Study On The Correlation Between Capital Structure And Profitability Of Listed Companies In China's Engineering Equipment Manufacturing Industry

Since the naissance of MM theory, the capital structure study is always a hot problem in financial theory. The study on capital structure from academic and foreign scholars focuses on the impact facts of capital structure, and the contribution of capital structure to enterprise value or company performance, the conclusions are different. But there are studies existed showing capital structure in different industries has different characteristics, an increasing amount of scholars start to study capital structure from one singe industry, we can see electric home appliance and real estate industry is the focus of research, however, there are less study on engineering equipment manufacture industry. As a result, the author thinks study on capital structure of engineering equipment manufacture industry still has research space and theoretical significance.Firstly, this paper introduces the background and meaning of study, the content and method of the study, the innovation and points needing improving of the paper. Afterwards, it reviews the theory of capital structure and the relevant literature. Secondly, the writer particularly analyzes the present condition of engineering equipment industry through financial data, in the hope of finding the characteristics and existed problems of capital structure in engineering equipment industry. Finally, author empirically analyzes the correlation relationship between capital structure and profitability. In this paper, the capital structure indicators are selected as common asset-liability ratio and other ratios concerning the characteristics of engineering equipment industry. As for profitability, in order to decrease the correlation between indicators, we choose employing factor analysis method to calculate a comprehensive evaluation score. Then we take asset-liability indicators as independent variable, the comprehensive evaluation score as dependent variable, establish relationship model, put the data in statistical software, and go along regression analysis.