Research On Financial Condition And Quality Evaluation Of Enterprise Group Finance Company

With the diversification of the economy and the continuous improvement of financial liberalization, China's finance company of enterprise group still expanding the scale of operation and their business areas, the company's assets show an upward trend. The most important indicator which reflects the level of development of the company is financial data. If we can mining valuable or meaningful information from the financial data of the finance company of enterprise group, and then according to the information, the different enterprise group finance company will Implement targeted monitoring, management and investment, both to protect the interests and interests of investors, also beneficial to the healthy and long-term development of enterprises, for and the orderly operation of the capital market has a very important practical significance. In this thesis, the financial quality evaluation of China's corporate finance companies is studied, the main contents are as follows:(1) First, the 12 secondary indicators which reflect the situation of financial quality were extracted from the audit report of 111 enterprise group finance companies in China, and then calculates the eight secondary indicators through the financial indicators. Finally, The method of factor analysis was used to extract three first-level indicators, they were profitability factor,economic growth ability factor and solvency factor.(2) Using traditional K-means clustering method, K-center clustering, system clustering,K-means clustering based on uniform initialization and K-means clustering based on optimal initialization method, With three first-level indicators as variables to classify the financial quality of 111 corporate finance companies. This thesis constructs the evaluation index system from the perspective of the financial status, Thus achieving the quantitative, classified management for different types of companies and systematically studies the application of cluster analysis method in the financial status of financial companies. Through comparative analysis, we choose a more reasonable clustering method. From the principle of clustering, the K-center clustering method improves the shortcomings of K-means clustering in sensitive to the outliers and extremes in the process of processing data. K-means clustering based on uniform initialization and K-means clustering based on optimal initialization method improves the initial center selection problem in the traditional K-means clustering method, so that the traditional K-means clustering method is no longer in random selection of the initial center, the local optimal solution problem has been solved, At the same time, the system operation reduces the number of times of clustering and iteration, and improves the efficiency of the algorithm.Clustering results shows that the traditional K-means clustering, K-center clustering, system clustering, two improved K-means clustering methods which used in the Classification of financial quality of enterprises has the same number of clustering categories which is four; and the difference between the four categories of the final classification is obvious.