Bloomberg Quant (BBQ) Seminar Series – June 2022
In this seminar chaired by Bruno Dupire, Antoine Savine, Chief Quantitative Analyst of Danske Bank, will present the keynote "Differential Machine Learning." It will be followed by a tribute to Marco Avellaneda, dearly departed Professor of Mathematics at New York University.
Keynote
Antoine Savine
Chief Quantitative Analyst
Danske Bank
Differential Machine Learning
This presentation addresses pricing and risk with modern machine learning. We discuss applications and limits of ML algorithms such as basis function regression, PCA or neural networks, and develop novel algorithms that combine adjoint differentiation (AAD) with ML to effectively resolve longstanding pricing challenges, and bottlenecks of computations like XVA, back-or-forward-testing or dynamic risk reports.
In particular, we introduce Differential Basis Regression, Relevant Component Analysis and Twin Networks, developed jointly with Brian Huge, and published in the two Risk.net articles “Differential Machine Learning: The Shape of Things to Come” and “Axes that Matter: PCA with a Difference,” as well as an upcoming book with Chapman & Hall.
Tribute
Marco Avellaneda 1955 – 2022
It is with deep sadness that we learned of the passing on June 11th of Marco Avellaneda — great scientist, inventor of the Uncertain Volatility Model, and professor of mathematics. His contributions to the field of quantitative finance are numerous. We will remember the man and the researcher in a conversation with Raphael Douady, Bruno Dupire, Mike Lipkin, and Nassim Taleb, sharing their memories of Marco.
Agenda
5:30 pm - Welcome
Bruno Dupire | Head of Quantitative Research, Bloomberg
5:40 pm - Keynote Q&A
Antoine Savine | Chief Quantitative Analyst, Danske Bank 6:30 pm - Tribute to Marco Avellaneda
Raphael Douady, Bruno Dupire, Mike Lipkin, and Nassim Taleb share their memories of Marco.
Speakers
Bruno Dupire
Head of Quantitative Research
Bloomberg
Bruno Dupire is the Global Head of Quantitative Research, CTO Office at Bloomberg, which he joined in 2004. Prior to this assignment in New York, he has headed the Derivatives Research teams at Société Générale, Paribas Capital Markets and Nikko Financial Products where he was a Managing Director. He is best known for having pioneered the widely used Local Volatility model (simplest extension of the Black-Scholes-Merton model to fit all option prices) in 1993 and the Functional Itô Calculus (framework for path dependency) in 2009. He is a Fellow and Adjunct Professor at NYU and he is in the Risk magazine “Hall of Fame”. He is the recipient of the 2006 “Cutting edge research” award of Wilmott Magazine and of the Risk Magazine “Lifetime Achievement” award for 2008. He runs and organizes the Bloomberg Quant (BBQ) seminar, the largest monthly event of this kind.
Antoine Savine
Chief Quantitative Analyst
Danske Bank
Antoine Savine is Chief Quantitative Analyst with Superfly Analytics at Danske Bank, after 25 years in leadership roles with global investment banks. He wrote the book on automatic differentiation (AAD) Modern Computational Finance and co-developed differential machine learning, and was also influential in volatility modelling and various areas of numerical finance. Antoine holds a PhD in mathematical finance from Copenhagen University, where he teaches derivatives models, computational finance, and machine learning in finance.