Early-warning Of Financial Distress Include Corporate Governance Variables

In recent years, financial distress has been an important subject in the economicfield. Enterprise’s financial status is a direct impact on the overall operation of theenterprise. Listed companies suffered financial crisis has brought huge losses not onlyto investors, creditors and other stakeholders, will also affect the normal developmentof China’s capital market. Therefore, the study on financial crisis, especially on thefinancial crisis early warning is very important.But most of previous studies only have been concerned with financial indicatorsas explanatory variables. This paper introduces corporate governance variables on thebasis of the financial data, using the Logist regression method and BP neural networkto the financial crisis early warning of China’s listed companies study.The first section introduces the background and significance of the study,discusses the concept of financial distress, reviews the important literature fromdomestic and abroad papers and proposes content and innovation of this study. Thesecond part introduces the theoretical basis of the financial crisis early warning,concept, function, and affects its financial crisis. The third part is the corporategovernance analysis, including the concept of corporate governance structure,corporate governance and theories of financial crisis, corporate governance andcorporate distressed relationship. The fourth part is the selection of samples andindicators defined during the study period, data source and select the study sampleaccording to this article on the definition of the concept of the financial crisis, theninitially selected financial early-warning indicators and corporate governance, earlywarning indicator system. The fifth part is the establishment of financial crisis earlywarning model and empirical analysis. This chapter, do a series of pretreatment toearly warning index primarily selected and samples first, then on the basis of thepretreatment, constructs the financial crisis early warning model using the BP neuralnetwork,and Logistic regression model. And then make a comparison about theforecasting effect among two model, at last, the conclusion of this paper is given. Thelast chapter summarizes the main conclusion, main contribution and the researchlimitations in this paper, then future research is prospected.In the process of research, this paper mainly has the following innovations:1.This paper selected quantifiable corporate governance indicators and financial indicators, these indicators are more comprehensive coverage of information on allaspects of the enterprise. Indicators of corporate governance introduced into themodel, prediction accuracy of the model is improved, this showsthat the corporate governance contribute to financial distress warning.2.This paper first select variable index that can summary company variousaspects information as comprehensive as possible, then simplify and optimize theindex through a series of method, such as principal component analysis, significanttest. Finally, the use of the Logist regression method and BP neural network, twosets of financial distress prediction model is constructed to compare, throughempirical analysis, the two groups compared model results are consistent.3. Attributed to the significant test,we found five variables,the number of boardmeetings, the proportion of independent directors, ownership of the Board, theproportion of shares not in circulation,the proportion of state-owned shares, were nosignificant differences in the ST companies and non-ST companies.But pluralism ofboard chairman and CEO,ownership concentration in ST companies is more than thenon-ST companies; ST companies executive pay is less than half of non-STcompanies, but the shareholding ratio of executives is8timesof non-ST companies.