IDEAS home Printed from https://ideas.repec.org/a/ids/injbaf/v3y2011i1p31-46.html
   My bibliography  Save this article

Entrepreneurship insolvency risk management: a case of Latvia

Author

Listed:
  • Irina Genriha
  • Gaida Pettere
  • Irina Voronova

Abstract

Financial crisis and its consequences are visible in the capital adequacy of many commercial banks, which indicates that the approach banks took to assess credit risk was not sufficiently sophisticated. This article discusses practical methods of insolvency risk modelling for enterprises. In this paper, the authors analysed the accuracy of ten models developed by foreign authors to assess insolvency risk, which were validated on the database of Latvian companies. The authors have shown that models developed on historical data for foreign companies are less accurate than the model developed on the basis of financial indicators of Latvian companies. The authors developed a three-factor model that estimates probability of default of Latvian enterprises based on historical data for 1,272 enterprises using binary logistic regression analysis.

Suggested Citation

  • Irina Genriha & Gaida Pettere & Irina Voronova, 2011. "Entrepreneurship insolvency risk management: a case of Latvia," International Journal of Banking, Accounting and Finance, Inderscience Enterprises Ltd, vol. 3(1), pages 31-46.
  • Handle: RePEc:ids:injbaf:v:3:y:2011:i:1:p:31-46
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=39370
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    Citations

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


    Cited by:

    1. Błażej Prusak, 2018. "Review of Research into Enterprise Bankruptcy Prediction in Selected Central and Eastern European Countries," IJFS, MDPI, vol. 6(3), pages 1-28, June.
    2. Beata Gavurova & Sylvia Jencova & Radovan Bacik & Marta Miskufova & Stanislav Letkovsky, 2022. "Artificial intelligence in predicting the bankruptcy of non-financial corporations," Oeconomia Copernicana, Institute of Economic Research, vol. 13(4), pages 1215-1251, December.
    3. Jonas Mackevičius & Ruta Šneidere & Daiva Tamulevičienė, 2018. "The waves of enterprises bankruptcy and the factors that determine them: the case of Latvia and Lithuania," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 6(1), pages 100-114, September.
    4. Jonas Mackevičius & Ruta Šneidere & Daiva Tamulevičienė, 2018. "The waves of enterprises bankruptcy and the factors that determine them: the case of Latvia and Lithuania," Post-Print hal-02121037, HAL.

    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:ids:injbaf:v:3:y:2011:i:1:p:31-46. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=277 .

    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.