数据挖掘技术在股票数据分析中的应用研究

Research on the Application of Data Mining Technology in Stock Data Analysis

本文分析了股票数据分析预测的特点,阐述了数据挖掘的基本流程,指出在股票数据分析过程中应用数据挖掘技术是可行的、必要的,并提出了股票数据分析应用数据挖掘的关键技术,即先利用关联规则算法挖掘出影响股票涨跌值的指标,再利用决策树算法找出最具有投资价值的股票池,最后应用神经网络算法预测股票价格的变化,后续还需要进一步改进,以提高预测精度。

This paper analyzes the characteristics of stock data analysis and prediction,expounds the basic process of data mining,points out that it is feasible and necessary to apply data mining technology in stock data analysis,puts forward the key technology,including mining the indexes affecting the rise and fall of stocks by using association rule algorithm,using decision tree algorithm to find the stock pool with the most investment value and using neural network algorithm to predict the change of stock price.It points out that further improvement is needed to improve the prediction accuracy.