Self organizing maps in corporate finance: Quantitative and qualitative analysis of debt and leasing

  • Authors:
  • Eric Séverin

  • Affiliations:
  • University of Lille 1, Department of GEA, Bítiment SHS no. 3, BP 179, 59653 Villeneuve d'Ascq cedex, France

  • Venue:
  • Neurocomputing
  • Year:
  • 2010

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Abstract

This article deals with the usefulness of self organizing maps in the area of corporate finance. The application of neural networks improve bankruptcy forecasting by showing a relationship between capital structure and corporate performance. Our results suggest the pertinence of the Kohonen algorithm applied to qualitative variables. These results allow us to question scoring models. In a larger framework, the methodology of Kohonen allowed a better perception of the factors able to explain the financing of leasing. The objective of our research is here to explain the factors of the choice between leasing and banking loans.