压力测试在我国商业银行房地产贷款中的应用研究

发布时间：2018-03-13 23:27

本文选题：压力测试　切入点：房地产按揭贷款　出处：《华中科技大学》2012年硕士论文　论文类型：学位论文

【摘要】：美国的“次贷危机”引起了全球的金融风暴，许多著名金融机构因此倒闭。风暴过后各国掀起压力测试的热潮。房地产按揭贷款跟民生有密切关系且在各家银行零售贷款中占有80%贷款余额，是各家银行的关注重点，对金融体系的稳定有严重的影响。因此研究房地产按揭贷款是否能经受住压力的冲击具有很强的现实意义。本文首先对房地产按揭贷款与银行体系稳定性的关系、压力测试的应用现状以及房地产压力测试的流程进行了总结，在此基础上建立了房地产压力测试模型，承压数据的计算方法并对结果进行了分析。本文选取了深圳X商业银行2007年12月到2011年12月为期49个月的数据。采用的是180+违约率作为衡量指标，测量在不同的压力情景下，未逾期贷款在施加压力一年后转化为180+逾期贷款的概率。文章采用的是Wilson的模型方程系统，对宏观经济变量回归不仅引入了它自身的滞后项，还引入了房地产市场价格和成交面积的滞后项，能够反映出银行表现对经济的反馈效应。系数的估计采用的是SUR估计方法，估计房地产按揭贷款和其它房产抵押贷款180+违约概率。SUR是一种面板数据分析方法，能够考虑到方程残差的相关关系，可以将房屋价格、房屋成交面积的同期相关性充分表现出来。假设干扰项不是0，带入压力情景下宏观经济的数据作为压力源头，，通过蒙特卡罗模拟法得到大量的预测PD值，由此可以得出一年后违约率在不同置信水平下的风险值(VaR)和分布情况。再结合初期的贷款额和迁徙率计算出最终的不良率。结果表明深圳X商业银行放贷的质量很好，能承受住压力，银行可以采取更加宽松的房贷政策获取更多的利益。
[Abstract]:The "subprime mortgage crisis" in the United States caused a global financial storm. Many famous financial institutions failed as a result. After the storm, there was a surge of stress testing in various countries. Real estate mortgage loans are closely related to the people's livelihood and account for 80% loans in the retail loans of banks, which are the focus of attention of banks. Therefore, it is of great practical significance to study whether real estate mortgage loans can withstand the impact of pressure. This paper summarizes the relationship between real estate mortgage loan and banking system stability, the application status of stress testing and the process of real estate stress test, and then establishes the real estate stress test model. In this paper, the data of Shenzhen X Commercial Bank for 49 months from December 2007 to December 2011 are selected. The 180-default rate is used as a measure to measure the data under different pressure scenarios. In this paper, the model equation system of Wilson is used. The regression of macroeconomic variables not only introduces its own lag term. The lag terms of real estate market price and transaction area are also introduced, which can reflect the feedback effect of bank performance on economy. The coefficient is estimated by SUR method. Estimate the probability of default on Mortgage and other Mortgages 180. Sur is a panel data analysis method that can take into account the correlation between the equation residuals and the price of the house. Assuming that the interference is not zero, the macroeconomic data brought into the stress scenario as the source of pressure, through Monte Carlo simulation method to obtain a large number of predicted PD value, From this, we can get the risk value VaRand distribution of default rate in different confidence levels after one year. Then combining the initial loan amount and migration rate, we can calculate the final bad rate. The result shows that the quality of Shenzhen X Commercial Bank's loan is very good. Under pressure, banks can benefit more from looser mortgage policies.
【学位授予单位】：华中科技大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：F832.45;F224

【相似文献】