Identifying Stocks Leaderby Complex Network Analysis

Financial markets are a complex system of individuals and institutions, tools and procedures that get savers and borrowers to gather in one place (Basely S. and Brigham E.F., 1999). Predict the trend of stocks is the most concern of investors. Different models of data mining will use to analyze stock behavior and identify future trends, and the results can affect on companies and investor’s strategic decisions. Over a century, the people are used the virtual network for implicit references to the social systems with complex interrelationships among all scales ranging from interpersonal to internationally relationships. In this paper the best common effective indicator identified by data panel model to create a correlation network using the stock data at different times from the Tehran Stock Exchange for April 2010 to April 2014. Result showed that return could be the best indicator, and as created network was scale-free so the modularity depicted the communities could conduct us to identify stocks leader

Keywords:

Stocks Complex Network , Scale-free , Modularity , Stocks Community