Dissertation > Economic > Economic planning and management > Economic calculation, economic and mathematical methods > Economic and mathematical methods

The Empirical Research of the Important Factors of the Financial Risks of Chinese A-share Construction Enterprises Market

Author ZhangZuoWen
Tutor FengLiXia
School Changsha University of Science and Technology
Course Accounting
Keywords construction enterprises Value Creation Financial risk Factors
CLC F426.92
Type Master's thesis
Year 2011
Downloads 103
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People are focused on the issues of the risk of early warning andprevention again, when a large number of companies bankrupted in the neweconomic crisis. The construction enterprise is in a pillar of the status ofChinese national economic development. Whether the building industrycould achieve survival and development in the environment which full ofuncertainty is important to the national economy. So, to know the riskstimely and implement the most effective approach to risk management toavoid possible adverse consequences is particularly important forconstruction enterprises. Studying the factor of financial risk is the basis ofthe whole financial risk management system. It is significant to study thekey factors of financial risk of construction enterprises for guiding theenterprise risk prevention, improving the accuracy of financial risk of theearly warning models, etc. Not using the special treated enterprises forsample, this paper uses the "value creation theory" to define the meaning offinancial risk. Through the theoretical analysis of the causes andmanifestations of financial risk of building businesses, we obtained the keyindicator of financial risk of construction enterprises. Multiple logisticregression and artificial neural network approach have been used forempirical research.The empirical studies have three steps. The first is to find the possibl efactors by analysis the causes of the financial risks of constructionenterprise and to select the different factors by comparing the two groups;the second ,using the principal component analysis and regression model tofind the important factors; the third step is finally to determine the keyinfluence index with artificial neural network method inspection.

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