Article ID Journal Published Year Pages File Type
384431 Expert Systems with Applications 2012 12 Pages PDF
Abstract

This paper proposes a new approach to the forecasting of firms’ bankruptcy. Our proposal is a hybrid method in which sound companies are divided in clusters using Self Organized Maps (SOM) and then each cluster is replaced by a director vector which summarizes all of them. Once the companies in clusters have been replaced by director vectors, we estimate a classification model through Multivariate Adaptive Regression Splines (MARS). For the test of the model we considered a real setting of Spanish enterprises from the construction sector. With this procedure we intend to overcome the sampling-bias problems that matched-pairs models often suffer. We estimated two benchmark models: a back propagation neural network and a simple MARS model. Our results show that the proposed hybrid approach is much more accurate than the benchmark techniques for the identification of the bankrupt companies.

► Hybrid methods are superior to single models for financial classification tasks. ► Our method clusters companies through Self-Organizing Maps. ► Then each cluster is replaced by a director vector. ► A Multivariate Adaptive Regression Splines (MARS) model is estimated. ► In a real setting, our system outperforms both a single MARS and a neural network.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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