基于VaR方法的房地产抵押贷款抵押率测算-金融学专业论文.docx

ABSTRACT In recent years, as the NPL ratio rising, the credit risk mitigation becomes the primary task of the banking sector at this stage. On the one hand, the deepening of financial integration makes the risk management of commercial banks more complex; On the other hand, the domestic credit rating system is not sound, so banks prefer to offer asset-backed loans in order to avoid the credit risk of the loans. With the growth of the real estate as security for loans in the proportion of bank loans business, precise measurement of the real estate mortgage risk seems particularly important. Because pricing mechanism of fully market-oriented interest rate has not been established, mortgage rate has become the main tool for regulating the mortgage risk . To identify and guard against risks in the real estate mortgage the real estate mortgage rate has far-reaching significance. The author first introduces the research background and significance. This article summarizes the real estate mortgage loans, mortgage rates, and VaR theoretical definition. The essence of the mortgage rate is VaR calculations. This paper elaborates VaR calculation methods based on the different distribution; then describes the historical simulation method and the improved hybrid simulation method to solve the problem that the assumed distribution would not meet the actual distribution conditions under VaR Measurement. An empirical research has been carried out based on 3 day average prices of real estates in 3 different areas of the city of Nanjing. As asset prices have more leptokurtosis and fatter tails, so we use EGARCH model to estimate the expected rate of return and volatility with the normal distribution, Students t distribution and GED distribution in order to calculate VaR in a certain period of time, and then estimates the asset for mortgage rate mortgage. The result indicates that commercial banks will face lower loan risks while choosing lower pledge ratio assets, but relatively with