Networks of Common Asset Holdings: Aggregation and Measures of Vulnerability

Braverman, Anton; Minca, Andreea

doi:10.2139/ssrn.2379669

Cited by 38 publications

(37 citation statements)

References 34 publications

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“…We call this network the indirect contagion network. Similar network structures were explored by Braverman and Minca (2016); Guo et al (2015) for mutual funds. Figure 6 displays the indirect contagion network for European banks as implied by EBA data collected in 2011.…”

Section: Portfolio Overlapsmentioning

confidence: 98%

Fire Sales, Indirect Contagion and Systemic Stress-Testing

Cont

Schaanning²

2014

SSRN Journal

117

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Section: Portfolio Overlapsmentioning

confidence: 98%

Fire Sales, Indirect Contagion and Systemic Stress-Testing

Cont

Schaanning²

2014

SSRN Journal

117

View full text Add to dashboard Cite

“…In addition to Billio et al (2012) and Brunetti et al (2016), Leitner (2005) and Babus (2009) model bank networks to explore contagion issues. Braverman and Minca (2014) describe how common holdings can transmit financial distress in bank networks with the severity of contagion depending on both the level and liquidity of common holdings. Braverman and Minca (2014) describe how common holdings can transmit financial distress in bank networks with the severity of contagion depending on both the level and liquidity of common holdings.…”

Section: Introductionmentioning

confidence: 99%

“…Similarly, Allen and Gale (2000) and Upper (2006) highlight how common asset holdings can drive interconnectedness within bank networks. Braverman and Minca (2014) describe how common holdings can transmit financial distress in bank networks with the severity of contagion depending on both the level and liquidity of common holdings. Similarly, Lagunoff and Schreft (2001) develop a model that shows that a high level of interconnectedness may increase financial fragility.…”

Section: Introductionmentioning

confidence: 99%

Trading networks

Adamic

Brunetti

Harris

et al. 2017

The Econometrics Journal

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In this paper, we analyse the time series of 12,000+ networks of traders in the E-mini S&P 500 stock index futures contract and we empirically link network variables with financial variables more commonly used to describe market conditions. We show that network variables lead trading volume, intertrade duration, effective spreads, trade imbalances and other market liquidity measures. Network variables reflect information, information asymmetry and market liquidity and significantly presage future market conditions prior to volume or liquidity measures. We also find two-way Granger-causality between network variables and both returns and volatility, highlighting strong feedback between market conditions and trading behaviour.

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“…[15] has been carried out for the case of Erdős-Renyi networks and banks with the same size, but in fact empirical studies [25,11,33,34] show that real financial networks of common portfolio holdings and balance sheet size distributions are more heterogeneous. Specifically, they provide evidence of power laws in these distributions.…”

Section: Introductionmentioning

confidence: 99%

The Effect of Heterogeneity on Financial Contagion Due to Overlapping Portfolios

Banwo

Caccioli

Harrald

et al. 2016

Advs. Complex Syst.

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We consider a model of financial contagion in a bipartite network of assets and banks recently introduced in the literature, and we study the effect of power law distributions of degree and balance-sheet size on the stability of the system. Relative to the benchmark case of banks with homogeneous degrees and balance-sheet sizes, we find that if banks have a power-law degree distribution the system becomes less robust with respect to the initial failure of a random bank, and that targeted shocks to the most specialised banks (i.e. banks with low degrees) or biggest banks increases the probability of observing a cascade of defaults. In contrast, we find that a power-law degree distribution for assets increases stability with respect to random shocks, but not with respect to targeted shocks. We also study how allocations of capital buffers between banks affects the system's stability, and we find that assigning capital to banks in relation to their level of diversification reduces the probability of observing cascades of defaults relative to size based allocations. Finally, we propose a non-capital based policy that improves the resilience of the system by introducing disassortative mixing between banks and assets.

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Networks of Common Asset Holdings: Aggregation and Measures of Vulnerability

Cited by 38 publications

References 34 publications

Fire Sales, Indirect Contagion and Systemic Stress-Testing

Fire Sales, Indirect Contagion and Systemic Stress-Testing

Trading networks

The Effect of Heterogeneity on Financial Contagion Due to Overlapping Portfolios

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