The interconnected nature of financial systems: Direct and common exposures

Abstract To capture systemic risk related to network structures, this paper introduces a measure that complements direct exposures with common exposures, as well as compares these to each other. Trying to address the interconnected nature of financial systems, researchers have recently proposed a range of approaches for assessing network structures. Much of the focus is on direct exposures or market-based estimated networks, yet little attention has been given to the multivariate nature of systemic risk, indirect exposures and overlapping portfolios. In this regard, we rely on correlation network models that tap into the multivariate network structure, as a viable means to assess common exposures and complement direct linkages. Using BIS data, we compare correlation networks with direct exposure networks based upon conventional network measures, as well as we provide an approach to aggregate these two components for a more encompassing measure of interconnectedness.

[1]  S. Battiston,et al.  Liaisons Dangereuses: Increasing Connectivity, Risk Sharing, and Systemic Risk , 2009 .

[2]  R. Mantegna Hierarchical structure in financial markets , 1998, cond-mat/9802256.

[3]  Matteo Barigozzi,et al.  NETS: Network Estimation for Time Series , 2018 .

[4]  Robert F. Engle,et al.  Volatility, Correlation and Tails for Systemic Risk Measurement , 2010 .

[5]  A. Lo,et al.  A Survey of Systemic Risk Analytics , 2012 .

[6]  D. F. Ahelegbey,et al.  Bayesian Graphical Models for Structural Vector Autoregressive Processes , 2012, Journal of Applied Econometrics.

[7]  Robert F. Engle,et al.  Capital Shortfall: A New Approach to Ranking and Regulating Systemic Risks † , 2012 .

[8]  Paolo Giudici,et al.  Graphical Network Models for International Financial Flows , 2016 .

[9]  Anthony Saunders,et al.  Syndication, Interconnectedness, and Systemic Risk , 2011 .

[10]  A. Lo,et al.  Econometric Measures of Connectedness and Systemic Risk in the Finance and Insurance Sectors , 2011 .

[11]  Patrick McGuire,et al.  Tracking International Bank Flows , 2006 .

[12]  Luc Laeven,et al.  Systemic Risk, Crises, and Macroprudential Regulation , 2015 .

[13]  Stefano Battiston,et al.  Systemic risk in a unifying framework for cascading processes on networks , 2009, 0907.5325.

[14]  F. Diebold,et al.  UNIVERSITY OF SOUTHERN CALIFORNIA Center for Applied Financial Economics (CAFE) On the Network Topology of Variance Decompositions: Measuring the Connectedness of Financial Firms , 2011 .

[15]  V. Acharya A Theory of Systemic Risk and Design of Prudential Bank Regulation , 2001 .

[16]  Giuliano Armano,et al.  Perception of similarity: a model for social network dynamics , 2013 .

[17]  M. Cropper,et al.  Sulfur Dioxide Control by Electric Utilities: What Are the Gains from Trade? , 1998, Journal of Political Economy.

[18]  Rosario N. Mantegna,et al.  Book Review: An Introduction to Econophysics, Correlations, and Complexity in Finance, N. Rosario, H. Mantegna, and H. E. Stanley, Cambridge University Press, Cambridge, 2000. , 2000 .

[19]  H. Stanley,et al.  Dynamical Macroprudential Stress Testing Using Network Theory , 2014 .

[20]  Nikolaus Hautsch,et al.  Financial Network Systemic Risk Contributions , 2013 .

[21]  Elena Dumitrescu,et al.  Which are the SIFIs? A Component Expected Shortfall (CES) Approach to Systemic Risk , 2012 .