This site is part of the Informa Connect Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them. Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 3099067.

Quant Finance
search
Video

New techniques in risk modelling

Posted by on 22 February 2023
Share this article

Complex environments require complex systems to model. In some cases machine learning techniques can be applied successfully, in other situations, we may need to address them individually. Join experts from QuantMinds International 2022 and discover new techniques in risk modelling.

Projecting exposures and margin: Getting risk models and pricing models to play nice

Andrew McClelland, Director, Quantitative Research at Numerix, presents his work on projecting off a dedicated risk model (discrete-time PCA etc.), the complex translation between the risk model and the pricing model on a per-scenario basis. Learn about:

  • The problem of projecting exposures and margin requirements off a pricing model (arbitrage free etc.) is well understood
  • We have a range of numerical techniques (e.g. LSMC) to do this efficiently when closed-form representations are not available
  • But what if we are projecting off a dedicated risk model (discrete-time PCA etc.)?
  • Translating between the risk model and the pricing model on a per-scenario basis is complex, and it may involve calibration
  • We investigate this problem and identify a natural classification according to the type of risk model employed
  • Some classes are amenable to simple extensions of standard techniques while others will require more advanced approaches

Practical implementation of machine learning techniques for risk and pricing

Enjoy this session from QuantMinds International, in which Christian Kappen, Manager at d-fine, shares his work on practical implementation of machine learning techniques for risk and pricing. Learn about:

  • Machine learning in finance – A retrospection
  • Machine learning in risk and pricing – The supervisory perspective
  • Machine learning in pillar II market risk – A pre-study at NRW.BANK
    • Description of the use case
    • Fast pricing of Bermudians in VaR: Machine learning approaches
    • Model lifecycle management
    • Technical implementations
    • Results
  • Outlook

Share this article

Sign up for Quant Finance email updates

keyboard_arrow_down