摘要
供应链金融作为新兴的融资方式,在融资市场上占据着越来越重要的地位,但其中的信用风险制约了供应链金融业务的扩大与发展。选择汽车供应链金融研究其中的信用风险问题,运用KMV模型量化汽车企业的违约风险并测算各个企业的违约距离和违约概率,有效地揭示了汽车供应链金融中的违约风险排序。在汽车供应链金融中,汽车经销商的违约风险最高,其次是零部件供应商,违约风险最低的是汽车核心制造商。同一类型企业中,由于其经济实力、生产规模、管理制度以及竞争力的不同,使企业间的违约概率存在较大差异。
As an emerging financing channel,supply chain finance occupies an increasingly important position in the financing market,but the credit risk in it restricts the expansion and development of supply chain financial business.This paper studies the credit risk issues in supply chain finance,uses the KMV model to quantify the default risk of auto companies and measures the default distance and default probability of each company,effectively revealing the default risk ranking in auto supply chain finance.It is found that in auto supply chain finance,auto dealers have the highest default risk,followed by parts suppliers,while core auto manufacturers bear the lowest default risk.Due to the differences in economic strength,production scale,management system and competitiveness,there are great differences in default probability among enterprises of the same type.
作者
郭维
黎俏欣
GUO Wei;LI Qiao-xin(School of Credit Management,Guangdong University of Finance,Guangzhou Guangdong 510521)
出处
《广东技术师范大学学报》
2021年第2期78-84,共7页
Journal of Guangdong Polytechnic Normal University
