Logistic Model-based Prediction of Financial Distress of Listed Chinese Real Estate Companies

Yueru Chai, Yixin Gan and Yiou Wang ()
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Yueru Chai: Fudan University
Yixin Gan: Shanghai International Studies University
Yiou Wang: Southwestern University of Finance and Economics

A chapter in Proceedings of the 2023 2nd International Conference on Economics, Smart Finance and Contemporary Trade (ESFCT 2023), 2024, pp 136-145 from Springer

Abstract: Abstract With the introduction of restrictive housing price policies in China contemporarily, real estate companies are facing new development challenges. China Evergrande Group’s debt crisis has made people emphasize more on the financial status of real estate companies. In this paper, 20 Chinese A-share companies facing financial distress and 20 companies without financial distress are selected as research samples. A total of 16 financial indicators and non-financial indicators are chosen to establish Logistic-based model. Finally, suitable early warning indicators were screened and a financial distress early warning model with high accuracy was derived. The percentage of administrative expenses has the greatest impact on whether a company is in financial distress, and real estate companies should strengthen their operating cost control. By analyzing the model of real estate companies, the company operators can pay attention to the problems that arise in the company’s operation in advance and can take corresponding measures to avoid the company from falling into financial distress. Overall, these results shed light on guiding further exploration of enterprise financial distress forecast.

Keywords: Financial Distress Early Warning; Real Estate Companies; Logistic Model (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-268-2_17

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DOI: 10.2991/978-94-6463-268-2_17

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