IDEAS home Printed from https://ideas.repec.org/a/prg/jnlefa/v2016y2016i3id161p39-52.html
   My bibliography  Save this article

Empirical Safety Thresholds for Liquidity and Indebtedness Ratios on the Polish Capital Market

Author

Listed:
  • Jacek Welc

Abstract

One of the elements of company's evaluation is ratio analysis. It includes computation of bankruptcy risk metrics. There are multiple such measures, of which two seem to be quite universal and commonly applied. These are current ratio and indebtedness ratio. In this study, the accuracy of bankruptcy predictions based on these two ratios is evaluated within a sample of data from the Polish market. Also, the safety thresholds (meant as values at which the probability of bankruptcy exceeds fifty percent) are estimated. The study is based on a sample of 84 companies, in which case a bankruptcy filing was announced in a period between the beginning of 2009 and the end of the first half of 2015. This sample of bankrupt firms is compared to the counter-sample of companies in which case no any bankruptcy filing occurred. The statistical analysis has confirmed the usefulness of both ratios. Even though the sample covers wide variety of businesses, the logit models with only one ratio used as an explanatory variable are capable of identifying bankrupt firms in about 70-73% of cases. Our research has also shown that the estimated safety thresholds lie near the typically assumed "rules of thumb".

Suggested Citation

  • Jacek Welc, 2016. "Empirical Safety Thresholds for Liquidity and Indebtedness Ratios on the Polish Capital Market," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2016(3), pages 39-52.
    • Handle: RePEc:prg:jnlefa:v:2016:y:2016:i:3:id:161:p:39-52
    DOI: 10.18267/j.efaj.161
    as

    Download full text from publisher

    File URL: http://efaj.vse.cz/doi/10.18267/j.efaj.161.html
    Download Restriction: free of charge
    File URL: http://efaj.vse.cz/doi/10.18267/j.efaj.161.pdf
    Download Restriction: free of charge
    File URL: https://libkey.io/10.18267/j.efaj.161?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. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    2. Zmijewski, Me, 1984. "Methodological Issues Related To The Estimation Of Financial Distress Prediction Models," Journal of Accounting Research, Wiley Blackwell, vol. 22, pages 59-82.
    3. Sudheer Chava & Robert A. Jarrow, 2008. "Bankruptcy Prediction with Industry Effects," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 21, pages 517-549, World Scientific Publishing Co. Pte. Ltd..
    4. Chris Charalambous & Andreas Charitou & Froso Kaourou, 2000. "Comparative Analysis of Artificial Neural Network Models: Application in Bankruptcy Prediction," Annals of Operations Research, Springer, vol. 99(1), pages 403-425, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Madalina Ecaterina Popescu & Victor Dragotă, 2018. "What Do Post-Communist Countries Have in Common When Predicting Financial Distress?," Prague Economic Papers, Prague University of Economics and Business, vol. 2018(6), pages 637-653.
    2. repec:prg:jnlpep:v:preprint:id:664:p:1-17 is not listed 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. Ilyes Abid & Farid Mkaouar & Olfa Kaabia, 2018. "Dynamic analysis of the forecasting bankruptcy under presence of unobserved heterogeneity," Annals of Operations Research, Springer, vol. 262(2), pages 241-256, March.
    2. Mohammad Mahdi Mousavi & Jamal Ouenniche, 2018. "Multi-criteria ranking of corporate distress prediction models: empirical evaluation and methodological contributions," Annals of Operations Research, Springer, vol. 271(2), pages 853-886, December.
    3. 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).
    4. John Y. Campbell & Jens Hilscher & Jan Szilagyi, 2008. "In Search of Distress Risk," Journal of Finance, American Finance Association, vol. 63(6), pages 2899-2939, December.
    5. Elizabeth Demers & Philip Joos, 2007. "IPO Failure Risk," Journal of Accounting Research, Wiley Blackwell, vol. 45(2), pages 333-371, May.
    6. Koresh Galil & Neta Gilat, 2019. "Predicting Default More Accurately: To Proxy or Not to Proxy for Default?," International Review of Finance, International Review of Finance Ltd., vol. 19(4), pages 731-758, December.
    7. Ahsan Habib & Mabel D' Costa & Hedy Jiaying Huang & Md. Borhan Uddin Bhuiyan & Li Sun, 2020. "Determinants and consequences of financial distress: review of the empirical literature," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(S1), pages 1023-1075, April.
    8. Huang, Hsing-Hua & Lee, Han-Hsing, 2013. "Product market competition and credit risk," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 324-340.
    9. Ruey-Ching Hwang & Huimin Chung & Jiun-Yi Ku, 2013. "Predicting Recurrent Financial Distresses with Autocorrelation Structure: An Empirical Analysis from an Emerging Market," Journal of Financial Services Research, Springer;Western Finance Association, vol. 43(3), pages 321-341, June.
    10. Asis, Gonzalo & Chari, Anusha & Haas, Adam, 2021. "In search of distress risk in emerging markets," Journal of International Economics, Elsevier, vol. 131(C).
    11. Lyandres, Evgeny & Zhdanov, Alexei, 2013. "Investment opportunities and bankruptcy prediction," Journal of Financial Markets, Elsevier, vol. 16(3), pages 439-476.
    12. Ruey-Ching Hwang & K. F. Cheng & Jack C. Lee, 2007. "A semiparametric method for predicting bankruptcy," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(5), pages 317-342.
    13. Aggarwal, Nidhi & Singh, Manish K. & Thomas, Susan, 2023. "Do decreases in Distance-to-Default predict rating downgrades?," Economic Modelling, Elsevier, vol. 129(C).
    14. Charitou, Andreas & Dionysiou, Dionysia & Lambertides, Neophytos & Trigeorgis, Lenos, 2013. "Alternative bankruptcy prediction models using option-pricing theory," Journal of Banking & Finance, Elsevier, vol. 37(7), pages 2329-2341.
    15. Mohammad Mahdi Mousavi & Jamal Ouenniche & Kaoru Tone, 2023. "A dynamic performance evaluation of distress prediction models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 756-784, July.
    16. Abinzano, Isabel & Gonzalez-Urteaga, Ana & Muga, Luis & Sanchez, Santiago, 2020. "Performance of default-risk measures: the sample matters," Journal of Banking & Finance, Elsevier, vol. 120(C).
    17. Anand Deo & Sandeep Juneja, 2021. "Credit Risk: Simple Closed-Form Approximate Maximum Likelihood Estimator," Operations Research, INFORMS, vol. 69(2), pages 361-379, March.
    18. du Jardin, Philippe, 2015. "Bankruptcy prediction using terminal failure processes," European Journal of Operational Research, Elsevier, vol. 242(1), pages 286-303.
    19. Jairaj Gupta & Andros Gregoriou & Jerome Healy, 2015. "Forecasting bankruptcy for SMEs using hazard function: To what extent does size matter?," Review of Quantitative Finance and Accounting, Springer, vol. 45(4), pages 845-869, November.
    20. 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.

    More about this item

    Keywords

    Bankruptcy prediction; Current ratio; Financial liquidity; Fundamental analysis; Indebtedness ratio; Ratio analysis;
    All these keywords.

    JEL classification:

    • 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:jnlefa:v:2016:y:2016:i:3:id:161:p:39-52. 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.