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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