Niet beschikbaar in het Nederlands
Mattia Montagna
- 6 August 2021
- WORKING PAPER SERIES - No. 2581Details
- Abstract
- This paper shows how the combined endogenous reaction of banks and investment funds to an exogenous shock can amplify or dampen losses to the financial system compared to results from single-sector stress testing models. We build a new model of contagion propagation using a very large and granular data set for the euro area. Based on the economic shock caused by the Covid-19 outbreak, we model three sources of exogenous shocks: a default shock, a market shock and a redemption shock. Our contagion mechanism operates through a dual channel of liquidity and solvency risk. The joint modelling of banks and funds provides new insights for the assessment of financial stability risks. Our analysis reveals that adding the fund sector to our model for banks leads to additional losses through fire sales and a further depletion of banks’ capital ratios by around one percentage point.
- JEL Code
- D85 : Microeconomics→Information, Knowledge, and Uncertainty→Network Formation and Analysis: Theory
G01 : Financial Economics→General→Financial Crises
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G23 : Financial Economics→Financial Institutions and Services→Non-bank Financial Institutions, Financial Instruments, Institutional Investors
L14 : Industrial Organization→Market Structure, Firm Strategy, and Market Performance→Transactional Relationships, Contracts and Reputation, Networks
- 29 January 2021
- WORKING PAPER SERIES - No. 2520Details
- Abstract
- After the announcement of the European Central Bank’s corporate quantitative easing program, non-financial corporations timed the bond market by shifting their issuance toward bonds eligible for the program. However, issuers of eligible bonds did not increase total issuance compared to other issuers; nor did they experience different economic outcomes. Instead, the announcement produced substantial spillover effects on risk premia. Credit risk premia declined, both in the corporate bond market and in the default swap market, whereas the valuation of eligible bonds did not change relative to comparable ineligible bonds. Firms took advantage of reduced risk premia by issuing riskier bond types. Using a novel and comprehensive dataset of corporate bonds in the euro area, we document how firms substituted across bond characteristics, and we find evidence of their intention to time the market. Our model indicates corporate market timing is instrumental in allowing quantitative easing to produce spillover effects.
- JEL Code
- G32 : Financial Economics→Corporate Finance and Governance→Financing Policy, Financial Risk and Risk Management, Capital and Ownership Structure, Value of Firms, Goodwill
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
- 15 December 2020
- WORKING PAPER SERIES - No. 2502Details
- 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
- 18 February 2020
- WORKING PAPER SERIES - No. 2374Details
- 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
- 20 November 2019
- FINANCIAL STABILITY REVIEW - ARTICLEFinancial Stability Review Issue 2, 2019Details
- Abstract
- This special feature discusses several ways in which the measurement of banks’ systemic footprint can be complemented with new indicators. The international approach is largely mechanical, but is intended to be complemented by expert judgement. The proposed additional systemic footprint measures may help macroprudential authorities in exercising that judgement. Using loan-level data matched with individual corporate balance sheet information allows macroprudential authorities to gain a better understanding of how a bank’s failure may affect employment and economic activity. Similar data, used in a model of network contagion, help assess the impact of a bank’s failure on the rest of the system. While the measures proposed in this special feature are not embedded in O-SII or G-SII scores, some evidence suggests that the concepts discussed have informed decisions of macroprudential authorities.
- 29 May 2019
- FINANCIAL STABILITY REVIEW - ARTICLEFinancial Stability Review Issue 1, 2019Details
- 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.
- 25 August 2016
- WORKING PAPER SERIES - No. 1944Details
- Abstract
- In this paper, we develop an agent-based multi-layered interbank network model based on a sample of large EU banks. The model allows for taking a more holistic approach to interbank contagion than is standard in the literature. A key finding of the paper is that there are material non-linearities in the propagation of shocks to individual banks when taking into account that banks are related to each other in various market segments. The contagion effects when considering the shock propagation simultaneously across multiple layers of interbank networks can be substantially larger than the sum of the contagion-induced losses when considering the network layers individually. In addition, a bank
- JEL Code
- C45 : Mathematical and Quantitative Methods→Econometric and Statistical Methods: Special Topics→Neural Networks and Related Topics
C63 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→Computational Techniques, Simulation Modeling
D85 : Microeconomics→Information, Knowledge, and Uncertainty→Network Formation and Analysis: Theory
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages - Network
- Macroprudential Research Network
- 25 November 2015
- FINANCIAL STABILITY REVIEW - ARTICLEFinancial Stability Review Issue 2, 2015Details
- Abstract
- This special feature proposes a methodology to measure systemic risk as the percentage of banks defaulting simultaneously over a given time horizon for a given confidence level. The framework presented here is applied to euro area banks. It is observed that since the announcement of the comprehensive assessment in October 2013 banks have significantly reshuffled their security portfolios. This has resulted in a decline in the probability of systemic events occurring.
- JEL Code
- G00 : Financial Economics→General→General
- 27 November 2013
- FINANCIAL STABILITY REVIEW - ARTICLEFinancial Stability Review Issue 2, 2013Details
- Abstract
- This special feature examines various macro-prudential tools through the lens of recent advances in the study of interbank contagion. The specific set of tools analysed are those designed to contain the “cross-sectional” dimension of systemic risk – that is, those designed to limit the systemic risk stemming from factors such as correlations and common exposures across financial institutions. These include tools such as large exposure limits and other regulatory requirements designed to limit the spread of systemic risk between banks. The analysis rests on the basic notion that interbank network structures, and hence the risk of contagion across the banking system in response to shocks, are influenced by banks’ optimising behaviour subject to regulatory (and other) constraints. Changes in macro-prudential policy parameters, such as large exposure limits, capital charges on counterparty exposures and capital and liquidity requirements more generally, will affect the contagion risk because of their impact on banks’ asset allocation and interbank funding decisions. This in turn implies that well-tailored macro-prudential policy can help reduce interbank contagion risk by making network structures more resilient. The analysis shows that to capture the full extent of potential interbank contagion, all of the different layers of bank interaction should be taken into account. Hence, if the regulator only focuses on one segment of interbank relationships (e.g. direct bilateral exposures), the true contagion risks are likely to be grossly underestimated. This finding has clear policy implications and flags the importance of micro- and macro-prudential regulators having access to sufficiently detailed data so as to be able to map the many interactions between banks.
- JEL Code
- G00 : Financial Economics→General→General