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Grading Prediction of Enterprise Financial Crisis Based on Nonlinear Programming Evaluation: A Case Study of Chinese Transportation Industry

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  • Zhi-yuan Li

Abstract

As the core of the effective financial crisis prevention, enterprise finance crisis prediction has been the focal attention of both theorists and businessmen. Financial crisis predictions need to apply a variety of financial and operating indicators for its analysis. Therefore, a new evaluation model based on nonlinear programming is established, the nature of the model is proved, the detailed solution steps of the model are given, and the significance and algorithm of the model are thoroughly discussed in this study. The proposed model can deal with the case of missing data, and has the good isotonic property and profound theoretical background. In the empirical analysis to predict the financial crisis and through the comparison of the analysis of historical data and the real enterprises with financial crisis, we find that the results are in accordance with the real enterprise financial conditions and the proposed model has a good predictive ability.

Suggested Citation

  • Zhi-yuan Li, 2014. "Grading Prediction of Enterprise Financial Crisis Based on Nonlinear Programming Evaluation: A Case Study of Chinese Transportation Industry," Abstract and Applied Analysis, John Wiley & Sons, vol. 2014(1).
    • Handle: RePEc:wly:jnlaaa:v:2014:y:2014:i:1:n:267234
    DOI: 10.1155/2014/267234
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    References listed on IDEAS

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    1. Dorit S. Hochbaum & Erick Moreno-Centeno & Phillip Yelland & Rodolfo A. Catena, 2011. "Rating Customers According to Their Promptness to Adopt New Products," Operations Research, INFORMS, vol. 59(5), pages 1171-1183, October.
    2. Ming Xu & Chu Zhang, 2009. "Bankruptcy prediction: the case of Japanese listed companies," Review of Accounting Studies, Springer, vol. 14(4), pages 534-558, December.
    3. Ravindra K. Ahuja & Dorit S. Hochbaum & James B. Orlin, 2003. "Solving the Convex Cost Integer Dual Network Flow Problem," Management Science, INFORMS, vol. 49(7), pages 950-964, July.
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