IDEAS home Printed from https://ideas.repec.org/p/osf/osfxxx/f3dv5.html

Comparative Analysis of Financial Sustainability Using the Altman Z-Score, Springate, Zmijewski and Grover Models for Companies Listed at Indonesia Stock Exchange Sub-Sector Telecommunication Period 2014 – 2019

Author

Listed:
  • Fauzi3, Samrony Eka
  • , Sudjono
  • Saluy, Ahmad Badawi
  • Institute of Research, Asian

Abstract

This study aims to compare the best bankruptcy prediction models between Altman, Springate, Zmijewski and Grover models against companies listed on the Indonesian stock exchange in the telecommunications sub-sector for the 2014-2019 period. The purposive sampling method is used to obtain a sample of companies with the following criteria: Companies listed on the Indonesian stock exchange, the telecommunications sub-sector, the company has conducted an IPO in 2010, the company is obedient in reporting annual reports from 2014 - 2019 and the company is free from delisting issues. There are 4 companies that meet the purposive sampling criteria, namely PT. Telkom TBK, PT. Indosat TBK. PT. XL Axiata TBK and PT. Smartfren TBK. The data used in this research is secondary panel data. The results showed that only PT. Telkom which is in a healthy financial condition. Meanwhile, PT. Indosat, PT. XL Axiata and PT. Smartfren is consistently in an unhealthy condition based on the analysis of the Altman and Springate models. The calculation of Zmijewski's model and Grover's model gave inconsistent results. Comparative testing of the four bankruptcy analysis models resulted in the Altman, Springate and Grover models recording accurate results but Altman modelling is the best because it is an accurate, consistent, and tested model both descriptively and statistically.

Suggested Citation

  • Fauzi3, Samrony Eka & , Sudjono & Saluy, Ahmad Badawi & Institute of Research, Asian, 2021. "Comparative Analysis of Financial Sustainability Using the Altman Z-Score, Springate, Zmijewski and Grover Models for Companies Listed at Indonesia Stock Exchange Sub-Sector Telecommunication Period 2," OSF Preprints f3dv5, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:f3dv5
    DOI: 10.31219/osf.io/f3dv5
    as

    Download full text from publisher

    File URL: https://osf.io/download/6019f2b2dd22250648589525/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/f3dv5?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. Zmijewski, Me, 1984. "Methodological Issues Related To The Estimation Of Financial Distress Prediction Models," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 22, pages 59-82.
    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. Christine V. Zavgren & Michael T. Dugan & James M. Reeve, 1988. "The Association Between Probabilities of Bankruptcy and Market Responses—A Test of Market Anticipation," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 15(1), pages 27-45, March.
    2. Matthew Smith & Francisco Alvarez, 2022. "Predicting Firm-Level Bankruptcy in the Spanish Economy Using Extreme Gradient Boosting," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 263-295, January.
    3. Ruey-Ching Hwang & Jhao-Siang Siao & Huimin Chung & C. Chu, 2011. "Assessing bankruptcy prediction models via information content of technical inefficiency," Journal of Productivity Analysis, Springer, vol. 36(3), pages 263-273, December.
    4. 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).
    5. Harlan Platt & Marjorie Platt, 2002. "Predicting corporate financial distress: Reflections on choice-based sample bias," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 26(2), pages 184-199, June.
    6. Richardson, Grant & Taylor, Grantley & Lanis, Roman, 2015. "The impact of financial distress on corporate tax avoidance spanning the global financial crisis: Evidence from Australia," Economic Modelling, Elsevier, vol. 44(C), pages 44-53.
    7. Garcia-Blandon, Josep & Argiles-Bosch, Josep Maria & Castillo-Merino, David & Martinez-Blasco, Monica, 2017. "An Assessment of the Provisions of Regulation (EU) No 537/2014 on Non-audit Services and Audit Firm Tenure: Evidence from Spain," The International Journal of Accounting, Elsevier, vol. 52(3), pages 251-261.
    8. Xavier Brédart & Eric Séverin & David Veganzones, 2021. "Human resources and corporate failure prediction modeling: Evidence from Belgium," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1325-1341, November.
    9. Postek, Łukasz & Thor, Michał, . "Modele predykcji bankructwa i ich zastosowanie dla rynku NewConnect," Gospodarka Narodowa-The Polish Journal of Economics, Szkoła Główna Handlowa w Warszawie / SGH Warsaw School of Economics, vol. 2020(1).
    10. Yihan Guo & Deborah Delaney & Ammad Ahmed, 2020. "Is an Auditor's Propensity to Issue Going Concern Opinions a Valid Measure of Audit Quality?," Australian Accounting Review, CPA Australia, vol. 30(2), pages 144-153, June.
    11. Dimitras, A. I. & Slowinski, R. & Susmaga, R. & Zopounidis, C., 1999. "Business failure prediction using rough sets," European Journal of Operational Research, Elsevier, vol. 114(2), pages 263-280, April.
    12. Bernard P.A. Santen & Auke de Bos, 2015. "The Effects of Legal Measures to Empower Supervisory Directors: Evidence from a Financial Distress Perspective," Journal of Management and Strategy, Journal of Management and Strategy, Sciedu Press, vol. 6(1), pages 45-61, February.
    13. Atanas Delev, 2016. "Issues and Challenges for Bankruptcy Risk Assessment in Bulgarian Companies," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 3, pages 118-136.
    14. Mohamed Sameh Gameel & Khairy El-Geziry, 2016. "Predicting Financial Distress: Multi Scenarios Modeling Using Neural Network," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 8(11), pages 159-166, November.
    15. Md. Borhan Uddin Bhuiyan & Solomon Opare & Zahir Ahmed, 2024. "Does Audit Committee Busyness Affect Financial Restatement? Evidence from Audit Committee Share Ownership," Australian Accounting Review, CPA Australia, vol. 34(1), pages 29-54, March.
    16. Chen, Xiao & Dai, Narisa Tianjing & Liu, Leo Jiahe, 2025. "Audit implications of major customer diversity," Journal of Contemporary Accounting and Economics, Elsevier, vol. 21(2).
    17. Meles, Antonio & Salerno, Dario & Sampagnaro, Gabriele & Verdoliva, Vincenzo & Zhang, Jianing, 2023. "The influence of green innovation on default risk: Evidence from Europe," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 692-710.
    18. Veres Ferrer, Ernesto Jesús & Labatut Serer, Gregorio & Pozuelo Campillo, Jose, 2009. "Hacia una ordenación de las pequeñas empresas atendiendo a su posible situación de fracaso/Towards a Ranking of Smaller Companies According to Their Failure Risk," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 27, pages 775(18á)-77, Diciembre.
    19. Jarmila Horváthová & Martina Mokrišová, 2018. "Risk of Bankruptcy, Its Determinants and Models," Risks, MDPI, vol. 6(4), pages 1-22, October.
    20. Stephen A. Hillegeist & Elizabeth K. Keating & Donald P. Cram & Kyle G. Lundstedt, 2004. "Assessing the Probability of Bankruptcy," Review of Accounting Studies, Springer, vol. 9(1), pages 5-34, March.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:osf:osfxxx:f3dv5. 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: OSF (email available below). General contact details of provider: https://osf.io/preprints/ .

    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.