THE 7TH ANNUAL INITIAL MARGIN & XVA CONFERENCE 21ST - 23RD MARCH 2018

Transcription

1 GRAND CONNAUGHT ROOMS, LONDON THE 7TH ANNUAL INITIAL MARGIN & XVA CONFERENCE 21ST - 23RD MARCH 2018 PRESENTERS Sarah B Tremel: Global Head of Analytics, Global Valuation Group, HSBC Bank Youssef Elouerkhaoui: Managing Director, Global Head of Credit Quant Analysis, Citigroup Nnamdi Okaeme: Director - Risk and Capital, International Swaps and Derivatives Association, Inc. (ISDA) Matthias Arnsdorf: Managing Director & Head Of Counterparty Credit Risk Modeling Group, JP Morgan Chase Michael Pykhtin: Manager, Quantitative Risk, U.S. Federal Reserve Board Damiano Brigo: Chair in Mathematical Finance and Stochastic Analysis, Imperial College London, Dept. of Mathematics Mats Kjaer: Head of Quant XVA Analytics, Bloomberg LP Jon Gregory: Independent xva Expert Pedro Gurrola-Perez: Senior Technical Specialist, Bank of England Massimo Morini: Head of Interest Rate and Credit Models, Gruppo Intesa Sanpaolo Christian Fries: Head of Model Development, DZ Bank Andrew Green: Managing Director, XVA Lead Quant, Scotiabank Ignacio Ruiz: Founder & CEO, MoCaX Intelligence Alexey Erekhinsky: XVA Modeller, Quantitative Strategies, Credit Suisse Chris Kenyon: Head of XVA Quant Modelling FOS-Quant Modelling, MUFG Securities EMEA Dong Qu: Global Head of Quantitative Product Group, UniCredit Vladimir Chorniy: Senior Technical Lead, BNP Paribas Gilles Artaud: Market and Counterparty Risk, Credit Agricole-CIB Vladimir Chorniy: Senior Technical Lead, BNP Paribas Kathrin Glau: Chair of Financial Mathematics, Technical University of Munich Lucia Cipolina Kun: VP, Bank of America Andrey Chirikhin PhD, MBA: Founder and CEO, Quantitative Recipes RECEIVE A 150 DISCOUNT WHEN YOU REGISTER TO THE MAIN CONFERENCE + WORKSHOP SPECIAL OFFER: WHEN 2 COLLEAGUES ATTEND THE 3RD GOES FREE! SPONSORS

2 CONFERENCE OVERVIEW LOCATION: Grand Connaught Rooms Great Queen Street, London, WC2B 5DA Tel: +44 (0) Website: WEDNESDAY 21ST MARCH: PRE-CONFERENCE WORKSHOP DAY XVA & Initial Margin in Theory and Practice by Andrew Green: XVA Lead Quant, Scotiabank THURSDAY 22ND MARCH: MAIN CONFERENCE, DAY ONE XVA, MVA & AAD Stream Initial Margin & SIMM Stream FRIDAY 23RD MARCH: MAIN CONFERENCE, DAY TWO XVA, MVA & AAD Stream Initial Margin & SIMM Stream CONFERENCE BOOKINGS: DISCOUNT STRUCTURE: Super Early Bird Discount: 25% until 9th February Early Bird Discount: 10% until 2nd March Main Conference + Workshop ( 150 Discount) SPECIAL OFFER: When 2 colleagues attend the 3rd goes free! 70% Academic Discount (FULL-TIME Students Only) CPD CERTIFICATION You will be able to receive up to 19.5 CPD points (19 hours and 15 minutes of structured CPD) for attending this event. The CPD Certification Service was established in 1996 as the independent CPD accreditation institution operating across industry sectors to complement the CPD policies of professional and academic bodies. The CPD Certification Service provides recognised independent CPD accreditation compatible with global CPD principles. IMPORTANT NOTES: Conference presentation files on USB memory sticks will be provided on arrival. The conference files will also be made available for download via a password protected website before the event. Please print out each presentation if you wish to have hard copies before the conference and bring them with you. Also, Wi-Fi access will be available at the venue to view presentations on laptops and mobile devices.

