A Study On Finacial Distress Prediction Of China Listed Real Estate Conpanies

With the process of China's urban housing reform, Real Estate economic is gradually becoming an important mainstay industry of China which plays an important role in sustained economic development and improves international people's livelihood. Real Estate promotes the development of economic and gradually becomes the focus of our government surveillance.This year's "The Central Government Work Report" points out: Insisting on strengthening the regulation and supervision of Real Estate market, regulating and maintaining the market order and promoting sustainable, stable and healthy development of Real Estate industry.However, the quantitative research on regulation and supervision of Real Estate is still relatively little, this paper make quantitative assessment about the effects of policy control through financial distress prediction of Listed Real Estate. In addition, the study of the paper can also be used by investors to evaluate investment options and to improve capital allocation efficiency; managers can also use it to evaluate their own operational risks. This paper analysises the special of operating characteristics of the Real Estate industry basing on the review of financial distress forecast studies from domestic and foreign, taking into account the special nature of Real Estate industry , which is aimed to construct finance difficult position forecast indicator system of the Listed Real Estate companies and try to find out the reason of Listed Real Estate companies trapped into finance difficult position .This paper uses stepwise regression removed method to screen out the factors that can best reveal the risk of financial difficult of companies.Through comparing and analysising the pros and cons of many kinds of financial distress prediction models and the advantages of panel data in explaining financial distress and the dynamics of economic changing, this paper select Panel Data Logit model as Listed Real Estate company's financial distress prediction models.Finally, this paper makes cluster sampling in Listed Real Estate companies of China, applying 52 Real Estate companies' panel data from the years 2000 to 2007 as research sample, setting the Logit model for panel data, studying the financial ratios, cash flow ratio, audit opinions, corporate governance characteristics variables and interest rates affecting Listed Real Estate Company's financial distress. The results of this paper manifestate that integrated forecast accuracy of the model building by this paper is up to 96.15% in the exercise samples, and 94.23% in test sample. Further, this paper discovers that the low ROI and cash sales rate etc. are the reasons why Real Estate companies are trapped into financial distress, and audit opinions and corporate governance characteristics also have good predictive ability.