Join Ryan as he lectures on Deeply Learning Derivatives in NYC at the IAQF. His talk explores the performance of deep neural networks in approximating pricing functions in the context of three major approaches currently used to accelerate pricing: GPUs, adjoint algorithmic differentiation and analytic function approximation. Examples will be drawn from a range of asset classes, and will demonstrate the current state of the art. It promises to be a very interesting and informative talk.
Deeply Learning Derivatives
a talk by
Monday March 2, 2020
5:45 PM Registration
6:00 PM Seminar Begins
7:30 PM Reception
The IAQF’s Thalesians Seminar Series is a joint effort on the part of the IAQF and the Thalesians. The goal of the series is to provide a forum for the exchange of new ideas and results related to the field of quantitative finance.
The IAQF is a not-for-profit, professional society dedicated to fostering the profession of quantitative finance by providing platforms to discuss cutting-edge and pivotal issues in the field. Founded in 1992, the IAQF is composed of individual academics and practitioners from banks, broker dealers, hedge funds, pension funds, asset managers, technology firms, regulators, accounting, consulting and law firms, and universities across the globe.