电子交易行情预测算法研究

【作者】 马大为；

【导师】 王世卿；

【作者基本信息】 郑州大学 ， 计算机软件与理论， 2004， 硕士

【摘要】 电子交易已替代传统交易方式广泛应用于股票、期货、技术产权等交易领域，伴随电子交易出现的海量历史数据以及信息的实时更新，为行情分析预测提供了可能。通过对交易过程中积累的大量历史记录进行分析，可为交易者及管理者提供有益的决策参考依据。 知识发现(KDD)与数据挖掘技术是计算机领域一个非常具有活力的研究课题，其研究成果已广泛应用于金融、医疗保健、零售、制造业、工程与科学等行业，现在国外已经把知识发现与数据挖掘技术应用于交易行情分析领域。 本文针对电子交易行情分析与预测四个方面的问题，采用知识发现与数据挖掘技术的概念、方法，综合运用数学等相关学科的技术，通过分析、比较，提出解决办法。并对实现细节进行了描述。其主要研究内容包括： 1．根据历史数据对若干可能的贝叶斯网络拓扑结构进行判优，实现判优算法设计，并利用简化的样本数据进行效果测试。 2．针对电子交易行情数据的动态特征，采用动态三维链表结构实现朴素贝叶斯分类器，并对其分类准确度和效率进行测试与分析。 3．为了能够利用关联规则发现算法对电子交易行情变化进行相关性发现，针对历史行情记录进行事务、事务集的构造算法设计，并对该方法的有效性用股票行情记录进行测试。 4．采用快速傅立叶变换(FFT)方法，实现交易行情信号从时间域向频率域的转换，并在频率域对相似性进行度量，用股票行情记录对该方法的有效性进行测试。 该课题的研究主要是根据河南省技术产权交易系统功能扩展的需要而进行，因此，在方法选择与算法设计上突出了与具体应用相结合的特点。更多还原

【Abstract】 Instead of the traditional trade mode, Electronic trade is applied to the stock, the future and many other trade fields. Mass market quotation records and the real time market quotation updating that can be used to analyze the market come force with this mode. As a result, useful information can be gotten by analyzing the records.KDD(Knowledge Discovery in Database) is a new emerging area in the research of artificial intelligence and databases .This technology is used in finance, medical treatment, retail, manufacture, engineering and science. It has already been used in market analysis.The thesis discusses how to analyze the market quotation records by solving four problems in this aspect. The methods brought forward are based on the conceptions and technologies in KDD and mathematics. The algorithms and data structures are expatiated in detail.The main work of the thesis:Firstly, an efficient algorithm and data structure is brought forward to select the optimum Bayesian network model which best represent the dependent relationships of the variables samples.Secondly, to realize the real time market analysis, a NB (naive Bayesian) classification engine based on a dynamic three-dimensional link table is realized and tested.Thirdly, the algorithms to construct the records aggregations which can be processed by Apriori algorithm are designed and tested by stock market quotation records.Fourthly, the market quotation records are transformed from time field to frequency field by FFT algorithm, the comparability is measured in frequency field.To meet the need of the He Nan province technology property trading system, the characteristic of practice use is concerned in choosing and designing the algorithms.更多还原