3 PRE-CONFERENCE WORKSHOP DAY WEDNESDAY 21ST MARCH XVA & INITIAL MARGIN IN THEORY AND PRACTICE BY ANDREW GREEN: XVA LEAD QUANT, SCOTIABANK DAY SCHEDULE: 09:00 17:30 BREAK: 10:30 10:45 / LUNCH: 12:30 13:30 / BREAK: 15:15 15:30 Foundations: CVA & DVA CVA & DVA by Replication CVA on Liquid & Illiquid Counterparties Credit Mitigants FVA FVA by Replication FVA & DVA (overlaps) FVA in pricing and accounting Exposure Modelling Generating expected exposures via Monte Carlo Choice of Monte Carlo dynamics Choice of Trade Valuation models XVA Sensitivities Sensitivities, Jacobians and Hessians Finite Difference Approximation Pathwise Derivatives Algorithmic Differentiation: Tangent mode and Adjoint mode XVA & Machine Learning Existing and potential applications of machine learning in XVA FRTB-CVA Introducing the final FRTB-CVA Proprosals Implications for XVA management Initial Margin & MVA The rise of Initial Margin Impact on XVA MVA by Replication MVA for VaR-type IM (CCPs) MVA for SIMM-IM KVA What is Capital? KVA by Replication KVA vs Hurdle Rates Which measure? The Cost of Capital Tutor Biography Andrew Green: Managing Director and XVA Lead Quant, Scotiabank Andrew Green is a Managing Director and lead XVA Quant at Scotiabank in London. Prior to joining Scotiabank, Andrew held roles as a quantitative analysis in several different banks in London. He is the author of XVA: Credit, Funding and Capital Valuation Adjustments, published by Wiley.

4 MAIN CONFERENCE DAY ONE THURSDAY 22ND MARCH 08:30 REGISTRATION AND MORNING WELCOME COFFEE 08:30 09:00 REGISTRATION AND MORNING 09:00 09:45 WELCOME COFFEE KEYNOTE SPEECH: USAGE OF MACHINE LEARNING IN FINANCE by Sarah B Tremel: Global Head of Analytics, Global Valuation Group, HSBC Bank What is Machine Learning Current usage in Finance, e.g. algo trading, fraud, etc Other possible applications in the future How to implement these technics 09:45 10:30 ISDA SIMM: EVIDENCED BASED APPROACH TO GOVERNANCE AND DEVELOPMENT Presenter: Nnamdi Okaeme: Director - Risk and Capital, International Swaps and Derivatives Association, Inc. (ISDA) 10:30 11:00 MORNING BREAK AND NETWORKING OPPORTUNITIES 11:00-11:45 MVA USING MACHINE LEARNING TECHNIQUES Initial Margin: why and what? IM Impacts on pricing (on different valuation adjustments Brute force computations; more elaborate techniques: AAD, American Monte Carlo How can Machine Learning help? 11:00-11:45 COUNTERPARTY LOSS MODELLING FOR CCAR Addressing incremental default risk for the trading book and counterparty risk Presenter: Matthias Arnsdorf: Managing Director & Head Of Counterparty Credit Risk Modeling Group, JP Morgan Chase Presenter: Gilles Artaud: Market and Counterparty Risk, Credit Agricole-CIB

