Exploiting corporate governance and common-size analysis for financial distress detecting models

Proceedings of the 9th Joint Conference on Information Sciences, JCIS 2006

Volumn 2006, Issue , 2006, Pages

  Huang, Pei Wen ^a   Liu, Chao Lin ^a  

^a NATIONAL CHENGCHI UNIVERSITY   (Taiwan)

Author keywords

Backpropagation neural networks; Common size analysis; Corporate governance; Financial distresses; Support vector machines

Indexed keywords

BACKPROPAGATION; DATA REDUCTION; NEURAL NETWORKS; QUALITY MANAGEMENT; REGRESSION ANALYSIS; SUPPORT VECTOR MACHINES;

BACKPROPAGATION NEURAL NETWORKS; COMMON SIZE ANALYSIS; CORPORATE GOVERNANCE; FINANCIAL DISTRESSES;

FINANCE;

EID: 33847709818     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.2991/jcis.2006.188     Document Type: Conference Paper

References (19)

1. E. I. Altman. Financial ratios, discriminant analysis, and the prediction of corporate bankruptcy. Journal of Finance, Vol. 23, pp. 589-609, 1968.
2. J. R. Coakley and C. E. Brown. Artificial neural networks in accounting and finance: modeling issues. International Journal of Intelligent Systems in Accounting, Finance & Management, Vol. 9, pp. 119-144, 2000.
3. K. Fanning, K. Cogger, and R. Srivastava. Detection of management fraud: a neural network approach. International Journal of Intelligent Systems in Accounting, Finance & Management, Vol. 4, pp. 113-26, 1995.
4. M. L. Nasir, R. I. John, S. C. Bennett, D. M. Russell, and A. Patel. Predicting corporate bankruptcy using artificial neural networks. Journal of Applied Accounting Research, Vol. 5, pp. 30-52, 2000.
5. M. D. Odom and R. Sharda. A neural network model for bankruptcy prediction. International Joint Conference on Neural Networks. Vol. 2, pp. 163-168, 1990.
6. H. Schilit. Financial shenanigans: how to detect accounting gimmicks & fraud in financial reports. New York: McGraw-Hill, 2002.
7. K. Fanning, K. Cogger, and R. Srivastava. Detection of management fraud: a neural network approach. International Journal of Intelligent Systems in Accounting, Finance & Management, Vol. 4, pp. 113-26, 1995.
8. S. Johnson, P. Boone, A. Breach, and E. Friedman. Corporate governance in the Asian financial crisis. Journal of Financial Economics, Vol. 58, pp. 141-186, 2000.
9. R. La Porta, F. Lopez-de-Silanes, A. Shleifer, and R. Vishny. Agency problems and dividend policies around the world. Journal of Finance, Vol. 55, pp. 1-33, 2000.
10. T. S. Lee and Y. H. Yeh. Corporate governance and financial distress: evidence from Taiwan. Corporate Governance, Vol. 12, pp. 378-388, 2004.
11. Y. H. Yeh, T. S. Lee and T. Woidtke. Family control and corporate governance: evidence for Taiwan. International Review of Finance, Vol. 2, pp. 21-48, 2001.
12. Van Rijsbergen. Information Retrieval, 2nd edition, Butterworth-Heinemann Newton, 1979.
13. K. S. Shin, T. S. Lee, and H. J. Kim. An application of support vector machines in bankruptcy prediction model. Expert Systems with Applications, Vol. 28, pp. 127-135, 2005.
14. A. Fan and M. Palaniswami. Selecting bankruptcy predictors using a support vector machine approach. Proceedings of the International Joint Conference on Neural Networks, Vol. 6, pp. 354-359, 2000.
15. S. Salcedo-Sanz, M. Deprado-Cumplido, and M. J. Segovia. Feature selection methods involving support vector machines for prediction of insolvency in non-life insurance companies. International Journal of Intelligent Systems in Accounting, Finance & Management, Vol. 12, pp. 261-281, 2004.
16. TEJ: http://www.tej.com.tw
17. MATLAB: http://www.mathwork.com
18. C. C. Chang and C. J. Lin, LIBSVM: A library for support vector machines, 2001. http://www.csie.ntu.edu.tw/~cjlin/libsvm
19. P.-W. Huang and C.-L. Liu. Using genetic algorithms for feature selection in predicting financial distresses with support vector machines. Proceedings of the 2006 IEEE International Conference on Systems, Man, and Cybernetics, to appear, 2006.