May 20, 2020 8:00 PM
Registration deadline: May 20, 2020

Deep Learning Applications in Valuation and Risk of Trading Books

by Antoine Savine, PhD - Superfly Analytics at Danske Bank, Lecturer and Author | Online

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Antoine Savine, PhD - Superfly Analytics at Danske Bank, Lecturer and Author

Antoine Savine is a French mathematician, academic and a leading practitioner with financial derivatives. Antoine was the Global Head of Derivatives Research at BNP-Paribas for 10 years, before moving on to Danske Bank in Copenhagen. Antoine is an expert C++ programmer and one of the key contributors to Danske Bank's xVA system, which won the In-House System of the Year 2015 Risk award. His current interests are in combining Deep Learning with financial modeling to unify derivatives risk management with CVA/XVA, FRTB, CCR, MVA and other capital calculations, and resolve related numerical and computational bottlenecks. His current research is known under the name "Deep Analytics". Antoine lectures Volatility and Numerical Finance at Copenhagen University since 2016. He is a regular speaker and chairman in professional and academic conferences in quantitative finance, including QuantMinds, RiskMinds and World Business Strategies. Antoine authored the series Modern Computational Finance with John Wiley and Sons, three volumes teaching financial quants, derivatives and risk professionals the essential mathematical, modeling, risk management and programming skills of modern finance. The first volume, released 2018, covers Automatic Adjoint Differentiation (also called back-propagation in Machine Learning), efficient generic Monte-Carlo simulations and parallel computing in modern C++. The other two, planned 2020, cover scripting and the combination of the Least-Square Method (LSM) with with Deep Learning. A PhD in Mathematics from Copenhagen University, Antoine Savine is best known for his work on volatility with Bruno Dupire, scripting with Jesper Andreasen and Leif Andersen, multi-factor interest rate models with Marek Musiela, or automatic differentiation and parallel Monte-Carlo simulations. He was influential in the adoption of scripting, the application of generalized derivatives in the context of local and stochastic volatility models, and the wide adoption of AAD in financial systems. Antoine is part of the 'Superfly Analytics' group at Danske Bank, and he will be presenting the work and achievements of the department during his ESS talk.

Registration deadline: May 20, 2020

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