IDEAS home Printed from https://ideas.repec.org/a/prg/jnlpol/v2022y2022i3id1353p265-287.html
   My bibliography  Save this article

Predikční schopnost Altmanova Z-skóre evropských soukromých společností
[Predictive Ability of Altman Z-score of European Private Companies]

Author

Listed:
  • Svatopluk Kapounek
  • Jan Hanousek
  • František Bílý

Abstract

The paper investigates the relationship between the financial distress of European private companies identified by the Altman Z-score and real bankruptcy. We extend the traditional Z-score with the asymmetric effect of economic activity. Our results show higher forecasting performance of the Altman Z-score of large companies in a three-year projection. We argue that our results differ from Altman (1968) because of specific market conditions in Europe that enable prolongation of activity after financial distress is identified. We also emphasize the role of liquidity, size, performance and indebtedness in increasing financial distress forecasting performance. Finally, we extend our prediction model with selected indicators of quality and development of the institutional environment.

Suggested Citation

  • Svatopluk Kapounek & Jan Hanousek & František Bílý, 2022. "Predikční schopnost Altmanova Z-skóre evropských soukromých společností [Predictive Ability of Altman Z-score of European Private Companies]," Politická ekonomie, Prague University of Economics and Business, vol. 2022(3), pages 265-287.
    • Handle: RePEc:prg:jnlpol:v:2022:y:2022:i:3:id:1353:p:265-287
    DOI: 10.18267/j.polek.1353
    as

    Download full text from publisher

    File URL: http://polek.vse.cz/doi/10.18267/j.polek.1353.html
    Download Restriction: free of charge
    File URL: http://polek.vse.cz/doi/10.18267/j.polek.1353.pdf
    Download Restriction: free of charge
    File URL: https://libkey.io/10.18267/j.polek.1353?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Altman, Edward I., 2005. "An emerging market credit scoring system for corporate bonds," Emerging Markets Review, Elsevier, vol. 6(4), pages 311-323, December.
    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. Jarko Fidrmuc & Svatopluk Kapounek & Martin Siddiqui, 2017. "Which Institutions Are Important for Firms Performance? Evidence from Bayesian Model Averaging Analysis," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 64(4), pages 383-400, September.
    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. Duc Hong Vo & Binh Ninh Vo Pham & Chi Minh Ho & Michael McAleer, 2019. "Corporate Financial Distress of Industry Level Listings in Vietnam," JRFM, MDPI, vol. 12(4), pages 1-17, September.
    2. Vo, D.H. & Pham, B.V.-N. & Pham, T.V.-T. & McAleer, M.J., 2019. "Corporate Financial Distress of Industry Level Listings in an Emerging Market," Econometric Institute Research Papers EI2019-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Erdely, Arturo, 2017. "Value at Risk and the Diversification Dogma || Valor en riesgo y el dogma de la diversificación," 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. 24(1), pages 209-219, Diciembre.
    4. Zhaklina Dhamo & Vasilika Kume, 2016. "Tendencies and Characteristics of Financial Distress: An Introductory Comparative Study among Three Industries in Albania," Athens Journal of Business & Economics, Athens Institute for Education and Research (ATINER), vol. 2(2), pages 167-180, April.
    5. Caro, Norma Patricia & Arias, Ver—nica & Ortiz, Pablo, 2017. "Predicci—n de fracaso en empresas latinoamericanas utilizando el mŽtodo del vecino más cercano para predecir efectos aleatorios en modelos mixtos || Prediction of Failure in Latin-American Companies U," 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. 24(1), pages 5-24, Diciembre.
    6. Pham Vo Ninh, Binh & Do Thanh, Trung & Vo Hong, Duc, 2018. "Financial distress and bankruptcy prediction: An appropriate model for listed firms in Vietnam," Economic Systems, Elsevier, vol. 42(4), pages 616-624.
    7. Marco Botta & Luca Colombo, 2016. "Macroeconomic and Institutional Determinants of Capital Structure Decisions," DISCE - Working Papers del Dipartimento di Economia e Finanza def038, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    8. 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).
    9. Suzan Hol, 2006. "The influence of the business cycle on bankruptcy probability," Discussion Papers 466, Statistics Norway, Research Department.
    10. 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.
    11. Christophe Godlewski, 2004. "Modélisation de la Prévision de Défaillance Bancaire Une Application aux Banques des Pays Emergents," Finance 0409026, University Library of Munich, Germany.
    12. Fougère, D. & Golfier, C. & Horny, G. & Kremp, E., 2013. "What has been the impact of the 2008 crisis on firms’ default? (in French)," Working papers 463, Banque de France.
    13. Maurice Peat, 2007. "Factors Affecting the Probability of Bankruptcy: A Managerial Decision Based Approach," Abacus, Accounting Foundation, University of Sydney, vol. 43(3), pages 303-324, September.
    14. Baumöhl, Eduard & Iwasaki, Ichiro & Kočenda, Evžen, 2019. "Institutions and determinants of firm survival in European emerging markets," Journal of Corporate Finance, Elsevier, vol. 58(C), pages 431-453.
    15. Shekar Shetty & Mohamed Musa & Xavier Brédart, 2022. "Bankruptcy Prediction Using Machine Learning Techniques," JRFM, MDPI, vol. 15(1), pages 1-10, January.
    16. Silvia Mariela Méndez-Prado & Ariel Flores Ulloa, 2022. "The Impact Analysis of Psychological Issues and Pandemic-Related Variables on Ecuadorian University Students during COVID-19," Sustainability, MDPI, vol. 14(20), pages 1-23, October.
    17. 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.
    18. Adriana Csikosova & Maria Janoskova & Katarina Culkova, 2020. "Application of Discriminant Analysis for Avoiding the Risk of Quarry Operation Failure," JRFM, MDPI, vol. 13(10), pages 1-14, September.
    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. Abele, Christian & Bénassy-Quéré, Agnès & Fontagné, Lionel, 2024. "The impact of financial tightening on firm productivity: Maturity matters," Journal of International Money and Finance, Elsevier, vol. 144(C).

    More about this item

    Keywords

    Firm bankruptcy; financial distress; Altman Z-score; institutional environment;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

    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:prg:jnlpol:v:2022:y:2022:i:3:id:1353:p:265-287. 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: Stanislav Vojir (email available below). General contact details of provider: https://edirc.repec.org/data/uevsecz.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.