Research On Financial Risk Early Warning Of Solar PV Enterprises In China

With the global environmental pollution intensified,fossil energy depletion,the world began to turn to the development of new energy industry,which,with its clean and pollution-free,widely distributed,easy to get the characteristics of the widely favored,solar photovoltaic industry can be said to be the future Unlimited development potential.Benefit from the national policy for the strong support of solar photovoltaic enterprises,2013-2015China’s new solar energy installed capacity ranks first in the world,China’s solar energy business development potential.However,in the photovoltaic industry,the rapid development of the environment,many solar photovoltaic enterprises are facing enormous financial risks.From an external point of view,a variety of capital competing into the solar PV market,hoping to share the PV market,"a cup of soup",which to the existing solar photovoltaic enterprises to bring a certain degree of impact.From the internal point of view,the solar energy companies themselves have poor management,weak profitability,cash flow shortages and other issues,how to effectively prevent the development of enterprise management level is low,the core technology is weak,weak cost control and imperfect construction and other issues to achieve effective To deal with financial risks,establish and improve the corporate financial risk early warning system for the purpose of the future development of enterprises is essent.In this paper,the research on the financial risk early warning of solar PV enterprises in China is taken as the breakthrough point,and the practical methods and models for predicting the financial risk early warning of solar PV enterprises are aiming.First of all,on the basis of summarizing the relevant theoretical literatures,the author compares and analyzes the research methods used by the comparative scholars in the empirical research,and finally selects the most suitable Logistic regression model as the financial risk early warning model of solar PV enterprises.Secondly,in the qualitative analysis,the paper analyzes the influencing factors of the financial risk of PV enterprises in our country.In the empirical research part,the paper analyzes the listed companies of 45 solar PV enterprises in Shanghai and Shenzhen,A total of 21 indicators of financial indicators and non-financial indicators for the four years from 2012 to 2015 are used as research variables,SPSS20.0 software was used to extract the principal components,and then the main components were tested for significant difference and partial correlation analysis.Finally,the independent variables needed to establish the Logistic model were obtained.Based on the empirical analysis,the Logistic regression model was established.There are: the establishment of the model on the sample detection results and predict the effect is better,the use of established models can basically predict the probability of financial crisis;It is realistic to choose the financial indicators and non-financial indicators inversely proportional to the probability of a financial crisis in the enterprise.At the same time,some suggestions are put forward for the optimization of the model and some policy suggestions for the financial risk prevention of solar PV enterprises in China.Finally,it is the conclusion of the research conclusion,and points out the shortcomings and future prospects of this paper.