World Business StrategiesServing the Global Financial Community since 2000

Thursday 14th March

08.00 - 09.00
Registration and Morning Welcome Coffee
09.00 - 09.45
Both Streams
Keynote: How Machine Learning Can Help Better Manage XVA
  • P&L explain
  • Sensitivities
  • Forecasting

Sarah B Tremel:

Global Head of Analytics – Product Control, HSBC

Sarah B Tremel: Global Head of Analytics – Product Control, HSBC

09.45 - 10.30
Both Streams
MVA Market Developments
  • MVA Overview
  • Pricing and Optimisation
  • MVA Reserves
  • IM Phase 4 and 5

Hannah Townsend:

xVA Trader, Lloyds Banking Group

Hannah Townsend: xVA Trader, Lloyds Banking Group

I have worked at Lloyds for 5 years. Spent a few years primarily focussed on risk management of C&FVA reserves, and c1 year ago moved to cover the full spectrum of xVA’s

I have been leading the implementation of Bilateral Initial Margin from the xVA Front Office perspective and oversaw implementation of Ring Fencing last year

In my spare time I play tennis, netball and I’m hoping to complete a half marathon in May

10.30 - 11.00
Morning Break and Networking Opportunities
11.00 - 12.30
Stream One: XVA & Initial Margin
Extended Talk: Symmetric or Asymmetric FVA?
  • Basic FVA and discounting
  • Funding strategies
  • NSFR
  • Evidence from Totem
  • A move to asymmetric FVA?
  • Link to initial margin and MVA

Jon Gregory: 

Independent xVA Expert

Jon Gregory: Independent xVA Expert 

DR JON GREGORY is an independent expert specialising in counterparty risk and xVA related projects. He has worked on many aspects of credit risk in his career, being previously with Barclays Capital, BNP Paribas and Citigroup. He is a senior advisor for Solum Financial Derivatives Advisory and a faculty member for the Certificate of Quantitative Finance (CQF). He also serves on the Academic Advisory Board of IHS Markit and is a Managing Editor of the journal Quantitative Finance.

In addition to publishing papers on the pricing of credit risk and related topics, Jon is author of the book “Counterparty Credit Risk The New Challenge for the Global Financial Markets” published by Wiley Finance in December 2009 (now in its third edition) and “Central Counterparties: Mandatory Central Clearing and Bilateral Margin Requirements for OTC Derivatives.”

Jon has a PhD from Cambridge University.

12.30 - 13.30
Lunch
13.30 - 14.15
Stream One: XVA & Initial Margin
The Pricing of XVA and Stochastic Corporate Liabilities
  • A structural model allows to construct a self-consistent and paradox-free theory of XVA.
  • Derivatives are treated as stochastic liabilities of issuers.
  • XVA on new business is always a corporate finance problem, as marginal debt (stochastic or not) must be priced. In practice it is approximated by various CCDSs, assuming marginal debt is small.
  • DVA is credit haircut on a theoretical value of a (stochastic) liability.  It is created together with the liability, it cannot be hedged and it must be borne by the original investor that then can later sell it physically or synthetically (CDS).
  • CVA is the counterparty’s DVA from the investor’s point of view.  Treatment of reciprocal investments is possible but requires settlement theory.
  • FVA is syntactic sugar for marginal DVA; valuing FVA requires explicit assumptions about marginal assets.
  • Cost of capital (KVA) must be borne by the party that decides on the asset/liability structure, i.e. by “effective shareholder”.  It cannot be transferred to pure bond investors (as DVA).
  • Collateralization turns deals into swaps with no initial exchange and shifts funding of PNL to third parties.  Such funding will attract its own DVA.

Andrey Chirikhin:

Founder at Quantitative Recipes

Andrey Chirikhin: Founder at Quantitative Recipes

Andrey was formerly Head of Modelling and Quantitative Analytics for L1 Treasury, part of a USD 25bn privately held investment vehicle LetterOne. Prior to LetterOne, Andrey was MD and Head of CVA and CCR quantitative Analytics at RBS. There he has created and run the front office cross asset CVA quant team. He also restructured and led the risk-side quant team charged with delivering a new Basel III compliant internal CCR methodology. The system utilizing the newly delivered methodology has won the 2013 Internal System of the year Risk award. In his 20 year career in investment banking, Andrey held several leadership and senior quant positions at Goldman Sachs, HSBC and Dresdner Kleinwort. Andrey Chirikhin holds PhD in Theoretical Statistics from Warwick University (UK), MBA from INSDEAD and MSc in Applied Mathematics from Moscow Institute for Physics and Technology (Phystech).

