MARGIN MOVES TO THE CENTER November 2014

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1 MARGIN MOVES TO THE CENTER November 2014 In collaboration with:

2 Mandatory clearing and the prospect of non-cleared swaps moving into a fullymargined, bilateral environment are starting to weigh heavily on bank P&Ls and available capital. With efforts to find business and operational efficiencies a major focus for all financial institutions, the ability to forecast, understand, and optimize margin numbers has never been as important or as organizationally far-reaching as it is today. The impact of margin calculations spans a wide swathe of functions, including front office, risk management, middle office and collateral management / operations. Each of these areas has specific sensitivities for precise margining, ranging from P&L management to stress testing and cost allocation (Figure 1). Figure 1. Impact of margining and use cases by job function. Central Market Risk Management l Stress testing l Improving understanding of risk Front Office l Full trading cost incorporation l Cheapest-to-clear venue l Margin optimisation Initial Margin Middle Office l Cost allocation to trades, books, desks l Funding costs for margin Collateral Management / Operations l Margin call validation l Client Clearing & Prime Services There are considerable differences in the way firms manage margin calculations. With a diversity of technology infrastructures supporting different business activities, the challenge for the industry is how to incorporate margin calculations into the current setup without having to overhaul existing systems yet in time to comply with regulatory deadlines. Regardless of the operational complexity, the number of situations that margining plays a role in is compelling institutions to focus on the need for accurate margin calculations particularly when it comes to CCP margining. In the following sections, we ll cover use cases of CCP initial margin for different areas of a typical financial institution in more detail. 1

3 FRONT OFFICE Incorporating initial margin into P&L management is becoming increasingly important. With profit margins being squeezed across the capital markets, there is a focus within each bank to fully understand the total cost of a trade, to ensure that any business conducted is profitable to the firm. Various components of an OTC trade can contribute to its cost, including: l Market pricing l Initial Margin (IM) l Variation Margin (VM - offset by Price Alignment Interest in many cases) l Default Fund contributions, either directly for a Member, or indirectly to a Client as a re-charge l Capital held by a Clearing Broker (CB) or Futures Commission Merchant (FCM) l Processing fees at the Central Counterparty (CCP) l Processing fees at the CB or FCM Measuring and including margin cost at execution better aligns the post-trade cost with the lifetime servicing costs of the trade. In a client clearing context, this provides as much transparency as possible to end-clients, while enabling sell-side firms to understand the full cost of hedge trades which should be included in the clients cost-per-trade. While margin and default fund contributions on a cleared OTC derivatives trade vary by CCP, direct members have partial or full access to the underlying calculation model. These sell-side firms can then replicate margin in their systems to generate exact forecasts and estimates. Non-members may not have the same tools, and are often forced to rely on their CB or FCM for calculations. A client may then be subject to a wide range of fees due to the economics of their CB or FCM. Cheapest-to-Clear Venue Broad-based efforts to reduce margin requirements have led participants to measure the impact of each new trade and, where possible, route them to the cheapest venue. Banks must account for all CCP fees, capital charges, FCM or CB charges and funding costs. Several approaches to routing cleared trades are in use. 1. Pre-determine which CB/FCM and CCP will be the recipient of their clearing business, based on up-front analyses of costs and services available. This simplistic approach to pre-determine the venue picks the CCP with the largest cleared volume for each asset class and always delivers trades to that CCP. However, given the proliferation of CCPs in the Interest Rate market, and the development of cross-margin and hybrid swap futures products, a more dynamic approach could yield significant cost savings. 2

4 2. Maintain a live simulation of a client portfolio in a model per CCP. When a new trade is about to be cleared, perform an incremental initial margin calculation to understand how this new trade will affect IM at each CCP. This model seeks to gradually minimize IM at each CCP for the client and the bank (assuming that all other costs are equal, and that all counterparties are available at all CCPs). It can also help assess the relative collateral requirements across clearing houses and allow clearing members to determine whether the client has posted sufficient collateral for the trade. 3. Expose a suite of margin calculators per CCP to enable clients to perform off-line analysis of what if scenarios. In many cases, the service providers have struck agreements with CCPs to model their IM calculations, although sometimes these are as near as possible rather than a direct replication from the CCP. Finally, liquidity itself may be determined by CCP, where dealers price off different curves based on where the trade would be cleared, so that the costs for the dealer are built into the pricing. Margin Optimization By extracting the profit & loss generated by each individual trade to the scenario selected (or in some cases multiple scenarios where an Expected Shortfall approach is taken), and looking at their original ownership within a bank, it is possible to consider options to reduce loss-making trades and encourage profitable business, by considering: l A comparison between the termination fees on a trade and the lifetime IM funding cost l The fees for putting on an off-market hedge to reduce IM l The cost of executing portfolio hedge trades to reduce IM Separately, an emerging business focus is cross-margining at CCPs. Both CME and Eurex now let clients reduce the IM on OTC trades by offsetting them with positions from a bank s futures and options portfolio within the same CCP. This has a number of effects, some beneficial but some not so obvious: l IM reduction on a daily basis, provided suitable futures and options positions exist l IM volatility as the CCP dynamically selects futures and options each day l Removal of futures and options positions for IM purposes from the processing vertical silo of the traditional ETD departments l Inclusion of ETD products into the default management process including the auction process l A more complex challenge to replicate the CCP IM calculation, needing to include the dynamically allocated ETD products These activities are a parallel to the cheapest to clear venue decision point. 3

