A Study On The Financial Early Warning System For Power Companies

Developments in the power industry have a direct impact on GDP, and it also closely related with people’s daily life. As a result of global economic integration the macroscopic economy and the coal price have formed the huge impact to the electric power enterprise’s profit, making the investment and operation of the electric power industry faces tough test. At the same time, because of the high corporate debt in the electric power industry enterprises, and by the environmental protection, energy constraints, the investment and business are more likely to cause financial risks. This paper summarizes the literature on the basis of at home and abroad, conclude and collate the research results of the financial risk early warning in the electric power industry, on the basis of the Z value of the traditional model, the research analyses actual industry environment of the enterprises and competition pattern from the macro point of view, confirm and select the suitable financial pre warning index for the electric power industry, learning the experience of predecessors, selected out the suitable new Z value model of index of electric power enterprises through the principal component and principal factor method; Finally, due to the fact that the principal component and the main factor Z value trend is the same, take the average as the comprehensive financial risk of the Z value of the electric power enterprise, and compared with traditional Z value of the model. The results indicate the prediction accuracy of the new Z value model built in this paper reaches up to 84.85%,which is much higher than traditional Z value model prediction accuracy of 70%.Then on this basis, do a deeper research, this paper combined logit model with new Z value model to study the financial risk early warning in the electric power industry, discuss the financial early warning model in the concrete application of the power industry, to provide a more accurate judgment and evaluation for its risk investment, which has vital significance on the electric power enterprise risk management:This paper break the traditional grouping method by whether the enterprise is ST as logit model samples. In this paper, the sample group of logit model of financial crisis is according to the new building Z value model for classification, it’s a kind of innovation. After confirm the grouping of the sample, use forward stepwise regression method to select variables to construct model, and use the maximum likelihood estimation to build the logit model. The results indicated prediction accuracy of logit model based on the new Z value model reaches up to 85.84%, superior to the traditional Z value model and the new Z value model. From the above analysis results, it’s fully proved that the research method by combining with the two kinds of models is more suitable to the actual situation of electric power industry.