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Proposal for a Decision Support System to Predict Financial Distress

Author

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  • Mãdãlina Ecaterina POPESCU

    () (The Bucharest University of Economic Studies, Romania)

Abstract

In the context of economic instability a decision support system that could provide early warning signals of financial distress to a company a few years before actually turning to insolvency could play an important role in the decision making processes inside a company. Thus, the aim of this paper consists in developing a decision support system for financial distress for the case of the Romanian companies listed on the Bucharest StockExchange. A practical solution for predicting financial distress with one or even two years in advance is presented and the results of the models’ prediction accuracy areencouraging us to believe that these models can actually improve the strategic management and planning departments in a company.

Suggested Citation

  • Mãdãlina Ecaterina POPESCU, 2015. "Proposal for a Decision Support System to Predict Financial Distress," REVISTA DE MANAGEMENT COMPARAT INTERNATIONAL/REVIEW OF INTERNATIONAL COMPARATIVE MANAGEMENT, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 16(1), pages 112-118, March.
  • Handle: RePEc:rom:rmcimn:v:16:y:2015:i:1:p:112-118
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    File URL: http://rmci.ase.ro/no16vol1/09.pdf
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    References listed on IDEAS

    as
    1. Mădălina Ecaterina ANDREICA, 2013. "Early warning models of financial distress. Case study of the Romanian firms listed on RASDAQ," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(5(582)), pages 7-14, May.
    2. Marin ANDREICA & Mãdãlina Ecaterina POPESCU & Dragos MICU, 2014. "Proposal of a SMEs Forecast Management Support System," REVISTA DE MANAGEMENT COMPARAT INTERNATIONAL/REVIEW OF INTERNATIONAL COMPARATIVE MANAGEMENT, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 15(2), pages 237-243, May.
    3. 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.
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    5. Eisenbeis, Robert A, 1977. "Pitfalls in the Application of Discriminant Analysis in Business, Finance, and Economics," Journal of Finance, American Finance Association, vol. 32(3), pages 875-900, June.
    6. Andreica, Madalina Ecaterina & Andreica, Marin, 2014. "Forecast of Romanian Industry Employment using Simulation and Panel Data Models," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 130-140, June.
    7. repec:bla:joares:v:4:y:1966:i::p:71-111 is not listed on IDEAS
    8. Chae Woo Nam & Tong Suk Kim & Nam Jung Park & Hoe Kyung Lee, 2008. "Bankruptcy prediction using a discrete-time duration model incorporating temporal and macroeconomic dependencies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(6), pages 493-506.
    9. Shumway, Tyler, 2001. "Forecasting Bankruptcy More Accurately: A Simple Hazard Model," The Journal of Business, University of Chicago Press, vol. 74(1), pages 101-124, January.
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    Cited by:

    1. repec:rom:mancon:v:11:y:2017:i:1:p:99-106 is not listed on IDEAS

    More about this item

    Keywords

    SMEs; decision support system; financial distress; prediction.;

    JEL classification:

    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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