Prediction of corporate financial health by Artificial Neural Network

Neural networks are perhaps the most significant forecasting tool to be applied to the financial markets in recent years and are gaining ascendancy because of reports of their success. This paper checks out the classification capability of Radial Basis Function Networks (RBF), Multi-Layer Perceptrons (MLPs) with and without Principal Component Analysis (PCA), Self-Organizing Feature Maps (SOFM) with MLP and Support Vector Machine (SVM) neural architecture for prediction of the financial health of firms.