Compositional Classification of Financial Statement Profiles: The Weighted Case

Abstract

This article classifies petrol retail companies in Spain based on their financial ratios using the compositional data analysis (CoDA) methodology. This methodology solves the most common distributional problems encountered in the statistical analysis of financial ratios. The main purpose of this article is to show that with the CoDA methodology, accounting figures presenting low values can have a disproportional influence on classification. This problem can be attenuated by applying weighted CoDA, which is a novelty in the financial statement analysis field. The suggested weight of each accounting figure is proportional to its arithmetic mean. The results of Ward clustering show that after weighting, the contributions of the accounting figures to the total variance and to the clustering solution are more balanced, and the clusters are more interpretable. Four distinct financial profiles are identified and related to non-financial variables. Only one of the profiles represents companies in financial distress, with low turnover, low return on assets, high indebtedness, and low liquidity. Further developments include alternative weighting schemes.

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