5 MAIN CONFERENCE DAY ONE THURSDAY 22ND MARCH 11:45-12:30 DYNAMIC IM AND XVAS VIA CHEBYSHEV SPECTRAL DECOMPOSITION The power of Chebyshev MoCaX as a Smart interpolation scheme Selection of interpolating points and functions Chebyshev nodes Chebyshev polynomials in the context of Risk Calculations Theoretical basis: three fundamental theorems Example: Parametric Chebyshev interpolation for Risk Calculations Practical cases studies: CVA, CVA on exotics, Accurate MVA, Ultra-fast XVA sensitivities Commercial benefits: reduction of hardware costs, effective computation of risk metrics, hedging regulatory risk Generic AAD for any pricer via Chebyshev Decomposition 11:45-12:30 INITIAL MARGIN SIMULATION AND OPTIMIZATION AcadiaSoft, the global leader in initial margin (IM) services, will provide observations from the Phase 1 and Phase 2 ISDA SIMMTM adoptions, including practical considerations and usage statistics. Additionally, Quaternion, AcadiaSoft s partner in the development of a range of IM-related services, will share recent research they have conducted on simulating future SIMMTM and computing Margin Value Adjustment (MVA) using various methodologies. Presenters: Fred Dassori: Director of Risk Business and Corporate Development, AcadiaSoft & Roland Lichters: Managing Director, Quaternion Risk Management Ltd. Presenter: Ignacio Ruiz: Founder & CEO, MoCaX Intelligence 12:30 13:30 LUNCH 12:30 13:30 LUNCH 13:30 14:15 ACCELERATED MVA IN THE PROBABILITY MATRIX METHOD Introduction to the Probability Matrix Method Simulating IM using full SIMM and CCP formulas Practical examples and benchmarks Live demo Presenter: Martin Engblom: Co-CEO tricalculate, TriOptima, an NEX Group Company 13:30 14:15 DISCRETE PORTFOLIO OPTIMISATION WITH APPLICATIONS IN CCP MARGIN, FUNDING, AND REGULATORY CAPITAL Optimal resource allocation often has competing goals: CCP margin vs balance sheet Partitioning of trades between entities as portfolio optimisation problem Genetic algorithms for discrete optimisation (e.g. simulated annealing, bees algorithm) Computational issues: parallelisation, non-linear objectives Similarities and differences to machine learning Presenter: Alexey Erekhinsky: XVA Modeller, Quantitative Strategies, Credit Suisse

6 MAIN CONFERENCE DAY ONE THURSDAY 22ND MARCH 14:15 15:00 UNCERTAINTY QUANTIFICATION FOR XVA APPLICATIONS Joint work with Gersende Fort, Emmanuel Gobet, and Uladzislau Stazhynski Stochastic Approximation (SA) Method and ApplicationsUncertainty Quantification for SA Limits The USA Algorithm Numerical Study XVA Applications Presenter: Stéphane Crépey: Professor, LaMME-Univ Evry-CNRS-Université Paris-Saclay, Dept. of Mathematics 14:15 15:00 EFFICIENT CVA CAPITAL FOR COLLATERALISED COUNTERPARTIES Short summary of new CVA Capital rules Challenges of collateralised CVA with Initial Margin Forward Initial Margin Settlement risk & dynamic dates CVA sensitivities Finite difference and AAD Case study for SA-CVA sensitivities Presenter: Jonathan Berryman: Senior Vice President Risk Strategy, FIS 15:00 15:30 AFTERNOON BREAK AND NETWORKING OPPORTUNITIES 15:00 15:30 AFTERNOON BREAK AND NETWORKING OPPORTUNITIES 15:30 16:15 REVISITING KVA Examine the choice of measure: risk-neutral vs. real world Explore the relationship between FVA, KVA and debt and equity nancing Relate KVA to corporate finance models Presenter: Andrew Green: Managing Director and XVA Lead Quant, Scotiabank 15:30 16:15 THE REVISED BASEL CVA FRAMEWORK The need to revise the framework The consultative paper The industry response The final rule Presenter: Michael Pykhtin: Manager, Quantitative Risk, U.S. Federal Reserve Board 16:15 17:00 KVA FROM THE BEGINNING ABSTRACT We use a single period structural model of a dealer balance sheet to study the impact of regulatory capital requirements on the marginal fair value and shareholder indifference price of a new derivative. As expected the former does not change. The latter is reduced by a capital valuation adjustment, which depends on the nancing method used by the dealer. Finally we show that if the dealer hedges the derivative, then the indifference price is related to the cost of setting up the hedge. 16:15 17:00 METHODOLOGIES FOR FORWARD INITIAL MARGIN MODELLING Capital Benefits of Modelling Dynamic IM Modelling options for Cleared and Uncleared Trades Dynamic IM and MVA Dynamic IM backtesting Presenter: Lucia Cipolina Kun: VP, Bank of America Presenter: Mats Kjaer: Head of Quant XVA Analytics, Bloomberg LP

