Eurex Clearing margin performance during 2020 

and reflection on the industry discussion

17 December 2020
Agenda

1 Summary

2 Covid 2020 lookback

3

Eurex Clearing reflection on the industry 

discussion

4 Appendix

2
Summary 1

3
Summary

▪ Year 2020 provided an important dataset to review the behavior of new financial market 

architecture introduced since 2009.

▪ Recently, FIA, ESRB and ECB published papers and studies outlining the effect of market 

volatility and CCP margin behavior on liquidity demand for Clearing Members and Clients: the 

two main topics emerging are the dynamics of the margin models and the intra day margin 

calls.

▪ This presentation aims to contribute Eurex Clearing perspective, facts and figures and also 

ideas on potential next steps.

4
B

C

A

E

D

CCP

F

A

F D

C

B

E

CCP market structure

Reduce systemic risk by:

• Reducing interconnectedness

• Counterparty risk reduction 

• by collateralization of exposures stemming from cleared portfolios

• changes over time due to

• Portfolio recomposition

• Market regime changes

• Margin parameters changes

2020 events generated an important dataset on 

the behavior of financial market architecture 

with central clearing playing 

a greater role since 2009

Bilateral market structure Key logic of central clearing

Benefits of central counterparty clearing

5
Covid 2020 lookback 2

6
Intraday Margin Calls

7

IDM Calls

(in bn) 2019-12 2020-01 2029-02 2020-03 2020-04 2020-05 2020-06 2020-07

2019 

average

EUR 7.21 7.42 12.93 70.31 16.58 8.26 18.44 8.64 6.99

USD 2.07 3.18 3.43 17.26 8.67 6.51 8.60 3.01 3.08

CHF 0.49 0.16 0.58 2.29 0.76 0.01 0.41 0.18 0.16

IDM Calls 

Count

2019-12 2020-01 2020-02 2020-03 2020-04 2020-05 2020-06 2020-07

2019 

average

EUR 172 213 288 853 279 187 347 190 266

USD 56 74 70 190 107 77 154 60 90

CHF 5 6 11 29 17 3 10 6 4

 -

 10

 20

 30

 40

 50

 60

 70

2020-1 2020-3 2020-5 2020-7

BILLION

Monthly cumulated volume of IDM Calls per currency

EUR IDM Call Volume USD IDM Call Volume CHF IDM Call Volume

0

100

200

300

400

500

600

700

800

900

2020-1 2020-3 2020-5 2020-7

IDM CALL COUNT

Monthly cumulated IDM Calls Count per currency

EUR IDM Call Count USD IDM Call Count CHF IDM Call Count
Margin Performance Summary

8

Intraday margin calls

▪ extreme market moves necessitated extraordinary number and volume of intraday margin calls in March 

2020; currently intraday calls are back to normal levels.

Margin requirements and margin collateral

▪ as the market volatility picked up and market participants increased their exposures, margin collateral 

increased from EUR 60bn to 110bn; currently it stands at EUR 71.2 bn.

Dynamics of margin parameters

▪ Prisma Margin parameters adapted to new level of volatility adequately and gradually, without manual 

interventions. Margins for different markets reacted differently, reflecting different volatility patterns.

▪ Margin parameters decline slowly. For most products, the indication is that it will take 3-6 months to revert 

to pre-crisis levels if market volatility is at pre-crisis levels during that time. 
Eurex Clearing has a sufficient coverage of margin requirements by margin collateral with a stable split between cash and securities

9

Key insights

• Following the peak in March, margin requirements started 

to decline at a slow pace

• Initial Margin and Total Margin Requirement are a function 

of both margin model (which in turn is a function of market 

volatility) as well as risk exposures of cleared portfolios

• Cash ratio remained stable throughout 2020; 

overcollateralization remained well above 10% at all times. 

• Stable collateral composition with dominant role of cash

Margin Requirements and Margin Collateral

Margin Requirement and Collateral Development (last 720 days)
10

Product-level margin performance for EURO STOXX® 50

• EuroSTOXX 50 futures represents the most actively traded equity derivative contract at Eurex Clearing

• The chart depicts margin levels (3-day MPOR) with and without floors, for long and short positions, over time and compares to 3-day PnLs

• The contract displayed increase in levels of volatility since second half of February. There were several exceedances of 3-day PnL against 

the margin levels. When comparing to 1-day PnL, number of margin exceedances is lower.

• Margins reacted gradually and adequately first exhausting the pro-cyclicality buffers thus smoothening the pace of the increase

• Slow-paced normalisation of margin levels since March, still significantly above pre-crisis levels.

• Observed a 7.99% 3-day move in November due to vaccine related announcement.
Eurex Clearing reflection on 3 the industry discussion

11
Derivatives clearing performance through the crisis

12

Good to have this discussion today

Worked as designed?

Learn from the new 

developments and continuously 

improve?
13

Intraday 

Margin 

Call

Timing

Trading Losses 

& Gains

Netting Level

Predictability

• Possible drivers for IDMC are 1) market movements 2) position changes and 3) margin features. 

