Discriminant Methods for Bankruptcy Prediction - Theory and Applications

Partial Least Square Discriminant Analysis for bankruptcy prediction

Comparative analysis of data mining methods for bankruptcy prediction

Article history: Received 11 March 2011 Received in revised form 3 August 2011 Accepted 4 October 2011 Available online 13 October 2011

Composite Classifiers for Bankruptcy Prediction

Business failures can cause financial damages to investors, creditors, or even society. For this reason bankruptcy prediction is one of the most challenging tasks in the field of financial decisionmaking. Business failure prediction has been an active research area since the 60s. The work of Beaver (1966) who performed univariate analysis of financial ratios and the work of Altman (1968) who em...

Ensemble KNNs for Bankruptcy Prediction

The business failure has been widely researched, trying to identify the various determinants that can affect the existence of firms. However, the variety of models as well as the variety of the theoretical frameworks, illustrates the lack of consensus on how to understand the phenomenon and the difficulties in formulating a general model interpretation. One hotspot nowadays is the prediction of...

Bankruptcy prediction models: probabilistic neural networks versus discriminant analysis and backpropagation neural networks1

The purpose of this paper is present probabilistic neural networks (PNN) as an alternative quantitative technique to both linear discriminant analysis (LDA) and backpropagated neural networks (BPNN) for forecasting corporate solvency. Although traditionally this task has been approached with rather simpler linear techniques such as LDA, there is increasing empirical evidence of the superiority ...