ISSN: 2225-8329
Open access
Bankruptcy is one of the key issues across the globe which influences the economy of all the countries. Heavy social investigating the research literature and providing some definitions on bankruptcy and its reasons, we will deal with different modes of predicting bankruptcy in two groups of parametric and non-parametric. Non-parametric methods such as neural networks have high level efficiency and accuracy due to their unique features compared to statistical model.and economic costs which are imposed by bankrupted companies on stockholders can cause motivation of researchers in providing different methods for predicting bankruptcy.
Altman, E. (1968). Financial ratios, Discriminant analysis and the prediction of corporate bankruptcy. Journal of Finance. 4 (September), pp. 54-89.
Altman, E. L. (1993), “Corporate financial distress and bankruptcy”, New York: NY, John Wiley & Sons Inc.
Altman, E. L., Marco, G., & Varetto, F. (1994), “Corporate distress diagnosis: Comparisons using linear Discriminant analysis and neural networks (the Italian Experience)”, Journal of Banking and Finance 18, pp. 505-529.
Beaver, W. H. (1966). Financial ratios as predictors of bankruptcy. Journal of Accounting Research 4, pp. 71-111.
Back, B., Laitinen, T., Sere, K., and Van Wezel, M. (1996), “Coosing bankruptcy predictors using dicriminant analysis, logit analysis, and genetic algorithms”, Turk Center for Computer Science, Technical Report No.40, www.google.com.
Dun and Bradstreet. (1998). Bankruptcy Insolvency Accounting Practice and Procedure. Wilcy, pp. 21-41.
Doumpos, M., and Zopounidis, C. (1999), A multicriteria discrimination method for the prediction of financial distress: The case of Greece, Multinational Finance Journal, vol. 3, no. 2, pp. 71-101.
Dimitras, A., Zanakis, A., Zopoudinis, C. (1996). A survey of business failures with an emphasis on failure prediction methods and industrial applications. European Journal of Operational Research. 90 (3), pp. 487-513.
Deakin, E. B. (1972). “A discriminating analysis of predictors of business failure”, Journal of Accounting Research 10(1), pp. 167-179.
Edmister, R. O. (1972), “An empirical test of financial ratio analysis for small business failure prediction”, Journal of Financial and Quantitative Analysis 7(2), pp. 1477-1493.
Frydman, H., Altman, E. I., KAO, D. (1985). “Introducing Recursive Partitioning for financial classification: The case of financial distress”, The Journal of Finance, XL (1), pp. 269-291.
Gordon, M. J. (1971). Towards Theory of Financial Distress. The Journal of Finance, pp. 74-56.
Johnson, C. G. (1970). “Ratio Analysis and the Prediction of Firm Failure”, The Journal of Finance 25(5), pp. 1166-1168.
Morris, R. C. (1997). “Early warning indicators of corporate failure: A critical review of previous research and further empirical evidence”, Aldershot, England: Ashgate publishing limited.
Rumelhart, D. E., Hinton, E., Williams, J. (1986). Warning internal representation by error propagation. Parallel Distributed Processing 1, pp. 318-362.
In-Text Citation: (Kasgari, 2013)
To Cite this Article: Kasgari, A. A., Salehnezhad, S. H., & Ebadi, F. (2013). A Review of Bankruptcy and its Prediction. International Journal of Academic Research in Accounting Finance and Management Sciences. 3(4), 364 – 369.
Copyright: © 2013 The Author(s)
Published by Human Resource Management Academic Research Society (www.hrmars.com)
This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at: http://creativecommons.org/licences/by/4.0/legalcode