Skip to main content
SpringerLink
Log in

Compositional DuPont Analysis. A Visual Tool for Strategic Financial Performance Assessment

  • Chapter
  • First Online:
Advances in Compositional Data Analysis

Abstract

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 is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  • J. Aitchison, Principal component analysis of compositional data. Biometrika 70(1), 57–65 (1983)

    Article  MathSciNet  Google Scholar 

  • J. Aitchison, M. Greenacre, Biplots of compositional data. J. Roy. Stat. Soc. C App. 51(4), 375–392 (2002)

    Article  MathSciNet  Google Scholar 

  • J. Aitchison, C. Barceló-Vidal, J.A. Martín-Fernández, V. Pawlowsky-Glahn, Logratio analysis and compositional distances. Math. Geol. 32(3), 271–275 (2000)

    Article  Google Scholar 

  • T. Baležentis, A. Galnaitytė, I. Kriščiukaitienė, V. Namiotko, L. Novickytė, D. Streimikiene, R. Melnikiene, Decomposing dynamics in the farm profitability: An application of index decomposition analysis to Lithuanian FADN sample. Sustainability 11(10), 2861 (2019)

    Article  Google Scholar 

  • P. Barnes, The analysis and use of financial ratios: a review article. J. Bus. Finan. Account. 14(4), 449–461 (1987)

    Article  Google Scholar 

  • J. Belles-Sampera, M. Guillén, M. Santolino, Compositional methods applied to capital allocation problems. J. Risk 19(2), 15–30 (2016)

    MATH  Google Scholar 

  • C. Bilbao, L. Valdés, Evaluation of the profitability of quality labels in rural tourism accommodation: a hedonic approach using propensity score matching. Appl. Econ. 48(34), 3253–3263 (2016)

    Article  Google Scholar 

  • T. Boonen, M. Guillén, M. Santolino, Forecasting compositional risk allocations. Insur. Math. Econ. 84, 79–86 (2019)

    Article  MathSciNet  Google Scholar 

  • A. Buccianti, G. Mateu-Figueras, V. Pawlowsky-Glahn, Compositional Data Analysis in the Geosciences: From Theory to Practice (Geological Society, London, 2006)

    MATH  Google Scholar 

  • M. Carreras-Simó, G. Coenders, Principal component analysis of financial statements. A compositional approach. Rev. Métodos Cuant. Econ. Empresa 29, 18–37 (2020)

    Google Scholar 

  • C. Castro, Rural tourism in Northern Portugal-Motivations and barriers. RITUR 9(2), 217–240 (2019)

    Google Scholar 

  • K.H. Chen, T.A. Shimerda, An empirical analysis of useful financial ratios. Financ. Manag. 10(1), 51–60 (1981)

    Article  Google Scholar 

  • L. Chen, S. Wang, Z. Qiao, DuPont model and product profitability analysis based on activity-based costing and economic value added. Eur. J. Bus. Manag. 6(30), 25–35 (2014)

    Google Scholar 

  • G. Coenders, B. Ferrer-Rosell, Compositional data analysis in tourism. Review and future directions. Tour. Anal. 25(1), 153–168 (2020)

    Google Scholar 

  • A.C. Costa, Influence of sociodemographic characteristics on the financial performance of micro and small businesses in rural tourism. Espacios 39(14), 12 (2018)

    Google Scholar 

  • S.S. Cowen, J.A. Hoffer, Usefulness of financial ratios in a single industry. J. Bus. Res. 10, 103–118 (1982)

    Google Scholar 

  • J. Creixans-Tenas, G. Coenders, N. Arimany-Serrat, Corporate social responsibility and financial profile of Spanish private hospitals. Heliyon 5(10), e02623 (2019)

    Article  Google Scholar 

  • E. Dale, R.S. Greenwood, R.G. Greenwood, Donaldson brown: GM’s pioneer management theorist and practioner. Acad. Manag. Proc. 1980(1), 119–123 (1980)

    Google Scholar 

  • B.C. Davis, K.M. Hmieleski, J.W. Webb, J.E. Coombs, Funders’ positive affective reactions to entrepreneurs’ crowdfunding pitches: the influence of perceived product creativity and entrepreneurial passion. J. Bus. Ventur. 32(1), 90–106 (2017)

    Article  Google Scholar 

  • M. Doorasamy, Using DuPont analysis to assess the financial performance of the top 3 JSE listed companies in the food industry. Invest. Manag. Financ. Innov. 13(2), 29–44 (2016)

    Article  Google Scholar 

  • J.J. Egozcue, V. Pawlowsky-Glahn, Basic concepts and procedures, in Compositional Data Analysis. Theory and Applications, eds. by V. Pawlowsky-Glahn, A. Buccianti (Wiley, New York, 2011)

