IDEAS home Printed from https://ideas.repec.org/a/ovi/oviste/v11y2011i1p2283-2288.html
   My bibliography  Save this article

Building a Scoring Model for Bankruptcy Risk Prediction on Multiple Discriminant Analysis

Author

Listed:
  • Vintila Georgeta

    (Academy of Economic Studies, Bucharest)

  • Toroapa Maria Georgia

    (Academy of Economic Studies, Bucharest)

Abstract

The purpose of this paper is to use discriminant analysis to substantiate a score function effective in bankruptcy risk prediction of enterprises on Romanian economy example. For achieving discrimination between bankrupt and non-bankrupt in the scoring model we used relevant financial ratios related to activity, liquidity, leverage and profitability. The weighting coefficients established between independent variables and the objective function-score, are determined by using optimization, through a solver in Excel, with four financial ratios as input:return on revenue, cash-flow to debt ratio, debt to assets ratio, total debt payment period. Based on financial information submitted for 2009, the analysis was conducted on a sample of companies listed on the Bucharest Stock Exchang and achieved a success rate for the scoring model. The results in this article can be used to observe the evolution of a Romanian company over time, to make an idea about curent and future financial situation, and take, if necessary, corrective measures.

Suggested Citation

  • Vintila Georgeta & Toroapa Maria Georgia, 2011. "Building a Scoring Model for Bankruptcy Risk Prediction on Multiple Discriminant Analysis," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 2283-2288, May.
  • Handle: RePEc:ovi:oviste:v:11:y:2011:i:1:p:2283-2288
    as

    Download full text from publisher

    File URL: http://stec.univ-ovidius.ro/html/anale/RO/cuprins%20rezumate/rezumate2011p1.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    discriminant analysis; bankruptcy; prediction; financial ratios; score;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

    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:ovi:oviste:v:11:y:2011:i:1:p:2283-2288. 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: Gheorghiu Gabriela (email available below). General contact details of provider: https://edirc.repec.org/data/feoviro.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.