct a comparative analysis based on both Canonical Discriminant Analysis and Logit models to examine and to determine the most accurate one....

This paper examines the usefulness of logit regression in forecasting the consumer bankruptcy of households using an imbalanced dataset. The research on consumer bankruptcy prediction is of paramount importance as it aims to build statistical models that can identify consumers in a difficult...

We propose a new approach based on a generalization of the classic logit model to improve prediction accuracy in US bank failures. We introduce mixed-data sampling (Midas) aggregation to construct financial predictors in a logistic regression. This allows us to relax the limitation of...