Download The Cost of Clearing: A Buy-Side Investigation - Sapient

©Copyright 2013 Sapient Corporation

THE COST OF CLEARINGA BUY-SIDE INVESTIGATION

June 2013

©Copyright 2013 Sapient Corporation

2

Table of Contents3 Section 1: Executive Summary

5 Section 2: Introduction

7 Section 3: Model Description

9 Section 4: Initial Margin Methodologies9 4.1: Uncleared Swaps, Pre-2008 Environment9 4.2: Eris Standard Swap-Futures10 4.3: LCH.Clearnet SwapClear Cleared Swaps11 4.4: Uncleared Swaps, BCBS/IOSCO Recommended Environment

12 Section 5: Results12 5.1: Tables and Graphs17 5.2: Discussion of Results

19 Section 6: Conclusion and Next Steps 19 6.1: Conclusion19 6.2: Next Steps21 6.3: Special Thanks

22 Section A: Appendix

The Cost of Clearing: A Buy-Side Investigation 3

1. Executive SummaryRecent regulatory reforms, such as Dodd-Frank and EMIR, were introduced to minimize systemic risk. Dodd-Frank stipulates that all vanilla over-the-counter (OTC) interest rate (IR) swaps traded in the US must be centrally cleared through a central counterparty (CCP). This directly impacts buy-side firms, who previously hedged their rate duration risk by trading OTC IR swaps bilaterally using CSAs with minimal initial margin (IM) costs. By the end of 2013, buy-side firms will be subject to mandatory clearing regulations and new clearing costs, which may have a significant impact on their bottom line.

Additionally, a new breed of swap-futures products are available, which have unique clearing costs associated with their execution and trade life cycle that must be considered in any comparison with more traditional cleared IR swaps.

Sapient Global Markets has embarked on a study to determine how these new central clearing mandates will impact alpha for buy-side firms. Through the study, Sapient Global Markets sought to quantify the cost of clearing for buy-side firms by comparing the overall portfolio performance of a fixed-income fund under four different hedging scenarios: uncleared swaps subject to pre-2008 margin requirements, uncleared swaps subject to the BCBS/IOSCO guidelines for margining (effective after 2015), swaps cleared through LCH.Clearnet SwapClear, and Eris Standard swap-futures (cleared through CME). In all four backtests, both the simulated fund returns (via benchmark index) and the overall portfolio strategy remain exactly the same. Performance between the backtests is measured in terms of the drag on overall portfolio returns.

The results of the study showed a marked difference (measured in basis points) between the four different models used and ranked performance as follows, in order of the lowest drag on returns:

(1) Uncleared swaps subject to pre-2008 margin requirements.(2) Eris Standard swap-futures (cleared via CME).(3) Swaps cleared through LCH.Clearnet SwapClear.(4) Uncleared swaps subject to the BCBS/IOSCO IM guidelines (effective after 2015)1.

Note that over the course of 2013, the trading of uncleared vanilla swaps will be prohibited as the CFTC central clearing mandate comes into effect. Although the suggested BCBS/IOSCO margin requirements will not become effective until after 2015, we included backtest number 4 above to provide a point of comparison between the uncleared and cleared swaps (and their swap-futures equivalents).

1 http://www.bis.org/publ/bcbs226.pdf.

4

Based on our results, the costs of hedging duration in a post-Dodd-Frank environment will increase. The drag2 on portfolio alpha in the new environment will range from between ~20bps to ~62bps for cleared trades, depending on the product, and up to ~91bps for traditional uncleared bilateral OTC trades.

Once all the proposed post-Dodd-Frank regulations are in place, hedging using centrally cleared instruments (both Eris Standard swap-futures and LCH-cleared swaps) will be cheaper than uncleared OTC instruments. Therefore, we expect market participants to choose this option and move to central clearing, regardless of trading costs.

Although the most significant factor driving the differences in clearing costs is IM, one must consider additional factors when selecting hedging products. Such factors include the basis between swaps and standard swap-futures, caused by the non-flexible fixed coupons and maturity dates of the swap-futures.

Post-Dodd Frank Portfolio Drag since Inception (%)

The post-Dodd-Frank cost of clearing, in terms of drag on cumulative portfolio returns, is shown here as between~20bps and ~62bps for cleared products.

2 “Post-Dodd-Frank portfolio drag” is the difference between pre-Dodd-Frank cumulative portfolio returns (i.e. backtest (4)) and post-Dodd-Frank cumulative portfolio returns for the backtest under consideration.

Rebalancing Date

5

2. IntroductionThe aim of this study is to quantify and compare the costs of a typical buy-side portfolio hedging strategy in terms of drag on portfolio returns. Therefore, we consider the costs related to the collateralization and clearing of IR derivative hedging instruments in various margining and regulatory environments.

Following the 2008 financial crisis, global regulatory bodies have introduced reforms designed to significantly reduce systemic risks posed by undercapitalized, interconnected financial institutions. The Dodd-Frank (DF) and Basel III guidelines were designed to encourage central clearing for as many eligible products as possible stipulating that all standardized, vanilla OTC IR swaps must be cleared by CCPs. On March 11, 2013, the CFTC clearing deadline went into effect for major swap participants, swap dealers and private funds3. Other institutions have until June 10, 2013 or September 9, 2013, depending on their classification, to comply with the deadline unless they are exempt from the mandatory clearing requirements.

