A Hybrid RST and GA-BP Model for Chinese Listed Company Bankruptcy Prediction

Authors:
Ying Sai;Chenjian Zhong;Peiyao Nie
Affiliations:
Shandong University of Finance, China;Shandong University of Finance, China;Shandong University of Finance, China
Venue:
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 02
Year:
2007

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Abstract

Bankruptcy is a worldwide economic and social problem with high costs. And the high social costs associated with bankruptcy have spurred searches for better theoretical understanding and prediction capability. In this paper, we suggest a hybrid approach to Chinese listed company bankruptcy prediction, using a GA-BP (genetic algorithm and back propagation) model to construct a bankruptcy prediction model with variables derived by rough set theory (RST). An example is given to validate this model. The results show our hybrid model has higher prediction accuracy and less execution time in bankruptcy prediction when compared against GA-BP algorithm.