5 MIDDLE OFFICE AND TREASURY The middle office needs the ability to accurately forecast margin calls and attribute IM costs back to the businesses that generated them. Who pays for IM? Once a trade is cleared, firms must be able to attribute the costs back to the individuals, desks or businesses that generated them. This enables firms to better manage and control budgets, risk and performance. One way to address cost attribution is a top-down split based on the size of each portfolio using notional, DV01 or other measures. However, this legacy approach does not account for modern CCP IM methodologies that are sensitive to extreme event analysis (either expected shortfall, VaR with an extremely high confidence interval, or worst case loss). An approach based on total notional or DV01 is unlikely to determine the true margin impact of trades under such methodologies. A better approach is to decompose the results of a CCP margin calculation, and drive the IM figure back to the organizational structure required. For instance, when your software completes the VaR calculation, it is apparent which scenario(s) caused the final IM result. By extracting the profit or loss contribution of each individual trade to that final scenario, and then grouping those trades by trade, desk, book or business, firms can calculate each subgroup s absolute contribution to the margin. By adding all absolute contributions by every subgroup, margin cost can be allocated by the absolute contribution. Each subgroup is getting an absolute contribution allocated at a lower rate due to both cross-hedging, and the fact that the scenario which created the loss is no worse than the scenario which would have been used just for that group. Firms can also rerun the margin calculation for that subgroup only, in a replication environment, to see the actual benefits of cross-margining. Funding Costs Due to regulations in the US and EU, CCPs must recalculate IM throughout each trading day. This means that the effect of new trades can cause an intraday margin call unexpectedly, and also alter the IM number until the CCP closes its books each day. Once a CCP closes for the day, they apply their IM model, revalue collateral assets and issue a call the following morning for any new IM amount, beyond what has already been met by the bank. Banks that can predict the following day s IM amount and begin deciding how to meet the IM call the following day have a cost advantage, compared to competitors that are blind to IM calls until they arrive each morning. This proactive approach to margin calls allows banks to avoid overpaying for funding at short notice, or finding securities that can cover the liability. 4

6 Margin call forecasting benefits all aspects of the cleared portfolio, including reduced costs attributed to traders, lower over-funding IM liabilities, and optimized capital usage. The same point applies to intraday margin calls some CCPs monitor the effect of new trade activity on VM and IM, and if needed will call for additional assets at certain points during the day. Should markets experience volatility, and new trades get cleared, an unexpected call for significant cash amounts will cause a cost hit to a bank s P&L. One approach to avoiding an intraday call is to over-fund the IM account, but this almost guarantees increases in IM funding costs. Banks with the right tools to replicate the CCP VM and IM calculations, plus a real-time market data feed, are able to predict intraday calls, and give themselves an additional time window to acquire funding. Alternatively, this modeling can be executed overnight using intraday stress scenarios, to minimize over-funding, and therefore cost. COLLATERAL MANAGEMENT / OPERATIONS The use case for initial margin on the operational side of collateral management focuses on ensuring the accuracy of margin calls to the institution. Margin Call Validation In the exchange-traded derivatives market, commercial software platforms have replicated the margin calculations for many years. This has given clearing members and their clients confidence in the accuracy of the figures produced by the CCP. In the OTC world, margin calculations are significantly more complicated, requiring large amounts of historical market data and configuration of the VaR model to achieve a result. On top of the basic historical VaR calculation, CCPs can add their own multipliers to the final number to account for concentration risk, liquidity risk and credit rating, which all need to be understood to properly replicate their calculations. Given this increased complexity, and the need for many firms to explain costs back to managers and investors, firms have implemented dynamic technologies to replicate the margin calculations at a CCP within their own environment. This enables them to compare numbers generated by the FCM or Clearing Broker with those from the CCP potentially resulting in considerable cost savings. 5

