Initial Margin, Funding & Regulatory Capital Stream
08:30: Morning Welcome Coffee
09.00 – 10.30: Practical considerations of implementing SIMM for Non Cleared Initial Margin Rules
- Background to SIMM
- SIMM Methodology Recap
- Lessons learnt from ISDA Backtesting Exercise
- Implementation issues that will need to be addressed
Presenter: Gordon Lee: Executive Director, Portfolio Quantitative Analytics, UBS
10.30 – 10.50: Morning Break and Networking Opportunities
10.50 - 11.40: Modeling Collateralized Exposure Under Dynamic Initial Margin Requirements
- Dynamic vs. static initial margin
- Estimating initial margin on a path
- Analytical results for scaling down expected exposure without initial margin
- Estimating conditional expected exposure on a path
Presenter: Michael Pykhtin: Manager, Quantitative Risk, Federal Reserve Board
11.40 - 12.30: Using AAD for Initial Margin, Capital, and KVA: A Case Study with TapeScript
Bullet points to be confirmed
Alexander Sokol: CEO and Head of Quant Research, CompatibL
12.30 - 13.30: Lunch
13.30 - 14.20: The Cost of Collateral for Clearing
- Regulations and Swap Clearing
- MVA – Margin Valuation Adjustment
- The Cost of funding Initial Margins (IMCA)
- The Cost and Benefit of funding Variation Margins (VMCA, VMBA)
- FVA, KVA – funding components of XVA
- OTC trade profitability
Presenter: To be confirmed
14.20 - 15.10: "Estimation of Future Initial Margins in a Multi-Curve Interest Rate Framework"
- Initial margin (IM) as a dynamic process
- Interest Model in Multi-curve framework as underlying for IM
- Efficient numerical implementation of future IM computation/simulation
- Calibration to option market and historical data
- Change of measure between Q and P and when to use each measure
Presenter: Marc Henrard: Head of Quantitative Research, OpenGamma
15.10 - 15.30: Afternoon Break and Networking Opportunities
15.30 - 16.20: Panel: “GPU vs. AAD” debate
- GPUs and AAD are not mutually exclusive – you can do both
- XVA Risk can be done using AAD but regulators and others clearly favour full revaluation for risk and stress testing
- The relative strengths and weaknesses of forward vs. reverse AD mode in practical calculations
- Are GPUs necessary or is AAD sufficient?
- How easy is it to implement AAD in practice? In new code and in legacy code?
- How easy are GPUs to use / code for?
- Is AAD compatible with regulatory requirements – e.g. FRTB?
- Can AAD be used on GPUs?
- Where is XVA technology headed – smartphones or supercomputers?
Panelists: (To be confirmed)
- Nicki S. Rasmussen: Counterparty Credit & Funding Risk, Danske Bank
- Alexander Sokol: CEO and Head of Quant Research, CompatibL
- Luca Capriotti: Head QS Global Credit Products EMEA, Credit Suisse & Visiting Professor, University College London
- Chris Kenyon: Director, Quantitative Research, CVA, Lloyds Banking Group
End of conference