In addition to compulsory central clearing of standard vanilla trades, regulators and clearing houses have adopted multiple approaches to increase the volume of trades voluntarily cleared through CCPs. First, regulators have assigned punitive capital charges to derivatives that remain bilateral in order to cover the counterparty credit risk inherent in these bilateral transactions. These charges include a higher risk-weighting for bilateral deals than for CCP deals, and CVA charges for any uncollateralized portions of bilateral portfolios. Second, regulators, clearing houses and exchanges have provided incentives for buy-side participants to use central clearing, such as lower risk-capital charges, opportunities for cross-product margining (which lowers IM requirements) and more lenient time horizons for calculating IM requirements. Specifically, a 1 to 2-day, or 5 to 7-day time horizon is allowed, depending on the type of derivative and clearing house, resulting in significant savings over the 10-day time horizon mandated in a recent BCBS/IOSCO paper, set to go into effect for non-centrally cleared derivatives by 2015.

Although these carrot-and-stick regulations aim to make central clearing more appealing, there is a lack of clarity as to how the cost-savings will ultimately work out for buy-side financial institutions. This is a particularly serious issue for fixed income funds, which typically track benchmark bond indices and use OTC derivatives to hedge their interest rates and credit exposures. In order to quantify the new clearing incentives, buy-side participants must examine fees, contributions to the mutual default fund, operational/systems overheads, IM and variation margin (VM) requirements and potential re-hypothecation limitations, among other things.

3 http://www.cftc.gov/PressRoom/PressReleases/pr6529-13

The Cost of Clearing: A Buy-Side Investigation

6

Our investigation consists of several portfolio backtests over a fixed historical time period. We assume that a fictitious buy-side firm is replicating a well-known fixed income benchmark while reducing duration exposure. We then examine the performance of this strategy in four different regulatory and clearing environments. The simulated portfolios are composed of cash bonds tracking a benchmark index and interest-rate derivatives that are dynamically traded to reduce the portfolios’ interest-rate exposures. Note that after the first interest rate hedge is placed in the first time period, subsequent hedges must take both the bond portfolio and past hedges into account. Each backtest takes place over eleven, one-month intervals starting in October 2011 and ending in September 2012.

The four backtests conducted for this study were performed with the appropriate hedging instruments in the following regulatory environments:

(1) Uncleared swaps in a pre-2008 environment.(2) Eris Standard swap-futures (cleared through CME).(3) Swaps cleared through LCH.Clearnet SwapClear.(4) Uncleared swaps subject to the BCBS/IOSCO IM guidelines (effective after 2015).

7

3. Model DescriptionFor the purpose of this study, we chose the Barclays U.S. Aggregate Bond Index as our hypothetical fund’s benchmark. We assume that the bond portfolio had zero tracking-error at all times, so the month-on-month relative returns of the physical bond portfolio matched the benchmark index in all periods.

The backtest was performed over the course of 11 months, using historical data (where possible) from October 2011 to September 2012, and the portfolio rebalancing dates were chosen as the last business dates of every month, making a total of twelve portfolio-rebalancing dates for each backtest (inclusive of the October 2011 initial date).

The backtest hedging strategy entailed a 2% reduction in overall portfolio duration. This is a plausible duration-management strategy for an actively managed fund. Therefore, on each of the monthly rebalancing dates the fund traded derivatives so that its duration equaled the Barclays Aggregate duration less 2%: (Barclays Agg Duration% - 2%).

The backtest assumes that IM and VM are recalculated (and the required margin-account deposits/withdrawals are performed) at month-end (on the portfolio rebalancing dates). The backtest also assumes that the portfolio mandate includes a “minimize cash” objective in order to maximize returns of performing assets. Therefore, any cash needed to cover IM and VM requirements comes from selling a slice of the physical bond portfolio. Conversely, the backtest assumes that any excess cash, left over after IM and VM requirements have been satisfied, is immediately reinvested in the indexed physical bond portfolio.

The swaps backtests also assume that net positive realized cash flows are reinvested into the physicals (and net negative cash flows are funded by a withdrawal from physicals) on the portfolio rebalancing dates.

We made the reasonable assumption that all hedging instruments traded on the rebalancing dates, whether swaps or swap-futures, had a tenor of 10y.

VM for all four backtests was calculated using Bloomberg yield-curve market data and analytics.


8

Each of the four backtests follows the steps outlined below:

At inception (October 31st, 2011):

(1) $9bn is invested in a portfolio equivalent to the Barclays U.S. Aggregate Bond Index (Barclays Agg).

(2) An OTC IR swap (or swap-future) is traded with a notional value such that the total portfoliodollar-duration target of Portfolio MV * (Barclays Agg Duration% - 2%) is met.

(3) IM is calculated for the newly traded derivative using the appropriate method (see Section 4).A portion of the physical bond portfolio must be sold off to fund the IM, and therefore the MV of the bond fund is reduced accordingly.

