Prediction of corporate financial health by Artificial Neural Network

International Journal of Electronic Finance

Volumn 1, Issue 4, 2007, Pages 442-459

  Chakraborty, Sumit ^a   Sharma, Sushil K ^b  

^a INDIAN INSTITUTE OF MANAGEMENT CALCUTTA   (India)

^b BALL STATE UNIVERSITY   (United States)

Author keywords

ANNs; Artificial Neural Networks; Corporate failure prediction; Financial health

Indexed keywords

EID: 53349099307     PISSN: 17460069     EISSN: 17460077     Source Type: Journal    
DOI: 10.1504/IJEF.2007.012898     Document Type: Article

References (94)

1. Abdelazim, H.Y. and Wahba, K. (2006) 'An artificial intelligence approach to portfolio selection and management', International Journal of Financial Services Management, Vol. 1, Nos. 2-3, pp.243-254.
2. Alici, Y. (1995) 'Neural networks in corporate failure prediction: The UK experience', in Y. Abu-Mostafa, J. Moody and A. Weigend (Eds.) Proc. Third International Conf. Neural Networks in the Capital Markets, London, UK, pp.393-406.
3. Altman, E.I. (1968) 'Financial ratios, discriminant analysis and the prediction of corporate bankruptcy', The Journal of Finance, Vol. 23, No. 4, pp.589-609.
4. Altman, E.I. (1984) 'The success of business failure prediction models - an international survey', Journal of Banking and Finance, Vol. 8, pp.171-198.
5. Altman, E.I. and Saunders, A. (1998) 'Credit risk measurement: Developments over the last 20 years', Journal of Banking and Finance, Vol. 21, Nos. 11-12, pp.1721-1742.
6. Altman, E.I., Marco, G. and Varetto, F. (1994) 'Corporate distress diagnosis comparisons using linear discriminant analysis and neural networks', Journal of Banking and Finance, Vol. 18, No. 3, pp.505-529.
7. Atiya, A.F. (2001) 'Bankruptcy prediction for credit risk using neural networks: A survey and new results', IEEE Transactions on Neural Networks, Vol. 12, No. 4, pp.929-935.
8. Back, B., Laitinen, T. and Sere, K. (1996a) 'Neural networks and bankruptcy prediction: Funds flows, accrual ratios and accounting data', Advances in Accounting, Vol. 14, pp.23-37.
9. Back, B., Laitinen, T. and Sere, K. (1996b) 'Neural networks and genetic algorithms for bankruptcy predictions', Expert System Application, pp.407-413.
10. Bansal, R.C. and Pandey, J.C. (2005) 'Load forecasting using artificial intelligence techniques: A literature survey', International Journal of Computer Applications in Technology, Vol. 22, Nos. 2-3, pp.109-119.
11. Beaver, W. (1967) 'Financial ratios predictors of failure. Empirical research in accounting: Selected studies 1966', Journal of Accounting Research, Supplement to Vol. 4, pp.71-111.
12. Becchetti, L. and Sierra, J. (2002) 'Bankruptcy risk and productive efficiency in manufacturing firms', Journal of Banking and Finance, Vol. 27, pp.2099-2120.
13. Bell, T., Ribar, G. and Verchio, J. (1990) 'Neural nets vs. logistic regression: A comparison of each model's ability to predict commercial bank failures', Proceedings of the 1990 Deloitte & Touche/University of Kansas Symposium on Auditing Problems, pp.29-58.
14. Bishop, C.M. (1995) Neural Networks for Pattern Recognition, Oxford University Press.
15. Boritz, J., Kennedy, D. and Albuquerque, A. (1995) 'Predicting corporate failure using a neural network approach', Intelligent Systems in Accounting, Finance and Management, Vol. 4, pp.95-111.
16. Boucher, J. (1990) 'Artificial neural systems and the prediction of corporate failure', Master's Project, School of Accountancy, University of Waterloo.
17. Chen, W.H., Shih, J.Y. and Wu, S. (2006) 'Comparison of support-vector machines and back propagation neural networks in forecasting the six major Asian stock markets', International Journal of Electronic Finance, Vol. 1, No. 1, pp.49-67.
18. Coats, P. and Fant, L. (1993) 'Recognizing financial distress patterns using a neural network tool', Financial Management, Vol. 22, pp.142-155.
19. Cybinski, P. (2000) 'The path to failure: where are bankruptcy studies at now?', Journal of Business and Management, Vol. 7, No. 1, pp.11-39.
20. Dave, D.S., Aggarwal, A.K. and Challa, C.D. (2006) 'Pricing analysis of decision-making software: Modelling and artificial intelligence approaches', International Journal of Computer Applications in Technology, Vol. 26, No. 4, pp.175-181.
