Title: A genetic-based hybrid approach to corporate failure prediction

Authors: Ping-Chen Lin, Jiah-Shing Chen

Addresses: Institute of Finance and Information, National Kaohsiung University of Applied Sciences, Kaohsiung 807, Taiwan. ' Department of Information Management, National Central University, Jhongli 320, Taiwan

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.

Keywords: corporate failure; genetic algorithms; GAs; neural networks; logistic regression; discriminant analysis; e-finance; electronic finance; failure prediction.

DOI: 10.1504/IJEF.2008.017543

International Journal of Electronic Finance, 2008 Vol.2 No.2, pp.241 - 255

Published online: 16 Mar 2008 *

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