Welcome to the first issue of Volume 8 of The Journal of Financial Market Infrastructures, which contains three papers.
In our first paper, “Supervisory stress testing for central counterparties: a macroprudential, two-tier approach”, Edward Anderson, Fernando Cerezetti and Mark Manning take stress testing for central counterparties (CCPs) from the microsupervisory level to the macrosupervisory level.1 The underlying motivation is that the robustness of a single CCP does not necessarily imply that an ensemble of all major CCPs globally will also be robust. From a systemic risk standpoint, the impact of the simultaneous default of two large banks on the broader financial system can best be studied when all linkages are taken into account. The authors of this paper therefore recommend using supervisory stress tests, involving multiple CCPs, that go beyond the current practice of the multi-CCP fire drills in the United States and the United Kingdom, or the EU-wide stress test conducted by the European Securities and Mar- kets Authority. The approach consists of two tiers. The first tier is intended to capture the resilience over time, using frequent but standardized tests, taking CCP-specific risk profiles into account. The second tier aims at the cross-section dimension, where a specific aspect of all CCPs is assessed at a single point in time.
Dermot Turing focuses on the extreme situation of a CCP that has exhausted its prefunded financial resources in “Central counterparties: magic relighting candles?”, this issue’s second paper. This implies that we are looking at CCPs in their recovery or resolution mode. To that end, the author provides a comparative analysis of the end-of-the-waterfall provisions in the rule books of four major CCPs. He concludes that, although these CCPs have arrangements in place to call for extra funds, they may be insufficient to cover default losses or they may put too much strain on clearing members. Given the systemic nature of CCPs, the author advocates a revised policy approach with a partial return to uncleared bilateral trading.
In our third paper, “Study of correlation impact on credit default swap margin using a GARCH–DCC-copula framework”, David Li and Roy Cheruvelil analyze time-varying correlation in the context of credit default swap (CDS) portfolios. This is important not only for CCPs but also for financial risk management in general. The aim of this paper is to understand the impact of different correlation regimes on margining CDS portfolios consisting of single names. The sample period (January 2008–August 2017) contains, among other extreme events, the Lehman Brothers and eurozone crises. The authors find that correlation sometimes breaks down over short time intervals. All in all, they conclude that for both balanced and directional portfolios it may be prudent to take correlation dynamics into account in margin calculations.
Finally, I would like to announce that we intend to publish a special issue of The Journal of Financial Market Infrastructures devoted to methodologies and applications of data science in financial market infrastructures and cryptocurrencies, broadly defined. The call for papers can be found in this issue and on Risk.net. I look forward to seeing your contributions on these subjects, but there is also still ample room for submissions on other topics that fall within the journal’s scope.
LCH and Tilburg University
This paper examines the role of supervisory stress testing of central counterparties (CCPs). A key message is that the design of supervisory stress tests (SSTs) should be tailored to CCPs’ roles, risk profiles and financial structures.
In this paper, the rules of selected major CCPs (LCH, CME, Eurex and ICE) are reviewed for both their end-of-waterfall procedures and the rights granted to clearing members in end-of-waterfall scenarios.
In this paper, the authors establish generalized autoregressive conditional heteroscedasticity–dynamic conditional correlation (GARCH–DCC) and constant conditional correlation (CCC) copula model frameworks to study time-varying correlation among credit…