Subsequent time-steps:

(4) On the next portfolio rebalancing date, the bond fund gains or loses value equivalent to the returnof the Barclays Agg between rebalancing dates. For the swaps, VM is equal to the change in NPV for the swap portfolio between the rebalancing dates. For the Eris swap-futures, VM is equal to the sum of the change in NPV and realized cash-flow payments between the rebalancing dates. If the buy-side fund owes VM, then a slice of the physical bond portfolio is sold off to meet the requirement. If the buy-side fund is owed VM from the counterparty/clearing-house, then this VM is immediately reinvested in the physical bond portfolio.

For the Eris swap-futures backtest, realized cash flows are included as a component of the VM calculation. For the swaps backtests, realized cash flows are accounted for on the rebalancing dates. Any coupons that were received since the previous rebalancing date can be reinvested in the physicals, and any coupons that were paid since the previous rebalancing date are funded by reducing the amount invested in physicals.

(5) IM is calculated for the portfolio of existing IR hedging instruments (see Section 4). If the IMrequirement increases, this must be funded by selling off a portion of the physical bond portfolio. If the IM requirement decreases, the excess cash can be withdrawn from the IM account and immediately reinvested in the physical bond portfolio.

(6) Durations for the derivatives and the fund are recalculated. A new IR swap (or swap-future) istraded to maintain the original duration hedge (-2%).

(7) IM is then recalculated for the portfolio of IR hedging instruments (including the newly-tradedinstrument). If the IM requirement increases, then a portion of the physical bond portfolio is sold off to meet the requirement. If the IM requirement decreases, then the excess cash can be reinvested into the physical bond portfolio.

(8) The backtest moves to the next time step (i.e. the following portfolio rebalancing date), and loopsback to step (4), continuing until the final portfolio rebalancing date of September 28, 2012.

9

4. Initial Margin Methodologies4.1 – Uncleared Swaps, Pre-2008 EnvironmentPre-2008 IM for the bilateral IR swaps, collateralized though an ISDA CSA, is assumed to be 1% of gross notional outstanding. Based on research and interviews, we have determined that this is a percentage that broker-dealers may reasonably have charged in the pre-2008 environment.

4.2 – Eris Standard Swap-Futures The IM for Eris Standards is normally calculated using a 2-day SPAN model. However, historical SPAN parameters were not available for any period prior to the December 2012 go-live.

We therefore used approximate IM percentages for the Eris Standards in our study, which were calculated according to the following method:

• The raw IM percentages obtained from Eris Exchange were calculated using the 5-day CME H-VaRmodel (which is used in production for Eris Flexes).

• The raw percentages were multiplied by a scaling factor of √(2/5) to approximate the CME H-VaRreturns under a 2-day time horizon (a conversion which assumes that returns can be scaled by the square root of the time horizon).

• We made no further adjustments to the IM to account for the differences between the H-VaR modeland the SPAN model, as we assumed that IM calculated under 2-day H-VaR would be reasonably close to IM calculated under 2-day SPAN.

The parameters for the CME H-VaR model are as follows:

• 5y of historical scenarios.• 5-day time horizon.• IM calculated at 99.7% confidence.• Historical returns are weighted using EWMA.


10

4.3 – LCH.Clearnet SwapClear Cleared SwapsLCH.Clearnet SwapClear calculates IM according to their proprietary Portfolio Approach to Interest Rate Scenarios (PAIRS) model. This is a weighted historical backtest model with the following parameters4:

• 5y of historical data.• 7-day time horizon for historical returns.• IM calculated as the worst-case loss.• Relative returns.• Historical returns are weighted using EWMA.

The LCH.Clearnet SwapClear SMART tool was used to calculate IM for the LCH-cleared swaps. The SMART tool uses a delta-gamma approximation for calculating the outcome of each historical backtest.

We made the reasonable assumption that buy-side funds centrally clear through intermediary Futures Commission Merchants (FCMs), and therefore our buy-side firm is subject to an IM charge calculated using a 7-day time horizon.

Note that in order to simplify the backtests, the model only calculates VM monthly. The effect is that realized cash flows are accounted for only on the rebalancing date. This simplification does not represent the actual behavior of LCH.Clearnet swap clearing. In practice, the accrued coupon is accumulated daily, and this is realized in the daily movement of VM. Furthermore, one would be able to take advantage of net-positive daily accrued interest and invest it in performing assets.

However, because we are applying VM monthly and our VM calculations only consider NPV, we must consider realized cash flows separately. We assume that realized cash flows are invested into performing assets at the next available rebalancing date, rather than on the day that the cash flows are paid out.

4 In February 2013, LCH.Clearnet went live with an update to their IM calculation methodology to provide enhanced IM calculation results in a sustained low interest-rate environment. This backtest was conducted using the old LCH.Clearnet model.

11

4.4 – Uncleared Swaps, BCBS/IOSCO Recommended EnvironmentAccording to BCBS/IOSCO guidelines updated in February 2013, any OTC derivatives that remain bilateral by 2015 should be subject to IM requirements calculated using a Historical Value-at-Risk (H-VaR) Model with the following parameters:

• 5y of historical data5.• 10-day time horizon for historical returns.• IM calculated at the one-tailed 99% confidence interval.