21. Dimitras, A., Zanakis, S. and Zopudinis, C. (1996) 'A survey of business failures with an emphasis on failure prediction methods and industrial applications', European Journal of Operational Research, Vol. 90, No. 3, pp.487-513.
22. Faining, K. and Cogger, K. (1994) 'A comparative analysis of artificial neural networks using financial distress prediction', International Journal of Intelligent Systems in Accounting, Finance and Management, Vol. 3, No. 3, pp.241-252.
23. Fausett, L. (1994) Fundamentals of Neural Networks, Prentice-Hall.
24. Fletcher, D. and Goss, E. (1993) 'Forecasting with neural networks: An application using bankruptcy data', Information and Management, Vol. 24, No. 3, pp.159-167.
25. Frydman, H., Altman, E.I. and Kao, D.L. (1985) 'Introducing recursive partitioning for financial classification: The case of financial distress', Journal of Finance, Vol. 40, No. 1, pp.269-291.
26. Gloubos, G. and Grammatikos, T. (1988) 'The success of bankruptcy prediction models in Greece', Studies in Banking and Finance, Vol. 7, pp.37-46.
27. Gupta, Y., Rao, R. and Bagchi, P. (1990) 'Linear goal programming as an alternative to multivariate discriminant analysis: A note', Journal of Business Finance and Accounting, Autumn, pp.593-598.
28. Gurney, K. (1997) An Introduction to Neural Networks, UCL Press.
29. Haweley, D.D. and Johnson, J.D. (1994) Artificial Neural Networks: Past, Present and Future: An Overview of the Structure and Training of Artificial Learning Systems in Advances in Artificial Intelligence in Economics, Finance and Management, by Johnson and Whinston (Eds.) Vol. 1, pp.1-24.
30. Hawley, D.D., Johnson, J.D. and Raina, D. (1990) 'Artificial neural systems: A new tool for financial decision-making', Financial Analysts Journal, Vol. 46, No. 6, pp.63-72.
31. Haykin, S. (1999) Neural Networks, Prentice Hall, Vol. 2.
32. Jones, F.L. (1987) 'Current techniques in bankruptcy prediction', Journal of Accounting Literature, Vol. 6, pp.131-164.
33. Kamruzzaman, J., Begg, R. and Sarker, R. (2006) Artificial Neural Networks in Finance and Manufacturing, USA: Idea Group Publications.
34. Keasey, K. and Watson, R. (1991) 'Financial distress models: A review of their usefulness', British Journal of Management, Vol. 2, No. 2, pp.89-102.
35. Kim, K.S. (2005) 'Examining corporate bankruptcy: An artificial intelligence approach', International Journal of Business Performance Management, Vol. 7, No. 3, pp.241-254.
36. Kudyba, S., Hamar, G.B. and Gandy, W.M. (2006) 'Utilising neural network applications to enhance efficiency in the healthcare industry: Predicting populations of future chronic illness', International Journal of Business Intelligence and Data Mining, Vol. 1, No. 4, pp.371-383.
37. Lacher, R.C., et al. (1995) 'A neural network for classifying the financial health of a firm', European Journal of Operation Research, Vol. 85, pp.53-65.
38. Lane, W.R., Looney, S.W. and Wansley, J.W. (1986) 'An application of the Cox proportional hazards model to bank failure', Journal of Banking and Finance, Vol. 10, pp.511-531.
39. Leigh, W., Purvis, R. and Ragusa, J.M. (2002) 'Forecasting the NYSE composite index with technical analysis, pattern recognizer, neural networks, and genetic algorithm: A case study in romantic decision support', Decision Support Systems, Vol. 32, No. 4, pp.361-377.
40. Liang, T.P., Chandler, J.S., Han, I. and Roan, J. (1992) 'An empirical investigation of some data effects on the classification accuracy of probit, ID3, and neural networks', Contemporary Accounting Research, Vol. 9, No. 1, pp.306-328.
41. Luoma, M. and Laitinen, E.K. (1991) 'Survival analysis as a tool for company failure prediction', Omega International Journal of Management Science, Vol. 19, No. 6, pp.673-678.
42. McKee, T.E. and Greenstein, M. (2000) 'Predicting bankruptcy using recursive partitioning and a realistically proportioned data set', J. Forecasting, Vol. 19, pp.219-230.
43. Dimitras, A., Zanakis, S. and Zopudinis, C. (1996) 'A survey of business failures with an emphasis on failure prediction methods and industrial applications', European Journal of Operational Research, Vol. 90, No. 3, pp.487-513.
44. Faining, K. and Cogger, K. (1994) 'A comparative analysis of artificial neural networks using financial distress prediction', International Journal of Intelligent Systems in Accounting, Finance and Management, Vol. 3, No. 3, pp.241-252.