Since 2018 Andrey runs his own company, Quantitative Recipes, that advises on wide rage of XVA, long-term market modelling for risk and quant infrastructure.

14.15 - 15.00
Stream One: XVA & Initial Margin
Fast Calculation of Credit Exposures
  • New method for the calculation of credit exposures of Bermudan, barrier and European options based on Chebyshev interpolation.
  • Closed form approximation of the option prices along the paths together with the options’ delta and gamma.
  • Polynomial structure of the approximation allows a highly efficient evaluation of the credit exposures, even for a large number of simulated paths.
  • The presented approach is flexible in the model choice, payoff profiles and asset classes.
  • Investigation of exposure profiles and discussion of practical implications.

(joint work with Kathrin Glau and Ricardo Pachon)

Christian Pötz:

Postgraduate Researcher at Queen Mary University of London

Christian Pötz, Postgraduate Researcher at Queen Mary University of London

15.00 - 15.30
Afternoon Break and Networking Opportunities
15.30 - 16.15
Stream One: XVA & Initial Margin
"Intraday Liquidity and the Settlement Dilemma"

Gordon Lee:

XVA and Capital Quantitative Analyst, UBS

Gordon Lee: XVA and Capital Quantitative Analyst, UBS

16.15 - 17.15
Panel: Both Streams
XVA, FRTB & Machine Learning Panel

Topics: 

XVA & Initial Margin

  • 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
  • Discuss the role of technology to increase the knowledge base from XVA calculations

Machine Learning  

  • Discuss the existing applications of machine learning in XVA
  • Discuss the potential new applications of machine learning in XVA going forward
  • How important is machine learning in calculation of XVAs?
  • Best practices to incorporate machine learning across XVAs
  • Is machine learning necessary for 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?

Moderator:

Gordon Lee: XVA and Capital Quantitative Analyst, UBS

Gordon Lee:

XVA and Capital Quantitative Analyst, UBS

Gordon Lee: XVA and Capital Quantitative Analyst, UBS

Ignacio Ruiz:

Founder & CEO, MoCaX Intelligence

Ignacio Ruiz: Founder & CEO, MoCaX Intelligence

Ignacio Ruiz has been the head strategist for Counterparty Credit Risk, exposure measurement, for Credit Suisse, as well as the Head of Risk Methodology, equities, for BNP Paribas. In 2010, Ignacio set up iRuiz Consulting as an independent advisory business in this field. In 2014, Ignacio founded iRuiz Technologies to develop and commercialise MoCaX Intelligence.

Ignacio has several publications in the space of quantitative risk management and pricing. He has also published a comprehensive guide to the subject of XVA Desks and Risk Management.

He holds a PhD in nano-physics from Cambridge University.

Andrew Green: 

Managing Director and XVA Lead Quant, Scotiabank

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. 

Satinder (Sid) Jandu:

Risk Management Consultant, Morgan Stanley

Satinder (Sid) Jandu: Risk Management Consultant, Morgan Stanley

Giovanni Cesari:

Head of XVA – Market and Traded Credit Risk, Standard Chartered

Giovanni Cesari: Head of XVA – Market and Traded Credit Risk, Standard Chartered

End of Day One

Thursday 14th March

08.00 - 09.00
Registration and Morning Welcome Coffee
09.00 - 09.45
Both Streams
Keynote: How Machine Learning Can Help Better Manage XVA
  • P&L explain
  • Sensitivities
  • Forecasting

Sarah B Tremel:

Global Head of Analytics – Product Control, HSBC

Sarah B Tremel: Global Head of Analytics – Product Control, HSBC

09.45 - 10.30
Both Streams
MVA Market Developments
  • MVA Overview
  • Pricing and Optimisation
  • MVA Reserves
  • IM Phase 4 and 5

Hannah Townsend:

xVA Trader, Lloyds Banking Group

Hannah Townsend: xVA Trader, Lloyds Banking Group

I have worked at Lloyds for 5 years. Spent a few years primarily focussed on risk management of C&FVA reserves, and c1 year ago moved to cover the full spectrum of xVA’s

