个人住房按揭贷款提前还款影响因素和预测模型的实证研究

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浙江财经学院硕士学位论文

摘要

自1998 年以来，随着我国城镇住房体制改革的深化和发展，房地产业已成为

我国经济的支柱产业，与房地产业息息相关的房地产金融也得到迅猛的发展。根

据央行数据显示在中长期消费贷款中购房贷款所占比重达到 95%以上，购房贷款

上升速度很快，截止 2009 年6月末金融机构商业性房地产贷款余额达为 6.21 万亿，

同比增长 18.8%。房地产贷款余额增速除 2007 年11 月至 2009 年1月出现下降态

势外，其它时间段增长速度一直保持上升态势。以住房开发和个人住房消费信贷

为主的房地产金融业务已成为商业银行利润增长的重要推动力。

然而，随着近几年房价的节节攀高，利率的频繁调整，以及个人住房贷款业

务发展时间的进行，我国商业银行面临一个新的风险——提前还款风险。长期以

来我国商业银行深受呆账、坏账困扰，银行担心的是“不偿”，而不是“早偿”。

我国商业银行经历十余年的对个人住房抵押贷款探索和尝试，对个人住房按揭贷

款的不良率方面已具备比较完善的风险管理经验。如何有效管理个人住房抵押贷

款提前还款风险的研究已成为我国商业银行的当务之急。

本文借鉴国内外学者研究的方法，并搜集、整理我国某商业银行住房抵押贷

款数据，以期运用规范分析和实证分析相结合的方法寻找影响我国抵押贷款提前

还款的主要因素，并以此建立模型来预测借款人的提前还款行为。从而为商业银

行有效进行个人住房按揭贷款提前还款风险管理提供理论支持和技术参考。

根据本文的研究思路，本文的框架如下：

第一章，绪论。本章首先对个人住房按揭贷款研究背景、研究目的进行阐述，

进而对国内外个人住房按揭贷款提前还款的影响因素及预测模型的理论体系进行

总结性回顾。

第二章，我国住房按揭贷款市场概述及提前还贷影响分析。本章主要介绍我

国商业银行个人住房按揭贷款市场现状及业务特点，然后详细分析了借款人提前

还款的决策。

第三章，变量的描述性统计和数据预处理。本章主要介绍本文数据来源，并

对数据进行统计性描述，进而对数据进行深层次剖析，并初步预测影响我国个人

住房按揭贷款提前还款的影响因素。

第四章，个人住房按揭贷款提前还款影响因素的实证分析。本章在借鉴国内

外对个人住房按揭贷款提前还款的研究基础上，结合商业银行信贷资料信息，对

变量选择，赋值和量化，最终选择 18 个变量作为进一步研究基础。在研究方法的

选择上，主要选择了因子分析和判别分析，最终得出影响我国个人住房按揭贷款

提前还款的主要影响因素。

浙江财经学院硕士学位论文

第五章，个人住房按揭贷款提前还款模型的实证分析。本章在第四章实证分

析的结果基础上，分别建立判别函数和 Logistic 模型预测提前还款模型。最后对判

别函数和 Logistic 模型进行比较。

第六章，结论与展望。本章在归纳和总结全文的基础上，并阐述了本文的不

足和有待进一步深层研究的问题。

关键词：提前还款风险；因子分析；判别分析；非线性的 Logistic 模型

浙江财经学院硕士学位论文

III

ABSTRACT

Since 1998, with the reform of urban housing system deepening and developing, the

real estate industry has become the pillar industry of China, and real estate finance,

which is closely related to real estate, has also achieved a rapid development. The figure

from Central Bank of China shows that the proportion of personal house mortgage loans

in the medium and long-term consumption loans reaches over 95%. By the end of June

of 2009, the balance of financial institute commercial real estate loan reaches 6.21

trillion, up by 18.8%. The growth rate of real estate loan balance is on the rise, except in

the period from November, 2007 to January, 2009. The real estate finance, based mainly

on housing development and personal house consumption loans, has become an

important impetus for profits growth of commercial banks.

However, with real estate prices rising continuously these years, frequent adjusting

of interest rates, and personal house mortgage loans business ongoing, our commercial

banks are facing a new risk, prepayment now. Our commercial banks have been deeply

obsessed by bad debts for a long time and what they worry about is no repayment, not

prepayment. After decades of exploring and experimenting on personal house mortgage

loans, Chinese commercial banks have fairly complete risk management experiences of

controlling delinquency rate of personal house mortgage loans. Therefore, the study on

how to manage the prepayment risk of personal house mortgage loans effectively

becomes the highest priority for commercial banks.

With reference to the study methods of domestic and foreign scholars, this article

expects to use threshold analysis and example analysis together based on the collected

data of personal house mortgage loans of one Chinese commercial bank to find out the

main factors influencing prepayment of personal house mortgage loans, and to build a

model based on these factors to forecast borrowers’ prepayment, and thus in this way to

offer theory support and technical references for the effective prepayment risk

management of commercial banks.

The general framework of this paper is as follows:

The first chapter is the introduction. In this chapter, we explain the background and

purpose of this research. Then we make a summarizing about theory of personal

housing mortgages loan repayment ahead both at home and abroad, including the

influence factors and prediction model theory system.

浙江财经学院硕士学位论文

The second chapter is a summary about our housing mortgages loan market and

an analysis about influence of repayment ahead. This chapter introduces the situation

and business characteristics in commercial bank individual housing mortgage market of

our country. In addition, we analyze the borrower’s decision-making of prepayment.

The third chapter is a description of variable statistics and a data preprocessing.

This chapter introduces data source, make a statistical description of data, and to

analyze the data deeply. We forecast the influence factors prepayment of individual

housing mortgages loan in our country preliminarily.

In the fourth chapter, we make an empirical analysis of the influence factors of

prepayment of personal housing mortgages loan. Based on research of individual

housing mortgage loan both home and aboard and situation of the commercial bank

credit information, we select 18 variables in our research. We choose factor analysis and

discriminatory analysis as the research methods of our thesis. We discover the main

influencing factors affected prepayment of our personal housing mortgages loan.

Chapter 5 is empirical analysis on the model of prepayment of personal housing

mortgages loan. Based on the results of chapter 4, we set up discriminatory function

and Logistic model to forecast the model of prepayment of personal housing

mortgages loan in this chapter. Finally we make a comparison on discriminatory

function and Logistic model.

Chapter 6 is the conclusion and prospect. On the basis of summing up the paper,

we expound the deficiencies and the direction of further research of this thesis in this

chapter.

Keywords: Prepayment risk, Factor analysis, Discriminatory analysis, Non-linear

logistic model

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摘要：

浙江财经学院硕士学位论文I摘要自1998年以来，随着我国城镇住房体制改革的深化和发展，房地产业已成为我国经济的支柱产业，与房地产业息息相关的房地产金融也得到迅猛的发展。根据央行数据显示在中长期消费贷款中购房贷款所占比重达到95%以上，购房贷款上升速度很快，截止2009年6月末金融机构商业性房地产贷款余额达为6.21万亿，同比增长18.8%。房地产贷款余额增速除2007年11月至2009年1月出现下降态势外，其它时间段增长速度一直保持上升态势。以住房开发和个人住房消费信贷为主的房地产金融业务已成为商业银行利润增长的重要推动力。然而，随着近几年房价的节节攀高，利率的频繁调整，以及个人住房贷款业务发...

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