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Abstract and Applied Analysis
Volume 2014, Article ID 723482, 9 pages
http://dx.doi.org/10.1155/2014/723482
Research Article

Dynamic Communities in Stock Market

1School of Mathematics and Statistics, Lanzhou University, Lanzhou 730000, China
2College of Computer and Communication, Lanzhou University of Technology, Lanzhou 730050, China

Received 19 March 2014; Accepted 16 April 2014; Published 8 May 2014

Academic Editor: Suohai Fan

Copyright © 2014 Xiangquan Gui et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The stock market has the huge effect and influence on a country or region’s economic and financial activities. But we have found that it is very hard for the prediction and control. This illustrates a critical need for new and fundamental understanding of the structure and dynamics of stock markets. Previous research and analysis on stock markets often focused on some assumptions of the game of competition and cooperation. Under the condition of these assumptions, the conclusions often reflect just part of the problem. The stock price is the core reflections of a stock market. So, in this paper, the authors introduce a methodology for constructing stock networks based on stock prices in a stock market and detecting dynamic communities in it. This strategy will help us from a new macroperspective to explore and mine the characteristics and laws hiding in the big data of stock markets. Through statistical analysis of many characteristics of dynamic communities, some interesting phenomena are found in this paper. These results are new findings in finance data analysis field and will potentially contribute to the analysis and decision-making of a financial market. The method presented in this paper can also be used to analyze other similar financial systems.