Research on Financial Distress Diagnosis of Real Estate Listed Companies Based on PCA-Logistic Model

Yu Jiang, Kai Xu (), Yan Hu, Dongyang Li and Dongxu Long
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Yu Jiang: Chengdu University, Business School
Kai Xu: Chengdu University, Business School
Yan Hu: Neijiang Normal University, School of Economics and Management
Dongyang Li: Chengdu University, Business School
Dongxu Long: Southwest Jiaotong University, School of Mechanical Engineering

A chapter in Proceedings of the 10th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC 2022), 2023, pp 306-312 from Springer

Abstract: Abstract Financial distress diagnosis is of great significance to the risk prevention and control and sustainable operation of real estate industry. This paper takes China's a-share listed real estate companies as samples, selects financial indicators based on the characteristics of the real estate industry, and uses PCA-Logistic system to build a model of the second year before the enterprise falls into financial difficulties. The results show that the company's profitability and capital market performance factors contribute the most to the prediction, and the prediction accuracy is high. The suc-cessful construction of the model provides a basis for decision-makers to accurately and prospectively judge the fi-nancial distress of real estate companies.

Keywords: Financial Distress; Listed Real Estate Companies; Principal Component Analysis; Logistic Regression (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-194-4_43

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DOI: 10.2991/978-94-6463-194-4_43

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