For the purpose of the study, we developed an Excel-based H-VaR model for calculating the BCBS/IOSCO-mandated IM on the portfolio rebalancing dates.

The Excel model was powered using FINCAD F3 analytics software, and the market data used for calculations was sourced from Bloomberg. The individual scenario P&Ls were calculated using delta-gamma approximations (explained in further detail in the appendix). The following describes the H-VaR-Excel model:

• The model uses absolute returns.• Returns are not filtered (i.e. the model uses raw-returns).• Single-curve USD-LIBOR bootstrapping is used throughout the calculator (as opposed to the

LCH.Clearnet and Eris models, which use dual-curve OIS discounting).

5 The BCBS/IOSCO guidelines actually require a historical data set that incorporates “a period of significant financial stress”. By choosing a 5y historical period, we are consistent with the LCH margin model, and we are also including the late-2008 period of financial stress in our scenarios.


12

5. Results5.1 – Tables and Graphs

Cumulative Portfolio performance since inception (%)

Figure 1: Cumulative Portfolio performance, in terms of percentage returns, since inception. The Barclays Agg unhedged performance is added for reference

Rebalancing Date

13

Rebalancing Date

Cumulative return (%) for Physicals Portfolio Hedged using LCH.Clearnet Cleared Swaps

Cumulative return (%) for Physicals Portfolio Hedged using Uncleared Swaps (BCBS/IOSCO)

Cumulative return (%) for Physicals Portfolio Hedged using Uncleared Swaps (Pre-2008)

Cumulative return (%) for Physicals Portfolio Hedged using Eris Swap-Futures

Cumulative return (%) for Unhedged Benchmark Index Performance

30-Nov-11 -1.42201% -1.42433% -0.57737% -0.84607% -0.17774%

30-Dec-11 -0.88132% -0.99079% -0.14366% -0.32356% 0.66776%

31-Jan-12 0.16359% 0.01638% 0.89109% 0.76396% 2.00386%

29-Feb-12 0.80042% 0.69425% 1.56961% 1.40649% 2.44308%

30-Mar-12 0.41400% 0.50310% 1.36584% 1.11706% 1.85372%

30-Apr-12 1.22627% 1.12781% 2.02700% 1.84571% 3.06423%

31-May-12 1.95518% 1.65929% 2.54917% 2.34813% 4.24085%

29-Jun-12 2.18425% 1.88170% 2.76916% 2.56572% 4.44807%

31-Jul-12 3.32862% 2.89916% 3.82660% 3.63446% 5.94449%

31-Aug-12 3.24036% 2.95094% 3.86790% 3.67087% 5.91118%

28-Sep-12 3.64143% 3.35615% 4.26415% 4.06900% 6.29174%

Table 1: Cumulative Portfolio performance, in terms of percentage returns, since inception. The Barclays Agg unhedged performance is added for reference


14

Difference in Cumulative Returns between Benchmark and Backtests since inception (%)

Figure 2: Difference in cumulative percentage returns between backtests and the benchmark performance, since inception

Rebalancing Date

15

Rebalancing Date Difference (%) in cumulative returns between benchmark and LCH.Clearnet Cleared Swaps backtest

Difference (%) in cumulative returns between benchmark and BCBS/IOSCO uncleared swaps backtest

Difference (%) in cumulative returns between benchmark and pre-2008 uncleared swaps backtest

Difference (%) in cumulative returns between benchmark and Eris Standards backtest

30-Nov-11 1.24427% 1.24659% 0.39963% 0.66834%

30-Dec-11 1.54908% 1.65855% 0.81142% 0.99131%

31-Jan-12 1.84028% 1.98748% 1.11277% 1.23990%

29-Feb-12 1.64265% 1.74883% 0.87347% 1.03659%

30-Mar-12 1.43972% 1.35062% 0.48788% 0.73666%

30-Apr-12 1.83796% 1.93643% 1.03723% 1.21852%

31-May-12 2.28567% 2.58155% 1.69168% 1.89272%

29-Jun-12 2.26382% 2.56637% 1.67891% 1.88235%

31-Jul-12 2.61587% 3.04533% 2.11788% 2.31003%

31-Aug-12 2.67082% 2.96025% 2.04329% 2.24031%

28-Sep-12 2.65032% 2.93559% 2.02759% 2.22275%

Table 2: Difference in cumulative percentage returns between backtests and the benchmark performance, since inception


16

Post-Dodd Frank Portfolio Drag since Inception (%)

Figure 3: Post Dodd-Frank Portfolio drag since inception (%)

Rebalancing Date

17

Rebalancing Date Drag (%) compared to pre-2008 backtest for LCH.Clearnet Cleared Swaps backtest

