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97
Network structure and systemic risk in banking systems
, 2012
"... We present a quantitative methodology for analyzing the potential for contagion and systemic risk in a network of interlinked financial institutions, using a metric for the systemic importance of institutions: the Contagion Index. We apply this methodology to a data set of mutual exposures and capi ..."
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Cited by 44 (3 self)
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We present a quantitative methodology for analyzing the potential for contagion and systemic risk in a network of interlinked financial institutions, using a metric for the systemic importance of institutions: the Contagion Index. We apply this methodology to a data set of mutual exposures and capital levels of financial institutions in Brazil in 2007 and 2008, and analyze the role of balance sheet size and network structure in each institution’s contribution to systemic risk. Our results emphasize the contribution of heterogeneity in network structure and concentration of counterparty exposures to a given institution in explaining its systemic importance. These observations plead for capital requirements which depend on exposures, rather than aggregate balance sheet size, and which
The Social System
"... into cally to a process of national selection. This article describes the process used, presents feedback from the assessors and candidates involved, and discusses possible improvements for future rounds. ..."
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Cited by 41 (0 self)
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into cally to a process of national selection. This article describes the process used, presents feedback from the assessors and candidates involved, and discusses possible improvements for future rounds.
Diffusion and cascading behavior in random networks
, 2009
"... We consider a model of diffusion on graphs generalizing both the contact process and the bootstrap percolation. The initial seed of active nodes is chosen at random and remain active forever. Then each node (not in the seed) is activated if the number of active nodes in a random subset of its neighb ..."
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Cited by 28 (12 self)
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We consider a model of diffusion on graphs generalizing both the contact process and the bootstrap percolation. The initial seed of active nodes is chosen at random and remain active forever. Then each node (not in the seed) is activated if the number of active nodes in a random subset of its neighborhood exceeds a random threshold. We study the final set of active nodes for a random graph on n vertices with a given degree sequence. We let n tends to infinity. Under some regularity conditions on the degree sequence, we show that the number of final active nodes satisfy a law of large numbers. We also consider the case of a seed with a single active node and give conditions under which it can trigger a large cascade, i.e. the final set of active nodes contains a positive fraction of the size of the graph. Our results allow to study games with local interactions on a complex network. In particular, we compute the contagion threshold for random networks. Our method is based on the properties of empirical distributions of independent random variables and leads to simple proofs unifying and extending results in the random graphs literature and social science literature. 1
Stability Analysis of Financial Contagion Due to Overlapping Portfolios. Working Paper 201210018, Santa Fe Institute
, 2012
"... SFI Working Papers contain accounts of scientific work of the author(s) and do not necessarily represent the views of the Santa Fe Institute. We accept papers intended for publication in peerreviewed journals or proceedings volumes, but not papers that have already appeared in print. Except for pap ..."
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Cited by 15 (3 self)
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SFI Working Papers contain accounts of scientific work of the author(s) and do not necessarily represent the views of the Santa Fe Institute. We accept papers intended for publication in peerreviewed journals or proceedings volumes, but not papers that have already appeared in print. Except for papers by our external faculty, papers must be based on work done at SFI, inspired by an invited visit to or collaboration at SFI, or funded by an SFI grant. ©NOTICE: This working paper is included by permission of the contributing author(s) as a means to ensure timely distribution of the scholarly and technical work on a noncommercial basis. Copyright and all rights therein are maintained by the author(s). It is understood that all persons copying this information will adhere to the terms and constraints invoked by each author's copyright. These works may be reposted only with the explicit permission of the copyright holder. www.santafe.edu SANTA FE INSTITUTEStability analysis of financial contagion due to overlapping portfolios
RM. Size and complexity in model financial systems
 Proc Natl Acad Sci USA 2012; 109
"... Working papers describe research in progress by the author(s) and are published to elicit comments and to further debate. Any views expressed are solely those of the author(s) and so cannot be taken to represent those of the Bank of England or to state Bank of England policy. This paper should there ..."
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Cited by 12 (0 self)
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Working papers describe research in progress by the author(s) and are published to elicit comments and to further debate. Any views expressed are solely those of the author(s) and so cannot be taken to represent those of the Bank of England or to state Bank of England policy. This paper should therefore not be reported as representing the views of the Bank of England or members
Heterogeneity, correlations and financial contagion
, 2011
"... We consider a model of contagion in financial networks recently introduced in [1], and we characterize the effect of a few features empirically observed in real networks on the stability of the system. Notably, we consider the effect of heterogeneous degree distributions, heterogeneous balance sheet ..."
