World Business StrategiesServing the Global Financial Community since 2000

Wednesday 18th March 2020

08.00 - 09.00
Registration and Morning Welcome Coffee
09.00 - 09.45
“Reinforcement Learning for xVA hedging”.

Ivan Zhdankin:

Associate, Quantitative Analyst, JPMorgan Chase & Co

Ivan Zhdankin: Associate, Quantitative Analyst, JPMorgan Chase & Co

Ivan Zhdankin is a quantitative researcher with experience in diverse areas of quantitative finance, including risk modelling, XVA, and electronic trading across asset classes, including commodity futures and G10 and emerging market currencies. Ivan was consulting various banks in quantitative modeling and has recently joined JP Morgan as a quantitative analyst. He has become one of the first researchers to generate convincing results in electronic alpha with neural nets. He has a solid mathematical background from New Economic School and Moscow State University, where he studied under the celebrated Albert Shiryaev, one of the developers of modern probability theory.

09.45 - 10.30
Marginal KVA via Mathematical Programming and Reinforcement Learning

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.

10.30 - 11.00
Morning Break and Networking Opportunities
11.00 - 11.45
Model Validation of XVAs with Variation and Initial Margins
  • Pricing and calibration under multicurve G2++ with time dependent volatility
  • Collateral simulation: variation margin and initial margin under ISDA SIMM.
  • Computing exposure and XVAs for swaps and swaptions with variation and initial margin.
  • Sensitivity analysis of model parameters

Abstract

In the last few years initial margin broke into the world of OTC transactions, required both by Central Counterparties and by current regulations of bilateral transactions to neutralize counterparty default risk. In particular, OTC derivatives between market counterparties are subject to the ISDA Standard Initial Margin Model (SIMM).

In our work we use a multicurve two factor Hull-White (G2++) model to compute exposures and XVA figures including variation and initial margins. We test both linear and optional instruments, i.e. IRS and Swaptions, and we assess the detailed effects of tuning several simulation parameters: collateral thresholds, minimum transfer amount, time simulation steps, Monte Carlo scenarios, interpolation schemes, etc. We show that there exist optimal parameters values leading to accurate and stable results in a reasonable computational time.

Marco Bianchetti:

Head of Fair Value Policy, Intesa Sanpaolo

Marco Bianchetti: Head of Fair Value Policy, Intesa Sanpaolo

Marco Bianchetti joined the Market Risk Management area of Intesa Marco joined the Financial and Market Risk Management area of Intesa Sanpaolo in 2008. His work covers pricing and risk management of financial instruments across all asset classes, with a focus on new products development, model validation, model risk management, interest rate modelling, funding and counterparty risk, fair and prudent valuation, applications of Quasi Monte Carlo in finance. He is in charge of the global Fair Value Policy of Intesa Sanpaolo group since Nov. 2015. Previously he worked for 8 years in the front office Financial Engineering area of Banca Caboto (now Banca IMI), developing pricing models and applications for interest rate and inflation trading desks. He is adjunct professor of Interest Rate Models at University of Bologna since 2015, and a frequent speaker at international conferences and trainings in quantitative finance. He holds a M.Sc. in theoretical nuclear physics and a Ph.D. in theoretical condensed matter physics.

Marco Scaringi:

Quant Risk Analyst, Fair Value Policy Office, Intesa Sanpaolo

Marco Scaringi: Quant Risk Analyst, Fair Value Policy Office, Intesa Sanpaolo

Marco Scaringi joined the Financial and Market Risk Management area of Intesa Sanpaolo in 2017 as quantitative analyst in the Fair Value Policy Office. His work focuses on interest rate models, XVAs, financial bubble analysis and portfolio optimization.

He holds a M.Sc. in theoretical physics from University of Milan, with a thesis on advanced statistical mechanics techniques applied to the description and detection of financial bubbles through optimization heuristics. He also holds a post lauream degree Executive Course of Quantitative Finance from MIP, Graduate School of Business, Polytechnic of Milan, with a thesis concerning interest rate and XVAs modelling.

