Bankruptcy Prediction Models in Galician companies. Application of Parametric Methodologies and Artificial Intelligence
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- McKee, Thomas E. & Lensberg, Terje, 2002. "Genetic programming and rough sets: A hybrid approach to bankruptcy classification," European Journal of Operational Research, Elsevier, vol. 138(2), pages 436-451, April.
- R. Slowinski & C. Zopounidis, 1995. "Application of the Rough Set Approach to Evaluation of Bankruptcy Risk," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 4(1), pages 27-41, March.
- Peel, MJ & Peel, DA & Pope, PF, 1986. "Predicting corporate failure-- Some results for the UK corporate sector," Omega, Elsevier, vol. 14(1), pages 5-12.
- 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.
- Martin, Daniel, 1977. "Early warning of bank failure : A logit regression approach," Journal of Banking & Finance, Elsevier, vol. 1(3), pages 249-276, November.
- Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
- 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.
- Hian Koh & Sen Tan, 1999. "A neural network approach to the prediction of going concern status," Accounting and Business Research, Taylor & Francis Journals, vol. 29(3), pages 211-216.
- Carcello, Jv & Palmrose, Zv, 1994. "Auditor Litigation And Modified Reporting On Bankrupt Clients," Journal of Accounting Research, Wiley Blackwell, vol. 32, pages 1-30.
- Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
- Lam, Kevin C.K. & Mensah, Yaw M., 2006. "Auditors' decision-making under going-concern uncertainties in low litigation-risk environments: Evidence from Hong Kong," Journal of Accounting and Public Policy, Elsevier, vol. 25(6), pages 706-739.
- Thomas E. McKee, 2003. "Rough sets bankruptcy prediction models versus auditor signalling rates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(8), pages 569-586.
- Simunic, Da, 1984. "Auditing, Consulting, And Auditor Independence," Journal of Accounting Research, Wiley Blackwell, vol. 22(2), pages 679-702.
- Pindado, Julio & Rodrigues, Luis & de la Torre, Chabela, 2008. "Estimating financial distress likelihood," Journal of Business Research, Elsevier, vol. 61(9), pages 995-1003, September.
- Frydman, Halina & Altman, Edward I & Kao, Duen-Li, 1985. "Introducing Recursive Partitioning for Financial Classification: The Case of Financial Distress," Journal of Finance, American Finance Association, vol. 40(1), pages 269-291, March.
- 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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More about this item
Keywords
Business Failure; Financial Distress; Prediction of Insolvency; Audit Reports;All these keywords.
JEL classification:
- G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
- C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
- C59 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Other
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