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Fallibility Of The Rough Set Method In The Formulation Of The Failure Prediction Index Model Of Dynamic Risk

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  • Mosqueda, Rubén

    (Instituto Tecnologico y de Estudios Superiores de Monterrey (ITESM))

Abstract

Bankruptcy is one of the most important entrepreneurial problems studied by financial theory. Despite this great effort, there is not a significant progress in order to predict the economic failure. In this way, the evidence suggests that this problem, related to the experimental design, is still present because of two main reasons: ignorance about bankruptcy process and the use of the accounting information as the unique input to construct the predictive models. In order to solve those problems, the RPV Model included both qualitative and accounting information with excellent results. So, the Earning Power Theory – upon which the RPV is based – could cause problems of specification and structure in the model. Empirical results not only verify those suspicions, but they made a stronger model possible by introducing to the equation ERC values adjusted to the risk.

Suggested Citation

  • Mosqueda, Rubén, 2010. "Fallibility Of The Rough Set Method In The Formulation Of The Failure Prediction Index Model Of Dynamic Risk," Journal of Economics, Finance and Administrative Science, Universidad ESAN, vol. 15(28), pages 65-88.
    • Handle: RePEc:ris:joefas:0016
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    References listed on IDEAS

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    1. Rebecca L. Rosner, 2003. "Earnings Manipulation in Failing Firms," Contemporary Accounting Research, John Wiley & Sons, vol. 20(2), pages 361-408, June.
    2. Laitinen, Ek, 1993. "Financial predictors for different phases of the failure process," Omega, Elsevier, vol. 21(2), pages 215-228, March.
    3. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    4. Zmijewski, Me, 1984. "Methodological Issues Related To The Estimation Of Financial Distress Prediction Models," Journal of Accounting Research, Wiley Blackwell, vol. 22, pages 59-82.
    5. Wilcox, Jw, 1973. "Prediction Of Business Failure Using Accounting Data," Journal of Accounting Research, Wiley Blackwell, vol. 11, pages 163-179.
    6. Wilcox, Jw, 1971. "Simple Theory Of Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 9(2), pages 389-345.
    7. Libby, R, 1975. "Accounting Ratios And Prediction Of Failure - Some Behavioral Evidence," Journal of Accounting Research, Wiley Blackwell, vol. 13(1), pages 150-161.
    8. William F. Messier, Jr. & James V. Hansen, 1988. "Inducing Rules for Expert System Development: An Example Using Default and Bankruptcy Data," Management Science, INFORMS, vol. 34(12), pages 1403-1415, December.
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