The stochastic block models is a popular statistical model for community detection in networks. This study employs a statistical model based approach to investigate the Community’s structure of Iraqi Stock Exchange and possible paths of systemic risk transmission. A threshold based network is constructed to demonstrate links between enterprises and a correlation matrix from normalized market data of 88 companies. Community detection was achieved by convexified modularity maximization approach based on degree corrected stochastic block model. The analysis identifying five communities that displayed a core periphery structure, composed of 72 peripheral nodes and 16 connection nodes. The results show that connector nodes have very strong links across different communities and are likely to be the channels for the spread of financial instabilities besides three enterprises with high participation coefficients, indicating their important bridging role in the network. Such findings may give useful insight into the ISX’s framework.