Drag (%) compared to pre-2008 backtest for Uncleared Swaps (BCBS/IOSCO) backtest

Drag (%) compared to pre-2008 backtest for Eris Swap-Futures backtest

30-Nov-11 0.84464% 0.84696% 0.26870%

30-Dec-11 0.73766% 0.84712% 0.17989%

31-Jan-12 0.72750% 0.87471% 0.12712%

29-Feb-12 0.76919% 0.87536% 0.16312%

30-Mar-12 0.95184% 0.86274% 0.24878%

30-Apr-12 0.80073% 0.89919% 0.18128%

31-May-12 0.59399% 0.88987% 0.20104%

29-Jun-12 0.58491% 0.88746% 0.20343%

31-Jul-12 0.49798% 0.92744% 0.19214%

31-Aug-12 0.62753% 0.91696% 0.19703%

28-Sep-12 0.62272% 0.90800% 0.19515%

Table 3: Post Dodd-Frank Portfolio drag since inception (%)

5.2 – Discussion of Results

Overall

The backtest results show that cumulative portfolio returns are highest when hedging is performed using uncleared swaps in a pre-2008 environment, and lowest when hedging is performed using uncleared swaps in a BCBS/IOSCO-recommended environment. These backtest results serve to show the significance of the impact of Dodd-Frank/BCBS legislation on clearing costs; the use of uncleared swaps has jumped from being the cheapest way to hedge to being the most expensive way to hedge.

This is due to differences in IM. IM costs are cheapest in the pre-2008 environment, and most expensive under the 2015 BCBS/IOSCO post-Dodd Frank guidelines. When IM costs are higher, there are fewer performing assets in the portfolio, and this manifests into lower portfolio returns.


18

Eris-Standards backtest vs. LCH-cleared swaps backtest

Of the two backtests for the cleared sets of hedging instruments, the Eris Standards result in a lower post-Dodd-Frank portfolio drag than LCH-cleared swaps. This is driven by IM requirements. The difference in returns between the LCH-cleared swaps and Eris swap-futures backtests reaches ~70bps at its peak, but the gap narrows down to around 40bps over the course of the backtests.

The causes of this narrowing can be attributed to the relative difference in the IM decrease that occurred from April-May 2012 for both the Eris Standards and LCH-cleared swaps backtests. Both backtests experienced a decrease in IM costs, but the decrease for the LCH-cleared swaps was more pronounced.

It should be noted that a small difference in alpha drag can be attributed to the basis between swaps and swap-futures. Because the fixed coupons and maturity dates for the Eris Standards are not flexible, the contracts don’t match the prevailing yield curves as closely as swaps. This means that, for the interest-rate environment in which this study was conducted, the Eris Standards were slightly more sensitive to yield curve movements than swaps, so the absolute VM for Eris Standards were slightly higher in either direction than the VM for swaps.

BCBS/IOSCO uncleared swaps backtest vs. LCH-cleared swaps backtest

The alpha drags for the LCH-cleared swaps and the BCBS/IOSCO uncleared swaps cross over each other twice during the course of the backtests. On the March month-end rebalancing date, the IM requirement is higher for LCH-cleared swaps than for BCBS/IOSCO uncleared swaps, but subsequent IM requirements for LCH are lower than those for BCBS/IOSCO.

The crossover between the two swaps backtests can be attributed to two competing effects. On one hand, the LCH IM is determined using a 7-day time horizon, but the BCBS/IOSCO IM is determined using a 10-day time horizon. IM costs tend to increase over longer time horizons for calculation. On the other hand, LCH IM (according to the pre-February 2013 model) uses worst-case-loss, whereas BCBS/IOSCO IM cuts off the distribution of losses at 99%. This tends to increase IM costs for LCH-cleared swaps. These simulations show that, for the historical time period considered for this study, the cut-off distribution of losses from 10-day market movements outweigh the most severe 7-day market movement. However, had this study been conducted in another historical time period, the results may have been different.

19The Cost of Clearing: A Buy-Side Investigation

6. Conclusion and Next Steps6.1 – ConclusionPost-Dodd-Frank, hedging costs increase due to tying up cash for IM. The drag on portfolio returns ranges from ~20bps for Eris Standards to ~62bps for LCH cleared swaps, and to ~91bps for bilateral OTC swaps. Based upon the results of our historical back tests, we can also conclude that the clearing costs for a typical hedge-portfolio are significantly lower for both types of centrally cleared hedges (i.e. swaps and swap-futures) than they are for uncleared-swap hedges in an environment recommended by BCBS/IOSCO. These results are driven primarily by the cost of IM. Once the post-Dodd-Frank regulations for uncleared derivatives take effect, using centrally cleared instruments will be the cheapest available option, and therefore we expect market participants to choose this option.

It is important to emphasize that one must consider various factors when selecting hedging-products. The cost savings due to differences in IM are just one factor driving overall clearing costs, and yet IM differences have received the widest attention by market participants. One must also consider the basis between swaps and swap-futures, due to the non-flexible fixed coupons and maturity dates of the Eris Standard contracts.

