This paper investigates the phenomenon of hidden negative capital (HNC) associated with bank failures and introduces a product mismatch hypothesis to explain the formation of HNC. Given that troubled banks tend to hide negative capital in financial statements from regulators to keep their...

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...

Economic time series are available at different frequencies due to their origin and data collection techniques. A mixed data sampling (MIDAS) regression is mainly a forecasting tool designed to harness mixed-frequency data. This dissertation proposes a computationally efficient estimation...

This paper studies the relationship between the asset-liability mismatch and the losses on bank failures over the last 20 years in the U.S. banking system. We first develop a simple theoretical model in which banks can choose to misreport their losses to the regulator if they draw sufficiently...