Proceedings of the 2023 2nd International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2023)

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Research on Financial Distress Prediction Models of Chinese Listed Companies in Pharmaceutical Manufactures Based on Machine Learning

Authors
Jian Ke1, *, Qiqi Wang1
1Newhuadu Business School, Fuzhou, 350100, Fujian, China
*Corresponding author.
Corresponding Author
Jian Ke
Available Online 28 August 2023.
DOI
10.2991/978-94-6463-222-4_59How to use a DOI?
Keywords
financial distress; random forest; svm; decision tree; logistic regression
Abstract

The pharmaceutical manufacturing industry, as a strategic emerging industry based on technology support, has received more and more investors’ attention, especially after the outbreak of the new crown epidemic. However, its industry characteristics, such as a long R&D cycle, sizeable upfront investment, and uncertain market returns in the later stage, make these companies vulnerable to financial distress if they do not focus on early warning monitoring of corporate financial and non-financial data. The purpose of this study is to build and evaluate machine learning models for financial distress prediction, including random forest (RF), decision tree (DT), logistic regression (LR), and support vector machine (SVM). The forecasting results of the above models were compared and analyzed to build more accurate forecasting models. The machine learning models were constructed using 156 financial and non-financial data sets containing 26 listed pharmaceutical manufacturing companies in China from 2016 to 2021.

Copyright
© 2023 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 Artificial Intelligence, Internet and Digital Economy (ICAID 2023)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
28 August 2023
ISBN
10.2991/978-94-6463-222-4_59
ISSN
2589-4919
DOI
10.2991/978-94-6463-222-4_59How to use a DOI?
Copyright
© 2023 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  - Jian Ke
AU  - Qiqi Wang
PY  - 2023
DA  - 2023/08/28
TI  - Research on Financial Distress Prediction Models of Chinese Listed Companies in Pharmaceutical Manufactures Based on Machine Learning
BT  - Proceedings of the 2023 2nd International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2023)
PB  - Atlantis Press
SP  - 544
EP  - 552
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-222-4_59
DO  - 10.2991/978-94-6463-222-4_59
ID  - Ke2023
ER  -