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Financial Crisis Warning for Listed Manufacturing Companies in China
In this paper, we have first selected 28 indicators based on the selection principle of financial indicators adopted in relevant studies both at home and abroad from seven aspects, which include profitability, long-term and short-term solvency, company development capacity, operating capacity, cash...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9054417/ https://www.ncbi.nlm.nih.gov/pubmed/35498193 http://dx.doi.org/10.1155/2022/1439057 |
Sumario: | In this paper, we have first selected 28 indicators based on the selection principle of financial indicators adopted in relevant studies both at home and abroad from seven aspects, which include profitability, long-term and short-term solvency, company development capacity, operating capacity, cash flow generation capability, equity characteristics, and board characteristics. Subsequently, we have conducted the comparative analysis and comprehensive study on the logistic early warning model and BP neural network to provide reference for managers and stakeholders to select the optimal model. In addition, through our study on the dynamic early warning of BP neural network, we intend to convey the concept of constantly updating the model to both managers and stakeholders. Therefore, this paper provides ideas for the research on the model of financial crisis early warning for China's manufacturing industry. The study is of significance for guiding the research of related issues in the manufacturing sector and can also provide reference for the early warning of other industries. |
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