 

11.45 - 12.30
Machine Learning + Chebyshev techniques for XVA: boosting each other"

The computation of risk metrics poses a huge computational challenge to banks. Many different techniques have been developed and implemented in the last few years to try and tackle the problem. We focus on Chebyshev tensors enhanced by machine learning, showing why they are such powerful pricing approximators  in risk calculations. We show how the presented unique mix of techniques can be applied in different calculations. We illustrate with Numerical results in Counterparty Credit Risk and Dynamic initial Margin. In particular, We will give special attention on how to side-step the curse of dimensionality and how machine learning techniques can be used to boost Chebyshev tensors.

Mariano Zeron:

Head of Research and Development: MoCaX Intelligence

Mariano Zeron: Head of Research and Development: MoCaX Intelligence

Mariano leads our Research & Development work. He has vast experience in Chebyshev Spectral Decomposition, machine-learning and related disciplines, and their application to quantitative problems in the financial markets. Mariano holds a Ph.D. in Mathematics from Cambridge University.

12.30 - 13.30
Lunch
13.30 - 14.15
Bayesian and Machine Learning Approaches to XVA Integration

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. 

14.15 - 15.00
Derivatives Pricing with A Deep Learning Approach

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.

15.00 - 15.30
Afternoon Break and Networking Opportunities
15.30 - 16.15
Balance Sheet XVA by Deep Learning and GPU

Stéphane Crépey:

Professor of Mathematics, University Of Evry

Stéphane Crépey: Professor of Mathematics, University Of Evry

Stéphane Crépey is professor at the Mathematics Department of University of Evry (France), head of Probability and Mathematical Finance and head of the Engineering and Finance branch (M2IF) of the Paris-Saclay Master Program in Financial Mathematics. His research interests are financial modeling, counterparty and credit risk, numerical finance, as well as related mathematical topics in the fields of backward stochastic differential equations and partial differential equations. He is the author of numerous research papers and two books: “Financial Modeling: A Backward Stochastic Differential Equations Perspective” (S. Crépey, Springer Finance Textbook Series, 2013) and “Counterparty Risk and Funding, a Tale of Two Puzzles” (S. Crépey, T. Bielecki and D. Brigo, Chapman & Hall/CRC Financial Mathematics Series, 2014).

He is an associate editor of SIAM Journal on Financial Mathematics, International Journal of Theoretical and Applied Finance, and a member of the scientific council of the French financial markets authority (AMF). Stéphane Crépey graduated from ENSAE and he holds a PhD in applied mathematics from Ecole Polytechnique and INRIA Sophia Antipolis.

16.15 - 17.00
The Impact of Initial Margin on Derivatives Pricing with an Application of Machine Learning

Presenter to be confirmed

17.00 - 17.45
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:

 

Ivan Zhdankin:

Associate, Quantitative Analyst, JPMorgan Chase & Co

Ivan Zhdankin: Associate, Quantitative Analyst, JPMorgan Chase & Co

Ivan Zhdankin is a quantitative researcher with experience in diverse areas of quantitative finance, including risk modelling, XVA, and electronic trading across asset classes, including commodity futures and G10 and emerging market currencies. Ivan was consulting various banks in quantitative modeling and has recently joined JP Morgan as a quantitative analyst. He has become one of the first researchers to generate convincing results in electronic alpha with neural nets. He has a solid mathematical background from New Economic School and Moscow State University, where he studied under the celebrated Albert Shiryaev, one of the developers of modern probability theory.

Sarah B Tremel:

Global Head of Analytics – Product Control, HSBC

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

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.

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. 

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.

  • Discount Structure
  • Special Offer
    When two colleagues attend the 3rd goes free!

  • Conference + Workshop
    £300 Discount

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

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