Thursday 19th March 2020
- Examine the timeline for the implementation of the initial margin regulations
- Explore the potential for increased CCP usage following the regulation and the role of bilateral trades
- Analyse the disparity of effects upon smaller and larger banks:
- How will the regulation affect these institutions?
- Consider the possibility of increased vendor usage as a response to the requirements of MVA
MD, Head of Counterparty Portfolio Optimisation Desk / CVA Trading, Citi
Gonzalo Garcia-Kenny: Managing Director, Head of Portfolio Optimisation Desk, Citi
- Review of Balance Sheet financing management.
- Interaction of Credit, Debit and Funding Value Adjustments.
- Funding Value Adjustment: accounting versus economic management perspectives.
Head of XVA Model Validation, Santander
Alberto Elices: Head of XVA Model Validation, Santander
Alberto Elices obtained a PhD in Power Systems Engineering at Pontificia Comillas University (Madrid, Spain) and a Masters in Financial Mathematics at the University of Chicago. He joined Santander in 2004 after spending two years in a hedge fund in New York. He has worked as Equity and FX quantitative analyst, headed Equity Model Validation and he is currently Head of XVA Model Validation within Model Risk Area at Santander in Madrid (Spain). During his professional career, he has also published a number of papers in practitioner and academic journals.
The two largest components of Capital Valuation Adjustment (KVA) are the costs of Counterparty Credit Risk (CCR) and CVA capital. For a bank using the most advanced capital models – Internal Models Method for CCR and the incoming SA-CVA capital –an accurate KVA involves forward simulating expected exposures (EE) over the lifetime of the portfolio – potentially a Monte Carlo in a Monte Carlo. We present a practical regression-based solution.
- Simulating EE: from regulatory stressed real-world measure to market implied measure
- A comparative study of regression vs brute force nested Monte Carlo
- SA-CVA: extending from simulating forward EE to simulating forward CVA sensitivities
Quantitative Strategy, Adaptiv, FIS
Justin Chan: Quantitative Strategy, Adaptiv, FIS
Justin Chan has over 11 years of experience in financial risk management and capital markets. Mr. Chan has a deep focus on quantitative modelling in areas such as xVA, credit exposure, and collateral simulations. He is currently responsible for the Risk Quantitative Strategy and Innovation program at FIS. Prior to FIS, Mr. Chan worked at Manulife Financial as a manager in corporate risk management.
Mr. Chan studied engineering science (BASc), and theoretical physics (MSc) at University of Toronto, where he also holds a Master of Mathematical Finance (MMF) degree.
Global head of Counterparty Credit Risk Quantitative Research, J.P. Morgan
Matthias Arnsdorf: Global head of Counterparty Credit Risk Quantitative Research, J.P. Morgan
Since 2012 Matthias has been heading the counterparty credit risk quantitative research team globally.
His main responsibilities include the development & support of J.P. Morgan’s suite of credit exposure models which are used for valuation and risk management as well as credit capital.
Prior to his work in credit risk, Matthias headed the market risk capital modelling effort in EMEA for two years. Matthias started his career in finance in 2002 as a credit derivatives quantitative researcher at UBS and J.P.Morgan.
Matthias holds a PhD in Quantum Gravity from Imperial College London and has spent two years as a post-doctoral researcher at the Niels Bohr Institute in Copenhagen prior to his move to quantitative finance.
Head of Quant XVA Analytics Bloomberg LP
Mats Kjaer: Head of Quant XVA Analytics Bloomberg LP
- An overview of the requirements of the final initial margin regulation and the impact on the XVA desk
- Consider the impact on the market the scope of the final regulation will pose
- Assess the difficulties with a lack of industry standard
- Explore the need to optimise systems in order to effectively account for MVA
- Investigate methodologies for pricing MVA into current derivative trades
Senior Director, Head of In Business Risk, Capital and Collateral, Lloyds Banking Group
Matteo Rolle: Senior Director, Head of In Business Risk, Capital and Collateral, Lloyds Banking Group
After finishing my MSC in physics Matteo worked 3 years and a half in equity derivatives Algo Trading in Italy before moving to London. After a short experience as a quant in option market making Matteo ended up in Lloyds where he is currently employed.
In Lloyds Matteo spent 2 years as a CVA/FVA quantitative researcher during which time he ended up making a lot of work from a quantitative and regulatory perspective for the repo desk as well as the CVA desk. At the beginning of 2014 he joined the repo desk as a Collateral Optimisation Trader and has been responsible for capital and collateral optimization trades such as clearings, compressions, setting up Bilateral Independent Amounts and Initial Margins, for choosing and sourcing the collateral to post for initial and variation margin for CCPs and CSAs.
Matteo is now heading the In Business Risk, Capital and Collateral team in Financial Markets with full responsibility for capital and collateral management and heading a first line risk team.
- Strategies to compute 2nd order XVA derivatives with AAD
- Finding discontinuities affecting the 2nd order derivatives
- Numerical convergence of path-wise risk
Head of Automatic Adjoint Differentiation, Matlogica
Dmitri Goloubentsev: Head of Automatic Adjoint Differentiation, Matlogica
Dmitri has 15 years of combined experience in model development working on C++ quant libraries. He worked as a Senior Quant Analyst in interest rate derivatives and played a leading role in delivering XVA solution at a major Canadian bank. Prior to focusing on AAD, he was responsible for construction of SIMM/MVA model. Dmitri earned his degree in Maths and Applied Maths from the Moscow State University.