Logistic回归分析在违约概率预测中的应用

Application of Logistic Regression Analysis in Prediction of Default Probability

新巴塞尔协议中,计算违约概率是对信用风险衡量很关键的步骤.该文以我国村镇银行实际数据作为基础,通过逐步回归判别法构建了较为科学的信用风险评估指标体系,采用Logistic回归模型构建了违约概率的测算模型,说明了Logistic模型具有非常可信的识别,预测及推广能力,可以对农村金融中的信用风险有效评估.

The new Basel agreement,calculating the probability of default is very key step to measure the credit risk. Based on the actual data of rural banks in China,through the stepwise regression method to build a more scientific credit risk evaluation system,the calculation model of default probability is constructed by logistic regression model in this paper. It shows that Logistic model has a very credible ability of identification,prediction and promotion,and can effectively evaluate credit risk in rural finance.