7 MAIN CONFERENCE DAY ONE THURSDAY 22ND MARCH 17:00 18:00 PANEL MODERATOR: Vladimir Chorniy: Senior Technical Lead, BNP Paribas PANELLISTS: Dong Qu: Global Head of Quantitative Product Group, UniCredit Massimo Morini: Head of Interest Rate and Credit Models, Gruppo Intesa Sanpaolo Ignacio Ruiz: Founder & CEO, MoCaX Intelligence Andrew Green: Managing Director and XVA Lead Quant, Scotiabank Mats Kjaer: Head of Quant XVA Analytics, Bloomberg LP TOPICS: MVA, INTIAL MARGIN & SIMM: Initial Margin, a push for more model standardization? Good or bad? How do you interpret the regulatory requirements to validate and monitor SIMM, and how would a firm best go about meeting those requirements? SIMM relies on counterparts calculating their own sensitivities. Do the panelists foresee that causing any problems meeting requirements or additional costs? Discuss Implementing SIMM for Non Cleared Initial Margin Rules Explore the interaction between MVA and XVAs: What does MVA mean for XVA overall? Can you simplify the valuation adjustments? Understand the impacts of initial margin, bi-lateral initial margin and MVA on business models Is it possible to ensure transparency of derivative pricing calculation to reduce disputes XVA & MACHINE LEARNING Discuss the existing and potential applications of machine learning in XVA DISCUSS THE IMPACT OF FRTB ON XVA S: How will the latest proposed regulations impact CVA calculations Review what are the most important factors to take into account when calculating the new CVA Calculating & Implementing FRTB CVA. How will it affect banks internal modelling for counterparty risk and risk management?

8 MAIN CONFERENCE DAY TWO FRIDAY 23RD MARCH 08:30 REGISTRATION AND MORNING WELCOME COFFEE 09:00 09:45 KEYNOTE SPEECH: SIMM IMPACT ON CREDIT XVA by Youssef Elouerkhaoui: Managing Director, Global Head of Credit Quant Analysis, Citigroup Motivation: Mandatory OTC Bilateral Margining Master Pricing Equation with Credit, Funding and IM SIMM, FRTB and AAD Conditional Expectations in the Enlarged Filtration Pre and Post Default Forward Exposure Profiles with SIMM Numerical Implementation Applications 09:45 10:30 BACK TO CVA TWO CURRENT ISSUES Loss given default Impact of different LGD assumptions Structural seniority and waterfall priority Entry price and exit price Wrong-way risk (WWR) WWR in cross currency swaps New evidence from the Quanto CDS market on Japanense names Implied jump sizes across sector and rating Evidence from the FX options market Presenter: Jon Gregory: Independent xva Expert 10:30 11:00 MORNING BREAK AND NETWORKING OPPORTUNITIES

