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Iván Alves

16 September 2013
OCCASIONAL PAPER SERIES - No. 3
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Abstract
Financial institutions are connected to each other by a series of bilateral transactions. In normal times, institutions’ connections may result in efficient risk transfer. But in crises, connections can facilitate contagion – as initial problems lead to chains of defaults and liquidity shortages – sparked by shocks which might arise within the financial system or from the real economy. Institutions are also interconnected in indirect ways, since they are exposed to common risk factors that can result in concurrent losses. For example, most banks extend loans secured by real estate: they are thus collectively exposed to falls in house prices. Resulting bank distress can then exacerbate initial problems: banks might simultaneously sell collateral (houses), thus worsening downward price spirals. Less tangibly, institutions can also be connected through perceptions of counterparties’ creditworthiness. Given uncertainty, financial institutions may in general become reluctant to lend to each other and hoard liquidity. Potential for contagion due to interconnectedness is a key component of systemic risk. As a first step towards understanding the mechanisms of contagion, this paper abstracts from complex indirect connections between banks, and rather focuses on direct linkages between 53 large EU banks, based on unique data on interbank exposures collected by national regulators as of the end of 2011.
JEL Code
G01 : Financial Economics→General→Financial Crises
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
13 July 2015
OCCASIONAL PAPER SERIES - No. 7
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Abstract
This paper contains an analysis of the network of the 29 largest European insurance groups and their financial counterparties. Insurance companies have direct exposures to other insurers, banks and other financial institutions through the holdings of debt, equity and other financial instruments. These exposures can cause direct contagion and thereby the spread of systemic risks. This analysis focuses on direct linkages between EU insurers and banks. Sectoral data show that at least 20% of insurers’ assets are investments in banks. As a result insurers are an important source of funding for banks. This paper adds to the expanding research on financial market networks and on systemic risks in the insurance sector.
JEL Code
L14 : Industrial Organization→Market Structure, Firm Strategy, and Market Performance→Transactional Relationships, Contracts and Reputation, Networks
G18 : Financial Economics→General Financial Markets→Government Policy and Regulation
8 August 2016
WORKING PAPER SERIES - No. 20
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Abstract
Research on interbank networks and systemic importance is starting to recognise that the web of exposures linking banks balance sheets is more complex than the single-layer-of-exposure approach. We use data on exposures between large European banks broken down by both maturity and instrument type to characterise the main features of the multiplex structure of the network of large European banks. This multiplex network presents positive correlated multiplexity and a high similarity between layers, stemming both from standard similarity analyses as well as a core-periphery analyses of the different layers. We propose measures of systemic importance that fit the case in which banks are connected through an arbitrary number of layers (be it by instrument, maturity or a combination of both). Such measures allow for a decomposition of the global systemic importance index for any bank into the contributions of each of the sub-networks, providing a useful tool for banking regulators and supervisors in identifying tailored policy instruments. We use the dataset of exposures between large European banks to illustrate that both the methodology and the specific level of network aggregation matter in the determination of interconnectedness and thus in the policy making process.
JEL Code
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
D85 : Microeconomics→Information, Knowledge, and Uncertainty→Network Formation and Analysis: Theory
C67 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→Input?Output Models
14 September 2016
WORKING PAPER SERIES - No. 1962
Details
Abstract
Research on interbank networks and systemic importance is starting to recognise that the web of exposures linking banks balance sheets is more complex than the single-layer-of-exposure approach. We use data on exposures between large European banks broken down by both maturity and instrument type to characterise the main features of the multiplex structure of the network of large European banks. This multiplex network presents positive correlated multiplexity and a high similarity between layers, stemming both from standard similarity analyses as well as a core-periphery analyses of the different layers. We propose measures of systemic importance that fit the case in which banks are connected through an arbitrary number of layers (be it by instrument, maturity or a combination of both). Such measures allow for a decomposition of the global systemic importance index for any bank into the contributions of each of the sub-networks, providing a useful tool for banking regulators and supervisors in identifying tailored policy instruments. We use the dataset of exposures between large European banks to illustrate that both the methodology and the specific level of network aggregation matter in the determination of interconnectedness and thus in the policy making process.
JEL Code
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
D85 : Microeconomics→Information, Knowledge, and Uncertainty→Network Formation and Analysis: Theory
C67 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→Input?Output Models