Modeling Interdependent Networks as Random Graphs: Connectivity and Systemic Risk

Understanding Complex Systems - Networks of Networks: The Last Frontier of Complexity ◽

10.1007/978-3-319-03518-5_4 ◽

2014 ◽

pp. 73-94 ◽

Cited By ~ 6

Author(s):

R. M. D’Souza ◽

C. D. Brummitt ◽

E. A. Leicht

Keyword(s):

Random Graphs ◽

Systemic Risk ◽

Interdependent Networks

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Bootstrap Percolation in Directed Inhomogeneous Random Graphs

The Electronic Journal of Combinatorics ◽

10.37236/7832 ◽

2019 ◽

Vol 26 (3) ◽

Author(s):

Thilo Meyer-Brandis ◽

Nils Detering ◽

Konstantinos Panagiotou

Keyword(s):

Random Graphs ◽

Systemic Risk ◽

Degree Distribution ◽

Bootstrap Percolation ◽

Mild Assumption ◽

Inhomogeneous Random Graphs ◽

To Receive ◽

Novel Model ◽

Individual Threshold

Bootstrap percolation is a process that is used to describe the spread of an infection on a given graph. In the model considered here each vertex is equipped with an individual threshold. As soon as the number of infected neighbors exceeds that threshold, the vertex gets infected as well and remains so forever. We perform a thorough analysis of bootstrap percolation on a novel model of directed and inhomogeneous random graphs, where the distribution of the edges is specied by assigning two distinct weights to each vertex, describing the tendency of it to receive edges from or to send edges to other vertices. Under the mild assumption that the limiting degree distribution of the graph is integrable we determine the typical fraction of infected vertices. Our model allows us to study a variety of settings, in particular the prominent case in which the degree distribution has an unbounded variance. As a second main contribution, we quantify the notion of "systemic risk", that is, we characterize to what extent tiny initial infections can propagate to large parts of the graph through a cascade, and discover novel features that make graphs prone/resilient to initially small infections.

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Random Graphs

10.1017/cbo9780511721342 ◽

1998 ◽

Cited By ~ 37

Author(s):

V. F. Kolchin

Keyword(s):

Random Graphs

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Macroprudential Policy Instruments of Central Banks

Voprosy Ekonomiki ◽

10.32609/0042-8736-2012-8-32-47 ◽

2012 ◽

pp. 32-47

Author(s):

S. Andryushin ◽

V. Kuznetsova

Keyword(s):

Systemic Risk ◽

Financial Stability ◽

Financial System ◽

Policy Instruments ◽

Central Banks ◽

Macroprudential Policy ◽

Policy Studies ◽

The Future ◽

Financial Cycles

The paper analyzes central banks macroprudencial policy and its instruments. The issues of their classification, option, design and adjustment are connected with financial stability of overall financial system and its specific institutions. The macroprudencial instruments effectiveness is evaluated from the two points: how they mitigate temporal and intersectoral systemic risk development (market, credit, and operational). The future macroprudentional policy studies directions are noted to identify the instruments, which can be used to limit the financial systemdevelopment procyclicality, mitigate the credit and financial cycles volatility.

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Risk Factors of Collateralized Loan Obligations and Corporate Bonds

Zeitschrift für Bankrecht und Bankwirtschaft ◽

10.15375/zbb-2020-0604 ◽

2020 ◽

Vol 32 (6) ◽

pp. 347-355

Author(s):

Mark Wahrenburg ◽

Andreas Barth ◽

Mohammad Izadi ◽

Anas Rahhal

Keyword(s):

Risk Factors ◽

Risk Factor ◽

Asset Pricing ◽

Systemic Risk ◽

Corporate Bonds ◽

Risk Exposure ◽

Expected Returns ◽

Yield Spreads ◽

Pricing Factors ◽

Return Difference

AbstractStructured products like collateralized loan obligations (CLOs) tend to offer significantly higher yield spreads than corporate bonds (CBs) with the same rating. At the same time, empirical evidence does not indicate that this higher yield is reduced by higher default losses of CLOs. The evidence thus suggests that CLOs offer higher expected returns compared to CB with similar credit risk. This study aims to analyze whether this return difference is captured by asset pricing factors. We show that market risk is the predominant risk factor for both CBs and CLOs. CLO investors, however, additionally demand a premium for their risk exposure towards systemic risk. This premium is inversely related to the rating class of the CLO.

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