Forecasting financial failure using a Kohonen map: A comparative study to improve model stability over time

Philippe du Jardin (philippe.dujardin@edhec.edu) and Eric Severin

MPRA Paper from University Library of Munich, Germany

Abstract: This study attempts to show how a Kohonen map can be used to improve the temporal stability of the accuracy of a financial failure model. Most models lose a significant part of their ability to generalize when data used for estimation and prediction purposes are collected over different time periods. As their lifespan is fairly short, it becomes a real problem if a model is still in use when re-estimation appears to be necessary. To overcome this drawback, we introduce a new way of using a Kohonen map as a prediction model. The results of our experiments show that the generalization error achieved with a map remains more stable over time than that achieved with conventional methods used to design failure models (discriminant analysis, logistic regression, Cox’s method, and neural networks). They also show that type-I error, the economically costliest error, is the greatest beneficiary of this gain in stability.

Keywords: Decision support systems; Finance; Bankruptcy prediction; Self-organizing map (search for similar items in EconPapers)
JEL-codes: C44 G33 (search for similar items in EconPapers)
Date: 2011-06-28, Revised 2012-04-03
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (28)

Published in European Journal of Operational Research 2.221(2012): pp. 378-396

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Journal Article: Forecasting financial failure using a Kohonen map: A comparative study to improve model stability over time (2012)
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