In this paper, we present a forecasting model of bank failures based on machine-learning. The proposed methodology defines a linear decision boundary separating the solvent from the failed banks. This setup generates a novel alternative stress testing tool. Our sample of 1443 U.S. banks includes...

Purpose -- This study presents an empirical model designed to forecast bank credit ratings using only quantitative and publicly available information from their financial statements. For this reason we use the long term ratings provided by Fitch in 2012. Our sample consists of 92 U.S. banks and...

Purpose - This study presents an empirical model designed to forecast bank credit ratings using only quantitative and publicly available information from their financial statements. For this reason we use the long term ratings provided by Fitch in 2012. Our sample consists of 92 U.S. banks and...

Purpose-This study presents an empirical model designed to forecast bank credit ratings. For this reason we use the long term ratings provided by Fitch in 2012. Our sample consists of 92 U.S. banks and publicly available information from their financial statements from 2008 to 2011. Methodology...

Purpose – This study aims to present an empirical model designed to forecast bank credit ratings using only quantitative and publicly available information from their financial statements. For this reason, the authors use the long-term ratings provided by Fitch in 2012. The sample consists of...