The Application Of Data Mining In The Analysis Of Financial Data Of Listing Corporation

In financial analysis of listing Corporation, most of the company's financial analysis using statistical methods or financial statements but the financial analyst in many cases difficult to analyzing and processing the financial data for many years or massive information of the entire industry. Can not find the internal relation among the financial data or financial attributes.Data mining is a technology based on data warehouse and business intelligence, can discover hidden and useful information, It can dig out the uncharted and indiscoverable information from the massive financial data. On the base of that, the company's policy makers can have a depth understanding of company's operating status.The data is obtained from the third quarter 2014 financial data of different listing Corporation on the sharp think database. Firstly, this paper introduces the clustering analysis, decision tree classification, association rule data mining algorithm, and then according to the data mining process from data pre-processing, data exploration to establishing data mining model, combined with the use of statistical analysis software like of R, Matlab for the data processing and mining. The results show that there is a more closely clustering method in the listing Corporation of 13 stocks. The classification of decision tree was improved significantly through the clustering of data. The analysis of association rules shows that there is a strong correlation between the various attributes in the financial data of the listing Corporation, and the financial index has important influence on the classification of stocks. If the current ratio has a low level(less than 1.5), the company is more likely to be a scarce resource. The application of data mining can not only provide data support for identifying financial fraud, Guide the masses or investors to invest, also help management to make timely and appropriate decisions.