Risk.net Machine Learning Forum

Risk.net Machine Learning Forum

March 5th 2019: Machine Learning Forum: The latest applications, data &  interpretability

Risk.net Quant Summit Europe is pleased present the 2nd edition of Machine Learning Forum, a workshop-style event designed to provide in-depth analysis on the latest ML/AI applications, challenges and limitations these tools pose, and showcase ideas of how can industry practitioners go about them.

At the Risk.net Machine Learning Forum, we will host multiple senior speakers sharing their experiences, research and opening up a debate about new ML applications in finance, this year, with particular focus on practical use cases, NLP tools, data access and aggregation, limitations and interpretability.

 

Why attend Risk.net Machine Learning Forum:

  • Unique multi speaker format featuring sessions from key industry practitioners;
  • Gain insights into the latest industry applications and what progress has been achieved since the ML boom;
  • Get insights into how to access Big Data and alternative data in financial markets  and how to work with it efficiently when building your models;
  • NLP applications: How are quants successfully harnessing data?
  • Discuss ML/AI limitations and how industry view interpretability issues;
  • Join the Harvest Session with our speakers  at the end of the day and have your questions answered!


Led by:

David Jessop, Managing Director, Global Head of Equities Quantitative Research, UBS
Christian Schwarz, Executive Director, Head of Quant Research, Focus on Machine Learning and Algo Trading, MIZUHO INTERNATIONAL
Giuliano De Rossi,  Head of European Quantitative Research, MACQUARIE GROUP
Saeed Amen, Founder, CUEMARCO

Further speakers to be confirmed

08:20

REGISTRATION & REFRESHMENTS 

09:00

Machine Learning in Finance: Limits and Potentials

  • Artificial intelligence (AI), in particular deep learning, has become a subject of intense media hype
  • Strengths and limitations of machine learning, deep learning and AI more generally
  • Applying deep learning techniques to the investment process
  • A stock selection model that uses neural networks and compare its performance to "classical" machine learning models, such as decision trees and regularised regression
  • Results and contribution to the long-term investment strategies

David Jessop, Managing Director, Global Head of Equities Quantitative Research, UBS

11:00

MORNING BREAK

11:30

Data challenges: Understanding complexities and importance of your approach to alternative data sources

Speaker to be confirmed

1:00

LUNCH & OPPORTUNITY TO NETWORK

2:00

I. Machine learning in algorithmic credit trading

  • Practical ML use cases
  • Data access and aggregation
  • Limitations & interpretability
  • How to build political capital and a positive feedback loop

Christian Schwarz, Executive Director, Head of Quant Research, MIZUHO INTERNATIONAL
 

II. New research on applications of NLP

Giuliano De Rossi,  Head of European Quantitative Research, MACQUARIE GROUP

3:30

AFTERNOON BREAK

4:00

Big Data and using machine readable news to trade FX

  • The concept of Big Data and alternative data in finance
  • Generating  trading signals for FX spot
  • Relationship between news and FX volatility
  • Case study on using  news to forecast volatility around ECB and FOMC meetings

Saeed Amen, Founder, CUEMARCO

5:00

HARVEST SESSION & Q&A

Each presenter will summarise key takeaways form their presentations and will open up for the Q&A and final thoughts on the industry’s adoption of ML tools!
 

5:30

END OF THE SEMINAR