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Giovanni Covi

30 April 2018
MACROPRUDENTIAL BULLETIN - ARTICLE - No. 5
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Abstract
This article presents stylised facts from the euro area network of large exposures and derives model-based interconnectedness measures of SSM significant institutions. The article has three main findings. First, the interbank network is relatively sparse and suggests a core-periphery network structure. Second, the more complex network measures on average correlate highly with the more simple size-based interconnectedness indicators, constructed following the EBA guidelines on the calibration of O-SII buffers. Third, there is nevertheless value for policymakers to take into account network-based measures in addition to the size-based interconnectedness indicators, as for some individual banks those measures can deviate considerably.
JEL Code
C63 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→Computational Techniques, Simulation Modeling
G01 : Financial Economics→General→Financial Crises
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
16 January 2019
WORKING PAPER SERIES - No. 2224
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Abstract
This paper presents a novel approach to investigate and model the network of euro area banks’ large exposures within the global banking system. Drawing on a unique dataset, the paper documents the degree of interconnectedness and systemic risk of the euro area banking system based on bilateral linkages. We then develop a Contagion Mapping (CoMap) methodology to study contagion potential of an exogenous default shock via counterparty credit and funding risks. We construct contagion and vulnerability indices measuring respectively the systemic importance of banks and their degree of fragility. Decomposing the results into the respective contributions of credit and funding shocks provides insights to the nature of contagion which can be used to calibrate bank-specific capital and liquidity requirements and large exposures limits. We find that tipping points shifting the euro area banking system from a less vulnerable state to a highly vulnerable state are a non-linear function of the combination of network structures and bank-specific characteristics.
JEL Code
D85 : Microeconomics→Information, Knowledge, and Uncertainty→Network Formation and Analysis: Theory
G17 : Financial Economics→General Financial Markets→Financial Forecasting and Simulation
G33 : Financial Economics→Corporate Finance and Governance→Bankruptcy, Liquidation
L14 : Industrial Organization→Market Structure, Firm Strategy, and Market Performance→Transactional Relationships, Contracts and Reputation, Networks
29 May 2019
FINANCIAL STABILITY REVIEW - ARTICLE
Financial Stability Review Issue 1, 2019
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Abstract
The financial system can become more vulnerable to systemic banking crises as the potential for contagion across financial institutions increases. This contagion risk could arise because of shifts in the interlinkages between financial institutions, including the volume and complexity of contracts between them, and because of shifts in the economic risks to which they are commonly exposed. Analysis of the euro area banking system’s interlinkages, using the newly available large exposure data, suggests that the system could be more vulnerable to financial contagion through long-term interbank exposures than noted in other studies. That said, common exposures to the real economy – a standard contagion channel in the literature – represent a potential source of individual bank distress and non-systemic events. This analysis also provides an insight into the changes in contagion risk in the system over time, helping us to interpret changes in market indicators of systemic risk, such as aggregated credit default swap (CDS) prices.
2 July 2019
OCCASIONAL PAPER SERIES - No. 226
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Abstract
This paper presents an approach to a macroprudential stress test for the euro area banking system, comprising the 91 largest euro area credit institutions across 19 countries. The approach involves modelling banks’ reactions to changing economic conditions. It also examines the effects of adverse scenarios on economies and the financial system as a whole by acknowledging a broad set of interactions and interdependencies between banks, other market participants, and the real economy. Our results highlight the importance of the starting level of bank capital, bank asset quality, and banks’ adjustments for the propagation of shocks to the financial sector and real economy.
JEL Code
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
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
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
18 February 2020
WORKING PAPER SERIES - No. 2374
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Abstract
This study documents significant differences in the interbank market lending and borrowing levels across countries. We argue that the existing differences in interbank market usage can be explained by the trust of the market participants in the stability of the country’s banking sector and counterparties, proxied by the history of banking crises and failures. Specifically, banks originating from a country that has lower level of trust tend to have lower interbank borrowing. Using a proprietary dataset on bilateral exposures, we investigate the Euro Area interbank network and find the effect of trust relies on the network structure of interbank markets. Core banks acting as interbank intermediaries in the network are more significantly influenced by trust in obtaining interbank funding, while being more exposed in a community can mitigate the negative effect of low trust. Country-level institutional factors might partially substitute for the limited trust and enhance interbank activity.
JEL Code
G01 : Financial Economics→General→Financial Crises
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
D85 : Microeconomics→Information, Knowledge, and Uncertainty→Network Formation and Analysis: Theory
15 December 2020
WORKING PAPER SERIES - No. 2502
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Abstract
Systemic risk in the banking sector is usually associated with long periods of economic downturn and very large social costs. On one hand, shocks coming from correlated exposures towards the real economy may induce correlation in banks' default probabilities thereby increasing the likelihood for systemic-tail events like the 2008 Great Financial Crisis. On the other hand, financial contagion also plays an important role in generating large-scale market failures, amplifying the initial shocks coming from the real economy. To study the sources of these rare phenomena, we propose a new definition of systemic risk (i.e. the probability of a large number of banks going into distress simultaneously) and thus we develop a multilayer microstructural model to study empirically the determinants of systemic risk. The model is then calibrated on the most comprehensive granular dataset for the euro area banking sector, capturing roughly 96% or EUR 23.2 trillion of euro area banks' total assets over the period 2014-2018. The output of the model decompose and quantify the sources of systemic risk showing that correlated economic shocks, financial contagion mechanisms, and their interaction are the main sources of systemic events. The results obtained with the simulation engine resemble common market-based systemic risk indicators and empirically corroborate findings from existing literature. This framework gives regulators and central bankers a tool to study systemic risk and its developments, pointing out that systemic events and banks’ idiosyncratic defaults have different drivers, hence implying different policy responses.
JEL Code
D85 : Microeconomics→Information, Knowledge, and Uncertainty→Network Formation and Analysis: Theory
G17 : Financial Economics→General Financial Markets→Financial Forecasting and Simulation
G33 : Financial Economics→Corporate Finance and Governance→Bankruptcy, Liquidation
L14 : Industrial Organization→Market Structure, Firm Strategy, and Market Performance→Transactional Relationships, Contracts and Reputation, Networks