سلمان عباسیان نقنه

Nowadays, financial markets in Iran have attracted the attention of many managers, investors and financial policymakers. Therefore, in order to make the optimal decision and reduce the risks in such a market, it is important to identify and analyze the network behavior of the financial markets at different times to obtain the optimal decision. The current study aims to answer the following research question; how is it possible to use the minimum spanning tree and hierarchical clustering in the network analysis of the Tehran Stock Exchange? The period examined was 2013 to 2018. The population consisted of all the companies accepted in Tehran Stock Exchange. The sampling was selected purposefully and contained the companies which had at least one trading day in the time span from the beginning of 2013 to the end of 2018. The stock of the investigated companies was considered as the vertexes of one graph and the coherent information criterion was considered as the weight of the edge. First, the minimum spanning tree of the graph was calculated. The results revealed that the stocks of DarooAbuReihan, DarooPakhsh and Alborzdaroo had a high influence on directing the prices of the other stocks. Furthermore, the results of hierarchical clustering classified the stocks of the companies into 8 clusters. This study presents a viewpoint about the modern method designed for the analysis of complex financial networks. Moreover, the study offers an analysis of Iran's stock market structure which can be the center of finance researchers and analysts' attention.

The purpose of this paper is investigating the effect of JCPOA on the network behavior analysis of Tehran Stock Exchange indexes using the minimum spanning tree (MST) and hierarchical clustering. By simplifying a complex system, network analysis allows for the extraction of important and essential information from that system. In this paper, using network analysis the simultaneous behavior of 38 industry indexes in Tehran Stock Exchange in manufacturing, service and invest-ment sectors during 2012-2017 was investigated. These analysis included identi-fying the main indexes in the direction of moving other indexes using the MST, providing a classification using hierarchical clustering for the behavioral similarity of the indexes as well as examining the degree of integration (behavioral similarity) of market indexes over time. The results showed that investment, automobile, industry and medicine indexes in the research period had a major role in guiding other indexes and indexes can be classified into six groups in terms of behavioral similarity. The market has also been moving toward integration of indexes since early 2015 and beginning the executive steps of Joint Comprehensive Plan of Action (JCPOA). This reflects the investors' hope for the promotion of all indexes.