Research On Financial Risk Early-Warning Of Listed Real Estate Companies Based On Asset Quality

The real estate industry is an important pillar industry of China's national economy.With the rapid development of the national economy and the acceleration of the urbanization process in recent years,the real estate price keeps rising,and the high housing price brings many challenges to people's livelihood.In order to prevent housing prices from going up too fast,the Central Economic Working Conference formally put forward the positioning of “housing not speculation” at the end of 2016.Under the general policy tone,real estate departments have successively issued a range of related supporting policies from 2017 to 2019.In this context,listed real estate companies with high debt,long asset turnover period and poor liquidity are easily fall into financial crisis because of fund chain break.Therefore,it is of great significant to effectively identify the financial risks of listed real estate companies and establish an early warning model to ensure the real estate industry and macro economy stable development.Firstly,this paper describes the background of the topic and the current situation both at home and abroad,and analyzes the cause of financial risks in depth by combining the current situation of real estate industry in our country and the financial characteristics of listed real estate companies,Secondly,the preliminary design of early warning model is carried out.According to the early warning mark of delisting risk of listed companies by the stock exchange,the warning degree is divided into Financial crisis and financial health range.By introducing the asset quality characteristics into the traditional early warning model and be clear with the primary index of financial risk.The research samples included 25 crisis companies and 50 matched healthy companies from listed real estate companies in Chinese A stock market.The sample year was from 2007 to 2018 and then preprocessed.Finally,Logistic model and BP neural network model were selected for model construction,and T-1 to T-2 year data were selected to predict the financial status in T year Compare the prediction results of the two models and then put forward countermeasures of financial risks according to the prediction results and the listed estate companies' financial characteristics.The results show that there is a significant difference between the asset quality indicators of listed estate companies and financial risk which can be used to build the warning financial indexes system.The model accuracy is about year of the crisis,the closer we get to the crisis year,the higher the prediction accuracy of the model.the empirical test shows that both models are suitable for real estate listed companies.However,in terms of model fitting degree and prediction accuracy,BP neural network model is better than Logistic model,so BP neural network model is more applicable for financial warning of listed real estate companies in China.Based on the characteristics of the real estate industry,this paper effectively analyzes the financial risk level and main influencing factors of listed real estate companies in China.The introduction of asset quality indicators make the early warning model more comprehensive and scientific,and the relevant conclusions can provide ideas for the theoretical research and practical management of financial early warning of listed real estate companies.