Antoine Savine discussed his book, Modern Computational Finance, at MOI Global’s Meet-the-Author Summer Forum 2019. Antoine is a Quantitative Researcher at Danske Bank.
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About the book:
Arguably the strongest addition to numerical finance of the past decade, Algorithmic Adjoint Differentiation (AAD) is the technology implemented in modern financial software to produce thousands of accurate risk sensitivities, within seconds, on light hardware.
AAD recently became a centerpiece of modern financial systems and a key skill for all quantitative analysts, developers, risk professionals or anyone involved with derivatives. It is increasingly taught in Masters and PhD programs in finance.
Danske Bank’s wide scale implementation of AAD in its production and regulatory systems won the In-House System of the Year 2015 Risk award. The Modern Computational Finance books, written by three of the very people who designed Danske Bank’s systems, offer a unique insight into the modern implementation of financial models. The volumes combine financial modeling, mathematics and programming to resolve real life financial problems and produce effective derivatives software.
This volume is a complete, self-contained learning reference for AAD, and its application in finance. AAD is explained in deep detail throughout chapters that gently lead readers from the theoretical foundations to the most delicate areas of an efficient implementation, such as memory management, parallel implementation and acceleration with expression templates.
The book comes with professional source code in C++, including an efficient, up to date implementation of AAD and a generic parallel simulation library. Modern C++, high performance parallel programming and interfacing C++ with Excel are also covered. The book builds the code step-by-step, while the code illustrates the concepts and notions developed in the book.
About the author:
Antoine Savine is a mathematician, academic and professional with financial derivatives. After globally running quantitative research for a leading French investment bank, Antoine joined Jesper Andreasen in Copenhagen to participate in the development of Danske Bank’s systems, which won the In-House System of the Year 2015 Risk award.
Antoine Savine also lectures at Copenhagen University’s Masters of Science in Mathematics-Economics, with topics including Volatility Modeling and Numerical Finance, for which he wrote the curriculum AAD and Parallel Simulations with Wiley.
Antoine Savine holds a Masters in Mathematics from the University of Paris-Jussieu and a PhD in Mathematics from Copenhagen University. He is best known for his influential work on risk management, volatility, multi-factor interest rate models, scripting, AAD and parallel Monte-Carlo.
Antoine’s current research interests are in combining financial modeling with deep learning, in order to unify derivatives risk management with capital calculations, CVA/XVA, CCR (counterparty credit risk), FRTB (fundamental review of the trading books) and MVA (initial margin valuation adjustment) and resolve related numerical and computational bottlenecks. All of those formed the major theme of the QuantMinds 2019 conference in Vienna, where Antoine chaired the Numerical and Computational Finance stream, emphasizing Danske Bank’s unique vision of One Quantitative Engine for the risk management of derivatives and regulations.