数据挖掘技术在证券市场分析中的应用研究

发布时间：2018-04-28 17:10

本文选题：数据挖掘 + 关联规则挖掘　；参考：《浙江大学》2012年硕士论文

【摘要】：本论文的研究方向为计算机的应用,旨在将自动化技术和系统理论等知识应用到与实际生活相关的各种复杂系统中,如金融系统,从而提高相关工作的效率和质量,并创造价值。证券市场是金融系统的主要领域,行业研究员在证券市场的发展中又起到了关键性的作用,所以行业研究员工作的质量和效率时刻影响着整个金融系统的发展。但目前行业研究员研究工作的开展存在着一些障碍,如基础数据库结构混乱,更新维护困难；数据处理和分析效率低下,变动弹性较小；数据挖掘知识的缺乏,难以深入分析数据等。本文深入的分析和研究了上述问题,并基于VBA语言、网页数据获取技术和数据挖掘技术,提出了解决这些问题的基本思路和实现方法,有效的提高了行业研究员的工作效率和质量,大幅降低了研究成本,有助于提高整个资本市场和金融系统的有效性,具有很高的商用价值。本文首先介绍了文中会涉及到一些主要的技术方法,接着介绍了基础数据库构建和自动更新的方法,并根据数据来源的不同,分别就基于WEB数据获取、基于Wind平台以及基于彭博、TEJ等平台的数据库构建和自动更新的方法做了介绍,其中重点介绍了基于WEB数据获取技术的数据库构建和自动更新的实现方法。然后本文介绍了如何对数据库中的数据进行自动化的分析和处理,如自动化图表法,基本数学方法和财务公式分析法。接着又介绍了如何将处理好的数据自动生成相应的文本报告以提高效率。最后,重点介绍了关联规则挖掘技术在行业研究中的应用,并用实验结果证明了本文实现的关联规则挖掘算法的实用性。
[Abstract]:The research direction of this thesis is the application of computer , aiming to apply the knowledge of automation technology and system theory to all kinds of complex system related to real life , such as financial system , so as to improve the efficiency and quality of related work and to create value .

The securities market is the main field of the financial system , and the industry researcher plays a key role in the development of the securities market , so the quality and efficiency of the research work of the industry researchers affect the development of the whole financial system . However , there are some obstacles in the research work of the industry researchers , such as confusion of the base database structure and difficult updating and maintenance ;
the data processing and analysis efficiency is low and the variation elasticity is small ;
The lack of data mining knowledge , it is difficult to deeply analyze the data , etc . This paper deeply analyzes and studies the above - mentioned problems . Based on VBA language , web page data acquisition technology and data mining technology , this paper puts forward the basic idea and implementation method to solve these problems , effectively improves the working efficiency and quality of the industry researcher , greatly reduces the research cost , and helps to improve the efficiency of the whole capital market and financial system , and has high commercial value .

This paper introduces some main technical methods , then introduces the basic database construction and automatic updating method , and introduces the database construction and automatic updating method based on WEB data acquisition , wind platform and platform based on Bloomberg , TEJ , etc . It also introduces how to automatically generate the corresponding text report based on WEB data acquisition technology , and then introduces how to apply the processed data automatically to the industry research . Finally , the paper introduces the application of the association rule mining technology in industry research and proves the practicability of the association rule mining algorithm implemented in this paper .

【学位授予单位】：浙江大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：TP311.13;F830.91

【引证文献】