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IAQF & Thalesians Seminar Series: Ryan Ferguson - Deeply Learning Derivatives

  • 02 Mar 2020
  • 6:00 PM
  • Fordham Gabelli School of Business, McNally Amphitheatre 140 West 62nd Street New York, NY 10023

Registration


Registration is closed


Deeply Learning Derivatives: 
Using DNNs to Compute Valuations

and Risk Sensitivities 1,000,000x Faster



A Talk by  

Ryan Ferguson


Monday, March 2, 2020

5:45 PM Registration

6:00 PM Seminar Begins
7:30 PM Reception



    

Abstract

This 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.


     

Biography

Ryan Ferguson is Founder and CEO at Riskfuel, a capital markets focused startup that is developing ultra-fast AI-based valuation technologies.


Previously, Ryan was Managing Director and Head of Securitization, Credit Derivatives and XVA at Scotiabank. Prior roles have included credit correlation trading and managing the equity derivatives trading desk. Ryan began his career with positions in risk management and financial engineering. Ryan has a PhD in Physics from Imperial College, and a BASc and MASc in Electrical Engineering from the University of Waterloo.



Acknowledgments

Special thanks to the Fordham University Gabelli School of Business for hosting and sponsoring the seminar. 


About the Series

The IAQF's Thalesians Seminar Series is a joint effort on the part of the IAQF (www.iaqf.org) and the Thalesians (www.thalesians.com). 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. This goal is accomplished by hosting seminars where leading practitioners and academics present new work, and following the seminars with a reception to facilitate further interaction and discussion. 

 


Registration Fees:
Complimentary for IAQF members through this site

Non-Members: $25.00 by registering through this site