Pas disponible en français
Iñaki Aldasoro
- 7 October 2024
- WORKING PAPER SERIES - No. 2987Details
- Abstract
- Using a new series of crypto shocks, we document that money market funds’ (MMF) assets under management, and traditional financial market variables more broadly, do not react to crypto shocks, whereas stablecoin market capitalization does. U.S. monetary policy shocks, in contrast, drive developments in both crypto and traditional markets. Crucially, the reaction of MMF assets and stablecoin market capitalization to monetary policy shocks is different: while prime-MMF assets rise after a monetary policy tightening, stablecoin market capitalization declines. In assessing the state of the stablecoin market, the risk-taking environment as dictated by monetary policy is much more consequential than flight-to-quality dynamics observed within stablecoins and MMFs.
- JEL Code
- E50 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→General
F30 : International Economics→International Finance→General
- 11 December 2020
- WORKING PAPER SERIES - No. 2499Details
- Abstract
- We provide a simple and tractable accounting-based stress-testing framework to assess loss dynamics in the banking sector, in a context of leverage targeting. Contagion can occur through direct interbank exposures, and indirect exposures due to overlapping portfolios with the associated price dynamics via fire sales. We apply the framework to three granular proprietary ECB datasets, including an interbank network of 26 large euro area banks as well as their overlapping portfolios of loans, derivatives and securities. A 5 percent shock to the price of assets held in the trading book leads to an initial loss of 30 percent of system equity and an additional loss of 1.3 percent due to fire sales spillovers. Direct interbank contagion is negligible in our analysis. Our findings underscore the importance of accurately estimating the price effects of fire sales.
- 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
G18 : Financial Economics→General Financial Markets→Government Policy and Regulation
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
- 14 September 2016
- WORKING PAPER SERIES - No. 1962Details
- 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