In this paper we present the neuro-fuzzy technology for the prediction of economic crisis of USA economy. Our findings support ANFIS models to traditional discrete choice models of Probit and Logit, indicating that the last models are not very useful for forecasting purposes. We have developed a...

The purpose of this paper is to present a neuro-fuzzy approach of financial distress pre-warning model appropriate for risk supervisors, investors and policy makers. We examine a sample of the financial institutions and electronic companies of Taiwan Security Exchange (TSE) from 2002 through...

In this paper we present the neuro-fuzzy technology for the prediction of economic crisis of USA economy. Our findings support ANFIS models to traditional discrete choice models of Probit and Logit, indicating that the last models are not very useful for forecasting purposes. We have developed a...

Predictive modeling focuses on iteratively trying various combinations and transformations of a set of variables to generate a decision rule that predicts outcomes for new observations. Although accounting researchers have demonstrated interest in predictive modeling, we identify a lack of...

Following the financial crisis of 2008, the regulators established a stress testing framework known as comprehensive capital analysis and review (CCAR). The regulatory stress scenarios are macroeconomic and do not define stress values for all the relevant risk factors. In particular, only three...

This study presents an extension of the Gaussian process regression model for multiple-input multiple-output forecasting. This approach allows modelling the cross-dependencies between a given set of input variables and generating a vectorial prediction. Making use of the existing correlations in...