风力发电企业财务风险预警模型研究

发布时间：2018-02-26 07:34

本文关键词： 风电企业财务预警模糊综合评价 BP神经网络　出处：《华北电力大学》2014年硕士论文　论文类型：学位论文

【摘要】：近些年,受到政府对于清洁可再生能源的重视,我国风力发电企业取得了高速的发展。但是由于风电产品的特殊性,其面临的财务风险也日趋加大。任何企业的财务危机是一个循序渐进的过程,财务的恶化情况可以反映危机的程度。为了防范风电企业财务风险带来的损失,要对风力发电企业的财务风险进行预警。但是现阶段对于行业特征展开的财务风险预警研究不多,而对风力发电企业的财务风险预警更少,准确针对风力发电企业的财务风险进行预警,对于风电企业的发展尤为重要。首先,在综述国内外财务预警成果及财务风险预警理论的基础上界定了财务风险和财务危机二者之间的界限,探讨了财务分析、财务评价和财务预警之间的关系。其次,分析了我国风力发电企业的财务现状,并对产生的原因进行了论证,建立了一套针对性较强的、包含了定量指标和定性指标的风力发电企业财务风险预警指标体系。这些指标体系除了偿债能力、营运能力、盈利能力、发展能力、盈利质量五个一级指标中常见的基本指标外,还引进了Eva、现金流量、审计意见和内部控制等较新的指标。再次,在指标体系的基础上,构建了两个数学模型,-即模糊综合评价财务风险预警模型和BP神经网络财务风险预警模型,并分别对模型进行了验证。最后,总结了模糊综合评价预警模型和BP神经网络预警模型对于风力发电企业的财务风险预测能力的研究成果,指出了存在的问题与不足,明确了今后进一步研究的方向。
[Abstract]:In recent years, due to the attention of the government on clean and renewable energy, wind power enterprises in China have made rapid development. However, due to the particularity of wind power products, Financial crisis of any enterprise is a gradual process, and the deterioration of financial situation can reflect the extent of the crisis. The financial risk of wind power enterprises should be forewarned. But at this stage, there are few researches on financial risk warning for industry characteristics, and less financial risk warning for wind power enterprises. It is very important for the development of wind power enterprise to accurately warn the financial risk of wind power enterprise. First of all, on the basis of summarizing the financial early warning results and the financial risk early-warning theory at home and abroad, this paper defines the boundary between financial risk and financial crisis, and probes into the relationship among financial analysis, financial evaluation and financial early-warning. This paper analyzes the present financial situation of wind power generation enterprises in China, and demonstrates the causes, and establishes a set of strong pertinence. The financial risk early warning index system of wind power enterprises including quantitative and qualitative indicators. These index systems include solvency, operating capacity, profitability, development ability, In addition to the basic indicators common in the five first-level indicators of profit quality, new indicators such as Eva, cash flow, audit opinions and internal controls have been introduced. Thirdly, on the basis of the indicator system, Two mathematical models, namely fuzzy comprehensive evaluation financial risk early warning model and BP neural network financial risk early warning model, are constructed and verified respectively. This paper summarizes the research results of fuzzy comprehensive evaluation early warning model and BP neural network early warning model for the financial risk prediction ability of wind power enterprises, points out the existing problems and shortcomings, and clarifies the direction of further research in the future.
【学位授予单位】：华北电力大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F406.7;F426.61

【参考文献】