Iñaki Aldasoro
- 26 February 2025
- OCCASIONAL PAPER SERIES - No. 368Details
- Abstract
- This paper provides an overview of recent analytical work conducted, under their own aegis, by experts from various European authorities and institutions in the field of crypto-asset monitoring. Currently, risks stemming from crypto-assets and the potential implications for central banking domains are limited and/or manageable, including as regards the existing regulatory and oversight frameworks. Nevertheless, the importance of monitoring developments in crypto-assets, raising awareness of the potential risks and fostering preparedness cannot be overstated. In light of this, this paper sets out the background to the establishment of the Crypto-Asset Monitoring Expert Group (CAMEG) in late 2023 to bring together experts from the Eurosystem’s central banks and from the European Systemic Risk Board (ESRB). It also provides abstracts of various papers and other analytical works presented at the inaugural CAMEG conference held on 24 and 25 October 2024. The conference aimed to take stock of analytical work and data issues in this area, while fostering European collaboration and monitoring in the field of crypto-assets. Finally, this paper outlines the prospective way forward for the CAMEG, focusing on gaining greater insight into data in this area and deepening analytical work on interlinkages, crypto-asset adoption and the latest trends.
- JEL Code
- E42 : Macroeconomics and Monetary Economics→Money and Interest Rates→Monetary Systems, Standards, Regimes, Government and the Monetary System, Payment Systems
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
O33 : Economic Development, Technological Change, and Growth→Technological Change, Research and Development, Intellectual Property Rights→Technological Change: Choices and Consequences, Diffusion Processes
- 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