【作者】 张胜权；

【导师】 周晓阳；

【作者基本信息】 华中科技大学 ， 概率论与数理统计， 2009， 硕士

【摘要】 随着社会经济的发展和人们投资意识的不断增强,股票已经成为投资理财的一种重要工具,从而股票走势的预测具有十分重要的意义,然而,股票市场是一个极其复杂的系统,股价走势的预测问题是一个非常困难的问题,尽管如此,股价走势的预测还是引起了越来越多人的关注和研究。数据挖掘,是90年代中后期发展起来的人工智能分支,它以发现海量数据中隐含的、新颖的、有价值的信息和模式为目标,是一种高层次的数据分析。股票市场中积累了大量的交易数据,数据中隐含了大量有用的信息,采用数据挖掘的相关技术对股市数据进行分析,探索股价走势中的规律,建立股价走势的预测模型,无疑具有重大的现实意义。本文以中国股票市场为背景,利用数具挖掘的相关技术建立了用于预测股票走势的定性预测模型和定量预测模型,并得到了比较好的结果,由于采用的数据是沪深股市其中550只个股近十年累计约120万个交易日的数据,数据具有很好的代表性,因此,模型具有良好的泛化能力,模型产生的结论也具有较强的说服力,模型具有一定的参考价值,同时,本文的研究页表明了采用数据挖掘的相关技术进行股价预测是可行的。更多还原

【Abstract】 With social-economic development and strengthening of people’s investment consciousness, The forecast of stock price movement is very important and meaningful,stocks have become an important investment instrument. However, as stock market is a very complicated system, forecast of stock price movement has become very difficult; despite the challenges, people are paying more attention to this area and are doing more research.Data-mining ,a new Artificial Intelligence branch developed since1990s’,focus on discovering valuable modes which are hidden in mega-data and it is high-level of data analysis. a large number of stock market transaction data is accumulated , a great deal of useful information is implied in stock data,Thus, using data-mining techniques to analyze stock data and explore the law in the stock price movement,building forecast model on stock price movement is very meaningful.This paper builds both the qualitative and quantitative forecast models of stock price movement using data-mining on the Chinese stock market with satisfactory results. Among the stocks traded on the Shenzhen and Shanghai Stock Exchange, 550 stocks have records of 1.2 million trading days accumulatively, Data are well represented, so the models can be widely extended with pervasive conclusions. We believe it is workable to forecast stock price movement using data-mining.更多还原