基于PCA-SVM的新能源产业财务预警模型研究  

Research on Financial Early Warning Model of New Energy Industry Based on PCA-SVM

作　　者：王晓华[1] 陈林凡 WANG Xiaohua;CHEN Linfan(Hebei University of Engineering,Handan 056038,China)

机构地区：[1]河北工程大学,河北邯郸056038

出　　处：《商业观察》2024年第23期52-55,共4页BUSINESS OBSERVATION

摘　　要：在“碳达峰、碳中和”的背景下,新能源产业初期投入高、技术壁垒多、融资风险大,而且其市场机制不完全成熟,公司会面临较多的财务风险。拟选取5年间(2019—2023年)沪深A股新能源上市公司为研究对象,构建适用于我国新能源产业的主成分分析法和支持向量机相结合的财务危机预警模型。该模型可以精确地对新能源上市公司进行财务风险预测,提高公司人员对于风险的防范意识,促使企业改善不合理的财务结构,为利益相关者识别和预防企业的财务危机提供参考意见。In the context of"carbon peaking and carbon neutrality",the new energy industry has high initial investment,many technical barriers,high financing risks,and its market mechanism is not fully mature,so the company will face more financial risks.It is proposed to select A-share new energy listed companies in Shanghai and Shenzhen from 2019 to 2023 as the research object,and construct a financial crisis early warning model suitable for the combination of principal component analysis and support vector machine for China's new energy industry.The model can accurately predict financial risks of new energy listed companies,improve the awareness of risk prevention of company personnel,promote enterprises to improve their unreasonable financial structure,and provide opinions for stakeholders to identify and prevent financial crises of enterprises.

关 键 词：新能源上市公司 财务危机预警 支持向量机 主成分分析法 

分 类 号：F426.2[经济管理—产业经济] F406.7