统计研究
統計研究
통계연구
Statistical Research
2013年
10期
54~60
,共null页
个人住房贷款 违约预测 利率政策模拟
箇人住房貸款 違約預測 利率政策模擬
개인주방대관 위약예측 리솔정책모의
Housing Mortgage; Default Forecasting; Interest Rate Policy Simulation
本文首次构建了基于非参数随机森林（Random Forest,RF）的住房贷款违约风险评估模型,利用某大型银行个人住房贷款数据,研究了借款人特征、贷款特征、房产特征和经济文化特征等因素对贷款违约的影响.实证研究发现已偿还比例、利率、贷款收入比、额度等是贷款违约最重要的影响因素,并且RF方法的预测准确率明显高于logistic模型等其他方法.此外,本文还研究了利率调整对贷款违约的影响,发现利率对违约率的影响是负方向的,且呈不对称性和非线性.
本文首次構建瞭基于非參數隨機森林（Random Forest,RF）的住房貸款違約風險評估模型,利用某大型銀行箇人住房貸款數據,研究瞭藉款人特徵、貸款特徵、房產特徵和經濟文化特徵等因素對貸款違約的影響.實證研究髮現已償還比例、利率、貸款收入比、額度等是貸款違約最重要的影響因素,併且RF方法的預測準確率明顯高于logistic模型等其他方法.此外,本文還研究瞭利率調整對貸款違約的影響,髮現利率對違約率的影響是負方嚮的,且呈不對稱性和非線性.
본문수차구건료기우비삼수수궤삼림（Random Forest,RF）적주방대관위약풍험평고모형,이용모대형은행개인주방대관수거,연구료차관인특정、대관특정、방산특정화경제문화특정등인소대대관위약적영향.실증연구발현이상환비례、리솔、대관수입비、액도등시대관위약최중요적영향인소,병차RF방법적예측준학솔명현고우logistic모형등기타방법.차외,본문환연구료리솔조정대대관위약적영향,발현리솔대위약솔적영향시부방향적,차정불대칭성화비선성.
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.