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Cited by 10 (5 self)
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We consider a model of contagion in financial networks recently introduced in [1], and we characterize the effect of a few features empirically observed in real networks on the stability of the system. Notably, we consider the effect of heterogeneous degree distributions, heterogeneous balance sheet size and degree correlations between banks. We study the probability of contagion conditional on the failure of a random bank, the most connected bank and the biggest bank, and we consider the effect of targeted policies aimed at increasing the capital requirements of a few banks with high connectivity or big balance sheets. Networks with heterogeneous degree distributions are shown to be more resilient to contagion triggered by the failure of a random bank, but more fragile with respect to contagion triggered by the failure of highly connected nodes. A power law distribution of balance sheet size is shown to induce an inefficient diversification that makes the system more prone to contagion events. A targeted policy aimed at reinforcing the stability of the biggest banks is shown to improve the stability of the system in the regime of high average degree. Finally, disassortative mixing, such as that observed in real banking networks, is shown to enhance the stability of the system. 1
‘Too Interconnected To Fail’ Financial Network of US CDS Market: Topological Fragility and Systemic Risk
, 2012
"... A small segment of credit default swaps (CDS) on residential mortgage backed securities (RMBS) stand implicated in the 2007 financial crisis. The dominance of a few big players in the chains of insurance and reinsurance for CDS credit risk mitigation for banks ’ assets has led to the idea of too int ..."
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Cited by 8 (2 self)
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A small segment of credit default swaps (CDS) on residential mortgage backed securities (RMBS) stand implicated in the 2007 financial crisis. The dominance of a few big players in the chains of insurance and reinsurance for CDS credit risk mitigation for banks ’ assets has led to the idea of too interconnected to fail (TITF) resulting, as in the case of AIG, of a tax payer bailout. We provide an empirical reconstruction of the US CDS network based on the FDIC Call Reports for off balance sheet bank data for the 4th quarter in 2007 and 2008. The propagation of financial contagion in networks with dense clustering which reflects high concentration or localization of exposures between few participants will be identified as one that is TITF. Those that dominate in terms of network centrality and connectivity are called ‘superspreaders’. Management of systemic risk from bank failure in uncorrelated random networks is different to those with clustering. As systemic risk of highly connected financial firms in the CDS (or any other)
Derivatives and Credit Contagion in Interconnected Networks
, 1202
"... The importance of adequately modeling credit risk has once again been highlighted in the recent financial crisis. Defaults tend to cluster around times of economic stress due to poor macroeconomic conditions, but also by directly triggering each other through contagion. Although credit default swap ..."
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Cited by 7 (0 self)
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The importance of adequately modeling credit risk has once again been highlighted in the recent financial crisis. Defaults tend to cluster around times of economic stress due to poor macroeconomic conditions, but also by directly triggering each other through contagion. Although credit default swaps have radically altered the dynamics of contagion for more than a decade, models quantifying their impact on systemic risk are still missing. Here, we examine contagion through credit default swaps in a stylized economic network of corporates and financial institutions. We analyse such a system using a stochastic setting, which allows us to exploit limit theorems to exactly solve the contagion dynamics for the entire system. Our analysis shows that, by creating additional contagion channels, CDS can actually lead to greater instability of the entire network in times of economic stress. This is particularly pronounced when CDS are used by banks to expand their loan books (arguing that CDS would offload the additional risks from their balance sheets). Thus, even with complete hedging through CDS, a significant loan book expansion can lead to considerably enhanced probabilities for the occurrence of very large losses and very high default rates in the system. Our approach adds a new dimension to research on credit contagion, and could feed into a rational underpinning of an improved regulatory framework for credit derivatives. 1
Robust distributed routing in dynamical networks – part II: Strong resilience, equilibrium selection and cascaded failures
 IEEE Trans. on Automatic Control
, 2013
"... Abstract — We consider a dynamical formulation of network flows, whereby the network is modeled as a switched system of ordinary differential equations derived from mass conservation laws on directed graphs with a single origindestination pair and a constant inflow at the origin. The rate of change ..."
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Cited by 7 (2 self)
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Abstract — We consider a dynamical formulation of network flows, whereby the network is modeled as a switched system of ordinary differential equations derived from mass conservation laws on directed graphs with a single origindestination pair and a constant inflow at the origin. The rate of change of the density on each link of the network equals the difference between the inflow and the outflow on that link. The inflow to a link is determined by the total flow arriving to the tail node of that link and the routing policy at that tail node. The outflow from a link is modeled to depend on the current density on that link through a flow function. Every link is assumed to have finite capacity for density and the flow function is modeled to be strictly increasing up to the maximum density. A link becomes inactive when the density on it reaches the capacity. A node fails if all its outgoing links become inactive, and such node failures can propagate through the network due to rerouting of flow. We prove some properties of these dynamical networks and study the resilience of such networks under distributed routing policies with respect to perturbations that reduce linkwise flow functions. In particular, we propose an algorithm to compute upper bounds on the maximum resilience over all distributed routing policies, and discuss examples that highlight the role of cascading failures on the resilience of the network. I.