关键词: 个人住房贷款, 违约预测, 利率政策模拟

Abstract: This paper proposed a housing mortgage default risk forecasting model based on non-parametric random forest at first. Then by using the housing mortgage database from a big famous bank in China, this paper studied the effect of housing mortgage default according to borrowers’ characteristics, loan characteristics, housing characteristics and local economic and cultural characteristics. The empirical study found that the proportion which had been repaid, interest rate, ratio of loan to income, loan amount were the most important factors. The results also showed the prediction accuracy of RF were much higher than other methods such as logistic regression. In addition, this paper also studied how the interest rate affected mortgage default, finding that interest rate had negative effect, which were asymmetry and nonlinear, on the mortgage default.

Key words: Housing Mortgage, Default Forecasting, Interest Rate Policy Simulation