%0 Journal Article
%T 基于Logistic回归模型的房地产上市公司信用风险研究<br>Research on Credit Risk of Real Estate Listed Companies Based on Logistic Regression Model
%A 杨璐菱
%J Finance
%P 46-54
%@ 2161-0975
%D 2024
%I Hans Publishing
%R 10.12677/FIN.2024.141007
%X 伴随着中国城镇化的发展，在过去二十年里，我国的房地产行业迅猛的发展。由于房地产行业的产业关联性极强，已然成为我国民经济的重要“支柱产业”之一。在此背景下，研究房地产的企业信用风险，对构建现代房地产企业管理机制，以及商业银行的风险管理有着重要的现实意义。本文搜集了2020年所有房地产上市公司的财务报表中的14个有关风险管理的财务指标，构建了房地产企业的财务信用评价指标体系。再通过因子分析法生成了对所有指标具有代表意义的4个公因子，并挑选出具有实际意义的两个公因子：即企业的“盈利能力”M1和企业的“偿债能力”M3。之后，选取M1和M3作为自变量，选取Y“企业是否为ST企业”作为因变量，建立Logistic回归模型。结果显示建立的Logistic回归模型能实际计算一个房地产企业信用风险，且一个房地产企业的盈利能力越好，其面临的信用风险就越低。最后根据输出结果提出了一些可行的实际建议，例如要关注与盈利能力相关的指标的变动，要制定相应的防范措施以避免企业出现信用风险等。<br />
Abstract: With the development of urbanization in China, in the past 20 years, China’s real estate industry has developed rapidly. Due to the strong industrial correlation of the real estate industry, it has become one of the important “pillar industries” of our national economy. In this context, the study of real estate enterprise credit risk is of great practical significance to the construction of modern real estate enterprise management mechanism and the risk management of commercial banks. This paper collects 14 financial indicators related to risk management in the financial statements of all listed real estate companies in 2020, and constructs the financial credit evaluation index system of real estate enterprises. Then, four common factors representing all indicators are generated through factor analysis, and two common factors with practical significance are selected, namely, the “profitability” M1 and the “solvency” M3. After that, the Logistic regression model was established by selecting M1 and M3 as independent variables and Y “whether the enterprise is ST enterprise” as dependent variable. The results show that the established Logistic regression model can actually calculate the credit risk of a real estate enterprise, and the better the profitability of a real estate enterprise, the lower the credit risk it faces. Finally, according to the output results, some practical suggestions are put forward, such as paying attention to the changes of the indicators related to profitability, and formulating corresponding preventive measures to avoid the credit risk of enterprises.
%K 信用风险，因子分析法，Logistic回归模型<br>Credit Risk
%K Factor Analysis
%K Logistic Regression Model
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=78731