This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of...

This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of...

In many economic applications it is desirable to make future predictions about the financial status of a company. The focus of predictions is mainly if a company will default or not. A support vector machine (SVM) is one learning method which uses historical data to establish a classification...

We present a dynamic structural model of subprime adjustable-rate mortgage (ARM) borrowers making payment decisions taking into account possible consequences of different degrees of delinquency from their lenders. We empirically implement the model using unique data sets that contain information...

We present a dynamic structural model of subprime adjustable-rate mortgage (ARM) borrowers making payment decisions taking into account possible consequences of different degrees of delinquency from their lenders. We empirically implement the model using unique data sets that contain information...