论文部分内容阅读
伴随着美国金融危机对全球金融环境的影响,信用风险问题受到了越来越多的关注。而我国信用文化和体系建设相对落后,尽快建立合适的模型、分析对企业发放贷款的信用风险,从而有效的管理企业贷款具有十分重要的现实意义。本文试图运用logistic回归模型以及决策树算法,从我国上市公司的财务状况角度对其存在的信用风险作出评价,结果表明决策树算法相比logistic回归模型有更好的预测判别能力。
With the impact of the U.S. financial crisis on the global financial environment, credit risk issues have drawn more and more attention. However, our country’s credit culture and system construction are relatively backward, as soon as possible to establish a suitable model to analyze the credit risk of loans to enterprises, and thus effective management of corporate loans has very important practical significance. This paper tries to use the logistic regression model and the decision tree algorithm to evaluate the credit risk of listed companies in China from the perspective of financial status. The results show that the decision tree algorithm has better predictive ability than the logistic regression model.