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 study investigates how well weekly Google search volumes track and predict bank failures in the United States between 2007 and 2012, contributing to the expanding literature that exploits internet data for the prediction of events. Different duration models with time-varying covariates are...

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...