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Guillaume Vuillemey

24 September 2018
WORKING PAPER SERIES - No. 2176
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Abstract
We study the allocation of interest rate risk within the European banking sector using novel data. Banks’ exposure to interest rate risk is small on aggregate, but heterogeneous in the cross-section. In contrast to conventional wisdom, net worth is increasing in interest rates for approximately half of the institutions in our sample. Cross-sectional variation in banks’ exposures is driven by cross-country differences in loan-rate fixation conventions for mortgages. Banks use derivatives to partially hedge on-balance sheet exposures. Residual exposures imply that changes in interest rates have redistributive effects within the banking sector.
JEL Code
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
E43 : Macroeconomics and Monetary Economics→Money and Interest Rates→Interest Rates: Determination, Term Structure, and Effects
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
20 February 2014
WORKING PAPER SERIES - No. 1638
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Abstract
We use an extensive data set of bilateral exposures on credit default swap (CDS) to estimate the impact on collateral demand of new margin and clearing practices and regulations. We decompose collateral demand for both customers and dealers into several key components, including the
JEL Code
G20 : Financial Economics→Financial Institutions and Services→General
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
G15 : Financial Economics→General Financial Markets→International Financial Markets
16 October 2013
WORKING PAPER SERIES - No. 1599
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Abstract
This paper presents a stress test model for the CDS market, with a focus on the interplay between banks' bond and CDS holdings. The model enables the analysis of credit risk transfer mechanisms, includes features of market and liquidity risk, and allows for contagious propagation of counterparty failures. As an illustration, we calibrate the model using sovereign bond and CDS data for 65 major European banks. The model simulation shows that, in case of a sovereign credit event, banks' losses due to direct and correlated bond exposures are significantly higher than losses due to CDS exposures. The main risk for CDS sellers is found to be sudden increases in collateral requirements on multiple correlated CDS exposures. Close-out netting considerably reduces the extent to which contagion may occur.
JEL Code
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
H63 : Public Economics→National Budget, Deficit, and Debt→Debt, Debt Management, Sovereign Debt
G15 : Financial Economics→General Financial Markets→International Financial Markets
Network
Macroprudential Research Network
29 August 2013
WORKING PAPER SERIES - No. 1583
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Abstract
This paper analyses the network structure of the credit default swap (CDS) market, using a unique sample of counterparties’ bilateral notional exposures to CDS on 642 sovereign and financial reference entities. We study the network structure, similarly to the literature on interbank and payment systems, by computing a variety of network metrics at the aggregated level and for several subnetworks. At a reference entity level, we analyse the determinants of some key network properties for large reference entities. Our main results, obtained on a sub-sample of 191 reference entities, are the following. First, the CDS network shows topological similarities with the interbank network, as we document a “small world” structure and a scale-free degree distribution for the CDS market. Second, there is considerable heterogeneity in the network structures across reference entities. In particular, the outstanding debt volume and its structure (maturity, collateralization), the riskiness, the type (sovereign/financial) and the location (European/non-European) of reference entities significantly influence the size, the activity and the concentration of the CDS exposure network. For instance, the network on a high-volatility reference entity is typically more active, larger in size and less concentrated.
JEL Code
G15 : Financial Economics→General Financial Markets→International Financial Markets