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Innovated Altman’s Model as a Predictor of Malfunctioning of Small and Medium-Sized Businesses in Bosnia and Herzegovina

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  • Vidimlić Selma

    (JP “Tržnica” Ltd. Zenica, Bosnia and Herzegovina)

Abstract

The research was conducted with the aim of finding a model that best predicts the financial success or failure of the company. On the sample of 392 SME in Bosnia and Herzegovina, testing possibilities using the innovated Altman’s model for prediction of financial difficulties of the enterprise was carried out. The financial statements from the end of the year 2014 of these companies were reviewed. The sample was divided into two groups: companies that had blocked transaction accounts during 2015 and 2016 and those companies that did not have blocked transaction accounts during this period. Testing has shown that the Altman’s model may, but with limited capability, be used to predict the disruption of small and medium-sized businesses in Bosnia and Herzegovina. The paper presents the facts that affect the business of SME in Bosnia and Herzegovina, and way they influence selection and, possibly, other predictors of non-business operations

Suggested Citation

  • Vidimlić Selma, 2019. "Innovated Altman’s Model as a Predictor of Malfunctioning of Small and Medium-Sized Businesses in Bosnia and Herzegovina," Economic Themes, Sciendo, vol. 57(1), pages 21-33, March.
    • Handle: RePEc:vrs:ecothe:v:57:y:2019:i:1:p:21-33:n:2
    DOI: 10.2478/ethemes-2019-0002
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    References listed on IDEAS

    as
    1. 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.
    2. Edward I. Altman & Gabriele Sabato, 2013. "MODELING CREDIT RISK FOR SMEs: EVIDENCE FROM THE US MARKET," World Scientific Book Chapters, in: Oliviero Roggi & Edward I Altman (ed.), Managing and Measuring Risk Emerging Global Standards and Regulations After the Financial Crisis, chapter 9, pages 251-279, World Scientific Publishing Co. Pte. Ltd..
    3. Mramor, Dusan & Valentincic, Aljosa, 2003. "Forecasting the liquidity of very small private companies," Journal of Business Venturing, Elsevier, vol. 18(6), pages 745-771, November.
    4. 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.
    5. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    6. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure - Reply," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 123-127.
    7. Shaike Marom & Robert N. Lussier, 2014. "A Business Success Versus Failure Prediction Model for Small Businesses in Israel," Business and Economic Research, Macrothink Institute, vol. 4(2), pages 63-81, December.
    8. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    prediction; SME; Altman’s model; financial failure; business distress; financial indicator;
    All these keywords.

    JEL classification:

    • M40 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - General
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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