Deep Hedging: from theory to practice

Dr Hans Bühler (JP Morgan)
Wednesday 24 April 2019, 18:00-19:00.

 

The seminar will be followed by a reception.

This event was live streamed, and the recording is available here.

Please use the link here for the slides.

Abstract

We discuss deep reinforcement learning methods for the hedging of derivatives portfolios. 

One of the  challenges involved is the joint simulation of scenarios for derivatives prices together with their underlyings, which we discuss in some detail.

Based on joint work with Baranidharan Mohan and Ben Wood.

 

Speaker

Hans Bühler is a Managing Director at JP Morgan, where he leads the “Analytics, Automation and Optimization” program in Equities and runs the Equities and Investor Services Data Analytics Quantitative Research team. His mandate is data-driven business transformation across derivatives, cash equity, electronic trading, prime, and securities services using both modern machine learning and classic derivatives analytics, AI-driven electronic execution and derivative risk management, and the use of modern machine learning techniques for engaging with clients. His team is behind JP Morgan’s LOXM AI effort in electronic trading. Before joining JP Morgan in 2008, Hans worked for seven years at Deutsche Bank. He has a PhD in Financial Mathematics from Technical University in Berlin and a Masters degree in Stochastic analysis from Humboldt University Berlin.

 

Venue

Citi Stirling Square
5-7 Carlton Gardens
London SW1Y 5AD

 

We are now fully booked for this event. However please email mathfin@maths.ox.ac.uk if you would like to be put on the wait-list.