The Credit Risks Research Of Real Estates Of Commercial Bank Based On The Logistic Regression Model

American bubble burst of real estate market triggered the subprime crisis, which led to the global financial crisis and made the world economy falters. China should regard it as an alert.Chinese the development of real estate market is so fast in recent10years and the commercial banks provides credit loan is the basic condition of real estate development.The credit loan of real estate accounts for about2.2%of total bank loan in2012. Strengthening the management of credit risks of real estate can enhance the capacity of commercial banks to risk prevention and control,which also promotes the stable operation of the national economy.This paper sees the credit risks of real estate as the research object.It explores a more effective judgment method to measure the credit risks of real estate for commercial banks.The article concludes predecessors related theories and methods, discusses assessment methods and metrics model of credit risk and compares them.Choosing the most suitable model for Chinese real estate credit risk measurement,which is Logistic regression model. At the same time, the paper selects the Shanghai and Shenzhen50listed real estate companies financial data in2012-2012.Using SPSS to carry on the principal component analysis and getting warning factors of the credit risk,which is independent variable of the Logistic regression model.The model of the empirical study shows that the Logistic regression model is set up on the sample prediction effect is very ideal and it can calculate the corporate default rates and provide a basic judgment for bank loans to the enterprise.Enterprise’s solvency indicators and profitability indicators eal. negative correlation with corporate default rates, and other factors are positively correlated with corporate default probability.