Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/275023 
Year of Publication: 
2022
Citation: 
[Journal:] Journal of Risk and Financial Management [ISSN:] 1911-8074 [Volume:] 15 [Issue:] 12 [Article No.:] 546 [Year:] 2022 [Pages:] 1-17
Publisher: 
MDPI, Basel
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.
Subjects: 
Spain
cluster analysis
accounting ratios
Aitchison distance
compositional data analysis (CoDA)
logratios
petrol stations
Ward clustering
weights
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.