Systemic Centrality and Systemic Communities in Financial Networks
Quantitative Finance and Economics 2 (2), pp. 468-496 (2018).
29 Pages Posted: 21 Jul 2019
Date Written: June 13, 2018
A systemically important firm could be too-connected-to-fail and/or too-important-to-fail, two properties which centrality measures and community detection methods can capture respectively. This paper examines the performance of these measures in a variance decomposition global financial network. Too-connected-to-fail risk and vulnerability rankings are quite robust to the choice of centrality measure. The PageRank centrality measure, however, does not seem as suitable for assessing vulnerabilities. Two community identification methods, edge betweenness and the map equation (Infomap) were used to identify systemic communities, which in turn capture the too-important-to-fail dimension of systemic risk. The first method appears more robust to different weighting schemes but tends to isolate too many firms. The second method exhibits the opposite characteristics. Overall, the analysis suggests that centrality measures and community identification methods complement each other for assessing systemic risk in financial networks.
Keywords: centrality, community detection, edge-betweenness, financial network, map equation, power law, systemic risk
JEL Classification: G1, D85, G31
Suggested Citation: Suggested Citation