Javascript Menu by Deluxe-Menu.com
World Business Strategies Logo

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: Back to CVA – Two Current Issues

Jon Gregory

  • Loss given default
    • Impact of different LGD assumptions
    • Structural seniority and waterfall priority
    • Entry price and exit price
  • Wrong-way risk (WWR)
    • WWR in cross currency swaps
    • New evidence from the Quanto CDS market on Japanense names
    • Implied jump sizes across sector and rating
    • Evidence from the FX options market

Presenter: Jon Gregory: Independent xVA Expert 


 10.30 - 11.00: Morning Break and Networking Opportunities


11.00 - 12.30:  Stochastic Automatic Differentiation: AAD for Monte-Carlo Simulation and Exact and Fast ISDA SIMM MVAChristian Fries

Part 1: Stochastic Automatic Differentiation: AAD for Monte-Carlo Simulation  

  • Automatic Differentiation - Introduction and Review
    • Forward Automatic Differentiation (AD)
    • Backward Automatic Differentiation (AAD)
  • Stochastic Automatic Differentiation – AD/AAD for Monte-Carlo Simulations
    • Pathwise Operators
    • Expectation Operator
    • Conditional Expectation Operator
    • Indicator Function
  • Application (I): Automatic Differentiation of Bermudan options, XVA, etc.
    • Example: Bermudan digital option
    • Differentiation of the 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 

 Part 2: Exact and Fast MVA (with or without AAD)  

  • Fast AAD Forward Sensitivities (aka Future Sensitivities)
    • 5 Million Sensitivities in 10 Seconds
    • Future Sensitivities: Forward Differentiation versus Backward Differentiation
  • Application (II): Fast and Efficient ISDA-SIMM MVA
    • ISDA-SIMM
    • MVA for Swaps, Swaptions and Bermudans
  • Melting Sensitivities: Fast Forward IM Approximations (with or without AAD)
    • The Computationally Expensive Parts in MVA Calculations
    • Transformation from Model Sensitivities to Market Rate Sensitivities
    • A simple Replication Argument for MVA Approximations
  • MVA for CCPs 

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: The Pricing of XVA and Stochastic Corporate LiabilitiesImage result for ANDREY CHIRIKHIN

Presenters: Andrey Chirikhin: PhD, MBA, Founder and CEO, Quantitative Recipes

  • Mainstream pricing of XVA effectively considers it a contingent CDS, i.e. a derivative.
  • This is partly correct for marking to market of XVA on running deals.
  • It is generally incorrect for pricing marginal XVA, because marginal credit risk is created in this case, which cannot be replicated and priced as a derivative, at least in the reduced-form model setup.
  • We illustrate how one can extend a structural model to consistently treat moth marginal and running XVA theoretically, which is possible here because hedging is done using the firm’s assets directly.
  • The practical application of this approach is not creation of a production-grade XVA model, but formulation of requirements on accounting and regulatory treatment of XVA, as well as identification of boundaries of applicability and limitations of the mainstream XVA pricing approaches.

  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 

  • Moving beyond the replication approach
  • Target performance: RAROC-type analysis
  • Cost of capital via indifference to RAROC type metrics
  • Whole bank view vs Shareholders view

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


 End of conference