Prediction of corporate financial health by Artificial Neural Network

Sushil Kumar Sharma

39 citations0/0 files storedInternational Journal of Electronic Finance

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Financial Distress and Bankruptcy Prediction Neural Networks and Applications Stock Market Forecasting Methods

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.

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References

1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY 1980Financial Ratios and the Probabilistic Prediction of Bankruptcy 1966Financial Ratios As Predictors of Failure 1984Methodological Issues Related to the Estimation of Financial Distress Prediction Models 1992Managerial Applications of Neural Networks: The Case of Bank Failure Predictions 1994Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience)2003Credit rating analysis with support vector machines and neural networks: a market comparative study 1990A neural network model for bankruptcy prediction

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