Antoine Savine

Head of Analytics at HRT

Speaker

Antoine Savine leads Macro Analytics at Hudson River Trading (HRT) after ten years with Danske Bank and twelve with BNP-Paribas, as Global Head of Derivatives Research.

Antoine wrote the book on Automatic Adjoint Differentiation (AAD): Modern Computational Finance (Wiley 2018), and co-created 'Differential Machine Learning' (Risk 2020-21), which combines AAD with modern Machine Learning to automate pricing and risk of arbitrary Derivatives and resolve bottlenecks in risk reports and regulations like XVA, CCR, FRTB or SIMM-MVA.

Antoine holds a PhD in Mathematics from Copenhagen University, where he taught graduate classes in Volatility, Computational Finance and Machine Learning in Finance for six years.

He is best known for his work on volatility and multifactor interest rate models. He was also influential in the adoption of cashflow scripting, the application of generalized derivatives in stochastic volatility models, and the wide adoption of AAD in the financial industry.

Antoine's many publications and conferences are widely attended in the Finance industry and help shape progress in risk management practices.