Bankruptcy prediction models based on multinorm analysis: An alternative to accounting ratios

Authors:
Javier de Andrés;Manuel Landajo;Pedro Lorca
Affiliations:
University of Oviedo, Spain;University of Oviedo, Spain;University of Oviedo, Spain
Venue:
Knowledge-Based Systems
Year:
2012

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Abstract

In this paper we address the bankruptcy prediction problem and outline a procedure to improve the performance of standard classifiers. Our proposal replaces traditional indicators (accounting ratios) with the output of a so-called multinorm analysis. The deviations of each firm from a battery of industry norms (computed by nonparametric quantile regression) are used as input variables for the classifiers. The approach is applied to predict bankruptcy of firms, and tested on a representative data set of Spanish firms. Results indicate that the approach may provide significant improvements in predictive accuracy, both in linear and nonlinear classifiers.