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Research On The Financial Crisis Warning For Listed Manufacturing Companies Based On The Normal Cloud Theory

Posted on:2017-08-13Degree:MasterType:Thesis
Country:ChinaCandidate:X N SongFull Text:PDF
GTID:2439330488465381Subject:Business management
Abstract/Summary:PDF Full Text Request
Manufacturing is the supporting industry of national economy,and the listed companies of manufacturing industry occupies the quite a number of total listed companies in China.However,there are a lot of difficulties during the development of China's manufacturing industry.Many developing countries obtained the competitive advantages of greatly with cheap labor cost,and China lost a lot of low-end manufacturing industry.At the same time,the strategy of developed countries made "return" about manufacturing industry has brought heavy pressure to China.So China issued the "made in China 2025" and let "made in China" heat up again on a global scale,but the road to develop China's manufacturing industry was still difficult,and there were quite a number of manufacturing listed companies appeared under pressure from both inside and outside the financial crisis.It was nearly eighty percent of manufacturing in listed companies that was implemented ST processing in 2015 years according to WIND information repository.Because the important position of manufacturing industry and the current dilemma of listed companies,“Made in China" could survive in adversity and back on its feet under adversity,and then response to the crisis and challenges timely should be attention.Therefore,if the manufacturing early warning model of listed companies could be established,it would be of great significance.Manufacturing listed companies was selected as the research object of this article,and among them,three ST companies and a normal companies as research samples,according to the actual manufacturing listed companies development characteristics.And then the manufacturing industry listed company financial crisis warning system was established from "the debt service,operation,development and profit,the ability to obtain cash",and including 23 early warning indicators.In addition,the dynamic manufacturing industry listed company financial crisis early warning model is established based on the theory of normal cloud and dependent function.Then the manufacturing listed companies' financial crisis conditions were evaluated from 2003 to 2013,and the development trend of manufacturing listed companies financial crisis in 2017 had also been warning came out.The research results could help manufacturing listed companies timely found short boards and promote the healthy operation with reference of theory and method.Early warning index system and early-warning model had strong characteristics of dynamic adaptability and flexibility about manufacturing listed company financial crisis.It could provide the scientific support for manufacturing industry listed company financial crisis warning to make decision.The early warning model not only could help measure the company's financial future changes in the overall situation,but also could help find the short boards of affect the company'sfinancial operating conditions.Different manufacturing listed companies had some short indicators,such as debt paying ability,operation ability,and ability to obtain cash,and so on.Therefore,the development of manufacturing industry listed companies in the later process should pay attention to focus on the following aspects: control the debt levels,adjust the structure of debt;improve the credit rating method,reduce bad debt losses,to strengthen the use of science and technology and innovation,eliminate backward production capacity,the development of new products,revitalize the assets,improve the ability of operating cycle;establish the cash flow management system and budget system,control of cash flow,and avoiding the occurrence of financial crisis due to the rupture of capital chain.
Keywords/Search Tags:Manufacturing Listed Companies, Financial Crisis, Early Warning, Cloud Model
PDF Full Text Request
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