Research On Financial Crisis Early Warning Of Real Estate Industry Based On Comment Data

The main measure to prevent business risks is financial crisis warning.Nowadays,the increasingly active market competition and the rapidly rising modern technology all directly or indirectly lead to the increasingly complex factors of financial crisis of enterprises.Real estate is one of the critical sectors of our society.If a financial crisis occurs,it will not only obstruct the survival and sustainability of real estate businesses,but also may have a significant influence on the economy and people’s living.Therefore,a more complete financial crisis prevention system needs to be formed in order to reduce the risk of operation to a great extent.As the financial indicators of enterprises are relatively single in recent years,and in the process of research,all human thinking may have some influence on the selection of non-financial indicators,which are difficult to define in terms of specific quantities.Therefore,it is difficult for such forecasting models to achieve the desired early warning effect.In this paper,we use the support of data technology and the effectiveness of review data,which can be confirmed by the research of domestic and foreign scholars,under the gradual influence of signaling,as well as the benefit of review data to financial early warning,by analyzing the relevant theories in order to make the rigor and rationality of review data to be used in the financial early warning of real estate enterprises.By obtaining the relevant financial indicators of real estate companies in the Guotaian database,establishing a logistic model,and then applying the established model to the selected Company A,we analyzed the specific content of Company A’s financial indicators and compared the impact of not introducing commentary indicators and introducing commentary indicators on the prediction accuracy of the financial crisis early warning model;Based on the research results of previous scholars in the field of crisis early warning research,I collected 15 real estate companies with normal listed financials and 45 real estate companies with listed financials in crisis according to the matching ratio of 1:3,and used the data of the first three years of the company’s crisis as the sample for calculation;31 financial early warning indicators were initially selected from the five capability indicators,and using SPSS 23.0 software,a series of tests and analyses were conducted on the initially selected indicators to clarify the Five integrated principal components: these five components contain 13 financial indicators and one commentary data indicator,after which regression analysis was performed using SPSS 23.0,and a correct prediction rate of 82.1% was obtained.The innovations of this paper are as follows: firstly,the samples are all selected from the real estate industry,which in turn makes the nature of the samples closer and finally makes the established model more applicable to the real estate industry;secondly,the concept as well as applicability of commentary data indicators based on the stock bar of Oriental Fortune are discussed to enlarge the range of indicators selected for the financial crisis early warning model.The exploration of this paper leads to the following findings: first,the accuracy of the model’s prediction can be enhanced significantly by introducing commentary data indicators into the traditional crisis early warning model;secondly,the model is successfully applied to real estate company A,which in turn shows that the model established in this paper is applicable to the listed real estate industry and has certain prediction accuracy.