Research In Financial Risk Prediction On Real Estate Industry Of China Listed Companies

? The real estate industry coexist the high risk and the high return, in order to keep social stability and majority people could enjoy their life, the state which through using tax,finance,fiscal policies to regulate the real estate industry. The experiment of property tax and the limited purchase of the hot city make the real estate industry suffer lots of huge financial pressure. Simultaneously the real estate industry response huge to the external environment uncertainty change. Its environment become more and more complex, the increasing of the profit takes the higher risk as the price. Therefore, to reduce and eliminate the financial crisis, it needs us to strengthen the risk prevention consciousness, to pay more attention on the financial crisis system.This paper is structured in six parts, with details followed by:Part one takes a brief review on the overall background of financial crisis theories analyzing, then describes the domestic and foreign financial distress literature, and describes the analysis method and the main innovation.Part two described the financial risk prediction which based on the cash flow perspective, introduced the theoretical basis of the financial risk prediction and the meaning of cash flow management and the status of the financial risk prediction.Part three elaborated the finance crisis origin and the characteristic in Real Estate Industry; it included an overview of real estate market, the specific performance of financial risk and the general characteristics of financial crisis.Part four described the financial distress which based on cash flow method, it introduced the thesis of the principal which using component analysis and logistic regressionPart five described the real estate financial forecasting model research which based on cash flow analysis, then using the component analysis method to select the index and using the logistic regression to conduct model analyze.Part Six described the final analysis result indicated by the 4 years validation, the model which based on the component analysis and Logistic regression method maintained a quite high accuracy. The innovation of this paper is the sample of sub-sectors. The collection using the non-paired method that using a relatively ST and non-ST companies that avoided the contingency and subjectivity defects in paired sample method; then amended the segmentation point to 0.08 in regression analysis.