Identifying the Topology of the Iranian Stock Market Network and Ranking its Groups

The stock market is a complex financial system with heterogeneous members which produces huge amounts of data. It is clear that analyzing this huge data and inferring practical results creates a significant competitive advantage for its participants. One method of analyzing financial market data expanded significantly after the global financial crisis is complex network-based analysis that considers the structure of interdependencies of a system's members. Therefore, the current study analyzes the Iranian stock market using the graph theory in mathematics. First, the correlation network of stock market groups is constructed in three time scales of daily, seasonal and annual, and then their topology will be compared. In the next stage, using the centrality indexes in the graph theory, the importance of each market group is calculated and the groups are ranked in the network. The results of this study have significant implications for market participants and regulators for making investment decisions, regulating and controlling risk.