IDEAS home Printed from https://ideas.repec.org/a/boh/actaub/v17y2014i2p103-111.html
   My bibliography  Save this article

Which Altman Model Do We Actually Use?

Author

Listed:
  • Miroslava Dolejšová

    (Tomas Bata University in Zlín)

Abstract

The aim of this paper is to critically evaluate the terms that are described by various authors in Czech literature, compare those terms with the terms used by the original Altman model, use data from selected enterprises to show whether enterprises could be considered at risk of bankruptcy due to such inaccuracies and verify whether the average Z-score values for small enterprises within the Zlín Region are greater than 3. The data were analysed using a one-sample t-test and the Altman model for enterprises that are not publicly-traded. Financial statements for 2007 through 2011 were used in the data analysis. The one-sample t-test showed that the sample of 32 small enterprises from the Zlín Region had good financial health. The largest percentage change that was associated with a decline in performance was demonstrated when adding net profit to retained earnings (-16.64%). The largest percentage change that was associated with an improvement in performance was demonstrated when using current assets instead of working capital (33.07%). Replacing retained earnings with net profit reduced the enterprise’s performance (a percentage change of -24.43%). Adding funds from profit and net profit to retained earnings reduced performance by 0.17 percentage points. We recommend using net working capital to calculate the X1 ratio. Retained earnings should be used to calculate the X2 ratio. Only sales should be used to calculate the X5 ratio. For manufacturing enterprises that are not publicly-traded, we recommend using equation (8). Publicly-traded enterprises may use equation (2). Enterprises that provide services and enterprises in emerging markets may use equation (4).

Suggested Citation

  • Miroslava Dolejšová, 2014. "Which Altman Model Do We Actually Use?," Acta Universitatis Bohemiae Meridionales, University of South Bohemia in Ceske Budejovice, vol. 17(2), pages 103-111.
  • Handle: RePEc:boh:actaub:v:17:y:2014:i:2:p:103-111
    DOI: 10.32725/acta.2014.007
    as

    Download full text from publisher

    File URL: https://doi.org/10.32725/acta.2014.007
    Download Restriction: no

    File URL: https://libkey.io/10.32725/acta.2014.007?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    2. Altman, Edward I. & Haldeman, Robert G. & Narayanan, P., 1977. "ZETATM analysis A new model to identify bankruptcy risk of corporations," Journal of Banking & Finance, Elsevier, vol. 1(1), pages 29-54, June.
    3. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    4. Grice, John Stephen & Ingram, Robert W., 2001. "Tests of the generalizability of Altman's bankruptcy prediction model," Journal of Business Research, Elsevier, vol. 54(1), pages 53-61, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lin, Hsiou-Wei William & Lo, Huai-Chun & Wu, Ruei-Shian, 2016. "Modeling default prediction with earnings management," Pacific-Basin Finance Journal, Elsevier, vol. 40(PB), pages 306-322.
    2. Antonio Angelo Romano & Giuseppe Scandurra & Alfonso Carfora, 2016. "Estimating the Impact of Feed-in Tariff Adoption: Similarities and Divergences among Countries through a Propensity-score Matching Method," International Journal of Energy Economics and Policy, Econjournals, vol. 6(2), pages 144-151.
    3. Ciampi, Francesco, 2015. "Corporate governance characteristics and default prediction modeling for small enterprises. An empirical analysis of Italian firms," Journal of Business Research, Elsevier, vol. 68(5), pages 1012-1025.
    4. Adriana Csikosova & Maria Janoskova & Katarina Culkova, 2019. "Limitation of Financial Health Prediction in Companies from Post-Communist Countries," JRFM, MDPI, vol. 12(1), pages 1-14, January.
    5. Francesco Ciampi & Valentina Cillo & Fabio Fiano, 2020. "Combining Kohonen maps and prior payment behavior for small enterprise default prediction," Small Business Economics, Springer, vol. 54(4), pages 1007-1039, April.
    6. Bhanu Pratap Singh & Alok Kumar Mishra, 2016. "Re-estimation and comparisons of alternative accounting based bankruptcy prediction models for Indian companies," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 2(1), pages 1-28, December.
    7. Miguel García-Posada & Juan Mora-Sanguinetti, 2014. "Are there alternatives to bankruptcy? A study of small business distress in Spain," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 5(2), pages 287-332, August.
    8. Gianpaolo Iazzolino & Rossella Gabriele, 2016. "Energy Efficiency and Sustainable Development: An Analysis of Financial Reliability in Energy Service Companies Industry," International Journal of Energy Economics and Policy, Econjournals, vol. 6(2), pages 222-233.
    9. Pindado, Julio & Rodrigues, Luis & de la Torre, Chabela, 2008. "Estimating financial distress likelihood," Journal of Business Research, Elsevier, vol. 61(9), pages 995-1003, September.
    10. fernández, María t. Tascón & gutiérrez, Francisco J. Castaño, 2012. "Variables y Modelos Para La Identificación y Predicción Del Fracaso Empresarial: Revisión de La Investigación Empírica Reciente," Revista de Contabilidad - Spanish Accounting Review, Elsevier, vol. 15(1), pages 7-58.
    11. Sebastian Klaudiusz Tomczak & Edward Radosiński, 2017. "The effectiveness of discriminant models based on the example of the manufacturing sector," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 27(3), pages 81-97.
    12. Mauro Paoloni & Massimiliano Celli, 2018. "Crisi delle PMI e strumenti di warning. Un test di verifica nel settore manifatturiero," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2018(2), pages 85-106.
    13. Iulian Viorel Brasoveanu & Florin Dobre & Laura Brad, 2014. "Increasing Financial Audit Quality Using A New Model To Estimate Financial Performance," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 88-107, October.
    14. Nawaf Almaskati & Ron Bird & Yue Lu & Danny Leung, 2019. "The Role of Corporate Governance and Estimation Methods in Predicting Bankruptcy," Working Papers in Economics 19/16, University of Waikato.
    15. Leila Bateni & Farshid Asghari, 2020. "Bankruptcy Prediction Using Logit and Genetic Algorithm Models: A Comparative Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 335-348, January.
    16. Li, Chunyu & Lou, Chenxin & Luo, Dan & Xing, Kai, 2021. "Chinese corporate distress prediction using LASSO: The role of earnings management," International Review of Financial Analysis, Elsevier, vol. 76(C).
    17. Suzan Hol, 2006. "The influence of the business cycle on bankruptcy probability," Discussion Papers 466, Statistics Norway, Research Department.
    18. Enrico Supino & Nicola Piras, 2022. "Le performance dei modelli di credit scoring in contesti di forte instabilit? macroeconomica: il ruolo delle Reti Neurali Artificiali," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2022(2), pages 41-61.
    19. Quader, Syed Manzur, 2017. "Differential effect of liquidity constraints on firm growth," Review of Financial Economics, Elsevier, vol. 32(C), pages 20-29.
    20. Campa, Domenico & Camacho-Miñano, María-del-Mar, 2015. "The impact of SME’s pre-bankruptcy financial distress on earnings management tools," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 222-234.

    More about this item

    Keywords

    Prediction of bankruptcy; Altman model; Misinterpretation; small enterprises; one-sample t-test;
    All these keywords.

    JEL classification:

    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • G34 - Financial Economics - - Corporate Finance and Governance - - - Mergers; Acquisitions; Restructuring; Corporate Governance
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

    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:boh:actaub:v:17:y:2014:i:2:p:103-111. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Tereza Šťástková (email available below). General contact details of provider: https://edirc.repec.org/data/efjcucz.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.