影响我国住房抵押贷款提前还款因素的实证研究

发布时间：2018-10-12 20:11

【摘要】：近年来,随着我国房地产业的长足发展以及住房制度改革进程的加快,中国的住房抵押贷款得到了快速发展。与此同时,住房抵押贷款证券化(MBS)作为国际金融创新的一个新亮点,是我国进一步深化住房金融发展的一个切入点。在MBS发行过程中,合理确定作为其标的资产的住房抵押贷款的价值始终是其核心问题之一,而借款人的提前还款行为带来的违约风险直接影响了资产池现金流,因此,准确研究提前还款因素是研究MBS的重要前提。加强对住房抵押贷款提前还款风险的研究已成为当务之急。本文拟通过实证研究的方法来对影响我国住房抵押贷款提前偿付的因素进行研究分析。首先,本文介绍了国内外影响住房抵押贷款提前还款因素的相关理论,包括影响提前还款的因素、相关的模型介绍以及提前还款的风险。随后,本文将收集到的某商业银行2000份住房抵押贷款的样本数据进行整理分析,引入定量分析法,通过因子分析、判别分析等多元统计方法寻找影响提前还款的主要因素。经研究后发现,影响我国住房抵押贷款提前还款的因子包括利率因子、房贷期限抵借比因子、提前还款金额因子、借款人性别因子、借款人经济状况因子和借款人年龄和婚姻因子。之后,本文通过收集到的数据利用判别分析以及逻辑回归模型来对上述因素进行实证分析,根据软件计算结果得出,通过构建统计模型来预测提前还款风险这一途径是很有效的。本文的实证分析结果表明,通过构建统计模型并且选择恰当的解释变量,不仅能够较好地预测提前还款风险,而且我们可以根据模型中的系数大小来掌握各个解释变量对提前还款风险的贡献程度,可为后续实施住房抵押贷款证券化的资产池选择上提供一定的参考依据。最后,本文结合实证分析部分对住房抵押贷款证券化提前偿付风险提出一些防范建议,期望可以有效的促进我国住房金融进一步的发展。
[Abstract]:In recent years, with the rapid development of China's real estate industry and the accelerated process of housing system reform, the housing mortgage loan in China has been developing rapidly. At the same time, as a new bright spot of international financial innovation, (MBS) is a breakthrough point for further deepening the development of housing finance in China. In the process of issuing MBS, it is always one of the core problems to reasonably determine the value of the housing mortgage loan as the underlying asset, and the default risk brought by the borrower's prepayment behavior directly affects the cash flow of the asset pool. Accurate study of prepayment factors is an important prerequisite for the study of MBS. It is urgent to strengthen the research on the prepayment risk of housing mortgage loan. This paper intends to analyze the factors that affect the advance payment of mortgage loans in China by empirical research. First of all, this paper introduces the domestic and foreign factors affecting the prepayment of housing mortgage loans, including the factors affecting prepayment, the relevant model and the risk of prepayment. Then, the sample data of 2000 housing mortgage loans collected by a commercial bank are analyzed, and the quantitative analysis method is introduced to find the main factors affecting prepayment by factor analysis, discriminant analysis and other multivariate statistical methods. After the study, we found that the factors that affect the prepayment of housing mortgage loans in China include interest rate factor, mortgage maturity credit ratio factor, prepayment amount factor, borrower gender factor. Borrower's economic condition factor and borrower's age and marriage factor. Then, through the data collected by discriminant analysis and logical regression model to carry out empirical analysis of the above factors, according to the results of the software calculation, It is effective to construct statistical model to predict prepayment risk. The empirical results show that by constructing statistical model and choosing appropriate explanatory variables, we can not only predict the risk of prepayment, but also predict the risk of prepayment. Furthermore, we can grasp the contribution of each explanatory variable to the prepayment risk according to the coefficient in the model, which can provide some reference for the selection of asset pool for the subsequent implementation of mortgage securitization. Finally, this paper puts forward some preventive suggestions on the risk of mortgage securitization in advance, hoping to promote the further development of housing finance in China.
【学位授予单位】：华南理工大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：F299.23;F832.4

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