数据挖掘在股票分析中的应用

发布时间：2018-01-29 07:30

本文关键词： 数据挖掘股票分析 MATLAB　出处：《复旦大学》2012年硕士论文　论文类型：学位论文

【摘要】：证券行业发展至今,每天都会产生海量数据。但是过去大部分券商都只注重新开户的开发,未予以重视。现在证券行业已接近饱和,竞争激烈,券商也渐渐将重心从挖掘新客户转向维护现有客户。为客户提供更高更好的服务,从而扩大交易量,提升业绩。投资顾问服务开始快速发展,目的就是为客户提供高质量的证券投资服务。股票市场受政治、经济和投资者心理等多种复杂因素的影响。虽然复杂,但是海量数据之中,进过分析简化,仍能从中得到我们想要的规律模型。数据挖掘技术就是能够实现从海量数据中挖掘有用信息的新兴技术,欧美等金融发达地区,都将广泛应用于投资建模中。利用数据挖掘技术建立有效的投资模型,从各种交易数据中,得出有效的投资信息,将其提供给客户作为投资参考,从而提高服务质量。本文讨论的主要是通过MATLAB工具,进行数据挖掘的分析,生成关于策略选股、资产组合风险评估和股票走势的有用信息。投资者可以根据这些信息,做出自己的投资决策,提高投资收益率
[Abstract]:The development of the securities industry up to now will produce massive data every day. But in the past most securities companies only pay attention to the development of new accounts and do not pay attention to it. Now the securities industry is close to saturation and fierce competition. Brokerage companies are also gradually shifting their focus from tapping new customers to maintaining existing customers, providing customers with higher and better services, thereby expanding trading volumes and improving performance. Investment advisory services have begun to grow rapidly. The purpose is to provide customers with high-quality securities investment services. The stock market is affected by many complex factors such as politics, economy and investor psychology. We can still get the law model we want. Data mining technology is a new technology that can mine useful information from massive data, such as Europe and the United States and other financial developed regions. It will be widely used in investment modeling. Using data mining technology to establish an effective investment model, from all kinds of transaction data, the effective investment information will be provided to clients as investment reference. Thus, the service quality is improved. This paper mainly discusses the analysis of data mining through MATLAB tools to generate useful information on strategic stock selection, portfolio risk assessment and stock trend. Investors can use this information. Make your own investment decisions and increase the return on investment
【学位授予单位】：复旦大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：TP311.13;F830.91

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