DebtRank: Too Central to Fail? Financial Networks, the FED and Systemic Risk

TLDR

Systemic risk depends on the network of financial exposures among institutions, yet no widely accepted method exists to identify systemically important nodes. We introduce DebtRank, a novel measure of systemic impact inspired by feedback‑centrality, to identify systemically important nodes. We apply DebtRank to a unique dataset on the USD 1.2 trillion FED emergency loans program to global financial institutions during 2008‑2010. Our analysis shows that 22 institutions receiving most funds formed a strongly connected graph where each became systemically important at the crisis peak, and that even small dispersed shocks could trigger a systemic default, indicating that too‑central‑to‑fail is a serious issue.

Abstract

Systemic risk, here meant as the risk of default of a large portion of the financial system, depends on the network of financial exposures among institutions. However, there is no widely accepted methodology to determine the systemically important nodes in a network. To fill this gap, we introduce, DebtRank, a novel measure of systemic impact inspired by feedback-centrality. As an application, we analyse a new and unique dataset on the USD 1.2 trillion FED emergency loans program to global financial institutions during 2008-2010. We find that a group of 22 institutions, which received most of the funds, form a strongly connected graph where each of the nodes becomes systemically important at the peak of the crisis. Moreover, a systemic default could have been triggered even by small dispersed shocks. The results suggest that the debate on too-big-to-fail institutions should include the even more serious issue of too-central-to-fail.