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Proportionate Growth and the Theoretical Foundations of Financial Ratios


  • Stuart McLeay
  • Duarte Trigueiros


The article proposes a theoretical framework for understanding financial ratios, showing that the multiplicative character of the financial variables from which financial ratios are constructed is a necessary condition of valid ratio usage, not just an assumption supported by evidence. Also, by assuming that firm size is a measurable statistical effect, the article offers an informed reappraisal of the limitations of financial ratios, particularly the well–known limitation of proportionality. The article is divided into two parts, one where ratio components are viewed as deterministic vari– ables and the other where they are random. Such an approach allows the characteristics of ratios to be more easily understood before generalizing the relationship between ratio components to encompass randomness. In the second part, when variability introduced by firm size is treated as a random effect, it is shown that if the accounting variables Y and X used to calculate a financial ratio Y/X are exponential Brownian motion, and if continuous growth rates are equal and proportionate to firm size, this may lead to ratios which are asymmetric but which do not necessarily drift.

Suggested Citation

  • Stuart McLeay & Duarte Trigueiros, 2002. "Proportionate Growth and the Theoretical Foundations of Financial Ratios," Abacus, Accounting Foundation, University of Sydney, vol. 38(3), pages 297-316, October.
  • Handle: RePEc:bla:abacus:v:38:y:2002:i:3:p:297-316

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    Cited by:

    1. Gonzalo Rodríguez‐Pérez & John Slof & Magda Solà & Margarita Torrent & Immaculada Vilardell, 2011. "Assessing the Impact of Fair‐Value Accounting on Financial Statement Analysis: A Data Envelopment Analysis Approach," Abacus, Accounting Foundation, University of Sydney, vol. 47(1), pages 61-84, March.
    2. David Ashton & Paul Dunmore & Mark Tippett, 2004. "Double Entry Bookkeeping and the Distributional Properties of a Firm's Financial Ratios," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 31(5-6), pages 583-606.
    3. Landajo, Manuel & de Andres, Javier & Lorca, Pedro, 2007. "Robust neural modeling for the cross-sectional analysis of accounting information," European Journal of Operational Research, Elsevier, vol. 177(2), pages 1232-1252, March.
    4. Postel-Vinay, Natacha, 2016. "What caused Chicago bank failures in the Great Depression? A look at the 1920s," LSE Research Online Documents on Economics 88844, London School of Economics and Political Science, LSE Library.
    5. Stuart McLeay & Maxwell Stevenson, 2009. "Modelling the longitudinal properties of financial ratios," Applied Financial Economics, Taylor & Francis Journals, vol. 19(4), pages 305-318.
    6. M. Naresh Kumar & V. Sree Hari Rao, 2015. "A New Methodology for Estimating Internal Credit Risk and Bankruptcy Prediction under Basel II Regime," Papers 1502.00882,
    7. M. Naresh Kumar & V. Sree Hari Rao, 2015. "A New Methodology for Estimating Internal Credit Risk and Bankruptcy Prediction under Basel II Regime," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 83-102, June.
    8. Julia, 2011. "About some difficulties with interpreting and measuring corporate performance," Bank i Kredyt, Narodowy Bank Polski, vol. 42(5), pages 41-60.
    9. repec:spr:scient:v:76:y:2008:i:3:d:10.1007_s11192-007-1877-7 is not listed on IDEAS
    10. Natacha Postel-Vinay, 2015. "What caused Chicago bank failures in the Great Depression? A look at the 1920s," Working Papers 22, Department of Economic and Social History at the University of Cambridge.

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