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

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.