QuantMinds International

Profile

John Hull is an internationally recognized authority on derivatives and risk management and has many publications in this area. His work has an applied focus. In 1999 he was voted Financial Engineer of the Year by the International Association of Financial Engineers. He has acted as consultant to many North American, Japanese, and European financial institutions. He has won many teaching awards, including University of Toronto’s prestigious Northrop Frye award.

Agenda Sessions

Volatility surface movements
May 15, 08:25
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08:25 - 09:05 40 mins

B: Volatility Modelling & Trading

Volatility surface movements

John Hull - Maple Financial Professor Of Derivatives & Risk Management, Joseph L. Rotman School of Management, University Of Toronto
Panel Discussion: Assessing new trends in quant finance
May 16, 09:10
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09:10 - 09:50 40 mins

Plenary

Panel Discussion: Assessing new trends in quant finance

Damiano Brigo - Chair and Co-Head Of Group, Mathematical Finance, Imperial College, London

Vladimir Piterbarg - MD, Head of Quantitative Analytics and Quantitative Development, NatWest Markets

John Hull - Maple Financial Professor Of Derivatives & Risk Management, Joseph L. Rotman School of Management, University Of Toronto

Peter Carr - Department Chair, Finance and Risk Engineering, NYU Tandon School
Workshop leader’s opening remarks
May 17, 09:00
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09:00 - 09:05 5 mins

Workshop: Machine learning in finance

Workshop leader’s opening remarks

John Hull - Maple Financial Professor Of Derivatives & Risk Management, Joseph L. Rotman School of Management, University Of Toronto
Introduction
May 17, 09:05
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09:05 - 10:30 85 mins
Info

Workshop: Machine learning in finance

Introduction

John Hull - Maple Financial Professor Of Derivatives & Risk Management, Joseph L. Rotman School of Management, University Of Toronto

Types of machine learning
Why ML is suddenly so popular in finance
Training, validation and test sets
Linear regression with many features: ridge, lasso, elastic regression. Case study
Bayes classification
Principal components
Supervised Learning
May 17, 11:00
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11:00 - 12:30 90 mins
Info

Workshop: Machine learning in finance

Supervised Learning

John Hull - Maple Financial Professor Of Derivatives & Risk Management, Joseph L. Rotman School of Management, University Of Toronto

Logistic regression. Case study
Support vector machines
Neural networks
Decision trees and random forests
Bagging and boosting; ensemble
The variance-bias trade-off
Reinforcement Learning
May 17, 13:30
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13:30 - 15:00 90 mins
Info

Workshop: Machine learning in finance

Reinforcement Learning

John Hull - Maple Financial Professor Of Derivatives & Risk Management, Joseph L. Rotman School of Management, University Of Toronto

Exploration vs. exploitation
Simple examples of multistage decision making
Bellman equations
Q-learning
Temporal difference learning
Application to trading
Unsupervised learning and review
May 17, 15:30
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15:30 - 17:00 90 mins
Info

Workshop: Machine learning in finance

Unsupervised learning and review

John Hull - Maple Financial Professor Of Derivatives & Risk Management, Joseph L. Rotman School of Management, University Of Toronto

Clustering and k-means algorithm
Other algorithm
Issues in machine learning
Data privacy, biases, ethics
Limitations of machine learning
Challenges of innovation
Workshop leader's closing remarks
May 17, 17:00
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17:00 - 17:15 15 mins

Workshop: Machine learning in finance

Workshop leader's closing remarks

John Hull - Maple Financial Professor Of Derivatives & Risk Management, Joseph L. Rotman School of Management, University Of Toronto

Mr Riccardo
Rebonato Mr Tiziano
Bellini

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Tiziano Bellini

Director

BlackRock

John Hull Maple Financial Professor Of Derivatives & Risk Management, Joseph L. Rotman School of Management at University Of Toronto

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