Explore the various uses, methodologies, and challenges of XVA. <br />
With falling interest rates and a widening of the funding spread significantly effecting FVA and CVA, the landscape for XVA has experienced several major challenges in recent months.
This virtual training course will deep dive into the complexity of XVA, its various methodologies and calculations, allowing delegates to hear different perspectives from expert practitioners and their peers.
Sessions will focus in detail on CVA, DVA, FVA, MVA, and KVA and discuss the journey of XVA in the context of recent market changes.
Participants will have the opportunity to develop their knowledge on the applications of machine and deep learning to XVA calculations, as well as discuss the importance of data management in XVA calculations and capital and funding optimisation.
This course will look at the future of XVA, its impact on P&L and how FRTB-CVA will affect capital, MVA and FVA.
What will you learn?
- How XVA has been affected by market volatility in 2020
- In depth understanding of the various methodologies used to calculate XVA
- The challenges of calculating hedging and P&L in CVA
- Accounting versus management perspectives relating to FVA
- Applications of machine learning in increasing XVA calculation efficiency
- The impact of FRTB-CVA
- Tools for data management to optimise XVA
Who should attend
Relevant departments may include but are not limited to:
- XVA Desk
- Counterparty credit risk
- Quant modelling
- Risk Management
Our live, virtual training courses have been designed to engage and inspire you. Much more than a webinar, our approach includes:
- Technical content compressed into 60-minute interactive sessions and spread out over two, three or four days
- Facilitated collaboration including Q&A, interactive polling and group workshops
- Live interaction with subject matter experts – get your questions answered in real time
- Receive comprehensive course materials and supporting content from Risk.net to reinforce your learning
- Stay connected with other learners and extend your network by joining our dedicated LinkedIn group for course participants
Formerly Global Portfolio Market Risk Manager
Global head of counterparty credit risk quantitative research
Since 2012 Matthias has been heading the J.P. Morgan 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.
Senior quant model development
Othmane Islah is currently the Head of Quantitative Research at Quantuply and a senior consultant for Traded Risk Models at Natwest Markets. He was previously a consultant for XVA at Lloyds Banking Group. Before that, he was the Head of Model Validation and Market Risk at the European Bank for Reconstruction and Development.
Funding manager/XVA trader
Dmitry Ilchenko manages Funding and Liquidity in ING’s Financial Markets team. He oversees the Bank’s Derivative Funding Framework and looks after collateral funding costs optimisation. His sphere of interests includes optimising FVA, KVA and MVA, managing FVA reserve, dealing with complex collateralised cases and, recently, implementing the MVA concept for both SIMM and CCP models.
Prior to his position at ING, he worked at Deutsche Bank, first as Market Risk Manager covering European Rates and further in CVA desk where he managed the Bank’s CVA and RWA positions.
Managing Director and XVA Lead Quant
Director, Financial Resource Management
Ali is currently a Director in the Financial Resource Management group at TD Securities. The group is responsible for measurement and management of xVAs including capital management for TD Securities, where he is also a member of the Global Credit Trading group. Before this position, he was responsible for model development of TD Securities risk model (Counterparty Credit Risk, Market Risk and Stress Testing). Prior to that role, he was at Scotiabank, Oliver Wyman, and Harvard University. He holds a PhD in theoretical physics.
Irina Ursachi is an independent Risk Management consultant. She has over eight years of experience in the banking industry, managing international projects in various European jurisdictions such as UK, France, and Germany. Her expertise covers the design and specification of business processes as well as the implementation of regulatory requirements, trading systems, and valuation models. Mrs. Ursachi is an active contributor to research projects and publications in the area of Risk Management. Prior to becoming an independent consultant, she has worked for the consulting companies d-fine and KPMG. She holds a Master’s degree in Mathematics from the University of Kaiserslautern.
Senior XVA Quantitative Consultant
Assad Bouayoun is a senior XVA Quantitative Analyst at Scotiabank with more than 15 years' experience in leading banks. He has designed industry standard hedging and pricing systems, first as a single asset quant (equity derivative at Commerzbank, credit derivatives at Credit Agricole) then as XVA quant 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. After developing a prototype of XVA platform integrating cutting-edge technologies (GPU, Cloud computing) and numerical methods (AAD) to enable fast and accurate XVA and sensitivities computation, he now participates to its productionisation. 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).