Why do vulnerability cycles matter in financial networks?
Thiago Silva (),
Benjamin Tabak () and
Physica A: Statistical Mechanics and its Applications, 2017, vol. 471, issue C, 592-606
We compare two widely employed models that estimate systemic risk: DebtRank and Differential DebtRank. We show that not only network cyclicality but also the average vulnerability of banks are essential concepts that contribute to widening the gap in the systemic risk estimates of both approaches. We find that systemic risk estimates are the same whenever the network has no cycles. However, in case the network presents cyclicality, then we need to inspect the average vulnerability of banks to estimate the underestimation gap. We find that the gap is small regardless of the cyclicality of the network when its average vulnerability is large. In contrast, the observed gap follows a quadratic behavior when the average vulnerability is small or intermediate. We show results using an econometric exercise and draw guidelines both on artificial and real-world financial networks.
Keywords: Networks; Systemic risk; DebtRank; Contagion; Financial markets (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
Working Paper: Why Do Vulnerability Cycles Matter in Financial Networks? (2016)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:471:y:2017:i:c:p:592-606
Access Statistics for this article
Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis
More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Haili He ().