| Manufacturing industry is an important factor in measuring economic strength and competitiveness of a nation.Faced with the situation of "big but not strong" in manufacturing in our country,Premier Li Keqiang put forward the goal of promoting "Made in China 2025" in the 2015 "Report on the Work of the Government," which brought more opportunities and challenges for Chinese manufacturing enterprises.In this context,once the enterprise is in financial crisis,it is more likely to face the risk of being eliminated.Manufacturing listed companies have more resources and development advantages,the development of which affects the nerves of many stakeholders.Therefore,paying attention to the financial crisis faced by itself and establishing a sensitive and effective financial early-warning mechanism so as to be invincible in the wave of mergers and acquisitions of enterprises is particularly necessary for manufacturing listed companies.This paper uses the normative research,empirical research and case studies combined research methods.In the normative part of the study,we first systematically expounded the current situation of financial early warning research both at home and abroad,summarized the research results,found the shortcomings and put forward the innovation points for the model construction and application.Secondly,The concepts of early warning of the former researchers are listed and the definition of financial early warning in this paper is proposed.Finally,the function and theoretical basis of financial early warning were clarified,and financial early warning model of this paper,that is the Logistics Regression Model,is concluded by introducing and comparing existing financial early warning models.In the part of empirical research and case analysis,this paper takes 53 listed manufacturing companies and 53 matched financial companies,which are divided into modeling samples and testing samples respectly for the first time for financial reasons from Shanghai and Shenzhen stock markets in 2014 and 2016.From the 39 indicators reflecting the financial and non-financial aspects of the model samples,23 indicators were selected,and the principal component analysis was used to reduce the dimension,and the financial early-warning model was established by using Logistics regression method.After that,the threshold points were determined by experimental comparison and the test samples were used for testing.Finally,a financial early warning model of manufacturing listed companies was constructed with an overall accuracy of about 80%.In addition,in order to improve the practicality of the constructed model and fully reflect the function of financial early warning,this paper provides a specific case analysis,that is,using the financial early warning model constructed in Chapter Three,China first heavy industries were forecasted and analyzed.In this case,we drew deep into the reasons why the enterprises got into the financial crisis and put forward corresponding countermeasures.The purpose is to provide a more scientific idea of financial early warning research for managers of listed manufacturing companies in the domestic manufacturing industry.Meanwhile,financial early warning research in other industries can also serve as a reference. |
