Research On Financial Risk Early-warning To Coal Listed Enterprises

Based on the literature review study, this artical identify the insufficience of the current research on financial risk early-warning for the coal industry and select financial early warning indicators and some non-financial early-warning indicators for coal listed companies through comparative analysis. This article establish logistic regression model whose financial risk prediction accuracy is relatively high for corporate financial risk early warning research. The research ideas are as follows: Firstly this article select early warning indicators of financial risk, from which elect main factors by factor analysis; Secondly, according to the selected main factors, 2014 coal listed companies are grouped into financial crisis and non-crisis financial group by cluster analysis; Finally, based on the grouping and selected indicators the paper build a logistic regression model to early warning, and then test the model.Through the research on financial risk early warning of China’s coal listed companies, the paper concluded that: Logistic regression can warn to the enterprise of financial risk and the warning effect is better than some other warning models. The innovation of this paper is: it is not grouped by ST and non-ST companies, but by the cluster analysis, which can make the grouping more objective. Studying on financial risk warning of no ST’ industry can help the industry which has a similar situation. This paper establish a financial risk early warning model suited to their characteristics. According to the standard reference value of the individual financial indicators which is gotten from the field survey of coal enterprises, Coal companies can also predict whether there is a financial crisis. Comprehensive financial risk early warning and individual indicators warning of financial risk early warning should be combined, which lead to a better Warning accuracy.