The stock market is a complex system that affects economic and financial activities around the world. Analysis of stock price data can improve our understanding of the past price movements of stocks. In this work, we develop a method to determine the highly interconnected subsystems of the stock market. Our method relies on a k-core decomposition scheme to analyze large networks. Our approach illustrates that the stock market is a nearly decomposable system which comprises hierarchic subsystems. This work also presents results from the analysis of a network derived from a large data set of stock prices. This network analysis technique is a new promising approach to analyze and classify stocks based on price interactions and to decompose the complex system embodied in the stock market.
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Paper provided by NET Institute in its series Working Papers with number
04-17.