Stability analysis of financial contagion due to overlapping portfolios

Caccioli, Fabio; Shrestha, Munik; Moore, Cristopher; Farmer, J. Doyne

doi:10.48550/arxiv.1210.5987

Cited by 9 publications

(26 citation statements)

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“…From this point of view, it appears that the widely used term "systemically important financial institution (SIFI)'' is harder to define than is usually thought. Recently, Caccioli et al [20] also argue that increasing the capital buffer of most highly connected banks may not affect systemic risk.…”

Section: Discussionmentioning

confidence: 99%

Network Versus Portfolio Structure in Financial Systems

Kobayashi

2013

SSRN Journal

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The question of how to stabilize financial systems has attracted considerable attention since the global financial crisis of 2007-2009. Recently, Beale et al. ("Individual versus systemic risk and the regulator's dilemma", Proc Natl Acad Sci USA 108: 12647-12652, 2011) demonstrated that higher portfolio diversity among banks would reduce systemic risk by decreasing the risk of simultaneous defaults at the expense of a higher likelihood of individual defaults. In practice, however, a bank default has an externality in that it undermines other banks' balance sheets. This paper explores how each of these different sources of risk, simultaneity risk and externality, contributes to systemic risk. The results show that the allocation of external assets that minimizes systemic risk varies with the topology of the financial network as long as asset returns have negative correlations. In the model, a well-known centrality measure, PageRank, reflects an appropriately defined "infectiveness" of a bank. An important result is that the most infective bank need not always be the safest bank. Under certain circumstances, the most infective node should act as a firewall to prevent large-scale collective defaults. The introduction of a counteractive portfolio structure will significantly reduce systemic risk.

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Section: Discussionmentioning

confidence: 99%

Network Versus Portfolio Structure in Financial Systems

Kobayashi

2013

SSRN Journal

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“…While network representations of complex systems have proven to be tremendously useful, it is often the case that a single (simplex) network cannot capture the complex interactions between systems or sub-systems. Examples include financial [1,2], ecological [3], infrastructure [4] and information systems [5].…”

Section: Introductionmentioning

confidence: 99%

Weak percolation on multiplex networks

et al. 2014

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Bootstrap percolation is a simple but nontrivial model. It has applications in many areas of science and has been explored on random networks for several decades. In single-layer (simplex) networks, it has been recently observed that bootstrap percolation, which is defined as an incremental process, can be seen as the opposite of pruning percolation, where nodes are removed according to a connectivity rule. Here we propose models of both bootstrap and pruning percolation for multiplex networks. We collectively refer to these two models with the concept of "weak" percolation, to distinguish them from the somewhat classical concept of ordinary ("strong") percolation. While the two models coincide in simplex networks, we show that they decouple when considering multiplexes, giving rise to a wealth of critical phenomena. Our bootstrap model constitutes the simplest example of a contagion process on a multiplex network and has potential applications in critical infrastructure recovery and information security. Moreover, we show that our pruning percolation model may provide a way to diagnose missing layers in a multiplex network. Finally, our analytical approach allows us to calculate critical behavior and characterize critical clusters.

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“…The probability that both banks will be solvent is then 1 − 2p. If asset returns are independent, then the corresponding probability is given by (1 − p) 2 . Since (1 − p) 2 − (1 − 2p) = p 2 , it follows that counteractive immunization reduces the probability that both banks will survive.…”

Section: Systemic Riskmentioning

confidence: 99%

“…Since the global financial crisis of 2007-2009, many researchers in various fields of natural and social sciences, such as physicists, ecologists and economists, have been tackling the question of how to reduce financial systemic risk. [1][2][3][4] Many of those studies are based on network theory, which has been used extensively to explore complex systems since the early 2000's.…”

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confidence: 99%

Efficient immunization strategies to prevent financial contagion

Kobayashi

Hasui

2014

Sci Rep

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Many immunization strategies have been proposed to prevent infectious viruses from spreading through a network. In this work, we study efficient immunization strategies to prevent a default contagion that might occur in a financial network. An essential difference from the previous studies on immunization strategy is that we take into account the possibility of serious side effects. Uniform immunization refers to a situation in which banks are “vaccinated” with a common low-risk asset. The riskiness of immunized banks will decrease significantly, but the level of systemic risk may increase due to the de-diversification effect. To overcome this side effect, we propose another immunization strategy, called counteractive immunization, which prevents pairs of banks from failing simultaneously. We find that counteractive immunization can efficiently reduce systemic risk without altering the riskiness of individual banks.

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Stability analysis of financial contagion due to overlapping portfolios

Cited by 9 publications

References 0 publications

Network Versus Portfolio Structure in Financial Systems

Network Versus Portfolio Structure in Financial Systems

Weak percolation on multiplex networks

Efficient immunization strategies to prevent financial contagion

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