Centrality measures of financial system interconnectedness: A multiple crises study

We explore how asset returns could be a good proxy to detect interlinkages in the financial system. This paper employs a US dataset for the 2002-2021 period. Pairwise returns correlation indicate the interconnectedness at the preliminary stage. The Principal Component Analysis captures a significant portion of variance and detects the co-movement and highly connected state of the financial market during crises. Granger centrality tested with pairwise directional variance decomposition indicates the importance of banks and insurance companies in the US financial system. This paper recommends policymakers use multiple network models to validate and calibrate the SIFIs list.

Automated summary

This paper examines the use of asset returns as a proxy for detecting interlinkages in the financial system. The study utilizes a US dataset covering the period from 2002 to 2021, and finds that pairwise returns correlation can indicate interconnectedness in the preliminary stage. The Principal Component Analysis identifies a significant portion of variance and detects the co-movement and highly connected state of the financial market during crises. Granger centrality, tested with pairwise directional variance decomposition, highlights the importance of banks and insurance companies in the US financial system. The paper suggests that policymakers should employ multiple network models to validate and calibrate the list of Systemically Important Financial Institutions (SIFIs).