会计学院知识库

摘  要

随着碳达峰和碳中和目标的实现，新能源企业不仅能够跟上技术发展的步伐，促进行业结构升级，而且能够提高我国的综合力量，这类公司的发展十分迅速。然而，由于国内新能源企业出现稍晚，并且新能源企业有着研发成本高与竞争激烈的特点，造成国内这类公司在长期发展阶段中面对着各种威胁。因此，新能源企业需高度重视自身财务情况，掌握引发财务风险的因素，构建相应的预警模型。财务风险预警作为一种财务风险管理方法，能够更好地预估公司的财务风险水平，了解到公司财务状况中面临的难题，以便公司能够事先采用防范措施，防止风险的发生或进一步扩大。

本文选择新能源企业金风科技作为案例公司，采用文献研究法与案例研究法相结合的方式，对金风科技财务风险预警模型的构建及应用进行研究。首先，查找国内外关于财务风险预警的文献，并且进行相应的归纳与整理。其次，基于金                                                                                                                                                                                                  风科技现实状况与资产负债结构，从其财务情况出发，对其投资、筹资、营运方面展开风险分析。再次，基于预警指标选取原则，根据产业特征，选择20种指标，借助熵值法和相关性分析，对于相关指标进行选择，筛选出11种指标来建立预警指标体系，采用熵值法对其重新赋权，再通过功效系数法求得金风科技在2016年至2020年期间的财务风险的具体分值，并划分预警程度，对预警结果进行分析。最后，提出预警模型的相关保障措施，以更好地体现其预警功能。

本文运用熵值法和功效系数法相结合的方法，为金风科技构建财务风险预警模型，希望本次研究能满足金风科技风险管理的需求，帮助提高自身风险防范水平，给金风科技的利益相关者的决策提供帮助和参考。

Abstract

With the achievement of carbon peaks and carbon neutralization goals, new energy companies are not only able to keep pace with technological development, promote structural upgrading of the industry and improve the overall strength of our country, these companies are developing very rapidly. However, due to the late emergence of domestic new energy companies, and the high cost of research and development and fierce competition, these companies are facing various threats in the long-term development phase. Therefore, new energy technology companies must pay close attention to their own operations, master the factors that cause financial risks, and build corresponding monitoring entity models. As a method of financial risk management , accounting risk early warning is to be able to better predict and analyze the level of financial risk, grasp the challenges faced by the business operation of the enterprise, and facilitate the enterprise to adopt preventive measures in advance to avoid the occurrence or further expansion of financial risks.

In this paper, Goldwind Technology, a new energy enterprise, is selected as a case company, and literature research method and case study method are combined to study the construction and application of actual situation and asset and liability structure, we analyse the risks in terms of its investment, financing and operation from its financial situation. Again, based on the principle of selecting early warning indicators, 20 indicators are selected according to the characteristics of the industry, with the help of entropy value method and correlation analysis, 11 indicators are selected to establish the corresponding indicator system, and the entropy value method is used to assign weights to them, and the efficacy coefficient method is used to obtain the specific score of Goldwind's financial risk between 2016 and 2020, and to classify the degree of early warning. The early warning results are analysed. Finally, we propose safeguards for the early warning model to better reflect its early warning function.

This paper uses a combination of entropy and efficacy coefficient methods to construct a financial risk early warning model for Goldwind Science and Technology. It is hoped that this study will meet Goldwind's risk management needs, help improve its own risk prevention level, and provide help and reference for Goldwind's stakeholders' decision-making.