Adapting Altman's bankruptcy prediction model to the compositional data methodology
The study adapts Altman's bankruptcy model using compositional data methodology to improve financial distress prediction. Using log-ratios from compositional data outperformed standard financial ratios in sensitivity, with random forests and logistic regression showing the best balanced accuracy. This suggests that accounting figures should be analyzed based on their relative proportions rather than absolute values.