Comparison of country risk models: hybrid neural networks, logit models, discriminant analysis and cluster techniques

Abstract This paper looks at the ability of a relatively new technique, hybrid ANN's, to predict country risk rating. These models are compared with traditional statistical techniques and conventional ANN models. The performance of hierarchical cluster analysis and another type of ANN, the self-organizing map were also investigated, as possible methods for making country risk analysis with visual effects. The results indicate that hybrid neural networks outperform all other models. This suggests that for researchers, policymakers and others interested in early warning systems, hybrid network may be a useful tool for country risk analysis.