基于CPV模型的房地产信贷信用风险的度量和预测

Research on Measurement and Forecast of the Real Estate Credit Risk Basing on CPV Model

本文基于CPV模型,对房地产信贷风险进行了度量与预测。结果表明,该模型在度量和预测房地产信贷违约率方面具有较好的效果。房地产信贷的违约率和宏观经济状况紧密相连,当经济状况恶化,房地产信贷违约率上升,当经济状况好转,房地产信贷违约率下降。分别从国家宏观经济、房地产行业状况、房地产企业状况三个层面选择出三个宏观经济因素指标——综合领先指标、国房景气指数和企业景气指数进行研究,结果表明,对于研究房地产信贷的信用风险来说它们是较好的指标,尤其是综合领先指标。

This paper measures and forecasts the real estate credit risk by using the CPV model. It shows that, CPV model is very efficient in measuring and forecasting the default rate of real estate credit risk, which is closely linked to the macro-economic condition. When the economy gets worse, the default rate increases; when the economy turns better, it decreases. The author chooses three macro-economic indexes-Composite Leading Indicator, China Real Estate Climate Index and Enterprise Climate Index-to make the further study, which are drown from three aspects, that is the domestic macro-economy, the situation of real estate industry and the condition of real estate enterprises. As a conclusion, those indexes can reflect the real estate credit risk very well, especially CLI.