Data Mining Application In The Analysis Of Securities

Data Mining aims to get previously unknown and potentially useful knowledgeflom a large alnount of data.Stock markct plays an essential role in securities and financial industry.It alsoattracts increasing attention from the investors.Valid stock forecast is of greatimportance in financial investment feld.Hence,making analysis and forecast onstock prices has extraordinary theoretic significance and practical value,However,due to the various complicated factors influenced by policy,economy and investors'mentality,there is no denying the fact that those uncertain factors bring greatdifficulty to the forecast of the stock..With the development of the stockmarket,lots of history exchange data have been stored in database.It attracts moreand more attention that how to use these history exchange data to discover the rulesof the stock market. Association rules mining is an important problem in datamining research field.The aim of the association rules mining is to extract associations from vast data or objects.According to the associations we can discover the interdependence among objects and infer the property of an object from the property of the other.As a kind of the time series data,the stock one has the special character of his own besides the general characters of the time series data.If we can do some exploring research on the stock time series data via applying advancd data mining technology(such as association rules mining),which is based on the traditional economic&statistical analysis method,and get the potentially valuable knowledge,this research, aparantly,has signality in theory and practice,This paper probes into the above problems,the main contents and research productions include 2 aspects as follows:1.It generally introduces Data Mining,including the concepts and the patterns,mainmining problems,system classifications,and the application and development trend.2.Discuss the classical algorithms for the association rules mining and general methods for time series data analyzing.According to the special propety of the stock time series data,we present an algorithm guided by Meta-Rule,which is basd on the Apriori algorithm,for mining the association rules aiming at describing the interdependent changes of the stock州ce.Firstly,we get the transaction sets which are suitable for mining rules after preprocess the original stock data by adopting the Sliding-Time-Window technology;Afterward,we detailedly discuss the procedure to construct the association rules by using SQL.