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A genetic-based hybrid approach to corporate failure prediction

Author

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  • Ping-Chen Lin
  • Jiah-Shing Chen

Abstract

This paper proposes a genetic-based hybrid approach to predict the possibility of corporate failure. We use Genetic Algorithm (GA) to select the critical variables set and optimise the weight of each classifier for integrating the best features of several classification approaches (such as discriminant analysis, logistic regression and neural networks) in order to enhance prediction results. GA with nonlinear searching capabilities extracts more critical feature variables if compared with the Stepwise Method. This means that the undesirable variables for classification models will be cleaned out by GA. In addition, our experimental results show that this hybrid approach obtains better prediction performance than when using a single approach effectively.

Suggested Citation

  • Ping-Chen Lin & Jiah-Shing Chen, 2008. "A genetic-based hybrid approach to corporate failure prediction," International Journal of Electronic Finance, Inderscience Enterprises Ltd, vol. 2(2), pages 241-255.
    • Handle: RePEc:ids:ijelfi:v:2:y:2008:i:2:p:241-255
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