Antoine Savine is a French mathematician, academic and a leading derivatives research professional with Danske Bank in Copenhagen. Antoine also teaches Volatility and Computational Finance at Copenhagen University. He is the author of Modern Computational Finance with John Wiley and Sons.
Antoine holds a PhD in Mathematics, and is best known for his work on volatility and interest rate models. He was influential in the development of cashflow scripting, the application of generalized derivatives to volatility, and the wide adoption of AAD in financial systems.
In this event hosted by Bruno Dupire at Bloomberg’s headquarters, I will present advances in differential machine learning at 17:40. My talk will be followed at 18:30 by a tribute to the great mathematician Marco Avellaneda by some of his closest pairs, including Bruno, Raphael Douady, Mike Lipkin and Nassim Taleb. The talks are followed by a reception at 19:00.
Differential regression illustrates the main ideas of differential machine learning, and demonstrates its power in a very simple context. We posted a small article with code on Google Colab, run it here: