Research On Financial Risk Early Warning Model Of Wind Power Generation Enterprises

The Chinese wind companies have enjoyed high-speed growth in recent years, benefited from the serious attention on the clean and renewable energy from Chinese government. Meanwhile, their financial risk is increasing too due to the nature of the wind power products. The financial crisis in every company is manifested as a step-by-step development. The deterioration of financial status represents the degree of crisis. A pre-warning on the financial risks of the wind companies shall be established to prevent losses brought by their financial risks. Currently, the research on the financial risk pre-warning based on the wind power industry characteristics is rather limited, while there is even less pre-warning on their financial risk pre-warning. In such context, an accurate pre-warning on the financial risks of wind companies is particularly important.First, a demarcation line between the financial risk and financial crisis is defined, and the interactions between financial analysis, financial assessment and financial pre-warning are discussed on the summarization of financial pre-warning achievements and financial risk pre-warning theories both domestically and abroad. Second, a specific financial risk pre-warning metric system is established, comprising of both quantitative and qualitative metrics, after an analysis of the current financial position of Chinese wind companies and an argumentation on the root causes of these issues. This metric system introduces Eva, cash flow, auditing comment, internal control and other new metrics in addition to the basic metrics typically in Tie-1metric system including solvency, operating capacity, profitability, developing ability and earnings quality. Third, two algorithms are constructed based on the metric system, e.g. the financial risk pre-warning model of fuzzy and comprehensive evaluation and the financial risk pre-warning metric model of BP neural network. Verification on each model is executed separately. Finally, the research results by the financial risk pre-warning model of fuzzy and comprehensive evaluation and the financial risk pre-warning metric model of BP neural network on their predictive ability of financial risks in the wind companies are summarized. The issues and weakness are indicated to specify the direction of future researches.