引入TOPSIS法的风险预警模型能提高模型的预警准确度吗?——来自我国制造业上市公司的经验证据

doi:10.16381/j.cnki.issn1003-207x.2015.11.012

Abstract

Abstract: Taking the indebted ST listed companies and twice as many the non-ST of manufacturing industry in Shanghai and Shenzhen A-share from 2011 to 2012 as sample, 30 financial indicators that can reflect the business profitability, profitability of shareholders, cash flow capacity, operational capacity, development capacity and debt solvency and other 8 qualitative indicators including ownership structure, management structure and location of the companies are selected. Considered the sample of 2011 as a training set while the 2012 as testing set, a traditional warning model and double classification model in which TOPSIS method are introduced on the basis of the principal component analysis are built. The results show that the introduction of TOPSIS in risk early-warning model can increase the accuracy of early-warning significantly. It can improve the accuracy of early warning system 18.5% for ST companies and 11.1% for samples in general. This suggests that the method of double classification can be applied to build an effective risk early-warning model.

Key words: TOPSIS, logit model, risk early-warning model, principal component analysis, double classification

CLC Number:

F224

ZHU Wei-dong, WU Peng. Canthe Introduction of TOPSIS in Risk Early-warning Model Improve theAccuracy of Early-warning?-A Case Study from Listed Companies of Manufacturing Industry[J]. Chinese Journal of Management Science, 2015, 23(11): 96-104.

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Canthe Introduction of TOPSIS in Risk Early-warning Model Improve theAccuracy of Early-warning?-A Case Study from Listed Companies of Manufacturing Industry

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