Ever since the G20 commitment of 2009 sparked a scramble to establish new CCP Clearing services for the Global OTC derivative market, there has been a broad consensus amongst CCPs around the use of a Filtered Historical Simulation Value-at-Risk (or FHS VaR) approach to the setting of Initial Margin levels.

1. The End of Convergence
www.catalyst.co.uk
Key clearing member and buy-side strategies to address
new margining methodologies for OTC derivatives
April 2013
The End of Convergence
Ever since the G20 commitment of 2009 sparked a scramble to establish new CCP Clearing
services for the Global OTC derivative market, there has been a broad consensus amongst CCPs
around the use of a Filtered Historical Simulation Value-at-Risk (or FHS VaR) approach to the
setting of Initial Margin levels.
Equally importantly, both the margining mechanism and the margin parameters have been broadly
aligned amongst Global CCPs. Key inputs such as the data history utilised, the confidence interval
selected, and the volatility scaling applied, were all seen to converge around a very similar standard. As a
result, there was little to differentiate between different CCPs in terms of the margins applied.
However in recent months both SwapClear and Eurex have indicated that they will overhaul their
margining algorithms, with each adopting a markedly different approach.
This move poses new challenges for the users of OTC derivative CCPs, who must now assess the impact
that these new margining approaches will have on the overall cost of Clearing, as well as the implications
for the level of protection offered by each CCP for Clearing Members and clients alike.

2. © Catalyst Development Ltd 2
In the case of SwapClear, the data history is expected to be significantly extended, absolute returns will
be used in preference to relative returns when defining scenarios, and an Expected Shortfall measure
replaces the existing Worst Case Loss. By contrast, the Eurex PRISMA model will introduce the concept
of liquidation groups for portfolio margining, and will use historical data in a way which minimises the
impact of autocorrelation, and includes a Stress VaR component. In both cases, there may be a material
increase in the margins called for certain portfolios of OTC derivatives.
Initial Margin – The Risk Measure
Up to the end of 2012, the majority of OTC
derivatives CCPs had adopted a Worst Case
Loss measure when calculating Initial Margin.
The Worst Case Loss was typically calculated
from a five year data history, with historical
scenarios based on overlapping returns. Such a
measure is nominally equivalent to a VaR
measure, with an input confidence interval of
100%.
The changes to SwapClear margining mark a
move away from Worst Case Loss, to the use of
an Estimated Shortfall measure. In effect, rather
than taking the largest result from the output of
the historical scenario set, SwapClear will now
use the average of the top X scenarios (taken
alone, a less conservative standard).
Estimated Shortfall is favoured by some
practitioners, as it meets the criteria of a
‘coherent’ risk model, by seeking to quantify the
risk in the tail of the distribution. However, the
use of overlapping returns may result in a
potential issue with autocorrelation, which is not
present in a Worst Case Loss approach. By
comparison, the Eurex PRISMA model favours a
VaR approach, with the historical data structured
so that overlapping returns are not used.
Although such a measure does not satisfy the
definition of a ‘coherent’ risk model, the Eurex
model benefits from the adoption of a
mechanism specifically tailored to addressing
auto-correlation.
Absolute and Relative Returns
The previous consensus on margining for OTC
derivatives had settled on the use of relative
returns when parameterising the historical
scenarios. However, the current rates
environment has highlighted some drawbacks
associated with this approach:
Transition to a Low Rate Environment – as rates
fall, the down shift scenarios generated may be
understated in a low rate environment;
Infinite Scenarios –zero rates can result in
infinite shift scenarios if not managed
appropriately; and
Negative Rates – a relative shift approach
cannot generate a negative rates scenario until
rates themselves go negative. Conversely, once
a negative rates scenario is logged, it will
continue to generate negative rates even in a
high rate environment.
Taken together, these drawbacks have proven
to be sufficiently material to prompt SwapClear
to move to an absolute returns approach.
However, the use of absolute returns is no
panacea for the issues associated with
Margining for OTC derivatives – if it were, it
would arguably have been used since inception.
Indeed, an absolute rates approach proves less
conservative in a rising rates environment, and
Comparing Margin Algorithms
The new SwapClear and Eurex margining algorithms have a number of striking differences to the
previous consensus model adopted by manyGlobal OTC derivative CCPs.
Consensus Model SwapClear Eurex PRISMA
Measure Worst Case Loss Estimated Shortfall VaR
Holding Period 5 Day 5 Day 5 Day
Data History 5 Year 10 Year 3 Year
Volatility Scaling Yes Yes Yes
AutoCorrelation No Yes No
Stress VaR No No Yes

