SOLVENCY ASSESSMENT IN AN UNBALANCED SAMPLE

Javier De Andrés, Pedro Lorca, Fernando Sánchez-Lasheras, Francisco Javier De Cos-Juez

Abstract

This paper proposes an improved approach to the assessment of firms’ solvency. First, sound companies are classified into clusters according to their financial similarities by using Kohonen’s Self Organizing Maps (SOM). Then, each cluster is replaced by a director vector which summarizes all the companies that the cluster includes. The next step is the estimation of 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. In this dataset the proportion of distressed firms is very close to that which is derived from Economic statistics. Our results indicate that our system performs better than two benchmarking models, namely a back-propagation neural network and a simple MARS model.

References

  1. Altman, E. I., 1968. Financial ratios, discriminant analysis and the prediction of the corporate bankruptcy, Journal of Finance, 23, 589-609.
  2. Altman, E. I., 1993. Corporate Financial Distress and Bankruptcy, New York: John Wiley and Sons.
  3. Bank for International Settlements (BIS), 2006. International Convergence of Capital Measurement and Capital Standards. A Revised Framework, Basel: BIS.
  4. Foglia A., Iannotti S., Marullo-Reedtz, P., 2001. The Definition of the Grading Scales in Banks' Internal Rating Systems. Economic Notes, 30, 421-456.
  5. Friedman, J. H., 1991. Multivariate adaptive regression splines. Annals of Statistics, vol. 19: 1-141.
  6. Kohonen T., 1995. Self-Organizing Maps, Berlin: Springer-Verlag, 1st edition.
  7. Mahalanobis, P. C., 1936). On the generalised distance in statistics. Proceedings of the National Institute of Science of India, 12: 49-55.
  8. Perner P., 2008. Advances in Data Mining - Medical Applications, E-commerce, Marketing, and Theoretical Aspects. Berlin: Springer-Verlag, 1st edition.
  9. Rousseeuw P. J., Van Zomeren B. C., 1990. Unmasking multivariate outliers and leverage points. Journal of the American Statistical Association, 85, 633-651.
Download


Paper Citation


in Harvard Style

De Andrés J., Lorca P., Sánchez-Lasheras F. and De Cos-Juez F. (2011). SOLVENCY ASSESSMENT IN AN UNBALANCED SAMPLE . In Proceedings of the International Conference on Knowledge Management and Information Sharing - Volume 1: KMIS, (IC3K 2011) ISBN 978-989-8425-81-2, pages 283-286. DOI: 10.5220/0003620202830286


in Bibtex Style

@conference{kmis11,
author={Javier De Andrés and Pedro Lorca and Fernando Sánchez-Lasheras and Francisco Javier De Cos-Juez},
title={SOLVENCY ASSESSMENT IN AN UNBALANCED SAMPLE},
booktitle={Proceedings of the International Conference on Knowledge Management and Information Sharing - Volume 1: KMIS, (IC3K 2011)},
year={2011},
pages={283-286},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003620202830286},
isbn={978-989-8425-81-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Management and Information Sharing - Volume 1: KMIS, (IC3K 2011)
TI - SOLVENCY ASSESSMENT IN AN UNBALANCED SAMPLE
SN - 978-989-8425-81-2
AU - De Andrés J.
AU - Lorca P.
AU - Sánchez-Lasheras F.
AU - De Cos-Juez F.
PY - 2011
SP - 283
EP - 286
DO - 10.5220/0003620202830286