During the Covid 2020 distress, 1) was identified as the biggest driver. 

• Scheduled batch vs. Event-driven. Tradeoff: operational facilitation vs. uncovered risk if strong 

market move between batches.

• 1) Adverse MtM changes can be covered by non-cash 2) Intraday pay-in/pay-out of trading 

losses/gains in respective currency. Tradeoff: combination of allowing non-cash collaterals and 

passing through pay-in/pay-out automatically is not feasible.

• 1) net across client pools – tradeoff with segregation 2) “eat” into IM – tradeoff with MPOR

• 1) timing predictability 2) amount predictability – reports are possible, markets remain 

unpredictable

• Stakeholders to agree on the right level of floors

• 1) Formula-based approach with predictable and transparent model – agree how quick/slow 

margins should react and calm down by setting parameters (e.g. decay/half-life) vs. 2) static 

modelling with discretionary adjustments. Mind the tradeoff with margin breaches backtesting.

• Any additional information on MPOR adequacy from analysing granular dataset 2020?

• Backtest on portfolio or product level? Against 1-day or MPOR-day PnL? With or without 

addons?

• Addons within or outside margin model?

• Lack of consistency across CCPs is criticised

Discussion landscape

IM 

model

Flooring

MPOR

Concentration & 

Liquidity

Reactiveness

Back Testing

Driver

Area Topic ECAG approach More discussion points / design choices / trade-offs

• Market movements (leading to

trading losses), position changes. 

No manual adhoc changes

• Event-driven (see drivers), 

operational thresholds

• Can be covered by non-cash

• Segregated pool level

• (new) Excess collateral pool helps

reduce number of calls

• Intraday margin reports

• Stress Period Floor targets 10y+ 

99-99.5% MPOR-day move

• Formula-based, gradual changes

reflect volatility regime. No manual

adhoc changes.

• Aligned with DMP: Fixed Income 

derivatives 2d, Equity derivatives 

3d, OTC 5d

• Portfolio and product-level backtest

• Addons are built into IM model

General • n/a
Zoom in: IM model - example for transparency on productlevel margin procyclicality and backtesting

14

Product ID Product Name MPOR

Target 

C.L.

Long Short

Breaches LTMR IM MRC Breaches LTMR IM MRC

FESX EURO STOXX 50 Index Futures 3 99.00% 2 103% 16% 1 105% 18%

FGBL Euro-Bund Futures 2 99.00% 1 103% 24% 0 - 11%

FBTP Long-Term Euro-BTP Futures 2 99.00% 2 154% 20% 1 187% 26%

Granular dataset of product-level margins and PnLs (here for the last 2 years) can be used to generate KPIs for 1) procyclicality and 2) backtesting. Some of these 

KPIs may also help to understand potential liquidity needs.

1) Procyclicality KPIs:

• IM MRC: IM Maximum Rate of Change over 1 day

• MRC can also be used as an estimate for liquidity needs – increase of IM due to increase in market volatility, position unchanged

• Other KPIs are possible e.g. rate of IM change over 1 week, 6 months, ...

2) Backtesting KPIs (product level, without addons)

• Exceptions: number of observed Margin Breaches

• Effective Confidence Level

• LTMR: Loss to Margin Ratio (worst 1-day Loss/IM) 

• Consistent usage of 1-day Loss (instead of MPOR-day loss) makes the results more comparable across CCPs

• LTMR Can also be used as an estimate for liquidity needs - potential size of intraday margin call (in relation to IM) due to market move
Zoom in: Intra Day Margin Call

15

Topic CM perspective Eurex Clearing perspective

Ad-hoc 

vs. 

scheduled 

intraday margin 

calls

▪ No harmonization between CCPs

▪ Possible liquidity squeeze under stressed market 

circumstances

▪ Difficulties to pass on ad-hoc intraday margin calls 

to clients

▪ Hard deadlines of ad-hoc intraday margin calls

▪ Operational thresholds limiting number of intraday 

margin calls favorable

▪ Ad-hoc intraday margin calls only times of 

extreme market dislocation

▪ Interest in resilient CCPs

▪ CCPs shall not be left with significant uncovered 

exposures

▪ Application of operational thresholds only intervene in 

case of significant uncovered exposures

▪ Transparency and intraday margin reports shall enable 

clearers to predict intraday margin calls

▪ Compliance with EMIR requirement to assess 

exposures on a near to real-time basis

Passing 

through of 

trading 

gains/losses 

intraday 

vs. 

