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Prediction of corporate financial health by Artificial Neural Network

Author

Listed:
  • Sumit Chakraborty
  • Sushil K. Sharma

Abstract

Neural networks are perhaps the most significant forecasting tool to be applied to the financial markets in recent years and are gaining ascendancy because of reports of their success. This paper checks out the classification capability of Radial Basis Function Networks (RBF), Multi-Layer Perceptrons (MLPs) with and without Principal Component Analysis (PCA), Self-Organizing Feature Maps (SOFM) with MLP and Support Vector Machine (SVM) neural architecture for prediction of the financial health of firms.

Suggested Citation

  • Sumit Chakraborty & Sushil K. Sharma, 2007. "Prediction of corporate financial health by Artificial Neural Network," International Journal of Electronic Finance, Inderscience Enterprises Ltd, vol. 1(4), pages 442-459.
    • Handle: RePEc:ids:ijelfi:v:1:y:2007:i:4:p:442-459
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    Cited by:

    1. Laskai András, 2019. "AI foundations of the international business planning and the AI consciousness model," International Journal of Science and Business, IJSAB International, vol. 3(1), pages 17-28.
    2. Amani, Farzaneh A. & Fadlalla, Adam M., 2017. "Data mining applications in accounting: A review of the literature and organizing framework," International Journal of Accounting Information Systems, Elsevier, vol. 24(C), pages 32-58.

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