May 6 - 7, 2020  |  Navy Pier, Chicago, IL

 

 

 
2000+
Attendees
250+
Speakers
75+
Exhibitors
120+
Sessions
 
1500+
Meetings

WHAT IS DATA & AI?

 

As more data becomes available, firms are finding unique ways to implement datasets into alpha generating strategies and as these datasets become more complex the use of AI and Machine Learning techniques are instrumental to avoid overfitting. Our Data & AI portions of the show will focus on proper use of data, standardization, and various use cases for AI and Machine Learning.

 

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DATA & AI AGENDA

 

Data, Wednesday 6 May 2020

Tom Anderson
08:50

Chairman’s Opening Remarks

Tom Anderson, President And Chairman Of The Board, Drawbridge Lending
Panel discussion
Data
11:20

The Data Process – how data moves from research to production

·Sourcing – receiving data from research teams and outside vendors·Onboarding – having the right team and technology to bring in new data·Data monitoring – ensuring the highest quality input throughout the process·Execution – turning alpha signals into usable models that make trades
Moderator: Morgan Slade, Chief Executive Officer, CloudQuant
Eli Bernstein, Head Of Data Architecture, Tudor Investment Corporation
Data
12:00

Data Standardization – setting up the industry for easier use of market information

·Data descriptions – better understanding of datasets prior to vendor calls·Structured API – finding a common format for easy access to data to save time and reduce costs·Compliance – covering best practices with vendor onboarding
Data
12:20

4) Quantitative and Fundamental analysis – how you can use data to support a quantamental investment process?

David Mascio, Managing Founder And Principal, Della Parola Capital Management
Ray Carroll, Chief Investment Officer, Neuberger Berman Breton Hill
John Slazas, Chief Investment Officer, DARMA Capital
Jimmy Yang
Data
12:20

5) Data Visualization – using tools for clearer alpha

Jimmy Yang, Global Head Of Credit And Operational Risk Analytics, BMO Financial Group
Jonathan Shaw, Risk Manager, TransMarket Group LLC
Data
12:20

6) Alternative Data trials and tribulations – what works and what doesn’t?

Panel discussion
Data
14:20

Data Sourcing – separating the relevant from the noise

·Web-scrapping – how is online behavior helping to develop untapped alphas?·Identifying credibility – finding appropriate sources to avoid ‘garbage in garbage out’·Vendor solutions – working with data providers to customize datasets
Andrew Curto, Trade Development Manager, Belvedere Trading
Ray Carroll, Chief Investment Officer, Neuberger Berman Breton Hill
Panel discussion
Data
15:00

Data Infrastructure – determining between in-house and outsourced data

·In-house Storage – building data management systems that meet the demand of alpha generation·Outsourcing – which vendors have the best server connectivity for efficient analysis?·Integration – creating clear channels for new datasets to be most useful in conjunction with less recent data
last published: 29/Jan/20 08:35

 

 

Data, Thursday 7 May 2020

Sal Abbasi
Data
11:20

Quant Strategy Research Process

Sal Abbasi, Co-Founder, Coatbridge Capital
Alex Popovici, Head Of Quantitative Trading, Clear Capital Group
Panel discussion
Data
11:40

Smart Beta – identifying true factor exposure and understanding factor correlation

·Factor selection – deciding which inputs matter most in your analysis and how do you know if they are performing well?·Risk horizon – how do you allocate based on risk premia?·Keeping your edge - how can a strategy that everyone knows about still work?
George Mylnikov, Head Of Quantitative Research, Windhaven Investment Management
Maxwell Rhee, Senior Quantitative Researcher, Citadel
Morgan Slade, Chief Executive Officer, CloudQuant
David Mascio, Managing Founder And Principal, Della Parola Capital Management
Data
12:20

4) How to launch a CTA or fund

Data
12:20

5) Stat Arb – what factors matter most?

Data
12:20

6) Event-based Trading – running models based on current events and other macro issues

last published: 29/Jan/20 08:35

 

 

A.I., Wednesday 6 May 2020

Tom Anderson
08:50

Chairman’s Opening Remarks

Tom Anderson, President And Chairman Of The Board, Drawbridge Lending
Panel discussion
A.I.
11:20

Testing fairness – finding the difference between alpha and coincidence

·Reading the data - what causes the positive performance?·Reliable algos – creating predesign equations to make your model reproducible·Finding the root cause – developing layers of AI to create confidence levels
Howard Getson, Chief Executive Officer, Capitalogix Trading
Alexander Kment, Financial Engineer, Hull Tactical Asset Allocation
Brian Peterson, Managing Member, Braverock Investments, LLC
Jim Creighton
A.I.
12:00

Measuring Prediction Accuracy – And Its Impact on Portfolio Construction

Jim Creighton, Chief Investment Officer, Creighton AI
A.I.
12:20

7) Humans and Machines – how supervised/unsupervised should ML algos be?

Hugo Kruyne, Vice President And Chief Operating Officer, Select Vantage Inc
A.I.
12:20

8) AI/ML for Forecasting – using new technologies for better price prediction models

A.I.
12:20

9) Variable Selection – influencing your models before inserting the dataset

Panel discussion
A.I.
14:20

Transparency – how can algos using AI explain blackbox trading?

·TCA – discovering what factors are going into the decision-making process·Loopholes – how to address ML that takes advantage of grey areas and the dangers of doing so·Staying in charge – how do you make sure that your evolving AI doesn’t change the rules on you?
Hugo Kruyne, Vice President And Chief Operating Officer, Select Vantage Inc
Che Guan, Data Scientist, Raymond James & Associates
Michael Mescher, Founder, Gammon Capital LLC
Panel discussion
A.I.
15:00

More than trading – other use cases for AI and machine learning

·Market Data Predictions – developing models to predict financial factors for trade-making decisions·Asset allocation – how can machine learning minimize risk and maximize returns?·Trade strategy layering – adding an AI-based layer designed to mitigate risk
Ernest Chan, Principal, QTS Capital Management
Chris Doloc, Founder And Principal, FINTELLIGEX
Peng Cheng, Head Of Machine Learning Strategies, J.P. Morgan
last published: 29/Jan/20 08:35

 

 

Data, Thursday 7 May 2020

Sal Abbasi
Data
11:20

Quant Strategy Research Process

Sal Abbasi, Co-Founder, Coatbridge Capital
Alex Popovici, Head Of Quantitative Trading, Clear Capital Group
Panel discussion
Data
11:40

Smart Beta – identifying true factor exposure and understanding factor correlation

·Factor selection – deciding which inputs matter most in your analysis and how do you know if they are performing well?·Risk horizon – how do you allocate based on risk premia?·Keeping your edge - how can a strategy that everyone knows about still work?
George Mylnikov, Head Of Quantitative Research, Windhaven Investment Management
Maxwell Rhee, Senior Quantitative Researcher, Citadel
Morgan Slade, Chief Executive Officer, CloudQuant
David Mascio, Managing Founder And Principal, Della Parola Capital Management
Data
12:20

4) How to launch a CTA or fund

Data
12:20

5) Stat Arb – what factors matter most?

Data
12:20

6) Event-based Trading – running models based on current events and other macro issues

last published: 29/Jan/20 08:35

 

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