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XVA, MVA & AAD Stream 


 08:30: Morning Welcome Coffee 


09.00 - 09.45: Youssef Elouerkhaoui: Managing Director, Global Head of Credit Quant Analysis, Citigroup Image result for Youssef Elouerkhaoui

Keynote: SIMM Impact On Credit XVA   

  • Motivation: Mandatory OTC Bilateral Margining
  • Master Pricing Equation with Credit, Funding and IM
  • SIMM, FRTB and AAD
  • Conditional Expectations in the Enlarged Filtration
  • Pre and Post Default Forward Exposure Profiles with SIMM
  • Numerical Implementation
  • Applications

09.45 - 10.30: To be confirmed Jon Gregory

Presenter: Jon Gregory: Partner, Solum Financial Partners

 

 


 10.30 - 11.00: Morning Break and Networking Opportunities


11.00 - 12.30:  Stochastic Automatic Differentiation: AAD for Monte-Carlo Simulation and Applications to MVAChristian Fries

  • Automatic Differentiation - Introduction and Review
    • Forward Automatic Differentiation
    • Backward Automatic Differentiation
  • Stochastic Automatic Differentiation - AD for Monte-Carlo Simulations
    • Pathwise Operators
    • Expectation Operator
    • Conditional Expectation Operator
    • Indicator Function
  • Application - Automatic Differentiation of Bermudan options
    • Bermudan digital option (differentiation of exercise boundary)
  • Memory Efficient Tapeless Implementation
    • Immutable Objects
    • Stochastic Operators
  • Implementation
    • AAD with 40 lines of code
    • Bermudan AAD with 5 lines of additional code
  • Applikation: Fast and Effizient ISDA-SIMM MVA
    • ISDA-SIMM
    • Fast AAD Forward Sensitivities
  • Numerical Results 

Presenter: Christian Fries: Head of Model Development, DZ Bank 


 12.30 - 13.30: Lunch


13.30 - 14.15: Chebyshev Interpolation for Parametric Option Pricing Image result for Kathrin Glau

Model calibration requires fast and accurate numerical methods. In the current paradigm, semi-closed pricing formulas for liquid options are seen as a prerequisite for modelling financial asset evolution. Thus attention is restricted to  stochastic processes that are simple enough to allow for straightforward expressions of the pricing formulas. This obviously imposes a severe modelling restriction. However, rising demands to include more realistic features, for instance stylized facts on asymptotics of the implied volatility surface, compel us to consider a wider class of processes and hence more complex models. We therefore propose numerical techniques to reduce the computational complexity of the resulting pricing tasks. In this talk we focus on interpolation of option prices in the parameter space. Both the theoretic and experimental results show highly promising gains in efficiency. As one specific application we derive an efficient interpolation of the implied volatility. To present an approach with a wide range of applications, we investigate the combination of Monte Carlo simulation and interpolation in the parameter space. 

[1] Chebyshev Interpolation for Parametric Option Pricing, M. Gaß, K. Glau, M. Mahlstedt and M. Mair (2016), http://arxiv.org/abs/1505.04648 

[2] The Chebyshev method for the implied volatility, K. Glau, P. Herold, D. B. Madan, C. Pötz (2017), http://arxiv.org/abs/1505.04648 

Presenter: Kathrin Glau: Chair of Financial Mathematics, Technical University of Munich


14.15 - 15.00: Approximation Methods for KVA under FRTB Expected Shortfall  

An approximation for forward CVA sensitivities for FRTB SA-CVA capital, combining trade sensitivities (by brute force or AAD) with American Monte Carlo methods to link forward CVA sensitivity with trade sensitivity.  

A regression proxy for forward FRTB SA-CVA capital. This dynamic FRTB SA-CVA capital approximation is based on the observation that the sensitivity calculation is itself a proxy for a 97.5th percentile Expected Shortfall (used under the IMM-CVA method). 

Presenter: To be confirmed


  15.00 - 15.15: Afternoon Break and Networking Opportunities


Conference Closing Presentation:
Damiano Brigo

15.15 - 16.00: Cost of Capital & Valuation: A Target Performance Approach

Presenter: 
Damiano Brigo:
 Chair in Mathematical Finance and Stochastic Analysis, Imperial College London, Dept. of Mathematics 

 


 End of conference