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Early Warning Research on Financial Risk of Transportation Enterprises Based on Logistic Regression Analysis

In: Proceedings of the 2023 3rd International Conference on Financial Management and Economic Transition (FMET 2023)

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  • Yueshan Han

    (Jiangsu University of Science and Technology, School of Economics and Management)

Abstract

In the of development, transport companies can be poorly operated thus resulting in sustained losses. To address such a situation, this paper adopts the data of listed companies in Luxembourg-Shenzhen transport from 2010 to 2022 as a sample, and applies factor analysis to screen out four principal component factors, then construct a financial risk early warning model for transport companies through binary logistic regression analysis. The results show that the overall correct rate of the model's early warning reaches 96.6%. Therefore, the model can better predict the financial crisis of listed transport companies.

Suggested Citation

  • Yueshan Han, 2024. "Early Warning Research on Financial Risk of Transportation Enterprises Based on Logistic Regression Analysis," Advances in Economics, Business and Management Research, in: Vilas Gaikar & Min Hou & Yan Li & Yan Ke (ed.), Proceedings of the 2023 3rd International Conference on Financial Management and Economic Transition (FMET 2023), pages 203-209, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6463-272-9_21
    DOI: 10.2991/978-94-6463-272-9_21
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