Financial Networks: A Study of the Toronto Stock Exchange

Abstract

In this study, filtered network approaches such as Minimum Spanning Tree and Planar Maximally Filtered Graphs, are used to analyse the topological structure of constituents of S&P Toronto Stock Exchange Composite Index for a period of three years from January 1, 2015 till Decemeber 31, 2017. For this purpose, rolling correlation for each pair of stocks was calculated for six different time windows of 1, 2, 3, 4, 6 and 12 months. Based on the topological structure, the stocks were categorized into core and peripheral stocks using network measures such as degree centrality, betweenness centrality, eccentricity and eigenvector centrality. Categorization of stocks into core and peripheral was consistent for both MST and PMFG based networks for all time windows. Financial stocks were found to be core stocks. Topological structure helps to understand the inter-relationship among the stocks. It would aid in interpreting the nature of economic factors affecting similar group of stocks. Identification and categorisation of core and peripheral stocks could be used as a base for construction of portfolios and risk management.