3. © Catalyst Development Ltd 3
can generate excessively negative rate
scenarios in a low rate environment.
As such, Clearing Members and Clients should
be alive to the possible downsides an absolute
or relative returns approach may have for their
own cleared portfolio, as neither caters
completely for changes in interest rate cycles.
Satisfying the Ten Year Rule
Under the technical standards for CCPs recently
adopted in Europe, CCPs must limit pro-
cyclicality by:
“ensuring that its margin requirements are not
lower than those that would be calculated using
volatility estimated over a 10 year historical look-
back period.”
The changes adopted by SwapClear and Eurex
are both likely to be tailored to meet this
standard.
In the case of SwapClear, the data history is
expected to be significantly extended, thereby
ensuring that volatility estimated over a 10 year
look-back period is explicitly included.
Eurex PRISMA adopts a different approach,
whereby a Stress VaR component is included in
the margin calculation. The stress VaR
component is then based on the highest period
of volatility observed over a 10 year period,
again theoretically meeting the standard.
It appears likely that other European CCPs who
are currently using a shorter look-back period of
historical data will need to respond in order to
satisfy this requirement.
There are issues, however, for implementing this
extended look back period for newer products
that do not have the depth of history.
Techniques which are available (eg the use of
proxy data) often lack mathematical rigour.
Managing Autocorrelation
Autocorrelation occurs when one time series
closely resembles a lagging time series for the
same data. It can be important in the calculation
of historical simulation VaR and Expected
Shortfall measures, when overlapping returns
are used together with a long holding period –
as a single extreme event can cause
pronounced moves for all of the historical
scenarios which span the extreme event in
question.
A Worst Case Loss measure does not suffer
from auto-correlation, as the highest loss is
always used, and no further reliance is placed
on the results of less severe scenarios.
The SwapClear Estimated Shortfall calculation
does not appear to explicitly include any
methodology for addressing auto-correlation,
and as such a single extreme event retains the
potential to dominate the output of the algorithm.
By contrast, Eurex PRISMA specifically
addresses the potential issue of auto-correlation,
by calculating five VaR measures on five time
series of non-overlapping returns (ie in different
phases). The mean of the five VaRs is then
taken when determining the final margin
number. As such, a single extreme event should
not overly influence the final output.
Conclusions
Before the changes proposed by SwapClear and
Eurex, there was little to choose between OTC
derivatives CCPs in terms of the margining
algorithm applied.
From early 2013, users of OTC derivatives
CCPs will now see greater differentiation
between the models offered by CCPs. All these
models are sound, conservative and appropriate
for their intended purpose. However, they may
result in material differences in the final margin
number produced for certain portfolios.
Faced with such a divergence in margining
models, it seems inevitable that the margining
approach used will become an increasingly
important component of the analysis made when
selecting a CCP – as all the models are
arguably equally valid, and margin represents a
material part of the cost of clearing.
This becomes increasingly challenging to those
Clearing Brokers who are offering choices of
CCPs, including margin optimisation, to their
clients.
As a result, Clearing Members and their clients
will need to assess the impact of margins
alongside other important considerations, such
as clearing venue of the extant portfolio,
liquidity, fees and segregation models, when
deciding where to clear certain trades.
As CCPs look to differentiate themselves further
in terms of risk models, this assessment will
become increasingly complex. As such, Clearing
Members and Buy-side firms will need to fully
understand each CCPs risk model, and

4. © Catalyst Development Ltd 4
Disclaimer: Comments in this presentation on are based on Catalyst's understanding of the global regulatory landscape as of April
2013. This document is neither intended to be comprehensive, nor to provide legal or accounting advice.
establish a methodology for quantifying the
impact of different clearing strategies. By doing
so, CCP users can calibrate their clearing
strategy to their particular needs, whether it be
minimising the cost of clearing, optimising their
use of assets, or guaranteeing the greatest level
of protection.
Meet our authors
christianlee@catalyst.co.uk damonbatten@catalyst.co.uk
Christian Lee
Christian is Head of
our Clearing, Risk and
Regulatory Practice
and one of the world’s
most experienced risk
management
professionals. He is a
specialist in OTC
clearing, market and
credit risk, financial
markets, middle office,
APAC and Latin
America.
Damon Batten
Damon is a risk
specialist in traded and
non-traded market risk,
CCP clearing and
current regulatory
initiatives, including the
FSAs ILAA regime,
Basel III, European
market infrastructure
regulation and Dodd-
Frank.
Catalyst uniquely combines
teams of financial markets
experts with organisational
change specialists to
deliver enduring results.
We provide honest
guidance to help you
succeed. We are catalysts
for enduring excellence.
Catalyst Development Ltd
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