7 CLIENT CLEARING / PRIME SERVICES The modern Client Clearing business shares many of the use cases of the other business functions referred to in this article. Some firms have chosen to extend their services to clients by offering access to CCPs on their behalf in the traditional clearing model. Once a firm commits to provide client clearing, a swathe of new functions are required to manage the risk of being an intermediary to client trades. 1 To offer client clearing a bank must have the ability to: l Measure the Credit and Market risk of taking on new client trades l Set and monitor limits for each client between the client and all the CCPs to which the bank provides access l Make these decisions very quickly, as the CFTC rule 1.74 requires firms to achieve clearing certainty as soon as technologically possible l Model and optimize client IM on their behalf l Provide a cheapest-to-clear venue decision support approach l Model and predict client IM flows, for the same reasons mentioned elsewhere, to manage and minimize cost CENTRAL MARKET RISK MANAGEMENT Central risk management must be able to demonstrate a full understanding of risks - in normal and stressed environments - to management and regulators. Improving the Understanding of Risk (as viewed by CCPs) Today s banks must be able to validate the IM call on a daily basis, and compartmentalize the IM calculation to understand the trades and positions which are at the root of the VaR calculation, including: l Expected losses at all levels (trade, currency, portfolio) per scenario, enabling users to understand the contribution of the underlying trades to a margin number l Sensitivities of the portfolio to changes in the market, highlighting areas of concentration and over-exposure With this information, risk managers can create heat-maps of risk within the portfolios as viewed by the different CCPs, and make informed business decisions. The capital allocated to each business unit or desk relates directly to the CCP IM requirements, which should be understood and provide a feedback loop to optimize IM, reduce costs and capital, and align a bank s P&L with risk limits and strategic goals. 1 Note: There are distinct models for offering Client Clearing; the US Futures Commission Merchant model where the bank acts as an agent for the client, and everywhere else in the world where the bank takes on a back-to-back trade between the client and the CCP. 6

8 Margin Call Stress Testing Banks risk divisions have a series of common scenarios that are integral to their stress testing processes. To ensure consistency, risk teams wish to apply the same scenarios to CCP IM requirements to understand potential future requirements. Default Fund Stress Testing An additional area of focus by banks is default fund contribution analysis. This is a measure of the risk to all clearing members of a number of the largest clearing members defaulting simultaneously. Under a stress scenario this can pose significant risk to the bank as a whole. As a result, many banks and their regulators are starting to include some form of default fund analysis as part of their stress testing efforts. Currently this can only be done via crude heuristics, as the core calculations to determine default fund impacts require data too sensitive to be extracted from clearing houses. In the future, it should be possible for the clearing houses or third-party services to allow more fundamental and accurate simulations of default fund impact to be performed in conjunction with a bank s core stress testing activities. 7

9 CONCLUSION In this article, we ve discussed a number of different use cases for CCP margin calculations across the different departments within a large financial institution. The challenges of accurate margin measurement are as complex as they are important. The range of business units and the diversity of technology frameworks being used at major institutions magnify the scale of the task at hand. The importance of these calculations is only going to increase as profit margins are squeezed further and efficient use of capital remains a top priority. In this environment, rebuilding the same functionality in different business units is clearly not smart. To address the inefficiencies of a fragmented and duplicative approach, it is important that an enterprise-wide view is taken. This entails greater levels of communication than are currently seen at many firms but the rewards for getting it right are significant. 8

10 ABOUT OPENGAMMA EUROPE: OpenGamma 185 Park Street London SE1 9BL United Kingdom NORTH AMERICA: OpenGamma 125 Park Avenue 25th Floor, Suite 2525 New York, NY United States of America OpenGamma helps financial services firms evaluate, understand, and manage market risk in an open, transparent manner. The OpenGamma Platform enables firms to optimize their businesses in the evolving OTC markets, improving capital efficiency and balance sheet management. It provides tools for multi-ccp margin calculations, whatif analysis and stress testing, and real-time, cross-asset risk and trading analytics across customized risk scenarios and industry-standard metrics. Used by both buy-side and sell-side firms, exchanges, CCPs, and other segments of the OTC derivatives market structure, OpenGamma brings a new standard of transparency to the industry, enabling users to gain more insight into their underlying risk exposures, better assess the true costs of trading, and respond more rapidly to the ever-evolving regulatory landscape. Backed by Accel Partners, FirstMark Capital, ICAP plc and Euclid Opportunities, OpenGamma is headquartered in London with an office in New York. ABOUT THE OTC SPACE The OTC Space provides high quality insight into the Capital Markets from subject matter experts. The site provides the latest News, such as announcements, decisions, regulations, reactions and day by day commentary on the market. It also provides analysis and articles, original writing seeking to demystify, explain and provide understanding of the market and education on how the market works, the mechanics, infrastructure, products, pricing and processes. The OTC Space is available on-line and via its magazine Rocket OpenGamma Limited. All rights reserved. This document is licensed to the public under a Creative Commons Attribution Non Commercial 3.0 Unported License ( Attribution under the license should be to OpenGamma. This document is for informational purposes only, and is provided as is. OpenGamma declines all responsibility of any errors and any loss or damage resulting from use of the contents of this document. User assumes the full risk of using this document. For more information, please see the text of the license ( OpenGamma Limited is a company registered in England and Wales with company number Registered office: 185 Park Street, London SE1 9BL, United Kingdom. 9