    Google Scholar 

  • J.J. Egozcue, V. Pawlowsky-Glahn, What are compositional data and how should they be analyzed? BEIO 32(1), 5–29 (2016)

    Google Scholar 

  • J.J. Egozcue, V. Pawlowsky-Glahn, Compositional data: the sample space and its structure. TEST 28(3), 599–638 (2019)

    Article  MathSciNet  Google Scholar 

  • J.J. Egozcue, V. Pawlowsky-Glahn, G. Mateu-Figueras, C. Barceló-Vidal, Isometric logratio transformations for compositional data analysis. Math. Geol. 35(3), 279–300 (2003)

    Article  MathSciNet  Google Scholar 

  • Eurostat, NACE Rev. 2 – Statistical classification of economic activities in the European Community. Eurostat methodologies and working papers. European Communities, Luxembourg (2008)

    Google Scholar 

  • J. Faello, Understanding the limitations of financial ratios. Acad. Account. Financ. Stud.J. 19(3), 75–85 (2015)

    Google Scholar 

  • B. Ferrer-Rosell, G. Coenders, G. Mateu-Figueras, V. Pawlowsky-Glahn, Understanding low cost airline users’ expenditure patterns and volume. Tour. Econ. 22(2), 269–291 (2016)

    Article  Google Scholar 

  • M. Greenacre, Variable selection in compositional data analysis using pairwise logratios. Math. Geosci. 51(5), 649–682 (2019)

    Article  MathSciNet  Google Scholar 

  • J.O. Horrigan, A short history of financial ratio analysis. Account. Rev. 43, 284–294 (1968)

    Google Scholar 

  • A. Joueid, G. Coenders, Marketing innovation and new product portfolios. A compositional approach. J. Open Innov. Technol. Mark. Complex. 4, 19 (2018)

    Google Scholar 

  • A. Kallmuenzer, M. Peters, Entrepreneurial behaviour, firm size and financial performance: the case of rural tourism family firms. Tour. Recreat. Res. 43(1), 2–14 (2018)

    Google Scholar 

  • L. Kaufman, P.J. Rousseeuw, Finding Groups in Data: An Introduction to Cluster Analysis (Wiley, New York, 1990)

    Book  Google Scholar 

  • P. Kokoszka, H. Miao, A. Petersen, H.L. Shang, Forecasting of density functions with an application to cross-sectional and intraday returns. Int. J. Forecast. 35(4), 1304–1317 (2019)

    Article  Google Scholar 

  • B. Lev, S. Sunder, Methodological issues in the use of financial ratios. J. Account. Econ. 1(3), 187–210 (1979)

    Article  Google Scholar 

  • S. Linares-Mustarós, G. Coenders, M. Vives-Mestres, Financial performance and distress profiles. From classification according to financial ratios to compositional classification. Adv. Account. 40, 1–10 (2018)

    Google Scholar 

  • W.L. Maldonado, J.J. Egozcue, V. Pawlowsky-Glahn, No-arbitrage matrices of exchange rates: some characterizations. Int. J. Econ. Theory (2021). https://doi.org/10.1111/ijet.12249

    Article  Google Scholar 

  • J.A. Martín-Fernández, C. Barceló-Vidal, V. Pawlowsky-Glahn, A critical approach to non-parametric classification of compositional data, in Advances in Data Science and Classification, eds. by A. Rizzi, M. Vichi, H.H. Bock (Springer, Berlin, 1998)

    Google Scholar 

  • J.A. Martín-Fernández, R.A. Olea-Meneses, V. Pawlowsky-Glahn, Criteria to compare estimation methods of regionalized compositions. Math. Geol. 33(8), 889–909 (2001)

    Article  Google Scholar 

  • G. Mateu-Figueras, V. Pawlowsky-Glahn, J.J. Egozcue, The principle of working on coordinates, in Compositional Data Analysis. Theory and Applications, eds. by V. Pawlowsky-Glahn, A. Buccianti (Wiley, New York, 2011)

    Google Scholar 

  • R. Ortells, J.J. Egozcue, M.I. Ortego, A. Garola, Relationship between popularity of key words in the Google browser and the evolution of worldwide financial indices, in Compositional Data Analysis. Springer Proceedings in Mathematics & Statistics, vol. 187, eds. by J.A. Martín–Fernández, S. Thió–Henestrosa (Springer, Cham, 2016)

    Google Scholar 

  • P.D. Parulekar, Dupont analysis for selected five nifty fifty companies. SFIMAR Res. Rev. 10(2), 8–16 (2015)

    Google Scholar 

  • V. Pawlowsky-Glahn, A. Buccianti, Visualization and modeling of sub-populations of compositional data: statistical methods illustrated by means of geochemical data from fumarolic fluids. Int. J. Earth Sci. 91(2), 357–68 (2002)

