Central counterparts margin models, procyclicality and clearing members - by Anne Job de Lescazes

central counterparts margin models, procyclicality and clearing members

by Anne Job de Lescazes

CCP resiliency within COVID-19 crisis, a lesson learned from 2008 market crisis

margin procyclicality versus sensitivity: trade-off is still to be found

The UK HMT1 provides a clear and elegant definition of Central Counterparties (CCPs): “financial institutions which firms use to reduce risks that arise when trading with others on financial markets. They provide more certainty than specific types of financial contracts, including derivatives, will, if cleared through the CCP’s services, be honoured if one of the counterparties to a trade were to default.”

In other words, CCPs are designed to bring down counterparty risk. They help to ensure that financial markets are both safer and more efficient.

Following the financial crisis in 2007-08, where CCPs confirmed their essential role of market stability cornerstone, regulators, upon G20 request, extended the derivative contracts perimeter to be ‘cleared’ processed by a CCP (EMIR, Dodd-Frank Act).

Parallelly, they published standardized principles to ensure that CCPs were well prepared and resourced to fulfil their increasing accountabilities (PFMI)2, complemented by numerous additional guidelines3 .

As a likely result of this worldwide effort to improve market resiliency against unavoidable crisis, CCPs, in particular European ones, remained resilient through the COVID-19 crisis, due to effective Business Continuity Plans and robust margin models. Additionally, further ESMA 3rd EU-wide CCP Stress tests did not reveal any systemic Risk concerns in either credit, liquidity, or concentration scenarios4 .

A robust margin model is doubtless key for financial markets stability. However, increase of margin calls during Q1 2020, brought reflexion about margin models procyclicality to the center stage.

The latter is officially defined as follows: “mutually reinforcing interactions between the financial and real sectors of the economy that tend to amplify business cycle fluctuations and cause or exacerbate financial instability”5 .

Too conservative margin calls, instead of safeguarding the financial market stability, would cause harmful liquidity stress for market participants. In other words, the medicine would be worse than the disease.

Key findings of EACH survey carried out after the crisis6 were that global margin levels increase, which was observed in Q1 2020, were not due to margin model changes during the COVID-19 market turmoil, but as market volatility integration in margin models, as well as position volume increase over this period.

One precision at this stage: margin requirements consist usually of two elements: Variation Margin and Initial Margin.

On one hand, Variation Margin Requirements are reflecting the effective change of market price of a product and allocating resulting gains and losses among market participants; VM is thus, in aggregate, not removing liquidity form the systems but redistributing it.7

On the other hand, Initial Margins (IM), designed to cover potential future losses in the event of a clearing member default, can entail a procyclical effect while jumping in a sudden way in reaction to market volatility increase, consequently demanding from them additional liquid assets at the most difficult moment to source them.

The regulators8, fully aware of these risks, gave the CCPs a choice between three AntiProCyclicality (APC) tools they had to integrate in their margin models.

• Adding a 25% margin buffer on top of their computed IM • Assigning a 25% weight to observations of stressed periods in their historical scenarios • Ensuring that IMs were not lower than would be computed using a lookback period of 10 years.

In addition, innovative APC measures are being elaborated, seeking to improve the balance of IM levels between sensitivity/reactivity and procyclicality, based for example on the use of a dynamic scaling factor9 .

Depending on their clearing services, CCPs IM models are adopting those 3 options in a quite equilibrated way10,while raising interpretation questions11 .

Parallelly, they keep enriching their margin framework with increasingly sophisticated APC measures.12, 13

consequences of IM frameworks changes facing clearing members

APC measures are embedded in a more global mutation of CCP margin models implementation, moving from analytic methodologies like SPAN to a portfolio-based historical V@R / Expected Shortfall computations.14

Those improvements in CCP margin frameworks, while providing undeniable benefits to market members and global market stability, entail technical challenges for clearing members.

Auto-calibration: it no longer requires regular calibration work on interclass/ intraclass spreads to represent correlations. As a result, CCP operational risks are reduced. Margin models get more transparent.

Scalability: it is more scalable and open to cross margining since the correlations are implicitly captured by times series of different risk factors. Therefore, it fully takes into account the effects of portfolio diversification in the context of multi-asset strategies.

In addition to portfolio-based V@R the Initial Margins are often complemented with additional requirements, to capture aspects of liquidity, concentration and credit risk correlation between portfolio/collateral and position holders.

As stated by the Bank of England15, no mystery that ‘market participants need to manage their liquidity in anticipation of potentially large margin calls in a stress’. This means being able, as EACH stresses, to predict the margin moves, by replicating margin models, as prices and margin parameters are deemed to be public.16

Even if this assertion is perfectly true, it should be kept in mind that depending on their size, and their margining process automation level, the clearing members are facing an increasingly complex implementation of margin models, requiring a higher level of investment and expertise as the historical and standardized SPAN methodology used to.17

This move is only one of a row of challenges that clearing members are facing, for which they may need carry out significant improvements in their daily risk margining process.18

1. HM Treasury: Expanded Resolution Regime: Central Counterparties, February 2021 2. https://www.bis.org/cpmi/publ/d163.pdf Resilience of central counterparties (CCPs): Further guidance on the PFMI – jul 2017

The PFMI outlines 24 principles for FMIs and five responsibilities for authorities and provides “[f]or each standard ... a list of key considerations that further explain the headline standard. An accompanying explanatory note discusses the objective and rationale of the standard and provides guidance on how the standard can be implemented.” 3. Resilience of central counterparties (CCPs): Further guidance on the PFMI – Jul 2017 4. ESMA 3 rd EU-wide CCP Stress Test 13 July 2020 - ESMA70-151-3186 5. Committee on the Global Financial System, The role of margin requirements and haircuts in procyclicality 2010 6. EACH Paper – CCP resilience during the COVID-19 Market Stress, June 2021 7. The Bank of England’s supervision of financial market infrastructures December 2020

references

8. Bank of International Settlements, (Avril 2012) Principles for financial market infrastructures, article n°3.6.10- Limiting procyclicality. 9. Lauren W. Wong and Yang Zhang, Procyclicality control in risk-based margin models 10. ESRB.report_200109_mitigating_procyclicality_margins_haircuts_in derivative markets and securities financing transactions_january 2020 11. EACH Paper – CCP resilience during the COVID-19 Market Stress June 2021 12. LCH SA FLR 2.0 Margin framework highlights, June 2021 13. CME, The SPAN2 Framework CME’s new margin methodology, April 26, 2021 14. SLIB White Paper 15. The Bank of England’s supervision of financial market infrastructures December 2020 16. EACH-Paper-CCP-resilience-during-the-COVID-19-Market-Stress-June-2021.pdf 17. Costas Mournelas, (September 2019) Risk.net, Span 2 : A fine balance, www.risk.net/6963921 18. SLIB White Paper

author

Anne Job de Lescazes

Marketing manager, SLIB Anne’s expertise lies in the area of risk, especially in clearing and counterparty risk, with 20 years experience as a senior consultant, functional architect, product owner in financial institutions like Société Générale and CIC Securities.

She’s currently working as product marketing manager at SLIB and driving an innovative revamping of the Credit Risk Product Line.

Anne is graduated from the Institut d’Etudes Politiques de Lyon and has a post-graduate diploma (DESS) in Organization and Protection of IT Systems.