References

Altman, E.I., 1968. Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. J. Finance, 23: 589-609.
CrossRef  |  Direct Link  |  

Altman, E.I., 1993. Corporate Financial Distress and Bankruptcy: A Complete Guide to Predicting and Avoiding Distress and Profiting from Bankruptcy. 2nd Edn., John Wiley Sons Inc., USA., ISBN-13: 9780471552536, Pages: 384.

Amiri, G.H.S., 2002. Evaluation of predictors of bankruptcy in the environmental conditions of Iran. Ph.D Thesis, University of Tehran, Tehran, Iran.

Amiri, G.S., 2003. Financial ratios to predict financial crises of companies in the Tehran Stock Exchange. Tehran Univ. Sch. Manage. J., 15: 121-136.

Beaver, W.H., 1966. Financial ratios as predictors of failure. J. Account. Res., 4: 71-111.
Direct Link  |  

Chen, W.S. and Y.K. Du, 2009. Using neural networks and data mining techniques for the financial distress prediction model. Expert Syst. Appl., 36: 4075-4086.
CrossRef  |  Direct Link  |  

Foster, G., 1985. Financial Statement Analysis. Prentice-Hill Inc, New Jersey, USA.,.

Jantadej, P., 2006. Using the combinations of cash flow components to predict financial distress. Master Thesis, University of Nebraska-Lincoln, Lincoln, Nebraska.

Lensberg, T., A. Eilifsen and T.E. McKee, 2006. Bankruptcy theory development and classification via genetic programming. Eur. J. Oper. Res., 169: 677-697.
Direct Link  |  

Nia, S.K., 2010. Prediction of the financial crisis of listed companies on Tehran Stock Exchange using genetic algorithms. Master Thesis, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran.

Saeed, F., 2004. Financial distress prediction of companies using Artificial Neural Networks (ANN). Master Thesis, Tehran University, Tehran, Iran.

Sayed, N.M., A.M.S. Taqi and K.T. Salim, 2010. Comparing the models of artificial neural networks and discriminant analysis, logistic regression as methods for predicting bankruptcy of companies. Econ. Res. Q., 2: 161-164.

Shin, K.S. and Y.J. Lee, 2002. A genetic algorithm application in bankruptcy prediction modeling. Expert Syst. Appl., 23: 321-328.
CrossRef  |