We propose a Support Vector Machine (SVM) based structural model in order to forecast the collapse of banking …. We train an SVM model to classify banks as solvent and insolvent. The resulting model exhibits significant ability in …

We propose a support vector machine (SVM)-based structural model to forecast the collapse of banking institutions in … procedure. We train an SVM model to classify banks as solvent and insolvent. The resulting model exhibits significant ability in …

We propose an Support Vector Machine (SVM) based structural model in order to forecast the collapse of banking …. We train an SVM model to classify banks as solvent and insolvent. The resulting model exhibits significant ability in …

changes. Specifically, we feed an overcomplete variable set to a Support Vector Machines (SVM) model and refine it through a …

Support Vector Machines (SVM) models, given that the latter originates from the area of machine learning and is gaining … popularity among economists and CRAs. Our results show that the most accurate, in terms of in-sample forecasting, is an SVM model … coupled with the nonlinear RBF kernel that identifies correctly 91.07% of the banks' ratings, using only 8 explanatory …