I have been leading the implementation of Bilateral Initial Margin from the xVA Front Office perspective and oversaw implementation of Ring Fencing last year

In my spare time I play tennis, netball and I’m hoping to complete a half marathon in May

10.30 - 11.00
Morning Break and Networking Opportunities
11.00 - 11.45
Stream Two: Machine Learning Applications in XVA
Deeply Learning Derivatives

Abstract

This paper uses deep learning to value derivatives. The approach is broadly applicable, and we use a call option on a basket of stocks as an example. We show that the deep learning model is accurate and very fast, capable of producing valuations a million times faster than traditional models. We develop a methodology to randomly generate appropriate training data and explore the impact of several parameters including layer width and depth, training data quality and quantity on model speed and accuracy.

Andrew Green: 

Managing Director and XVA Lead Quant, Scotiabank

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. 

11.45 - 12.30
XVA with SIMM using Machine Learning Techniques
  • Motivation – SIMM, FRTB and ANN
  • Master Pricing Equation with Credit, Funding and IM
  • Mathematical Introduction to Neural Networks
  • The Universal Representation Theorem
  • Pre and Post Default Forward Exposures with SIMM
  • Numerical Implementation
  • Applications

Youssef Elouerkhaoui:

Managing Director, Head of Credit Derivatives, CITI

Youssef Elouerkhaoui, Managing Director, Head of Credit Derivatives, CITI  

Youssed Elouerkhaoui is the global Head of Credit Quantitive Analysis at Citi. His group supports all aspects of modelling and product development across desks, thais includes: Flow Credit Trading, Correlation Trading, CDOs, Exotics and Emering Markets.

He also supports CVA, Funding and Regulatory Capital for Credit Markets. Prior to this, he was a Director in the Fixed Income Derivatives Quantitative Research Group at UBS, where he was in charge of developing and implementing models for the Structured Credit Desk. Before joining UBS, Youssef was a Quantitative Research Analyst at Credit Lyonnais supporting the Interest Rates Exotics business. He has also worked as a Senior Consultant in the Risk Analytics and Research Group at Ernst & Young. He is a graduate of Ecole Centrale Paris and he holds a PhD in Mathematics from Paris-Dauphine University.

12.30 - 13.30
Lunch
13.30 - 14.15
Stream Two: Machine Learning Applications in XVA
Reinforcement Learning for Marginal KVA Pricing
  • Capital creation and consumption
  • Models for lifetime costs and benefits of capital in trading
  • Contract design vs KVA model
  • Solution framing and methods: F-K/FBSDE: Stochastic programming; reinforcement learning
  • Numerical results

Chris Kenyon:

Director: Head of XVA Quant Modelling, MUFG Securities EMEA plc

Chris Kenyon: Director: Head of XVA Quant Modelling, MUFG Securities EMEA plc 

Dr Chris Kenyon is head of XVA Quant Modelling at MUFG Securities EMEA plc. Previously he was Head of XVA Quantitative Research at Lloyds Banking Group, head quant for Counterparty Credit Risk at Credit Suisse, and (post-crisis) Head of Structured Credit Valuation at DEPFA Bank Plc. He is active in XVA research, introducing KVA and MVA, with Andrew Green in 2014-15, their accounting treatment in 2016-17, as well as double-semi-replication and behavioural effects on XVA. He contributes to the Cutting Edge section of Risk magazine (most-cited author in 2016; 5th most-published author 1988-present in 2017), co-edited “Landmarks in XVA” (Risk 2016). He has a Ph.D. from Cambridge University and is an author of the open source software QuantLib.

14.15 - 15.00
Stream Two: Machine Learning Applications in XVA
Quantum Annealing for Multi-Period XVA Reverse Stress Testing
  • Modelling
    • XVA reverse stress testing formula
    • XVA reverse stress testing as a QUBO problem ( Quadratic Unconstrained Binary Optimisation)
    • Generalisation to multi-period case
  • Optimisation using annealing
    • Quantum annealing
    • Simulated annealing
  • Applications
    • Simple portfolio of swaps
    • Firm level management

Assad Bouayoun:

Senior XVA Quantitative Consultant, HSBC Global Banking and Markets

Assad Bouayoun: Senior XVA Quantitative Consultant, HSBC Global Banking and Markets