9 MAIN CONFERENCE DAY TWO FRIDAY 23RD MARCH 11:00-12:30 STOCHASTIC AUTOMATIC DIFFERENTIATION: AAD FOR MONTE-CARLO SIMULATION AND APPLICATIONS TO MVA Part 1: Stochastic Automatic Differentiation: AAD for Monte-Carlo Simulation Automatic Differentiation - Introduction and Review Forward Automatic Differentiation Backward Automatic Differentiation Stochastic Automatic Differentiation - AD for Monte- Carlo Simulations Pathwise Operators Expectation Operator Conditional Expectation Operator Indicator Function Application (I): Automatic Differentiation of Bermudan options, XVA, etc. Example: Bermudan digital option Differentiation of the Exercise Boundary Memory Efficient Tapeless Implementation Immutable Objects Stochastic Operators Implementation AAD with 40 lines of code Bermudan AAD with 5 lines of additional code 11:00-12:30 EFFICIENT INITIAL MARGIN The Initial Margin is an amount of collateral that CCPs and Regulators require dealers to post beside Variation Margin. Computing the funding cost associated to Initial Margin requirements, at times called MVA (Margin Value Adjustment), presents both conceptual and computational challenges. Here we propose a method that, di erently from other proposals in the literature, does not involve nested monte carlo simulations under di erent probability measures, but only risk-adjusted simulation without approximations. Since in some cases this method is computationally intensive, in the next we show how to achieve computational e ciency by exploiting mathematical inequalities for skipping lenghty calculations without affecting final results. We conclude by showing some numerical analysis of the computational performances and some empirical verication of the soundness of the outcomes. Presenter: Massimo Morini: Head of Interest Rate and Credit Models, Gruppo Intesa Sanpaolo Part 2: Exact and Fast MVA (with or without AAD) Fast AAD Forward Sensitivities (aka Future Sensitivities) 5 Million Sensitivities in 10 Seconds Future Sensitivities: Forward Differentiation versus Backward Differentiation Application (II): Fast and Efficient ISDA-SIMM MVA ISDA-SIMM MVA for Swaps, Swaptions and Bermudans Melting Sensitivities: Fast Forward IM Approximations (with or without AAD) The Computationally Expensive Parts in MVA Calculations Transformation from Model Sensitivities to Market Rate Sensitivities A simple Replication Argument for MVA Approximations MVA for CCPs Presenter: Christian Fries: Head of Model Development, DZ Bank 12:30 13:30 LUNCH 12:30 13:30 LUNCH

10 MAIN CONFERENCE DAY TWO FRIDAY 23RD MARCH 13:30 14:15 CHEBYSHEV INTERPOLATION FOR PARAMETRIC OPTION PRICING Model calibration requires fast and accurate numerical methods. In the current paradigm, semi-closed pricing formulas for liquid options are seen as a prerequisite for modelling financial asset evolution. Thus attention is restricted to stochastic processes that are simple enough to allow for straightforward expressions of the pricing formulas. This obviously imposes a severe modelling restriction. However, rising demands to include more realistic features, for instance stylized facts on asymptotics of the implied volatility surface, compel us to consider a wider class of processes and hence more complex models. We therefore propose numerical techniques to reduce the computational complexity of the resulting pricing tasks. In this talk we focus on interpolation of option prices in the parameter space. Both the theoretic and experimental results show highly promising gains in efficiency. As one specific application we derive an efficient interpolation of the implied volatility. To present an approach with a wide range of applications, we investigate the combination of Monte Carlo simulation and interpolation in the parameter space. 13:30 14:15 MANAGING MARKET LIQUIDITY RISK IN CCPS CCPs often manage market liquidity (or concentration) risk by requiring members to post additional collateral to their initial margin in the form of concentration-add-ons Concentration add-ons are usually determine by attempting to estimate the cost of liquidating a position or assuming a su ciently extended margin period of risk during which liquidation costs would be minimal The above two approaches are not always equivalent CCPs generally face data constraints in calibrating their concentration add-ons The CCP default waterfall should account for cases of extreme but plausible market illiquidity Presenter: Pedro Gurrola-Perez: Senior Technical Specialist, Bank of England [1] Chebyshev Interpolation for Parametric Option Pricing, M. Gaß, K. Glau, M. Mahlstedt and M. Mair (2016), [2] The Chebyshev method for the implied volatility, K. Glau, P. Herold, D. B. Madan, C. Pötz (2017), Presenter: Kathrin Glau: Chair of Financial Mathematics, Technical University of Munich

11 MAIN CONFERENCE DAY TWO FRIDAY 23RD MARCH 14:15-15:00 THE PRICING OF XVA AND STOCHASTIC CORPORATE LIABILITIES Presenter: Andrey Chirikhin PhD, MBA: Founder and CEO, Quantitative Recipes 14:15-15:00 BEHAVIOURAL XVA Normal hedging behaviour changes client XVA prices by breaking assumption of counterparty independence Whilst clients are non-defaulted hedges with defaulting counterparties will be replaced, whereas on client default hedges will be removed We provide mathematical pricing framework and numerical examples Significant effect on MVA with CCPs when hedging client trades; variable effects on XVA from multiple non-ccp hedge defaults Without taking behaviour into account client XVA prices can be materially incorrect Presenter: Chris Kenyon: Head of XVA Quant Modelling FOS-Quant Modelling, MUFG Securities EMEA plc AFTERNOON BREAK AND NETWORKING OPPORTUNITIES CLOSING PRESENTATION: COST OF CAPITAL & VALUATION: A TARGET PERFORMANCE APPROACH by Damiano Brigo: Chair in Mathematical Finance and Stochastic Analysis, Imperial College London, Dept. of Mathematics Moving beyond the replication approach Target performance: RAROC-type analysis Cost of capital via indifference to RAROC type metrics Whole bank view vs Shareholders view END OF CONFERENCE