netting of 

requirements

▪ Asymmetry of handling: intraday profits should be 

passed through

▪ Netting of requirements and credits

▪ Provision of non-cash collaterals

▪ Intraday provision of possibly illiquid product 

currencies shall be avoided

▪ Excess collateral can be withdrawn when adhering to 

cut-off times or on request

▪ Intraday all requirements can be covered by non-cash 

collaterals

▪ Netting of variation margin and initial margin allows 

higher capital efficiency

▪ (new) excess collateral pool allows more efficient cash 

management and lower liquidity needs

▪ Combination of allowing non-cash collaterals, netting 

and passing through variation margin automatically is 

not feasible

Opportunity to 

engage in 

discussion to 

understand pain 

points, needs, 

constraints, 

develop solution 

alternatives and 

approach 

enhanced target 

state
CCP

• 1 CCP many CMs

Cleared and Uncleared Ecosystem

CM

• 1 CM many Clients, 

many CCPs

Cleared Ecosystem

• many Clients, many CMs, many CCPs

• Different jurisdictions

Broader Financial System

Zoom out: Levels of pain points and solutions

16

Identification of 

current issues 

and pain points

Fact based / data 

driven 

analysis, outline 

solution space, 

assessment of 

alternatives

Inform policy 

response on 

intended 

enhanced target 

state, followed by 

implementation

Local

Steps of solution design and implementation

1. Pain Points 2. Solution

Alternatives

3. Target State

In search of enhancements 

to prevent potential 

systemic issues, it is worth 

to elaborate also higher 

level solutions (Cleared & 

Uncleared) in addition to 

more “local” solutions at 

CCPs/CMs or Cleared 

Ecosystem level

Global/ 

systemic

Level of 

Problem/ 

Solution
Key takeaways / potential next steps

17

▪ Shorter term Quick Wins:

• Collect granular Dataset 2020 (product level margins, PnLs) across CCPs and perform quantitative 

study

• Create transparency and evaluate tradeoffs between:

• Procyclicality KPIs (e.g.: maximum 1-day change of IM)

• Backtesting KPIs (product level, against 1day PnL, without addons)

• Derive ideal margin performance “trajectory” to inform progression towards enhanced target state 

with harmonization (MPOR, Floors, reactivity, ...)

▪ Mid term goals

• Evaluate further pain points in necessary granularity and structure, derive solution alternatives and 

inform potential regulatory policy response to achieve intended enhanced target state

Preview on 

p 14.
18

Thank You!
Appendix

19

4
Dynamics of margin parameters over time

Margin Floor by means of Stress Period VAR

determines how low margin can go during calm times

• Stress Period VaR acts as an anti-procyclicality margin floor in Eurex 

Clearing Prisma IM model

▪ As an example, thanks to SP VaR component, the pre-crisis 

IM for EuroSTOXX 50 futures was 7% of notional; 

substantially higher than peers‘ margins for their benchmark 

equity products

• Eurex Clearing has performed annual recalibration of its Stress 

Period VaR component in May 2020 reflecting Covid-19:

▪ Recalibration is based on a long history of data reaching back 

to Lehman crisis and now also including Covid-19 crisis

▪ The impact of recalibration on productive portfolios was 

minimal as vast majority of portfolios were above this margin 

floor

Filtered Historical Simulation VAR 

determines how quickly margin reacts to changes in volatility

• The reactivity of Eurex Clearing Prisma model is driven by Filtered 

Historical Simulation component

▪ The parameter governing reaction speed is lambda in an 

exponentially weighted moving average (EWMA) estimator

▪ Currently, lambda parameter is calibrated to achieve half-life 

of a single shock of approx. 50 working days

▪ Margin adequacy remains above 99% target (99.5% for OTC)

• Another effect is the expected time it takes for margins to revert to 

pre-crisis levels. Eurex Clearing risk team performed forward-looking 

scenario simulations for several market volatility levels.

▪ Current volatility is above pre-crisis levels

▪ For equity products products, the indication is that it will take 

another 3-6 months to revert to pre-crisis levels if market 

volatility is normalised during that time. 

Prisma margin model has two main components determining how margin reacts to changes in market volatility

20
21

Product-level margin performance for Euro-Bund Futures 

(FGBL)

• Euro-bund Futures is the most traded fixed income future contract on Eurex

• The chart depicts margin levels (2-day MPOR) with and without floors, for long and short positions, over time and compares to 2-day PnLs

• While initially less volatile than equity contract, it picked up steam in March leading to a few margin exceedances. When comparing to 1-

day PnL, number of margin exceedances is lower.

• Pro-cyclicality buffer was larger for short position than long positions as most of stress periods historically characterised by price moves up 

in a crisis.

• The new returns resulted in IM adapting to new, higher volatility regime, e.g. IM for short positions going up from 1.5% of notional to 2% 

notional as of 20 March.
22

Product-level margin performance for Euro-BTP Futures 

(FBTP)

• The chart depicts margin levels (2-day MPOR) with and without floors, for long and short positions, over time and compares to 2-day PnLs

• The situation with Covid-19 in Italy led to several margin exceedances when measured against 2-day backtesting PnL. When comparing to 

1-day PnL, number of margin exceedances is lower.

• Margins gradually increased even further in second half of March further as ECB actions resulted in a price spike in the opposite direction
EURO STOXX® 50 Simulation of future margin development

Several paths have been simulated under different 

scenarios on future levels of (annualised) market volatility

• MRIM: Market Risk Initial Margin (i.e. without 

concentration Addons)

• Stress Floor is shown as a black dashed line

• Simulation assumes the productive setting of half-life 

equal to 50 days. 

• Simulation date: 22 October 2020

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