See a brief, non-technical abstract on QuantMinds page here. The 6-hour workshop is a technical one. We will discuss the mathematics of deep learning and back-propagation, and the application of AAD with implementations in Python/TensorFlow and C++. The presentation slides are found on my GitHub repo (Intro2AADinMachineLearningAndFinance.pdf), together with supplementary material: code, spreadsheets and notebooks in the folder ‘Workshop’: https://github.com/asavine/CompFinance
The event was arranged by Blanka Horvath, author of Deep Learning Volatility, where the matter of quick European option pricing in rough volatility models is resolved with deep learning methods. Thank you, Blanka.
Registration is absolutely free, but seating is limited to 40 people. I am looking forward to meet an audience interested in the most recent additions to computational finance.
I am working on a set of exercises and assignments for the chapters of the Modern Computational Finance book. In the meantime, interested readers will find below the final hand-in for the computational finance lecture of autumn 2018 at Copenhagen University, where the book is used as curriculum:
The RiO 2018 conference in mathematical finance, organized by IMPA, was held in Buzios, Rio de Janeiro, Brazil, on 24-28 November 2018, to celebrate the 60th birthday of Bruno Dupire, one of the most influential figures in the history of financial derivatives. The event gathered a number of leading scientists and professionals in one of the most productive and satisfying conferences of the year.
As one of his original alumni, I was given the responsibility to retrace some of Bruno’s ground breaking innovations, and, as a lecturer in Volatility, put them in perspective in the context of volatility modeling and derivatives trading.