12 CONFERENCE SPONSORS MoCaX Intelligence is a new-to-the-market algorithm that accelerates existing Risk Engines without the need for complex systems development or expensive hardware upgrades. MoCaX removes the pricing step bottleneck that often uses over 90% of computational effort in existing engines and increases capabilities by several orders of magnitude with no loss of accuracy. MoCaX builds on the new Algorithmic Pricer Acceleration (APA) and Algorithmic Greeks Acceleration (AGA) methods. APA synthesises your existing pricers and creates an accelerated version of them. Even your very slowest and complex pricer, passed through MoCaX, will return the same results (down to precision) ultra-fast (up to a few nanoseconds). For example, this enables highly accurate Monte Carlo within Monte Carlo in an instant. AGA is a further enhancement, creating also an ultra-accurate, ultra-fast function of the Greeks of your pricers, even when you do not have an expression for them. This enables for example exact MVA and MVA sensitivity calculations. APA and AGA work for any pricing function: analytical, tree or MC based; and with any asset class. With one million accurate Price or Greek values in a few milliseconds, MoCaX delivers: massive acceleration of your current simulations previously-impossible simulations, e.g. accurate and ultra-fast MVA via real Dynamic SIMM potential for trades that had been too slow to simulate, e.g. non-linear products, barriers, bermudans enhanced regulatory approval, because MoCaX delivers perfect pricing and widens IMM product scope MoCaX Intelligence: the next step forward. Please ask for a free version of MoCaX so you can test it for yourself. mocaxintelligence.com i.ruiz@iruiztechnologies.com Since its creation in 1986, Murex has played a key role in proposing effective technology as a catalyst for growth and innovation in capital markets, through the design and implementation of integrated trading, risk management, processing and post-trade platforms. Driven by innovation, Murex s MX.3 Front-to-Back-to-Risk platform leverages the firm s collective experience and expertise, accumulated through its strategic client partnerships, to offer an unrivalled asset class coverage and best-of-breed business solutions at every step of the financial trade lifecycle. Clients worldwide benefit from the MX.3 platform s modular set of business solutions, specifically designed to solve the multi-faceted challenges of a transforming financial industry, while relying on the strength of 2,000 dedicated specialists. The Numerical Algorithms Group (NAG) are experts in numerical algorithms, software engineering and highperformance computing. They have served the finance industry with numerical software and consulting services for over four decades because of their outstanding product quality and technical support. Specifically, relevant to the finance industry, NAG pioneer in the provision of the NAG Library numerical and statistical components ideal for building Quant Libraries, Risk Applications and the like. NAG also provides best-in-class C++ operator-overloading AD tools for CPU and GPU called dco (derivative computation through overloading) and dco/map (dco meta adjoint programming). The NAG Library and AD tools are used by many of the largest Investment Banks where they are embedded in Quant Libraries and XVA applications. As a not-for-profit company, NAG reinvests surpluses into the research and development of its products, services, staff and its collaborations.

