Information Technology and Quantitative Management ( ITQM 2013 ) Financial Distress Prediction for Chinese Listed Manufacturing Companies

Abstract Financial distress prediction can be formulated as a classification problem and accomplished by advanced data mining techniques. In classification based on multiple criteria linear programming (MCLP), we need to find the optimal solution as a classifier, by solving the MCLP problem. However, the errors can be caused by a fixed cutoff between a “good” group and a “bad” group by MCLP structure. In many applications, such as credit card account classification and bankruptcy prediction, how to handle two types of error is a key issue. Using the structure of multiple criteria and multiple constraint levels linear programming (MC 2 LP), which allows alterable cutoff, two types of errors can be systematically corrected. In order to do so, a penalty is imposed to find the potential solution for all possible trade-offs in solving MC 2 LP problem. Real dataset of Chinese listed manufacturing companies is used to validate MC 2 LP method. Comparison with classical optimization-based method SVM and MCLP is also provided.

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