6.2 – Next StepsThis study could be significantly extended if we considered additional factors contributing to cost-drag in the backtests. We limited the costs of collateralizing a portfolio of derivatives to IM and VM requirements, but we did not consider several other significant effects, including:

• Dealer funding costs

o In the pre-2008 market environment dealers traded swaps with buy-side counterparties on one-way CSA agreements. This meant that dealers didn’t have a requirement to post collateral.

o For centrally-cleared swaps, and for swaps traded on two-way CSA agreements (which havebecome increasingly common since the financial crisis), dealers must now post collateral in the form of margin.

o This requirement ties up dealer capital, which could otherwise be invested in the returns ofperforming assets. Therefore, the requirement to post collateral represents a “funding cost” for the dealer, which would be passed onto their buy-side clients at the beginning of the deal.

• Clearing-house fees, including annual clearing fees, booking fees and maintenance fees.

• Broker fees that FCMs typically charge buy-side funds in order to act as their clearingintermediaries. This could also include default-fund contributions owed by the FCMs to the clearing houses. We can reasonably assume that default fund fees are passed from FCMs onto their clients.

20

In addition to considering dealer funding costs, clearing-house fees and broker fees, we could significantly extend our study in the following ways:

• Additional backtests. This includes:

o Running the backtests for other historical time periods. This would allow us to performa deeper investigation into the relationship between yield-curve environments and the performance of swap-futures compared to SwapClear cleared swaps.

o Running the backtests with different absolute notional amounts invested into our benchmarkportfolio, in order to measure the effects of scale on fees and transaction costs. Our study considered all costs as the same relative to the amount invested into the benchmark. However, in practice, the fees, transaction costs and IM and VM thresholds do not scale linearly with notional amounts invested into benchmark index and associated hedges. In addition, we did not consider the effects of concentration risk when purchasing hedging derivatives in our present study. When investigating the effects of scale, we could consider discretionary extensions of credit for clearing participants only just breaching threshold amounts.

o Running the back tests, assuming that our buy-side fund engages in different amounts ofleverage. This would allow us to perform an investigation into the relationship between alpha drag (compared to pre-2008 environment) and different leverage ratios.

• Collateral optimization. We could consider a more optimal way of attaining collateral than sellingoff slices of the benchmark index. In practice, the buying and selling of slices of the benchmark would incur transaction costs, which we did not consider in our original study. (For example, this could be funded through the periodic coupons received on the underlying bonds). In addition, the bonds themselves may be eligible as collateral, which would significantly reduce funding costs.

• Reducing over-hedging when rebalancing. We solved for the hedge-instrument notionals beforethe hedging trades took place. This method didn’t take into account the post-hedge oscillations of the total portfolio duration caused by the execution of the hedge instruments themselves (as funding the IM requires a reduction of the amount invested in physicals, which in turn reduces the total portfolio duration). As a result, the portfolio was typically over-hedged after rebalancing. We could seek to minimize oscillations due to over-hedging by solving for the correct notional after the hedge.

• Including collateral interest. Interest is paid in the case of received collateral, and received in thecase of posted collateral. Overnight interest is paid or received at the federal funds rate, assuming that the collateral is suitable enough.

• Additional hedging strategies. This could include a credit-exposure hedging strategy (using CDSCDX indices) or an inflation-exposure hedging strategy (using inflation swaps). This would allow us to include the costs of clearing credit and inflation derivatives into the backtests.


• Incorporating OIS discounting into the uncleared swaps in a BCBS/IOSCO environment backtest.

• Incorporating Price Alignment Interest (PAI) into the Eris swap-futures and LCH cleared swaps backtests.

• Incorporating daily recalculations and transfers IM and VM instead of monthly calculations andtransfers for all backtests.

6.3 – Special ThanksThis study would not have been possible without the help of our partners:

FINCAD

• We used the FINCAD F3 Excel analytics package to build an internal Excel H-VaR model in order tocalculate IM according to the BCBS/IOSCO guidelines.

Eris Exchange

• Eris Exchange provided us with historical contract properties for on-the-run, nearest-to-expiry 10yEris Standards contracts6.

• Eris Exchange also provided us with the IM percentages for the Eris Standard contracts on theportfolio rebalancing dates, based upon CME’s 5-day H-VaR margin calculator.

LCH.Clearnet SwapClear

• LCH provided us with their Excel SMART tool, which allowed us to calculate the IM for centrallycleared IR swaps in the LCH backtests.

Barclays

• Barclays provided us with the historical MVs and modified durations for the benchmark indextracked by our buy-side bond fund.

In addition, we’d like to thank the following individuals for reviewing our study and providing their input and expertise:

- Dr. Roland Stamm (Deutsche Pfandbriefbank AG).- Sol Steinberg (LCH.Clearnet).- Tony Webb (FINCAD).- Kevin Samborn (Sapient Global Markets).- Dave Depew (Sapient Global Markets).- Phil Matricardi (Sapient Global Markets).

6 Given that the Eris Standards market did not go live until December 2012, these were hypothetical contract properties, created synthetically from the Bloomberg yield curves according to no-arbitrage principles

22

A. AppendixAppendix I: Portfolio Results using Dollar Returns

Figure 4: Physicals portfolio performance

The above graph shows the growth in market value of the initial $9bn portfolio under the four collateralization regimes. The benchmark performance is included for comparison purposes; as expected for this time period, duration hedging in all four cases has resulted in decreased overall return and volatility. Because all scenarios had the same duration hedging target, the comparative costs of clearing/collateralization are visible in this graph as inhibiting portfolio growth.

