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The 2008/9 financial crisis highlighted the importance of evaluating vulnerabilities owing to interconnectedness, or Too-Connected-to-Fail risk, among financial institutions for country monitoring, financial surveillance, investment analysis and risk management purposes. This paper illustrates the use of balance sheet-based network analysis to evaluate interconnectedness risk, under extreme adverse scenarios, in banking systems in mature and emerging market countries, and between individual banks in Chile, an advanced emerging market economy.
This paper applies network analysis to assess the extent of systemic vulnerabilities in the ECCU banking system. It includes two sets of illustrative stress tests. First, solvency and liquidity shocks to each individual bank and the impact on other banks in the network through their biltareal net asset exposures. Second, country and region-wide tail shocks to GDP affecting capital and liquidity of all banks in the shocked jurisdictions, followed by the rippling effects through the regional network. The results identify systemic institutions that merit hightened attention by the regulator, as determined by the degree of connectivity with the rest of the system, and the extent to which they are vulnerable to the failure of other banks.
In this paper we explore the properties of the global banking network using cross-border bank lending data for 184 countries over 1978-2009. Specifically, we analyze financial interconnectedness using network metrics of centrality, connectivity, and clustering. We document a relatively unstable global banking network, with structural breaks in network indicators identifying several waves of capital flows. Interconnectedness rankings, especially for borrowers, are relatively volatile over the period. Connectivity tends to fall during and after systemic banking crises and sovereign debt crises. The 2008-09 global financial crisis stands out as an unusually large perturbation to the cross-border banking network.
Effective cross-border financial surveillance requires the monitoring of direct and indirect systemic linkages. This paper illustrates how network analysis could make a significant contribution in this regard by simulating different credit and funding shocks to the banking systems of a number of selected countries. After that, we show that the inclusion of risk transfers could modify the risk profile of entire financial systems, and thus an enriched simulation algorithm able to account for risk transfers is proposed. Finally, we discuss how some of the limitations of our simulations are a reflection of existing information and data gaps, and thus view these shortcomings as a call to improve the collection and analysis of data on cross-border financial exposures.
The recent global financial crisis has forced a re-examination of risk transmission in the financial sector and how it affects financial stability. Current macroprudential policy and surveillance (MPS) efforts are aimed establishing a regulatory framework that helps mitigate the risk from systemic linkages with a view towards enhancing the resilience of the financial sector. This paper presents a forward-looking framework ("Systemic CCA") to measure systemic solvency risk based on market-implied expected losses of financial institutions with practical applications for the financial sector risk management and the system-wide capital assessment in top-down stress testing. The suggested approach uses advanced contingent claims analysis (CCA) to generate aggregate estimates of the joint default risk of multiple institutions as a conditional tail expectation using multivariate extreme value theory (EVT). In addition, the framework also helps quantify the individual contributions to systemic risk and contingent liabilities of the financial sector during times of stress.
The IMF has had extensive involvement in the stress testing of financial systems in its member countries. This book presents the methods and models that have been developed by IMF staff over the years and that can be applied to the gamut of financial systems. An added resource for readers is the companion CD-Rom, which makes available the toolkit with some of the models presented in the book (also located at elibrary.imf.org/page/stress-test-toolkit).
Shortly after the financial crisis of 2007-2008 many authors began to write about certain “huge institutions” potentially able to damage the entire financial system through negative shocks, approaching the issue of systemic risk in banking through the evaluation of the so called “Too-Big-to-Fail” actors. While the size of a bank is certainly a factor of risk when considering systemic implications, this book also explores the properties of some deeply interconnected institutions. The author’s main intuition is based on the renowned work by Mark Granovetter on “The Strength of Weak Ties” and “Economic Action and Social Structure: The Problem of Embeddedness”: dangerous flows, like financial shocks, may travel very quickly through networks in unexpectedly efficient ways thanks to “Weak Ties”. The existence of weaker yet longer ties implies a naturally “robust yet fragile” network where even distant actors are closely interconnected, sharing both opportunities and risks. As a consequence, some nodes may act as key actors under the structural perspective. It is therefore critical for the central authority to identify and closely monitor said institutions. Thanks to a journey through the history of Social Network Analysis this book offers a complete overview on the evolution of the methodology and the most recent applications to systemic risk assessment, which are completed by a critical approach towards the “Too-Interconnected-to-Fail” perspective.
Using network models to investigate the interconnectivity in modern economic systems allows researchers to better understand and explain some economic phenomena. This volume presents contributions by known experts and active researchers in economic and financial network modeling. Readers are provided with an understanding of the latest advances in network analysis as applied to economics, finance, corporate governance, and investments. Moreover, recent advances in market network analysis that focus on influential techniques for market graph analysis are also examined. Young researchers will find this volume particularly useful in facilitating their introduction to this new and fascinating field. Professionals in economics, financial management, various technologies, and network analysis, will find the network models presented in this book beneficial in analyzing the interconnectivity in modern economic systems.
The analysis of interconnectedness and contagion is an important part of the financial stability and risk assessment of a country’s financial system. This paper offers detailed and practical guidance on how to conduct a comprehensive analysis of interconnectedness and contagion for a country’s financial system under various circumstances. We survey current approaches at the IMF for analyzing interconnectedness within the interbank, cross-sector and cross-border dimensions through an overview and examples of the data and methodologies used in the Financial Sector Assessment Program. Finally, this paper offers practical advice on how to interpret results and discusses potential financial stability policy recommendations that can be drawn from this type of in-depth analysis.