Financial risk warning of listed real estate companies in China

Abstract

The main methods of this analysis include principal component analysis and binary logistic regression, and the essence of the study is to predict and find out which financial factors will lead to the financial and credit risks of real estate companies. This paper examines the real estate companies listed on the main board of China in the A-share market, and the financial data analysis period is from 2014 to 2020. Through empirical analysis, it can be found that cash profit rate, sales profit rate, sales cash rate and operating profit rate have the greatest impact on the accuracy of financial early warning. Finally, the accuracy rate of the financial early warning model obtained by analyzing these two indicators reaches 91.3%, indicating that the model is suitable for accurate measurement of financial early warning.