IDEAS home Printed from https://ideas.repec.org/a/pab/rmcpee/v29y2020i1p18-37.html
   My bibliography  Save this article

Principal component analysis of financial statements. A compositional approach || Análisis en componentes principales de los estados financieros. Un enfoque composicional

Author

Listed:
  • Carreras Simó, Miquel

    (Department of Business Studies. University of Girona)

  • Coenders, Germà

    (Department of Economics, Faculty of Economics and Management. University of Girona)

Abstract

Financial ratios are often used in principal component analysis and related techniques for the purposes of data reduction and visualization. Besides the dependence of results on ratio choice, ratios themselves pose a number of problems when subjected to a principal component analysis, such as skewed distributions. In this work, we put forward an alternative method drawn from compositional data analysis (CoDa), a standard statistical toolbox for use when data convey information about relative magnitudes, as financial ratios do. The method, referred to as the CoDa biplot, does not rely on any particular choice of financial ratio but allows researchers to visually order firms along the pairwise financial ratios for any two accounts. Non-financial magnitudes and time evolution can be added to the visualization as desired. We show an example of its application to the top chains in the Spanish grocery retail sector and show how the technique can be used to depict strategic management differences in financial structure or performance, and their evolution over time. || Las ratios financieras se utilizan a menudo en el análisis en componentes principales y técnicas relacionadas con el fin de reducir y visualizar los datos. Además de la dependencia de los resultados de la elección de las ratios, las ratios en sí plantean una serie de problemas cuando se someten a un análisis de componentes principales, por ejemplo, distribuciones asimétricas. En este trabajo, presentamos un método alternativo que proviene del análisis de datos composicionales (CoDa), una caja de herramientas estadística estándar para usar cuando los datos contienen información sobre magnitudes relativas, como lo hacen las ratios financieras. El método, conocido como el biplot CoDa, no se basa en una elección particular de ratios financieras, sino que permite a los investigadores ordenar visualmente las empresas a lo largo de las ratios financieras entre cualesquiera pares de cuentas. Las magnitudes no financieras y la evolución temporal se pueden agregar a la visualización como se desee. Mostramos un ejemplo de su aplicación a las principales cadenas de supermercados españolas y mostramos cómo la técnica puede utilizarse para describir las diferencias de gestión estratégica en la estructura o el rendimiento financieros, y su evolución en el tiempo.

Suggested Citation

  • Carreras Simó, Miquel & Coenders, Germà, 2020. "Principal component analysis of financial statements. A compositional approach || Análisis en componentes principales de los estados financieros. Un enfoque composicional," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 29(1), pages 18-37, June.
  • Handle: RePEc:pab:rmcpee:v:29:y:2020:i:1:p:18-37
    as

    Download full text from publisher

    File URL: https://www.upo.es/revistas/index.php/RevMetCuant/article/view/3580/3930
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    financial ratio; compositional data analysis (CoDa); biplot; grocery retail sector; data visualization; ratio financiera; análisis de datos composicionales (CoDa); biplot; sector de distribución alimentaria; visualización de datos.;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • G30 - Financial Economics - - Corporate Finance and Governance - - - General
    • M10 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - General
    • M49 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Other

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pab:rmcpee:v:29:y:2020:i:1:p:18-37. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Publicación Digital - UPO (email available below). General contact details of provider: https://edirc.repec.org/data/dmupoes.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.