我国农业上市公司信用风险实证研究——基于Logistic模型

Empirical Study on Credit Risk Assessment of Agricultural Listed Companies Based on Logistic Model

本文分析了农业上市公司年度财务报表中的几个指标,并通过因子分析对所选取的12个变量进行缩减,得出四个总体指标,运用逻辑回归模型进行实际测量农业上市公司信用风险并进一步区分第一类错误和第二类错误。即将低风险公司误判为高风险公司和将高风险公司误判为低风险公司。得出的结论是,使用Logistic模型进行评估可以更好地识别低风险公司,不容易犯第一类错误,而容易犯第二类错误,也就是说,容易将高风险企业评估为低风险企业。这值得商业银行等金融机构高度重视,并为其是否对融资企业给予信贷提供新的思路。

This paper analyzes several indicators in the annual financial statements of agricultural listed companies,and reduces the selected 12 variables through factor analysis,and obtains four overall indicators.The logistic regression model is used to actually measure the credit risk of agricultural listed companies and further Distinguish between the first type of error and the first type of error.That is,low-risk companies are misjudged as high-risk companies and high-risk companies are misjudged as low-risk companies.The conclusion is that the use of the Logistic model for evaluation can better identify low-risk companies,and it is not easy to make the first type of mistakes,but it is easy to make the second type of mistakes,that is,it is easy to evaluate high-risk companies as low-risk companies.This deserves great attention from financial institutions such as commercial banks and provides new ideas for whether to grant credit to financing enterprises.