The use of genetic programming for the construction of a financial management model in an enterprise |
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Authors: | Wen-Tsao Pan |
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Affiliation: | 1. Department of Information Management, Fooyin University, 3F., No. 12, Lane 271, Longjiang Rd., Jhongshan District, Taipei City, 104, Taiwan, ROC
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Abstract: | The fast development in China’s economy has caused the rapid expansion of the domestic market. Since many economists do not
have optimistic views regarding the bubble economy of China, it is necessary for Taiwanese businessmen to understand in-depth
the business operational performance and financial situation of enterprises in China, so as to reduce the risk of a potential
investment. In this article, data from the China Economic Research Database (CCER), the financial database of financial corporations
are collected for analysis to investigate the business operation and management performance and financial characteristic of
enterprises in China. In this article, grey relational analysis is applied first in order to investigate the business operational
performance of 600 enterprises in China. Afterwards, a more recent clustering technique is used to divide, based on financial
characteristic, enterprises in China into two groups. Finally, three models, namely genetic programming, Back-Propagation
Neural Network and Logistic Regression are adopted to construct an Enterprise Operational Performance model and an Enterprise
Finance Characteristic model, respectively. Based on the results found, it can be concluded that genetic programming yielded
the best classification and forecast performance, compared to the other three techniques. |
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Keywords: | |
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