| How can companies stand up to the tide of globalisation without being swept away?Economic globalization has put countries into the increasingly open market,providing endless development opportunities but also bringing endless business risks to companies.In such an economic environment,companies can easily fall into financial crisis or even bankruptcy if they do not operate well.For listed companies in the manufacturing industry in particular,they face more intense market competition due to the low entry barrier to the industry,the low market concentration in some segments and the large number of companies in the industry..At the same time,listed companies in the manufacturing sector account for a large share of the stock market and have a stake in the interests of many stakeholders.Therefore,listed companies in the manufacturing industry should pay more attention to their own financial situation,establish an effective early warning model for financial crises,and discover the signals of financial crises in time so as to be fully prepared to deal with them,thereby ensuring healthy operation of the company,reducing the risk of being eliminated from the market,safeguarding the benefits of stakeholders and maintaining the stability of social order.This paper combines literature research method,empirical research method and comparative analysis method to study the financial crisis early warning of listed companies in the manufacturing industry.Firstly,by combing the relevant literature,we summarise and analyse the current status of research on financial crisis early warning.Secondly,the theoretical basis of this paper is clarified by combining the definition of financial crisis and financial crisis early warning with the existing literature.Then,we study the current development status of the manufacturing industry and analyse its financial characteristics from "three dimensions",so as to lay the foundation for the subsequent selection of indicators and model construction.A total of 36 listed companies in the manufacturing industry that were firstly ST listed due to their financial status between 2019 and 2022 were selected as companies in financial crisis,108 companies in financial health were paired together as the training group sample,while 28 companies were randomly selected as the test group sample.Then,based on the selection of traditional financial indicators,the non-financial factors that may influence the occurrence of a financial crisis are analysed from both internal and external aspects of the company’s operations.The non-financial factors were quantitatively or qualitatively described as non-financial crisis warning indicators,and a total of 29 indicators were selected through normality and significance tests.Factor analysis was then used to extract the main factors,and a binary logistic regression method was used to build a financial crisis early warning model.In addition,the model performance was analysed from three aspects: statistical test,empirical test and comparative test.The model was statistically analysed,substituted into the test group sample data,plotted the prediction probability ROC curve and compared with the prediction accuracy of the Z-score model respectively.The validity and adaptability of the binary logistic regression model established in this paper are finally verified,and countermeasures and suggestions for the manufacturing industry are proposed based on the financial crisis warning results. |