13 CONFERENCE SPONSORS AcadiaSoft, Inc. is a financial industry collaborative that is uniquely focused on delivering margin automation and standards for counterparties engaged in collateral management. AcadiaSoft allows market participants to communicate vital information on exposures, commitments and adjustments between counterparties in a complete, verifiable and secure manner. Owned and backed by the investment of 16 major industry participants and infrastructures, the AcadiaSoft community has grown to over 400 member firms exchanging approximately $400B of collateral on daily basis. The Company s growth has been driven by regulatory change in the derivatives industry that is increasing the demand for automated, transparent and verifiable collateral management. AcadiaSoft s Advisory Groups, Best Practice Forums and Working Groups provide a unique framework for integrating the thought leadership and capabilities of over 700 market participants, market infrastructures and key service providers across the industry. AcadiaSoft is headquartered outside of Boston in Norwell, MA and has offices in London, Tokyo and New York. For more information, see TriOptima provides risk management services for OTC derivatives, reducing costs and eliminating operational and credit risk through a range of services. triresolve for proactive reconciliation of OTC derivative portfolios, repository validation and dispute resolution trireduce for multilateral portfolio compression services across OTC product types tribalance for rebalancing counterparty risk exposure between multiple CCPs and bilateral relationships tricalculate for the complete spectrum of counterparty credit risk analytics leveraging state-of-the-art massively parallel computing devices TriOptima maintains offices in London, New York, Singapore, Stockholm, and Tokyo. FIS Adaptiv provides solutions for enterprise-wide risk management solutions, spanning trade capture to operations management. Adaptiv Analytics is a state-of-the-art calculation engine that offers marketleading performance for market risk, counterparty credit risk, and regulatory calculations. AAD-enabled Analytics software is the latest exciting development from FIS Adaptiv. This will add to the suite of performant technologies upon which Analytics is built, which includes vectorization and GPU support, and will enable real-time calculation of exact XVA sensitivities for effective risk reporting, credit limit monitoring, and position management. Through the depth and breadth of our solutions portfolio, global capabilities and domain expertise, FIS serves more than 20,000 clients in over 130 countries. Headquartered in Jacksonville, Fla., FIS employs more than 55,000 people worldwide and holds leadership positions in enterprise risk management, payment processing, financial software and banking solutions. Providing software, services and outsourcing of the technology that empowers the financial world, FIS is a Fortune 500 company and is a member of Standard & Poor s 500 Index.

14 THE 7TH ANNUAL INITIAL MARGIN & XVA CONFERENCE GRAND CONNAUGHT ROOMS, LONDON 21ST - 23RD MARCH 2018 CONFERENCE FEE STRUCTURE Super Early Bird Discount: 25% until 9th February Early Bird Discount: 10% until 2nd March Regular Event Fee Conference + Workshop ( 150 Discount): UK VAT UK VAT UK VAT Conference Only: UK VAT UK VAT UK VAT Workshop Only (No Discount): UK VAT UK VAT UK VAT Special Discount Code: SPECIAL OFFER: When 2 colleagues attend the 3rd goes free! 70% Academic Discount / FULL-TIME Students Only DELEGATE DETAILS COMPANY: NAME: JOB TITLE/POSITION: NAME: JOB TITLE/POSITION: NAME: JOB TITLE/POSITION: DEPARTMENT: ADDRESS: COUNTRY: TELEPHONE: DATE: SIGNATURE: TO REGISTER, PLEASE THE COMPLETED BOOKING FORM TO: sales@wbstraining.com FLIGHT DETAILS: All delegates flying into London on the morning of the event are reminded that they should arrive 30 minutes before the workshop starts for registration. The hotels West End location is approximately 1 hour from all 3 main London airports, Heathrow, Gatwick and City. Returning flights should equally allow for the events finishing time. SPONSORSHIP: World Business Strategies Ltd, offer sponsorship opportunities for all events, headers and the web site. Contact sponsorship via telephone on: +44 (0) DISCLAIMER: World Business Strategies command the rights to cancel or alter any part of this programme. CANCELLATION: By completing of this form the client hereby enters into a agreement stating that if a cancellation is made by fax or writing within two weeks of the event date no refund shall be given. However in certain circumstances a credit note maybe issued for future events. Prior to the two week deadline, cancellations are subject to a fee of 25% of the overall course cost. DISCOUNT STRUCTURE: The discount is available on any day permutation, and can be combined across delegates within the same company (only at the time of booking and not retrospectively). REGISTRATION: Tel: +44 (0) CONTACT: sales@wbstraining.com