摘要
2020年新冠肺炎疫情暴发很多行业的供应链受阻甚至中断,企业的信用风险增大,供应链金融体系受到严重冲击.为了应对疫情的冲击,中央出台了全面复工复产政策,多措并举地推动经济发展.文章以汽车供应链为例,研究复工复产前后供应链金融的信用风险状况,选取在汽车板块上市的22家企业作为研究对象,利用主成分分析对企业的财务指标进行降维处理,再使用Logistic回归模型对企业的信用风险状况进行预测.研究结果表明复工复产政策之后汽车供应链的信用风险状况得到了缓解,并针对汽车行业的特点提出了对策与建议.
Due to the outbreak of COVID-19 in 2020,the supply chain of many industries was blocked or even disrupted,and the credit risk of enterprises increased,supply chain finance system was seriously affected.In order to cope with the impact of the epidemic,the central government has issued a comprehensive policy of returning to work and production,and taken many measures to promote economic development.This paper takes the automobile supply chain as an example to study the credit risk of the supply chain financial before and after the resumption of work,selects 22 listed companies in the automotive sector of stock market as the research object,and uses principal component analysis to reduce the dimension of financial indicators,then establishes Logistic regression model to predict the credit risk of enterprises.The results show that the credit risk of the automobile supply chain has been alleviated after the resumption of work and production policy,and the countermeasures and suggestions are put forward according to the characteristics of the automobile industry.
作者
刘昆仑
LIU Kun-lun(School of Mathematics,Qilu Normal University,Jinan 250013,China)
出处
《辽宁大学学报(自然科学版)》
CAS
2021年第4期371-380,共10页
Journal of Liaoning University:Natural Sciences Edition
基金
山东省自然科学基金项目(ZR201709260255)
山东省社会科学规划研究项目(18CCZJ11)。
关键词
复工复产
信用风险
主成分分析
LOGISTIC回归模型
resumption of work and production
credit risk
principal components analysis
Logistic regression model