The Applications Of Stock Analysis Based On Grey System Theory Of Data Mining

The stock market is influenced by political and economic and cultural factors, the internal discipline is very profound, so the prediction results of traditional prediction technology are unsatisfied.Facing the existing problems in stock market prediction, such as the nonlinear property and high noise property of stock price (stock index). This paper attempts to integrate traditional Grey System Theories into Data Mining and apply the new hybrid method (models) which called it Grey-Data Mining to direct our stock analysis.Now, Grey System Theories and Data Mining application have accomplished many achievements at home and abroad, and the research is also ongoing and explorating on guiding practical application. For Grey-Data Mining is a new attempt to explore, this paper will improved the concept of Grey-Data Mining and deeply explorated the build of Grey-Data Mining system.The paper not only build grey-neural-network model composed neural-network model with GM model, but also improve grey prediction mode and apply improved grey-neural-network model in stock prediction and draw some meaningful conclusions. In addition, the paper improve grey association model and grey-cluster model of exploration,so it will apply in stock prediction from now on.I believe my studies are not only application explorats to the Grey-Data mining, but also a useful complementarity to traditional statistics in securities analysis.