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Compositional DuPont Analysis. A Visual Tool for Strategic Financial Performance Assessment Saus Sala, Elisabet Farreras Noguer, M. Àngels Arimany Serrat, Núria Coenders, Germà Anàlisi de conglomerats Cluster analysis DuPont, Anàlisi de DuPont analysis Anàlisi de ràtios Ratio analysis DuPont analysis is a classical tool for assessing the determinants of financial performance of firms. It is based on financial ratios comparing revenues with costs (the so-called margin ratio), revenues with assets (turnover ratio), and debt with assets (leverage ratio). DuPont analysis thus focuses on comparing accounting values in relative terms and lends itself naturally to compositional analysis. In this chapter, we show how to graphically display firms according to margin, turnover and leverage by means of a standard compositional biplot, and how to cluster firms into strategic groups by means of k-means compositional cluster analysis. Practitioners who prefer to stick to the classic definitions of industry or cluster-level financial ratios can compute them with the usual formulae from the centre of the composition, i.e. from the industry or cluster geometric averages rather than the totals or arithmetic averages commonly used. An illustration is presented with farm-tourism firms This work was supported by the Spanish Ministry of Science, Innovation and Universities/FEDER (grant RTI2018–095518–B–C21), the Spanish Ministry of Health (grantCIBERCB06/02/1002) and the Catalan Government (grants 2017SGR656, 2017SGR386 and 2017SGR155) 2021 info:eu-repo/semantics/bookPart info:eu-repo/semantics/acceptedVersion peer-reviewed info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-030-71175-7_10 info:eu-repo/semantics/altIdentifier/isbn/978-3-030-71174-0 RTI2018-095518-B-C21 info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-095518-B-C21/ES/METODOS DEL ANALISIS COMPOSICIONAL DE DATOS/ Tots els drets reservats info:eu-repo/semantics/openAccess Springer © Filzmoser, P., Hron, K., Martín-Fernández, J.A., Palarea-Albaladejo, J. (eds). 2021. Advances in Compositional Data Analysis. Springer, Cham. https://doi.org/10.1007/978-3-030-71175-7_10, p. 189-206 Llibres / Capítols de LLibre (D-EC)