IDEAS home Printed from https://ideas.repec.org/a/osi/journl/v5y2009p607-616.html
   My bibliography  Save this article

Financial Instability Prediction in Manufacturing and Service Industry

Author

Listed:
  • Robert Zenzerovic

    (Juraj Dobrila University of Pula, Department of Economics and Tourism “Dr. Mijo Mirkovic”, Croatia)

Abstract

This article presents an attempt to derive models for financial instability prediction in manufacturing and service industry especially suitable for transitional environments. Research results indicate that the most important ratios – independent variables that discriminate financially stable from unstable companies consist of liquidity, solvency and profitability ratios. Financial instability models have high degree of diagnostic and prognostic power what was statistically validated on the sample units. Aforementioned predictive ability makes these models appropriate tools for predicting the degree of financial stability of company’s business partners as well as useful instrument in estimating the appropriateness of going concern assumption for company itself. Financial instability models can be used, not only as instrument for choosing adequate business partners, but also as a tool for estimating the level and trends of financial stability in manufacturing and service industry on macro level preseting in this way instrument for macro policy decision makers.

Suggested Citation

  • Robert Zenzerovic, 2009. "Financial Instability Prediction in Manufacturing and Service Industry," Interdisciplinary Management Research, Josip Juraj Strossmayer University of Osijek, Faculty of Economics, Croatia, vol. 5, pages 607-616.
  • Handle: RePEc:osi:journl:v:5:y:2009:p:607-616
    as

    Download full text from publisher

    File URL: http://www.efos.hr/repec/osi/journl/PDF/InterdisciplinaryManagementResearchV/IMR5a50.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Deakin, Eb, 1972. "Discriminant Analysis Of Predictors Of Business Failure," Journal of Accounting Research, Wiley Blackwell, vol. 10(1), pages 167-179.
    2. 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.
    3. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    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. Zhou, Fanyin & Fu, Lijun & Li, Zhiyong & Xu, Jiawei, 2022. "The recurrence of financial distress: A survival analysis," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1100-1115.
    2. 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.
    3. 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.
    4. Lin, Fengyi & Yeh, Ching Chiang & Lee, Meng Yuan, 2013. "A Hybrid Business Failure Prediction Model Using Locally Linear Embedding And Support Vector Machines," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 82-97, March.
    5. Lillian Cheung & Amnon Levy, 1998. "An integrative analysis of business bankruptcy in Australia," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 22(2), pages 149-167, June.
    6. Chen, An-Sing & Chu, Hsiang-Hui & Hung, Pi-Hsia & Cheng, Miao-Sih, 2020. "Financial risk and acquirers' stockholder wealth in mergers and acquisitions," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    7. Taieb Hamadi & Sami El Omari, & Wafa Khlif, 2012. "Poids De L'Avis De L'Expert Comptable Judiciaire Dans La Decision Du Juge En Matiere De Redressement Judiciaire : Cas De La Tunisie," Post-Print hal-00937922, HAL.
    8. Youssef Zizi & Mohamed Oudgou & Abdeslam El Moudden, 2020. "Determinants and Predictors of SMEs’ Financial Failure: A Logistic Regression Approach," Risks, MDPI, vol. 8(4), pages 1-21, October.
    9. Catherine Refait, 2004. "La prévision de la faillite fondée sur l’analyse financière de l’entreprise : un état des lieux," Économie et Prévision, Programme National Persée, vol. 162(1), pages 129-147.
    10. Balcaen, Sofie & Ooghe, Hubert, 2006. "35 years of studies on business failure: an overview of the classic statistical methodologies and their related problems," The British Accounting Review, Elsevier, vol. 38(1), pages 63-93.
    11. Nicoleta BARBUTA-MISU, 2011. "A Specific Model for Assessing the Financial Performance:Case study on Building Sector Enterprises of Galati County - Romania," Risk in Contemporary Economy, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, pages 318-325.
    12. Amin Jan & Maran Marimuthu & Muhammad Kashif Shad & Haseeb ur-Rehman & Muhammad Zahid & Ahmad Ali Jan, 2019. "Bankruptcy profile of the Islamic and conventional banks in Malaysia: a post-crisis period analysis," Economic Change and Restructuring, Springer, vol. 52(1), pages 67-87, February.
    13. Fayçal Mraihi, 2016. "Distressed Company Prediction Using Logistic Regression: Tunisian’s Case," Quarterly Journal of Business Studies, Research Academy of Social Sciences, vol. 2(1), pages 34-54.
    14. Hu, Yu-Chiang & Ansell, Jake, 2007. "Measuring retail company performance using credit scoring techniques," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1595-1606, December.
    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. García-Gallego, Ana & Mures-Quintana, María-Jesús, 2013. "La muestra de empresas en los modelos de predicción del fracaso: influencia en los resultados de clasificación || The Sample of Firms in Business Failure Prediction Models: Influence on Classification," 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. 15(1), pages 133-150, June.
    17. du Jardin, Philippe, 2015. "Bankruptcy prediction using terminal failure processes," European Journal of Operational Research, Elsevier, vol. 242(1), pages 286-303.
    18. Eleonora Bartoloni & Maurizio Baussola, 2014. "Financial Performance in Manufacturing Firms: A Comparison Between Parametric and Non-Parametric Approaches," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 49(1), pages 32-45, January.
    19. Ha-Thu Nguyen, 2014. "Default Predictors in Credit Scoring - Evidence from France’s Retail Banking Institution," EconomiX Working Papers 2014-26, University of Paris Nanterre, EconomiX.
    20. repec:ctc:sdimse:dime21_01 is not listed on IDEAS
    21. Michal Karas & Mária Režňáková, 2017. "The Potential of Dynamic Indicator in Development of the Bankruptcy Prediction Models: the Case of Construction Companies," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 65(2), pages 641-652.

    More about this item

    Keywords

    Financial crisis; bankruptcy; loss above equity; financial instability prediction models; discriminant analysis; manufacturing and service industry;
    All these keywords.

    JEL classification:

    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • O16 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Financial Markets; Saving and Capital Investment; Corporate Finance and Governance

    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:osi:journl:v:5:y:2009:p:607-616. 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: Hrvoje Serdarusic, PhD (email available below). General contact details of provider: https://edirc.repec.org/data/efosihr.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.