Rebalancing Date


Rebalancing Date

MV ($m) for Physicals Portfolio Hedged using LCH.Clearnet Cleared Swaps

MV ($m) for Physicals Portfolio Hedged using Uncleared Swaps (BCBS/IOSCO)

MV ($m) for Physicals Portfolio Hedged using Uncleared Swaps (Pre-2008)

MV ($m) for Physicals Portfolio Hedged using Eris Swap-Futures

MV ($m) for Unhedged Benchmark Index Performance

31-Oct-11 8,891.65 8,900.77 8,980.86 8,948.13 9,000.00

30-Nov-11 8,872.02 8,871.81 8,948.04 8,923.85 8,984.00

30-Dec-11 8,920.68 8,910.83 8,987.07 8,970.88 9,060.10

31-Jan-12 9,014.72 9,001.47 9,080.20 9,068.76 9,180.35

29-Feb-12 9,072.04 9,062.48 9,141.26 9,126.58 9,219.88

30-Mar-12 9,037.26 9,045.28 9,122.93 9,100.54 9,166.83

30-Apr-12 9,110.36 9,101.50 9,182.43 9,166.11 9,275.78

31-May-12 9,175.97 9,149.34 9,229.43 9,211.33 9,381.68

29-Jun-12 9,196.58 9,169.35 9,249.22 9,230.92 9,400.33

31-Jul-12 9,299.58 9,260.92 9,344.39 9,327.10 9,535.00

31-Aug-12 9,291.63 9,265.58 9,348.11 9,330.38 9,532.01

28-Sep-12 9,327.73 9,302.05 9,383.77 9,366.21 9,566.26

Table 4: Portfolios performance

24

Appendix II: Delta Gamma Approximation MethodThe delta-gamma approximation method is used to calculate the IM for uncleared swaps with BCBS/IOSCO recommended margin guidelines. Details for this method are as follows:

• A LIBOR curve is constructed for a given portfolio rebalancing date.

• Zero rates from this LIBOR curve are extracted at 30 key maturities (between o/n and 15y).

• The swap in our portfolio is valued using an unshifted curve for the rebalancing date. The resultingvalue is known as the “central point” valuation.

• 30 new LIBOR curves are constructed for the same date. A new curve is created by shifting one ofthe 30 zero-rates upward one basis point.

• The swap in our portfolio is valued using each of the 30 new curves. The central point valuation issubtracted from the 30 new valuations, and the resulting P&Ls are the delta-sensitivities (or DV01s) of the swap to the zero rates at key maturities on the curve.

IM for uncleared swaps is a 10-day, 99% VaR calculation. The calculations of the 10-day historical returns for the portfolio swap use the LIBOR curve at time t vs. the LIBOR curve at time t-10.The change in yields at each point in the yield curve is multiplied by the DV01s calculated above to determine the 10-day return of the portfolio swap.

If there is more than one swap in the portfolio, then the 5-step method above is repeated for each swap.


Appendix III: Summary of AssumptionsThe following section is a summary of the assumptions used throughout the project, at various different stages.

Global Backtest Model

• The bond portfolio has zero tracking error, so that benchmark returns match the bond-portfolioreturns exactly.

• IM and VM deposits/withdrawals only take place on the monthly portfolio rebalancing dates; weassume that only considering monthly, rather than daily, IM & VM calls does not have a significant impact on the outcome of the study.

• Whenever IM or VM was required in the margin account, collateral was always available to meetthose calls.

• Because the model only calculates the VM monthly, for all swaps backtests, the realized netpositive cash flows (from the swap coupon payments) are not reinvested into physicals on the day in which they’re paid out; instead, they are reinvested on the next available rebalancing date. Conversely, whenever net-negative cash flows are paid out, the necessary VM account deposit is made on the next available rebalancing date.

• All swaps and swap-futures traded on the portfolio rebalancing dates had an underlying tenor of 10y.

• All swaps and swap-futures contracts are executed at the mid, and VM/IM is valued using curvesconstructed from mid-prices.

• The portfolio is assumed to be perfectly collateralized at all times, therefore we do not considerany mandatory CVA or funding costs.

• No fees were considered in our study. This includes both clearing house fees and fees charged bythe FCMs to the buy-side fund.

• We do not consider the effect of dealer funding-costs passed onto our fictitious buy-side firm, dueto post-Dodd-Frank margin requirements.

• We assume no minimum/maximum thresholds for IM and VM deposits and withdrawals—evensmall changes in calculated VM/IM amounts result in a cash transfer.

• We did not assume any effects of concentration risk in purchasing large notional amounts of IRswaps, large orders of swap-futures contracts and large pieces of the benchmark.

• The IR swaps and Eris swap-futures markets are assumed to be perfectly liquid.

• The Barclays Agg portfolio components are assumed to be perfectly liquid.

• No transaction costs are incurred when buying or selling slices of the benchmark index.

• No slippage occurs when executing IR swap or Eris swap-future trades on the portfoliorebalancing dates.

• No slippage occurs when buying or selling the Barclays Agg components.

