Bankruptcy prediction for Russian companies: Application of combined classifiers

作者：

Highlights：

• We use a dataset of more than 3,500 Russian manufacturing companies.

• We use different combined classifiers (LR, ANN, MDA, CRT) for bankruptcy prediction.

• Classical models of bankruptcy demonstrate low accuracy of bankruptcy prediction.

• Classifiers combined by AdaBoost approach show highest classification accuracy.

• Only one indicator stipulated by Russian legislation is effective for prediction.

摘要

•We use a dataset of more than 3,500 Russian manufacturing companies.•We use different combined classifiers (LR, ANN, MDA, CRT) for bankruptcy prediction.•Classical models of bankruptcy demonstrate low accuracy of bankruptcy prediction.•Classifiers combined by AdaBoost approach show highest classification accuracy.•Only one indicator stipulated by Russian legislation is effective for prediction.

论文关键词：Bankruptcy prediction,Logit-regression,Artificial neural networks,Classification and regression trees,AdaBoost

论文评审过程：Available online 17 July 2013.

论文官网地址：https://doi.org/10.1016/j.eswa.2013.07.032