A Hybrid Device of Self Organizing Maps (som) and Multivariate Adaptive Regression Splines (mars) for the Forecasting of Firms' Bankruptcy

Abstract

This paper proposes a hybrid approach to the forecasting of firms' bankruptcy of Spanish enterprises from the construction sector. Our proposal starts splitting the group of healthy companies into two subgroups: borderline and non-borderline companies. Borderline companies are healthy companies with marked financial similarities with bankrupt ones. Then, each subgroup is divided in clusters according to their financial similarities and then each cluster is replaced by a director vector which represents the companies included in the cluster. In order to do this, we use Self Organizing Maps (SOM). Once the companies in clusters have been replaced by director vectors, we estimate a classification model through Multivariate Adaptive Regression Splines (MARS). Our results show that the proposed hybrid approach is much more accurate for the identification of the companies that go bankrupt than other approaches such as a multi-layer perceptron neural network and a simple MARS model. [ABSTRACT FROM AUTHOR]Copyright of Accounting & Management Information Systems / Contabilitate si Informatica de Gestiune is the property of Journal of Accounting & Management Information Systems and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)