An Application of Support Vector Machine to Compan

Authors: XiaoFeng Hui Jie Sun

Publish Date: 2006/4/3

Volume: , Issue: , Pages: 274-282

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Abstract

Because of the importance of companies’ financial distress prediction this paper applies support vector machine SVM to the earlywarning of financial distress Taking listed companies’ threeyear data before special treatment ST as sample data adopting crossvalidation and gridsearch technique to find SVM model’s good parameters an empirical study is carried out By comparing the experiment result of SVM with Fisher discriminant analysis Logistic regression and back propagation neural networks BPNNs it is concluded that financial distress earlywarning model based on SVM obtains a better balance among fitting ability generalization ability and model stability than the other models

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