Stock Selection Based on Data Clustering Method

Author

Wang, Ruizhong

Author_Institution

Inf. Eng. Sch., Tianjin Univ. of Commerce, Tianjin, China

fYear

2011

fDate

3-4 Dec. 2011

Firstpage

1542

Lastpage

1545

Abstract

Stock selection is stock market participants facing a difficult problem. This article aims to apply clustering in data mining techniques to analyze the financial data and stock trading data, give the classification of stocks, provide the decision support of stock selections for the dealer. The main work include: the construction of the financial data and stock market data, the pre-processing of the data in the data set, the analysis of the data set applying the clustering techniques, giving the stock´s classification, verifying the classification results. The stock selection base on cluster analysis improves the success rate and yield, and have important practical value of guidance of investment decisions.

Keywords

data analysis; data mining; decision support systems; financial data processing; investment; pattern classification; pattern clustering; stock markets; data clustering method; data mining techniques; data preprocessing; data set analysis; financial data; investment decisions; stock classification; stock market participants; stock selection decision support; stock trading data; Companies; Data mining; Investments; Security; Stock markets; Cluster analysis; Data mining; Stock selection;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Security (CIS), 2011 Seventh International Conference on

Conference_Location

Hainan

Print_ISBN

978-1-4577-2008-6

Type

conf

DOI

10.1109/CIS.2011.345

Filename

6128386