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 08:30: Morning Welcome Coffee


To be confirmed 

09.00 - 09.45: Keynote Speech

Presenter: Vacslav Glukhov, PhD: Executive Director, Linear Quantitative Research, Global Equities, J.P. Morgan (To be confirmed)

Topics in Self-Learning Agents and Traditional Quantitative Models in Finance  

  • What can we draw from our experience of training and running an industry first self-learning agent for electronic order execution?
  • Will traditional hand-crafted heuristic- and quant-based execution algorithms go extinct within 10 years?
  • Does the success of ML and AI agents in finance indicate the eventual demise of traditional quantitative models?
  • Practical aspects of using feeder models and heuristics in AI agents for trading applications.
  • Do we have practical solutions for the equivalence puzzle in Neural Nets

09.45 - 10.30: XVA, AAD, Intial Margin & FRTB Panel:   


  • Alexandre Antonov: Director, Standard Chartered Bank


  • Andrew Green: Managing Director and XVA Lead Quant, Scotiabank
  • Andrew Mcclelland: Director, Quantitative Research, Numerix
  • Ignacio RuizFounder & CEO, MoCaX Intelligence
  • Gilles Artaud: Market and Counterparty Risk, Credit Agricole-CIB
  • Assad Bouayoun: Director, XVA Senior Quant, Scotiabank


  • Initial Margin, a push for more model standardization? Good or bad?
  • How do you interpret the regulatory requirements to validate and monitor SIMM, and how would a firm best go about meeting those requirements?
  • SIMM relies on counterparts calculating their own sensitivities. Do the panelists foresee that causing any problems meeting requirements or additional costs?
  • Discuss Implementing SIMM for Non Cleared Initial Margin Rules
  • Explore the interaction between MVA and XVAs: 
    • What does MVA mean for XVA overall? Can you simplify the valuation adjustments?
    • Understand the impacts of initial margin, bi-lateral initial margin and MVA on business models
    • Is it possible to ensure transparency of derivative pricing calculation to reduce disputes 

 XVA & Machine Learning    

  • Discuss the existing and potential applications of machine learning in XVA

Discuss the Impact of FRTB on XVA’s: 

  • How will the latest proposed regulations impact CVA calculations
  • Review what are the most important factors to take into account when calculating the new CVA
  • Calculating & Implementing FRTB CVA. How will it affect banks’ internal modelling for counterparty risk and risk management?

10.30 – 11.00: Morning Break and Networking Opportunities

11.00 - 11.45: Using Machine Learning Methods for Volatility Trading 

• Statistical models for realized volatility estimation and forecast
• Model selection using machine learning
• Supervised machine learning and learning to rank
• Applications for volatility trading and asset allocation 

Presenter: To be confirmed

11.45 - 12.30: MVA using Machine Learning Techniques   

  • Initial Margin: why and what?
  • IM Impacts on pricing (on different valuation adjustments
  • Brute force computations; more elaborate techniques: AAD, American Monte Carlo
  • How can Machine Learning help?   

Presenter: Gilles Artaud: Market and Counterparty Risk, Credit Agricole-CIB

 Lunch: 12.30 - 13.30

13.30 - 14.15: Vectorised Approach to Tree-Based Machine Learning Problems 

Presenter: Jan Novotny: eFX Quant, Global Banking and Markets, HSBC

14.15 - 15.00: Industry Breakthroughs in Quantum Computing: 

An inside glimpse into how quantum computing is starting to be applied to finance  

Presenter: Alexei Kondratyev: Managing Director, Head of Prime Services Analytics, Standard Chartered Bank & Davide Venturelli: Quantum Computing Lead, NASA-USRA Quantum AI Lab (To be confirmed)

15.00 – 15.15: Afternoon Break and Networking Opportunities

15.15 - 16.00: Closing Presentation 

Examining Real Possibilities and Applications of Distributed Ledger Technologies 

  • Which applications are game changing for finance and why?

Presenter: Massimo Morini: Head of Interest Rate and Credit Models, Banca IMI 

  End of Conference