26

Uncleared Swaps, Pre-2008 Backtest

• IM calculated as 1% of the total gross notional for the underlying swaps portfolio. We believe this isa percentage that broker-dealers may reasonably have set in a pre-2008 environment.

Eris Standard Swap-Futures Backtest

• To obtain approximate IM percentages for Eris Standards (in the absence of available 2-day SPANparameters), we performed the following steps:

o The raw IM percentages obtained from Eris Exchange were calculated using the CME H-VaRmodel for Eris Flexes, which use a 5-day time horizon.

o This percentage was then multiplied by √(2/5) to approximate the H-VaR returns under a 2-day timehorizon (which assumes that returns can be scaled by the square root of the time horizon).

o We made no further adjustments to the IM to account for the differences between the H-VaRmodel and the SPAN model, as we assumed that IM calculated under 2-day H-VaR would be reasonably close to IM calculated under 2-day SPAN.

• IM percentages were provided by Eris Exchange as IM per-swap-futures contract. We assumedthat overall IM for the swap-futures hedging portfolio could be calculated linearly as the sum of IMs for the individual swap-futures contracts.

• We considered overnight interest accrued on the IM (the Price Alignment Interest, or PAI) to benegligible, so we did not include it in our calculation of VM. (We did, however, include historical cash flows in the swap-futures VM calculations).

• Although IM is calculated using CME yield curves, we calculated VM using Bloomberg yield-curvedata and analytics, and assumed that there is no discrepancy between the two.


LCH.Clearnet SwapClear Cleared Swaps Backtest

• Although IM is calculated using LCH.Clearnet SwapClear yield curves, we calculated VM usingBloomberg yield-curve data and analytics, and assumed that there is no discrepancy between the two.

• We are assuming that our buy-side firm clears through an intermediary FCM, and is thereforesubject to an IM charge according to a 7-day time horizon.

• The SMART tool calculates IM based on a 5-day time horizon. We assumed this could be convertedinto a 7-day time horizon by multiplying the IM by √(7/5). This assumption is in line with LCH’s own PAIRS methodology.

• Because the model only calculates VM monthly, realized cash flows are accountedfor only on the rebalancing date. We therefore assume that the realized cash flows are invested into performing assets at the next available rebalancing date, rather than on the day that the cash flows are paid out.

Uncleared Swaps, BCBS/IOSCO Guidelines Backtest

• The calculations in the VaR model for IM were performed using LIBOR (rather than OIS)discounting.

• We used 5 years’ worth of historical simulations because:

o This is similar to the LCH IM calculation methodology.

o Using 5y worth of data includes the period of significant market stress around September/October 2008.

• We did not perform any filtering or scaling of the historical returns; we kept them in their raw state.

GLOBAL OFFICES

AmsterdamSapient Netherlands B.V.Damrak 701012 LM AmsterdamTel: +31 (0) 20 330 0011

BangaloreSalarpuria GR Tech Park6th Floor, “VAYU” Block#137, Bengaluru 560066KarnatakaIndiaTel: +91 (080) 410 47 000

Boston131 Dartmouth Street3rd FloorBoston, MA 02116Tel: +1 (617) 621 0200

Calgary888 3rd Street SWSuite 1000Calgary, Alberta T2P 5C5CanadaTel: +1 (403) 444 5574

Chicago30 West Monroe,12th floorChicago, IL 60603Tel: +1 (312) 458 1800

DelhiTowers D & E,DLF Cyber GreensDLF Phase IIISector 25-AGurgaon 122002HaryanaIndiaTel: +91 (124) 416 7000

DüsseldorfSpeditionstraße 2140221 DüsseldorfGermanyTel: +49 (0) 211 540 34 0

FrankfurtSkyper VillaTaunusanlage 160329 FrankfurtGermany+49 (0) 69 505 060 594

GenevaSapient Switzerland S.a.r.l.Succursale Genèvec/o Florence Thiébaud, avocaterue du Cendrier 151201 GenevaSwitzerlandTel: +41 (0) 58 206 06 00

HoustonHeritage Plaza1111 Bagby Street Suite 1950Houston, TX 77002Tel: +1 (713) 493 6880

LondonEden House8 Spital SquareLondon, E1 6DUUnited KingdomTel: + 44 (0) 207 786 4500

Los Angeles1601 Cloverfield Blvd.Suite 400 SouthSanta Monica, CA 90404Tel: +1 (310) 264 6900

MunichArnulfstraße 6080335 MünchenGermanyTel: +49 (0) 89 552 987 0

New York40 Fulton Street22nd FloorNew York, NY 10038Tel: +1 (212) 206 1005

Singapore158 Cecil Street, #03-01Singapore 069545Tel: +65 6671 4933

Toronto129 Spadina AvenueSuite 500Toronto, Ontario M5V 2L3CanadaTel: +1 (416) 645 1500

ZürichSapient Switzerland GmbHSeefeldstrasse 358008 ZurichSwitzerlandTel: +41 (58) 206 06 00

Download The Cost of Clearing: A Buy-Side Investigation - Sapient

Documents

Transcript of Download The Cost of Clearing: A Buy-Side Investigation - Sapient