基于KMV和关联规则算法的行业供应链信用风险传染研究

Study on the Transmission of Industry Supply Chain Credit Risk with KMV Model and Association Rule Algorithm

从行业供应链视角,以钢铁行业和医药流通行业供应链中上市企业市场数据为研究对象,上市公司信用风险大小以KMV模型中的违约距离值代替,利用Apriori算法挖掘上市公司信用风险传染的关联规则。研究结论表明,医药流通行业供应链中企业信用风险传染频率和传染强度均高于钢铁行业供应链中企业;供应链中上下游企业整合以及信用技术引进是影响供应链企业信用风险传染重要影响因素。

From the perspective of the supply chain industry, this paper studies the market data of the listed companies se- lected from the steel industry and the pharmaceutical distribution industry which come from the same supply chain. The credit risk indicators of listed companies are measured by the distance to default calculated through KMV computational method. Besides, Apriori algorithm is used to dig the transmission of credit risk between the listed companies. The result indicates that ： compared with the steel industry supply chain, the frequency and intensity of supply chain credit risk conta- gion were higher in pharmaceutical distribution industry supply chain; supply chain integration and information sharing in the supply chain are important influence factors for reducing credit risk contagion between the enterprises in supply chain.