Investigating the Importance of Different Companies of Tehran Stock Exchange using Lower Tail Dependency based Interaction Network

Examining the importance and influence of financial market companies is one of the main issues in the field of financial management because sometimes the collapse of a stock exchange company can affect an entire financial market. One systematic way to analyze the significance and impacts of companies is to use complex networks based on Interaction Graphs (IGs). There are different methods for quantifying the edge weight in an IG. In this method, the graph vertices represent the stock exchange companies that are connected by weighted edges (corresponding to the extent to which they relate to each other). In this paper, using the GARCH model (۱,۱) and the Clayton copula, we obtained the lower tail dependence interaction network of the first ۵۲ companies of the Tehran Stock Exchange in terms of average market value, between June ۲۰۱۷ and October ۲۰۲۰. Then, based on the minimum spanning tree of the interaction network, we divided the companies into different communities. Using this classification, it was observed that the companies of the first group (Food Industry) and the second group (Oil Refinery) have the greatest impact on other companies. We also calculated the central indexes of the minimum spanning tree for each company. According to the results, the companies of the third group (Steel) have the highest average in the central indicators.

Keywords:

interaction network , Minimum Spanning Tree , GARCH model , Clayton Copula , Lower Tail Dependence