Proceedings of the 2023 2nd International Conference on Economics, Smart Finance and Contemporary Trade (ESFCT 2023)

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

Authors
Yueru Chai1, Yixin Gan2, Yiou Wang3, *
1Fudan University, Shanghai, 310000, China
2Shanghai International Studies University, Shanghai, 200000, China
3Southwestern University of Finance and Economics, Chengdu, 610000, China
*Corresponding author. Email: wyo@smail.swufe.edu.cn
Corresponding Author
Yiou Wang
Available Online 10 October 2023.
DOI
10.2991/978-94-6463-268-2_17How to use a DOI?
Keywords
Financial Distress Early Warning; Real Estate Companies; Logistic Model
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.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2023 2nd International Conference on Economics, Smart Finance and Contemporary Trade (ESFCT 2023)
Series
Advances in Economics, Business and Management Research
Publication Date
10 October 2023
ISBN
978-94-6463-268-2
ISSN
2352-5428
DOI
10.2991/978-94-6463-268-2_17How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Yueru Chai
AU  - Yixin Gan
AU  - Yiou Wang
PY  - 2023
DA  - 2023/10/10
TI  - Logistic Model-based Prediction of Financial Distress of Listed Chinese Real Estate Companies
BT  - Proceedings of the 2023 2nd International Conference on Economics, Smart Finance and Contemporary Trade (ESFCT 2023)
PB  - Atlantis Press
SP  - 136
EP  - 145
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-268-2_17
DO  - 10.2991/978-94-6463-268-2_17
ID  - Chai2023
ER  -