    Article  Google Scholar 

  • V. Pawlowsky-Glahn, A. Buccianti, Compositional Data Analysis. Theory and Applications (Wiley, New York, 2011)

    Google Scholar 

  • V. Pawlowsky-Glahn, J.J. Egozcue, R. Tolosana-Delgado, Modelling and Analysis of Compositional Data (Wiley, Chichester, 2015a)

    Google Scholar 

  • V. Pawlowsky-Glahn, J.J. Egozcue, D. Lovell, Tools for compositional data with a total. Stat. Model 15(2), 175–190 (2015b)

    Google Scholar 

  • A.I. Polo Peña, D.M. Frías Jamilena, M.Á. Rodríguez Molina, The effect of customer orientation on smaller sized service firms and on the market: a multilevel application embracing firms and customers. J. Small Bus. Manag. 54(2), 566–581 (2016)

    Google Scholar 

  • J.C. So, Some empirical evidence on the outliers and the non-normal distribution of financial ratios. J. Bus. Finan. Account. 14(4), 483–496 (1987)

    Article  Google Scholar 

  • M.T. Soliman, The use of DuPont analysis by market participants. Account Rev. 83(3), 823–853 (2008)

    Article  Google Scholar 

  • M.T. Tascón, F.J. Castaño, P. Castro, A new tool for failure analysis in small firms: frontiers of financial ratios based on percentile differences (PDFR). Span. J. Financ. Account. 47(4), 433–463 (2018)

    Google Scholar 

  • R. Verbelen, K. Antonio, G. Claeskens, Unravelling the predictive power of telematics data in car insurance pricing. J. Roy. Stat. Soc. C App. 67(5), 1275–1304 (2018)

    Article  MathSciNet  Google Scholar 

  • A. Voltes-Dorta, J.L. Jiménez, A. Suárez-Alemán, An initial investigation into the impact of tourism on local budgets: a comparative analysis of Spanish municipalities. Tour. Manag. 45, 124–133 (2014)

    Article  Google Scholar 

  • H. Wang, S. Lu, J. Zhao, Aggregating multiple types of complex data in stock market prediction: a model-independent framework. Knowl. Based Syst. 164(15), 193–204 (2019)

    Article  Google Scholar 

  • J. Willer do Prado, V. de Castro Alcântara, F. de Melo Carvalho, K. Carvalho Vieira, L.K. Cruz Machado, D. Flávio Tonelli, Multivariate analysis of credit risk and bankruptcy research data: a bibliometric study involving different knowledge fields (1968–2014). Scientometrics 106(3), 1007–1029 (2016)

    Google Scholar 

  • S. Ye, H. Xiao, L. Zhou, Small accommodation business growth in rural areas: effects on guest experience and financial performance. Int. J. Hosp. Manag. 76, 29–38 (2019)

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the Spanish Ministry of Science, Innovation and Universities/FEDER (grant RTI2018–095518–B–C21), the Spanish Ministry of Health (grant CIBERCB06/02/1002) and the Catalan Government (grants 2017SGR656, 2017SGR386 and 2017SGR155).

Author information

Authors and Affiliations

  1. Department of Business Studies, University of Girona, c./ Universitat de Girona 10, 17003, Girona, Spain

    Elisabet Saus–Sala & Àngels Farreras–Noguer

  2. Department of Economics and Business, University of Vic-UCC, c./ Sagrada Familia 7, 08500, Vic, Spain

    Núria Arimany–Serrat

  3. Department of Economics, University of Girona, c./ Universitat de Girona 10, 17003, Girona, Spain

    Germà Coenders

Authors
  1. Elisabet Saus–Sala
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Àngels Farreras–Noguer
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Núria Arimany–Serrat
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Germà Coenders
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Germà Coenders .

Editor information

Editors and Affiliations

  1. Institute of Statistics and Mathematical Methods in Economics, TU Wien, Vienna, Austria

    Peter Filzmoser

  2. Department of Mathematical Analysis and Applications of Mathematics, Palacký University, Olomouc, Czech Republic

    Karel Hron

  3. Department of Computer Science, Applied Mathematics and Statistics, University of Girona, Girona, Spain

    Josep Antoni Martín-Fernández

  4. Biomathematics and Statistics Scotland, Edinburgh, UK

    Javier Palarea-Albaladejo

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Saus–Sala, E., Farreras–Noguer, À., Arimany–Serrat, N., Coenders, G. (2021). Compositional DuPont Analysis. A Visual Tool for Strategic Financial Performance Assessment. In: Filzmoser, P., Hron, K., Martín-Fernández, J.A., Palarea-Albaladejo, J. (eds) Advances in Compositional Data Analysis. Springer, Cham. https://doi.org/10.1007/978-3-030-71175-7_10

Download citation

Publish with us

Policies and ethics

Search

Navigation