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Francesco Vacirca

17 November 2021
Financial Stability Review Issue 2, 2021
This box establishes stylised facts about the significant increase in initial margin (IM) in the euro area derivatives market during the March 2020 market turmoil. First, it shows that the increase was concentrated almost entirely in centrally cleared derivatives and driven mainly by equity, credit and interest rate portfolios. Second, by comparing static portfolios with those where portfolio repositioning took place, the IM increase is decomposed into (i) changes attributable to the CCP model sensitivity to market volatility, and (ii) changes attributable to portfolio repositioning by investors. For centrally cleared interest rate and credit derivatives (where this method is applicable), CCP model sensitivity to market volatility is found to be a key driver of the IM increase. Overall, the results suggest that it is important to develop a clearer understanding of “excessive procyclicality” for IM and possibly, on the basis of this common understanding, to review the models which CCPs use to calibrate IMs. The supervisory and regulatory framework governing the liquidity management of market participants, and in particular that of some non-bank financial intermediaries, should also be strengthened.
JEL Code
C60 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→General
G10 : Financial Economics→General Financial Markets→General
G13 : Financial Economics→General Financial Markets→Contingent Pricing, Futures Pricing
17 December 2019
The global nature of derivatives markets, and the presence of large key financial institutions trading in several markets across the globe, call for taking a “macro” view on the interconnections arising in the clearing network. Based on the analysis of derivatives transactions data reported under the EMIR Regulation we reconstruct the network of relationships in the centrally-cleared derivatives market and analyse its topology providing insight into its structural features. The centrally-cleared derivatives network is modelled in the form of a multiplex network where each layer is represented by a derivatives asset class market. In turn, each node represents a single counterparty in that market. On the basis of different centrality measures applied to the collapsed aggregate and to the multiplex network, the critical participants of the euro area centrally-cleared derivatives market are identified and their level of interconnectedness analysed. This paper provides insight on how the collected data pursuant to the EMIR regulation can be used to shed light on the complex network of interrelations underlying the financial markets. It provides indications on structural features of the euro area centrally-cleared derivatives market and discusses policy relevant implications and future applications.
JEL Code
G01 : Financial Economics→General→Financial Crises
G15 : Financial Economics→General Financial Markets→International Financial Markets
G23 : Financial Economics→Financial Institutions and Services→Non-bank Financial Institutions, Financial Instruments, Institutional Investors