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

DOI

10.2991/978-94-6463-272-9_21How to use a DOI?

Keywords

transport companies; factor analysis; logistic regression

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.

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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TY  - CONF
AU  - Yueshan Han
PY  - 2023
DA  - 2023/10/15
TI  - Early Warning Research on Financial Risk of Transportation Enterprises Based on Logistic Regression Analysis
BT  - Proceedings of the 2023 3rd International Conference on Financial Management and Economic Transition (FMET 2023)
PB  - Atlantis Press
SP  - 203
EP  - 209
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-272-9_21
DO  - 10.2991/978-94-6463-272-9_21
ID  - Han2023
ER  -