School Events

21.05.2018

Financial applications of Machine Learning at Man AHL

Abstract

In this talk I will explain how Man AHL – one of the world’s largest systematic investment managers – uses machine learning to derive new algorithms for both alpha capture and trade execution. We discuss the Oxford-Man Institute of Quantitative Finance – our unique decade-long collaboration with the University of Oxford – and then examine some of the main hurdles that have to be overcome in applying machine learning within financial forecasting. We aim to dispel the often encountered “black box” criticism of machine learning by demonstrating a key diagnostic for interpreting what a machine learning model will do next. We illustrate the discussion with a selection of machine learning examples taken from Man AHL’s systematic research and trading portfolio.

About the Speaker

Anthony Ledford is Man AHL’s Chief Scientist and Academic Liaison. He is based in the Man Research Laboratory (Oxford) and has overall responsibility for AHL’s strategic research. Anthony has worked for Man AHL since 2001 on research projects spanning trading models, automated execution, portfolio optimisation and risk monitoring. Prior to that he was Reader in Statistics at the University of Surrey. Dr Ledford read Mathematics at Cambridge University, holds a PhD from Lancaster University in the development and application of multivariate extreme value methods and is a former winner of the Royal Statistical Society’s Research Prize.

Dr Anthony Ledford
Dr Anthony Ledford

Event Details

Date 21 May 2018 (Monday)
Time 1:30 - 2:30 pm (light lunch will be provided at 1:00 pm)
Venue G003, G/F, Lee Shau Kee Business Building
Admission All HKUST staff and students
Language English

Enrollment

Please fill in the online registration form.  

Enquiries

For questions, please email bmschool@ust.hk.

Arrangement of event in case of Bad weather
All programs would be suspended once the Rainstorm Black Warning or Typhoon Signal No.8 (or above) is hoisted, or there is information that the Warning or Signal would be hoisted within 1 to 2 hours before the event starts. Notification on reschedule or refund arrangement would be announced in due course.