An Empirical Research On Financial Crisis Prediction Of The Real Estate Industry Listed Companies In China

The real estate industry is the foundation and pillar industry of national economy in China. The financial health of the real estate listed companies or not directly affects all stakeholders in the market, and affects the development of the whole national economy and social development. As a capital intensive industry, the real estate industry has the characteristics of the huge investment, long cycle, high risk and returns, long supply chain, strong regional. What’s more, the development of the real estate industry is over-rapid in recent years, the government frequently introduced a series of policies to curb the development of real estate discord. So financial risks has become an urgent problem to solve for survival and development in domestic real estate company. Therefore, building a suitable financial crisis early warning mechanism for real estate enterprise is very meaningful, which is used for forecasting the enterprise’s financial and operational situation.This paper refers to the literature and data of domestic and foreign financial early warning, considering the basic characteristics of the real estate industry, analyses the related factors of the enterprise into a financial crisis, and based on these factors, selects the relevant research variables. Through the statistical analysis and modeling on these variables, We establishes a suitable financial crisis early warning system for real estate enterprise in China. Our paper includes five parts, and we summarized as follows:Firstly, introduction. This paper expounds the realistic and theoretical background, significance of pre-warning for financial distress of real estate listed companies.Then we introduce the main contents, methods and the innovation points of this paper.The second part, research review. We define the financial distress and the financial early warning, then briefly review of the findings already achieved in this field, which establishing the theoretical foundation for the research. At the same time, this paper especially elaborates present situation of our country in this field and analyzes the development trend of the financial early warning theory.The third chapter, analysis of financial crisis in the real estate industry of China. Combining with the present situation and characteristics, we state financial risk of real estate enterprises in our country and analyze the macro and micro factors affecting the development of the real estate industry.The fourth part, the empirical research. This part is mainly for the design of the model, in which we introduces the selecting and eliminating process of samples,and the source of the data. We have applied SPSS19.0to do the K-S normal distribution on indicators’data.Furthermore, We use the independent T test for the indicators satisfying normal distribution, but for the other indicators we do the non-parameter test. Later we screen out the main elements from significant financial indicators. The main innovation points of this essay is that we constract the pre-warning Logistic models(M1) for financial crisis based on sample data of the weighted average from2009to2011. The Cut Value is usually chosen to be0.5.However this paper are tentative to adjust threshold. We choose a smaller one0.38in the paper, in order to improving the effectiveness of our model to identify enterprise with financial crisis. This paper not only carries on the Test of Goodness for Fit, but also verify the models by using the data in2012.In order to compare, We use the sample data of2009to establish the pre-warning Logistic models(M2).The fifth part, conclusion and prospect. This part summarizes the results and shortcomings of the empirical research, then prospects the future research and puts forward related suggestions.The results show that compared to M2, models M1shows better in over-all degree of fitting and prediction accuracy, the accuracy of Ml is up to98.1%. We tests our models by using the latest data from Annual Report of2012,the accuracy of it is up to76.19%.So we finally choose the Ml model as the research object in this paper. In addition, the conclusion of model Ml tells that principal components F3and F4are negatively related to the probability of companies’financial crisis, where F3is mainly accounted for profitability, size of company, Tobin Q; F4mainly for profitability.