45. Fausett, L. (1994) Fundamentals of Neural Networks, Prentice-Hall.
46. Fletcher, D. and Goss, E. (1993) 'Forecasting with neural networks: An application using bankruptcy data', Information and Management, Vol. 24, No. 3, pp.159-167.
47. Frydman, H., Altman, E.I. and Kao, D.L. (1985) 'Introducing recursive partitioning for financial classification: The case of financial distress', Journal of Finance, Vol. 40, No. 1, pp.269-291.
48. Gloubos, G. and Grammatikos, T. (1988) 'The success of bankruptcy prediction models in Greece', Studies in Banking and Finance, Vol. 7, pp.37-46.
49. Gupta, Y., Rao, R. and Bagchi, P. (1990) 'Linear goal programming as an alternative to multivariate discriminant analysis: A note', Journal of Business Finance and Accounting, Autumn, pp.593-598.
50. Gurney, K. (1997) An Introduction to Neural Networks, UCL Press.
51. Haweley, D.D. and Johnson, J.D. (1994) Artificial Neural Networks: Past, Present and Future: An Overview of the Structure and Training of Artificial Learning Systems in Advances in Artificial Intelligence in Economics, Finance and Management, by Johnson and Whinston (Eds.) Vol. 1, pp.1-24.
52. Hawley, D.D., Johnson, J.D. and Raina, D. (1990) 'Artificial neural systems: A new tool for financial decision-making', Financial Analysts Journal, Vol. 46, No. 6, pp.63-72.
53. Haykin, S. (1999) Neural Networks, Prentice Hall, Vol. 2.
54. Jones, F.L. (1987) 'Current techniques in bankruptcy prediction', Journal of Accounting Literature, Vol. 6, pp.131-164.
55. Kamruzzaman, J., Begg, R. and Sarker, R. (2006) Artificial Neural Networks in Finance and Manufacturing, USA: Idea Group Publications.
56. Keasey, K. and Watson, R. (1991) 'Financial distress models: A review of their usefulness', British Journal of Management, Vol. 2, No. 2, pp.89-102.
57. Kim, K.S. (2005) 'Examining corporate bankruptcy: An artificial intelligence approach', International Journal of Business Performance Management, Vol. 7, No. 3, pp.241-254.
58. Kudyba, S., Hamar, G.B. and Gandy, W.M. (2006) 'Utilising neural network applications to enhance efficiency in the healthcare industry: Predicting populations of future chronic illness', International Journal of Business Intelligence and Data Mining, Vol. 1, No. 4, pp.371-383.
59. Lacher, R.C., et al. (1995) 'A neural network for classifying the financial health of a firm', European Journal of Operation Research, Vol. 85, pp.53-65.
60. Lane, W.R., Looney, S.W. and Wansley, J.W. (1986) 'An application of the Cox proportional hazards model to bank failure', Journal of Banking and Finance, Vol. 10, pp.511-531.
61. Leigh, W., Purvis, R. and Ragusa, J.M. (2002) 'Forecasting the NYSE composite index with technical analysis, pattern recognizer, neural networks, and genetic algorithm: A case study in romantic decision support', Decision Support Systems, Vol. 32, No. 4, pp.361-377.
62. Liang, T.P., Chandler, J.S., Han, I. and Roan, J. (1992) 'An empirical investigation of some data effects on the classification accuracy of probit, ID3, and neural networks', Contemporary Accounting Research, Vol. 9, No. 1, pp.306-328.
63. Luoma, M. and Laitinen, E.K. (1991) 'Survival analysis as a tool for company failure prediction', Omega International Journal of Management Science, Vol. 19, No. 6, pp.673-678.
64. McKee, T.E. and Greenstein, M. (2000) 'Predicting bankruptcy using recursive partitioning and a realistically proportioned data set', J. Forecasting, Vol. 19, pp.219-230.
65. Wilson, R.L. and Sharda, R. (1994) 'Bankruptcy prediction using neural networks', Decision Support Systems, Vol. 11, No. 5, pp.545-557.
66. Wong, B.K., Bodnovich, T.A. and Selvi, Y. (1997) 'Neural networks applications in business: A review and analysis of the literature', Decision Support Systems, Vol. 19, pp.301-320.
67. Yang, Z.R., Platt, M.B. and Platt, H.D. (1999) 'Probabilistic neural networks in bankruptcy prediction', Journal of Business Research, Vol. 44, No. 2, pp.67-74.
68. Yoon, Y., Swales, G. and Margavio, T. (1993) 'A comparision of discriminant analysis versus artificial neural networks', Journal of Operational Research Society, Vol. 44, pp.51-60.
69. Zavgren, C. (1983) 'The prediction of corporate failure: The state of the art', Journal of Accounting Literature, Vol. 2, pp.1-37.
