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Marco D'Errico

22 September 2016
OCCASIONAL PAPER SERIES - No. 11
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Abstract
Policy is only as good as the information at the disposal of policymakers. Few moments illustrate this better than the uncertainty before and after the default of Lehman Brothers and the subsequent decision to stand behind AIG. Authorities were forced to make critical policy decisions, despite being uncertain about counterparties’ exposures and the protection sold against their default. Opacity has been a defining characteristic of over-the-counter derivatives markets – to the extent that they have been labelled “dark markets” (Duffie, 2012). Motivated by the concern that opacity exercerbates crises, the G20 leaders made a decisive push in 2009 for greater transparency in derivatives markets. In Europe, this initiative was formalised in 2012 in the European Markets Infrastructure Regulation (EMIR), which requires EU entities engaging in derivatives transactions to report them to trade repositories authorised by the European Securities Markets Authority (ESMA). Derivatives markets are thus in the process of becoming one of the most transparent markets for regulators. This paper represents a first analysis of the EU-wide data collected under EMIR. We start by describing the structure of the dataset, drawing comparisons with existing survey-based evidence on derivatives markets. The rest of the paper is divided into three sections, focusing on the three largest derivatives markets (interest rates, foreign exchange and credit).
JEL Code
G15 : Financial Economics→General Financial Markets→International Financial Markets
G18 : Financial Economics→General Financial Markets→Government Policy and Regulation
22 December 2016
WORKING PAPER SERIES - No. 33
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Abstract
We develop a framework to analyse the Credit Default Swaps (CDS) market as a network of risk transfers among counterparties. From a theoretical perspective, we introduce the notion of flow-of-risk and provide sufficient conditions for a bow-tie network architecture to endogenously emerge as a result of intermediation. This architecture shows three distinct sets of counterparties: i) Ultimate Risk Sellers (URS), ii) Dealers (indirectly connected to each other), iii) Ultimate Risk Buyers (URB). We show that the probability of widespread distress due to counterparty risk is higher in a bow-tie architecture than in more fragmented network structures. Empirically, we analyse a unique global dataset of bilateral CDS exposures on major sovereign and financial reference entities in 2011 −2014. We find the presence of a bow-tie network architecture consistently across both reference entities and time, and thatt the flow-of-risk originates from a large number of URSs (e.g. hedge funds) and ends up in a few leading URBs, most of which are non-banks (in particular asset managers). Finally, the analysis of the CDS portfolio composition of the URBs shows a high level of concentration: in particular, the top URBs often show large exposures to potentially correlated reference entities.
JEL Code
G10 : Financial Economics→General Financial Markets→General
G15 : Financial Economics→General Financial Markets→International Financial Markets
15 March 2017
WORKING PAPER SERIES - No. 40
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Abstract
This paper provides a unique snapshot of the exposures of EU banks to shadow banking entities within the global financial system. Drawing on a rich and novel dataset, the paper documents the cross-sector and cross-border linkages and considers which are the most relevant for systemic risk monitoring. From a macroprudential perspective, the identification of potential feedback and contagion channels arising from the linkages of banks and shadow banking entities is particularly challenging when shadow banking entities are domiciled in different jurisdictions. The analysis shows that many of the EU banks’ exposures are towards non-EU entities, particularly US-domiciled shadow banking entities. At the individual level, banks’ exposures are diversified although this diversification leads to high overlap across different types of shadow banking entities.
JEL Code
F65 : International Economics→Economic Impacts of Globalization→Finance
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
29 March 2017
WORKING PAPER SERIES - No. 2041
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Abstract
We develop a framework to analyse the Credit Default Swaps (CDS) market as a network of risk transfers among counterparties. From a theoretical perspective, we introduce the notion of flow-of-risk and provide sufficient conditions for a bow-tie network architecture to endogenously emerge as a result of intermediation. This architecture shows three distinct sets of counterparties: i) Ultimate Risk Sellers (URS), ii) Dealers (indirectly connected to each other), iii) Ultimate Risk Buyers (URB). We show that the probability of widespread distress due to counterparty risk is higher in a bow-tie architecture than in more fragmented network structures. Empirically, we analyse a unique global dataset of bilateral CDS exposures on major sovereign and financial reference entities in 2011 - 2014. We find the presence of a bow-tie network architecture consistently across both reference entities and time, and that the flow-of-risk originates from a large number of URSs (e.g. hedge funds) and ends up in a few leading URBs, most of which are non-banks (in particular asset managers). Finally, the analysis of the CDS portfolio composition of the URBs shows a high level of concentration: in particular, the top URBs often show large exposures to potentially correlated reference entities.
JEL Code
G10 : Financial Economics→General Financial Markets→General
G15 : Financial Economics→General Financial Markets→International Financial Markets
2 May 2017
WORKING PAPER SERIES - No. 44
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Abstract
In this paper, we show both theoretically and empirically that the size of over-the-counter (OTC) markets can be reduced without affecting individual net positions. First, we find that the networked nature of these markets generates an excess of notional obligations between the aggregate gross amount and the minimum amount required to satisfy each individual net position. Second, we show conditions under which such excess can be removed. We refer to this netting operation as compression and identify feasibility and efficiency criteria, highlighting intermediation as the key element for excess levels. We show that a tradeoff exists between the amount of notional that can be eliminated from the system and the conservation of original trading relationships. Third, we apply our framework to a unique and comprehensive transaction-level dataset on OTC derivatives including all firms based in the European Union. On average, we find that around 75% of market gross notional relates to excess. While around 50% can in general be removed via bilateral compression, more sophisticated multilateral compression approaches are substantially more efficient. In particular, we find that even the most conservative multilateral approach which satisfies relationship constraints can eliminate up to 98% of excess in the markets.
JEL Code
C61 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→Optimization Techniques, Programming Models, Dynamic Analysis
D53 : Microeconomics→General Equilibrium and Disequilibrium→Financial Markets
D85 : Microeconomics→Information, Knowledge, and Uncertainty→Network Formation and Analysis: Theory
G01 : Financial Economics→General→Financial Crises
G10 : Financial Economics→General Financial Markets→General
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
20 November 2019
WORKING PAPER SERIES - No. 2331
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Abstract
We study the interplay between two channels of interconnectedness in the banking system. The first one is a direct interconnectedness, via a network of interbank loans, banks' loans to other corporate and retail clients, and securities holdings. The second channel is an indirect interconnectedness, via exposures to common asset classes. To this end, we analyze a unique supervisory data set collected by the European Central Bank that covers 26 large banks in the euro area. To assess the impact of contagion, we apply a structural valuation model NEVA (Barucca et al., 2016a), in which common shocks to banks' external assets are reflected in a consistent way in the market value of banks' mutual liabilities through the network of obligations. We identify a strongly non-linear relationship between diversification of exposures, shock size, and losses due to interbank contagion. Moreover, the most systemically important sectors tend to be the households and the financial sectors of larger countries because of their size and position in the financial network. Finally, we provide policy insights into the potential impact of more diversified versus more domestic portfolio allocation strategies on the propagation of contagion, which are relevant to the policy discussion on the European Capital Market Union.
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