Neural Networks in Bankruptcy Prediction - A Comparative Study on the Basis of the First Hungarian Bankruptcy Model

A Comparative Study of Neural Networks in Bankruptcy Prediction

Application of Support Vector Machines on the Basis of the First Hungarian Bankruptcy Model

In our study we rely on a data mining procedure known as support vector machine (SVM) on the database of the first Hungarian bankruptcy model. The models constructed are then contrasted with the results of earlier bankruptcy models with the use of classification accuracy and the area under the ROC curve. In using the SVM technique, in addition to conventional kernel functions, we also examine t...

a study on insurer solvency by panel data model: the case of iranian insurance market

the aim of this thesis is an approach for assessing insurer’s solvency for iranian insurance companies. we use of economic data with both time series and cross-sectional variation, thus by using the panel data model will survey the insurer solvency.

Applying Backpropagation Neural Networks to Bankruptcy Prediction

Bankruptcy prediction is an important classification problem for a business, and has become a major concern of managers. In this paper, two well-known backpropagation neural network models serving as data mining tools for classification problems are employed to perform bankruptcy forecasting: one is the backpropagation multi-layer perceptron, and the other is the radial basis function network. ...

Ensemble with neural networks for bankruptcy prediction

0957-4174/$ see front matter 2009 Elsevier Ltd. A doi:10.1016/j.eswa.2009.10.012 * Corresponding author. Tel.: +82 51 32