70. Zavgren, C.V. (1985) 'Assessing the vulnerability to failure of American industrial firms: A logistic analysis', Journal of Business Finance and Accounting, Spring, Vol. 12, No. 1, pp.19-45.
71. Zmijewski, M.E. (1984) 'Methodological issues related to the estimation of financial distress prediction models', Studies on Current Econometric Issues in Accounting Research, pp.39-82.
72. Baba, N. and Suto, H. (2000) 'Utilization of artificial neural networks and the TD-learning method for constructing intelligent decision support systems', European Journal of Operational Research, Vol. 122, pp.501-508.
73. Balkin, S.D. and Ord, K.J. (2000) 'Automatic neural networks modeling for univariate time series', International Journal of Forecasting, Vol. 16, pp.509-515.
74. Barniv, R., Agarwal, A. and Leach, R. (1997) 'Predicting the outcome following bankruptcy filing: A three-state classification using neural networks', International Journal of Intelligent Systems in Accounting, Finance and Management, Vol. 16, No. 3, pp.177-194.
75. Beaver, W. (1966) 'Financial ratios as predictors of failure', Journal of Accounting Research, Vol. 5, No. 1966, pp.71-111.
76. Boritz, J. and Kennedy, D. (1995) 'Effectiveness of neural network types for prediction of business failure', Expert Systems Applications, Vol. 9, pp.504-512.
77. Brockett, P., Cooper, W., Golden, L. and Pitaktong, U. (1994) 'A neural network model for obtaining an early warning for insurance insolvency', J. Risk and Insurance, Vol. 61, pp.402-424.
78. Cao, O., Leggio, K.B. and Schniederjans, M.J. (2005) 'A comparison between Fama and French's model and artificial neural networks in predicting the Chinese stock market', Computers and Operations Research, Vol. 32, No. 10, pp.2499-2512.
79. Dimitras, A.I., Slowinski, R., Susmaga, R. and Zopounidis, C. (1999) 'Business failure prediction using rough sets', European Journal of Operational Research, Vol. 114, pp.263-280.
80. Doumpos, M. and Zopoudinis, 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.
81. Feraud and Clerot (2002) 'A methodology to explain neural network classification', Neural Networks, Vol. 15, No. 2, pp.237-246.
82. Huang, Z., Chen, H., Hsu, C-J., Chen, W.H. and Wu, S. (2004) 'Credit rating analysis with support vector machine and neural networks: A market comparative study', Decision Support Systems, Vol. 37, pp.543-558.
83. Jo, H. and Han, I. (1996) 'Integration of case-based forecasting, neural network, and discriminant analysis for bankruptcy prediction', Expert Systems with Applications, Vol. 11, pp.415-422.
84. Kimoto, T., Asakawa, K., Yoda, M. and Takeoka, M. (1993) Stock Market Prediction System with Modular Neural Networks Neural Networks in Finance and Investing, in R.R. Trippi and E. Turban (Eds.) pp.343-356.
85. Leondes, C.T. (1998) Image Processing and Pattern Recognition (Neural Network Techniques and Applications).
86. Marquez, L., Hill, T., Worthley, R. and Remus, W. (1993) 'Neural networks models as an alternative to regression neural networks in finance and investing', in R.R. Trippi and E. Turban (Eds.) pp.435-449.
87. Mehrotra, K., Mohan, C.K. and Ranka, S. (1997) Elements of Artificial Neural Networks, Pemram International.
88. Ooghe, H., Camerlynck, J. and Balcaen, S. (2003) 'The Ooghe-Joos-De Vos failure prediction models: A cross-industry validation', Brussels Economic Review, Vol. 46, No. 1, pp.39-70.
89. Shadbolt, J. (2002) Neural Networks and the Financial Markets: Predicting, Combining and Portfolio Optimization (Perspectives in Neural Computing).
90. Swales, G.S. and Yoon, Y. (1992) 'Applying artificial neural networks to investment analysis', Financial Analysts Journal, Vol. 48, pp.78-80.
91. Yoon, Y. and Swales, G. (1993) 'Predicting stock price performance: A neural networks approach in neural networks', in R.R. Trippi and E. Turban (Eds.) Finance and Investing, pp.315-328.
92. Zahedi, F.M. (1996) 'A meta - analysis of financial applications of neural networks', International Journal of Computational Intelligence and Organizations, Vol. 1, No. 3, pp.164-178.
93. Zhang, G.P., Hu, M.Y., Patuwo, B.E. and Indro, D.C. (1999) 'Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis', European Journal of Operational Research, Vol. 116, pp.16-32.
94. Zopoudinis, C. and Dimitras, A.I. (1998) Multicriteria Decision Aid Methods for the Prediction of Business Failure, Dordrecht: Kluwer Academic Publishers.