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A Comparative Analysis of Artificial Neural Networks Using Financial Distress Prediction

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  • Kurt M. Fanning
  • Kenneth O. Cogger

Abstract

This paper examines the efficiency of a generalized adaptive neural network algorithm (GANNA) processor in comparison to earlier model‐based methods, a back‐propagation artificial neural network, and logistic regression approaches to data classification. The research uses the binary classification problem of discriminating between failing and non‐failing firms to compare the methods. The results indicate the potential in time savings and the successful classification results available from a GANNA processor.

Suggested Citation

  • Kurt M. Fanning & Kenneth O. Cogger, 1994. "A Comparative Analysis of Artificial Neural Networks Using Financial Distress Prediction," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 3(4), pages 241-252, December.
    • Handle: RePEc:wly:isacfm:v:3:y:1994:i:4:p:241-252
    DOI: 10.1002/j.1099-1174.1994.tb00068.x
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    References listed on IDEAS

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    Cited by:

    1. Kurt Fanning & Kenneth O. Cogger & Rajendra Srivastava, 1995. "Detection of Management Fraud: A Neural Network Approach," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 4(2), pages 113-126, June.
    2. James R. Coakley & Carol E. Brown, 2000. "Artificial neural networks in accounting and finance: modeling issues," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 9(2), pages 119-144, June.
    3. Goriunov Dmytro & Venzhyk Katerina, 2013. "Loan Default Prediction in Ukrainian Retail Banking," EERC Working Paper Series 13/07e, EERC Research Network, Russia and CIS.
    4. Zhang, Guoqiang & Y. Hu, Michael & Eddy Patuwo, B. & C. Indro, Daniel, 1999. "Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis," European Journal of Operational Research, Elsevier, vol. 116(1), pages 16-32, July.
    5. Daniel E. O'Leary, 2010. "Intelligent Systems in Accounting, Finance and Management: ISI journal and proceeding citations, and research issues from most‐cited papers," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 17(1), pages 41-58, January.
    6. Chrysovalantis Gaganis & Fotios Pasiouras & Charalambos Spathis & Constantin Zopounidis, 2007. "A comparison of nearest neighbours, discriminant and logit models for auditing decisions," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 15(1‐2), pages 23-40, January.
    7. Daniel E. O'Leary, 2009. "Downloads and citations in Intelligent Systems in Accounting, Finance and Management," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 16(1‐2), pages 21-31, January.
    8. Kenneth O. Cogger, 2010. "Nonlinear multiple regression methods: a survey and extensions," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 17(1), pages 19-39, January.
    9. J.E. Boritz & D.B. Kennedy & Augusto de Miranda e Albuquerque, 1995. "Predicting Corporate Failure Using a Neural Network Approach," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 4(2), pages 95-111, June.

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