Bankruptcy prediction in Norway: a comparison study

Bankruptcy Prediction in Norway: A Comparison Study

In this paper we develop statistical models for bankruptcy prediction of Norwegian firms in the limited liability sector using annual balance sheet information. We fit generalized linear-, generalized linear mixedand generalized additive models in a discrete hazard setting. It is demonstrated that careful examination of the functional relationship between the explanatory variables and the proba...

A Comparative Study of Neural Networks in Bankruptcy Prediction

Bankruptcy Prediction by Supervised Machine Learning Techniques : A Comparative Study

It is very important for financial institutions which are capable of accurately predicting business failure. In literature, numbers of bankruptcy prediction models have been developed based on statistical and machine learning techniques. In particular, many machine learning techniques, such as neural networks, decision trees, etc. have shown better prediction performances than statistical ones....

A comparative study of classifier ensembles for bankruptcy prediction

The aim of bankruptcy prediction in the areas of data mining and machine learning is to develop an effective model which can provide the higher prediction accuracy. In the prior literature, various classification techniques have been developed and studied, in/with which classifier ensembles by combining multiple classifiers approach have shown their outperformance over many single classifiers. ...

Comparison of Bankruptcy Prediction Models with Public Records and Firmographics

Many business operations and strategies rely on bankruptcy prediction. In this paper, we aim to study the impacts of public records and firmographics and predict the bankruptcy in a 12month-ahead period with using different classification models and adding values to traditionally used financial ratios. Univariate analysis shows the statistical association and significance of public records and ...