| With the changes in international oil prices,petrochemical industry related industries are showing a large market fluctuations,and then on the market uncertainty to strengthen the trend.In the unstable market environment,market changes to the business to bring more risks,this risk will be directly reflected in the enterprise’s various types of financial data.In order to effectively prevent the occurrence of financial risks,early diagnosis of the risk of the occurrence of the signal,companies need to control the direct origin of risk and tracking.Because of the sensitivity and predictability of financial data,it can be used as the basis for establishing the early warning system.Through the early warning system indicators for analysis and research to enhance business risk in the business to avoid the ability to avoid.Improve the level of enterprise risk response,improve the business management of the status,the development of business leaders have a positive practical significance.Based on the existing research results,this paper studies the relevant financial risk indexes at home and abroad on the basis of predecessors.Combined with China’s petrochemical industry’s internal and external environment and internal financial risk warning status,based on the efficiency coefficient method for the petrochemical industry to build a financial risk early warning system,and select A company as a research object,the financial risk assessment and analysis.The main contents of this paper are from theoretical analysis and case study.The first is the theoretical analysis,this part focuses on the application of the theoretical reality,as well as the development trend of the petrochemical industry.For financial risk warning,the main concepts are financial risk,financial crisis and early warning three groups of concepts.This part mainly studies the financial risk and early warning,and explores the relationship between the two and the model structure.On this basis,the method of power law is used to analyze and study,and then the feasibility of financial early warning model construction is realized.The development of the petrochemical industry is poor,the need for financial risk early warning indicators to select and design optimization.On the basis of analyzing the necessity of establishing the index,the paper puts forward the principles,methods and calculation modes of building the financial risk early warning model.This paper chooses 15 financial early warning indicators,and then constructs the financial risk early warning model of petrochemical industry based on the efficiency coefficient method.In the case study,based on the financial data of Company A in 2012-2015,the financial risk early warning model is used to analyze the financial risk situation of Company A in a comprehensive and systematic way.On the one hand,the financial risk of Company A is predicted by the scoring situation of the comprehensive index.On the other hand,the main reason for the financial risk of Company A is found from the perspective of individual financial early warning index,which proves the feasibility of the model’s financial risk early warning research And applicability.Finally,it is concluded that the financial risk early warning system and the method of coercivity are beneficial to the financial analysis and easy to operate.Not only can be based on comprehensive index score analysis of corporate financial risk situation,and can be based on individual indicators of the situation analysis of corporate financial risk,to the right medicine,as soon as possible to solve the problem.In the process of risk early warning,the comprehensive evaluation and analysis of the early warning indexes of each system are added,which can help the early warning results.The evaluation of the degree of the fluctuation of the indicators and the degree of information provided will help to help the financial managers to focus on the analysis of the risk warning at different times and make precautions.And for the actual situation of A company,put forward four improvement measures. |