Assad Bouayoun is a senior XVA Quantitative Analyst with more than 15 years’ experience in leading banks. He has designed industry standard hedging and pricing systems, first in equity derivative at Commerzbank, then in credit derivatives at Credit Agricole, in XVA at Lloyds in Model Validation at RBS in Model Development. Assad has an extensive experience in developing enterprise wide analytics to improve the financial management of derivative portfolios, in particular large scale hybrid Monte-Carlo and Exposure computation. Assad is currently building the prototype of a new XVA platform integrating cutting-edge technologies (GPU, Cloud computing) and numerical methods (AAD) to enable fast and accurate XVA and sensitivities computation. He holds a MSc in Mathematical Trading and Finance from CASS business school and a Master in Applied Mathematics and Computer Science from Université de Technologie de Compiegne (France).

15.00 - 15.30
Afternoon Break and Networking Opportunities
15.30 - 16.15
Stream Two: Machine Learning Applications in XVA
Agent-Based XVA

Abstract:

One to one relations among banks are often the limit of risk models. Counterparty dynamics beyond a one to one relation has started to appear in network risk metrics, but these network models often rely on Pareto distributed random networks to integrate out the known structural constraints and interactions that dictate the flow of risk modelled by xVA. Interdependencies are integral to credit risk modelling, but the default xVA assumption is counterparty independence. This independence assumption results in an unrealistic picture of credit risk. In light of the rich dynamics available through network models and xVA, we present an interconnected Agent-based xVA model of this complex interconnected system of banks as agents interacting according to their behavioural dynamics. This new Agent-based xVA model results in a higher-order impact assessment of emergent counterparty risk.

Krishnen Vytelingum:

Agent-based Modelling Specialist, Simudyne

Krishnen Vytelingum: Agent-based Modelling Specialist, Simudyne

Specialist in Agent-based Modelling and Machine Learning with over 20 widely cited and refereed publications in top AI conferences and journals and with a PhD Thesis titled ‘The Structure and Behaviour of the Continuous Double Auction’ on the intersection of Agent-Based modelling, Machine Learning and Evolutionary Game Theory. Experience Market Risk Quant with 7 years of experience in finance, more recently working as a Quant at JPMorgan in market risk.

16.15 - 17.15
Panel: Both Streams
XVA, FRTB & Machine Learning Panel

Topics: 

XVA & Initial Margin

  • 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
  • Discuss the role of technology to increase the knowledge base from XVA calculations

Machine Learning  

  • Discuss the existing applications of machine learning in XVA
  • Discuss the potential new applications of machine learning in XVA going forward
  • How important is machine learning in calculation of XVAs?
  • Best practices to incorporate machine learning across XVAs
  • Is machine learning necessary for 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?

Moderator:

Gordon Lee: XVA and Capital Quantitative Analyst, UBS

Gordon Lee:

XVA and Capital Quantitative Analyst, UBS

Gordon Lee: XVA and Capital Quantitative Analyst, UBS

Ignacio Ruiz:

Founder & CEO, MoCaX Intelligence

Ignacio Ruiz: Founder & CEO, MoCaX Intelligence

Ignacio Ruiz has been the head strategist for Counterparty Credit Risk, exposure measurement, for Credit Suisse, as well as the Head of Risk Methodology, equities, for BNP Paribas. In 2010, Ignacio set up iRuiz Consulting as an independent advisory business in this field. In 2014, Ignacio founded iRuiz Technologies to develop and commercialise MoCaX Intelligence.

Ignacio has several publications in the space of quantitative risk management and pricing. He has also published a comprehensive guide to the subject of XVA Desks and Risk Management.

He holds a PhD in nano-physics from Cambridge University.

Andrew Green: 

Managing Director and XVA Lead Quant, Scotiabank

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. 

Satinder (Sid) Jandu:

Risk Management Consultant, Morgan Stanley

Satinder (Sid) Jandu: Risk Management Consultant, Morgan Stanley

Giovanni Cesari:

Head of XVA – Market and Traded Credit Risk, Standard Chartered

Giovanni Cesari: Head of XVA – Market and Traded Credit Risk, Standard Chartered

End of Day One
  • Discount Structure
  • Special Offer
    When two colleagues attend the 3rd goes free!

  • Conference + Workshop
    £150 Discount

  • 70% Academic Discount
    (FULL-TIME Students Only)

Event Email Reminder

Error

Also attend