Conference Day One: March 19 2019

7:45 am - 8:50 am Welcoming tea, coffee and registration

KEYNOTES & OPENING PLENARY SESSIONS

8:50 am - 9:00 am Chair's opening remarks

9:00 am - 9:20 am Opening keynote: Outlook for the hedge fund industry: survival of the leanest or the most tech savvy?


  • Evaluation: What does a buy side investor look for in quantitative strategies
  • Analysis: Finding risk, uniqueness and maintaining a diverse yet unbiased holding: the challenges of asset allocation 
  • Risk: Meeting your mandate while incorporating technologically forward investment strategies
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Joseph Simonian

Director of Quantitative Research
Natixis Investment Managers

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Amit Soni

Director
New York Life Investments

10:00 am - 10:30 am Interview: Learn from this industry icon as they share their experience and insights

Sandy Rattray - Chief Investment Officer, Man Group

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Sandy Rattray

Chief Investment Officer
Man Group

10:30 am - 11:10 am Networking refreshment break in the exhibition area

MORNING SESSIONS

11:10 am - 11:30 am Keynote: A new breed of investor: The development and disruption of asset management through machine learning techniques

Marcos López de Prado - Principal and Head of Machine Learning, AQR Capital Management
  • The new model: What do you really need to launch a new age hedge fund?
  • Practical recent examples and insights into what it takes to succeed and common pitfalls to avoid
  • The best and worst attributes of AI: Where do funds go wrong?
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Marcos López de Prado

Principal and Head of Machine Learning
AQR Capital Management

  • How to reach the best people and the top minds
  • Understanding that all data scientists and quants are not created equal: what looks like a data scientist may not be!
  • How to create a culture that will entice them to join and stay with you: understand your value proposition as an employer
  • Motivating your workforce to share their best ideas, and building a culture of collaboration in a typically combative and siloed industry
  • Considering the factors that will affect retaining and motivating top talent
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Afsheen Afshar

Former Chief Artificial Intelligence Officer and Senior Managing Director
Cerberus Capital Management

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Dan Furstenberg

Global Head of Hedge Fund Distribution & Data Strategy
Jefferies

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Nitish Maini

General Manager, Virtual Research Centre & Vice President, Portfolio Manager
WorldQuant

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Richard Pook

Partner
Dore Partnership

12:10 pm - 12:30 pm Keynote: "Big Data" is the new currency

Armando Gonzalez - CEO, RavenPack
The way data is collected, anonymized and monetized largely without the owner’s permission is ready to be disrupted providing many benefits to hedge fund data buyers.  This presentation provides a pathway for the individual to control and share in the value their data creates, and for data users to gain access to richer more specific data sets.
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Armando Gonzalez

CEO
RavenPack

12:20 pm - 1:30 pm Networking lunch in the exhibition area


AFTERNOON STREAMS


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Michael Marrale

Chief Executive Officer
M Science LLC

  • Usefulness of data – evaluating the landscape and the trends
  • Filtering and working with vendors: 
  • Excessive demand for newer/more interesting data sources places the onus of data prep firmly on the purchaser whilst low quality/inconsistent data gives a low conversion rate to prospective sources. How can you work with your supplier to provide the product you need?
  • Evaluating the pros and cons of searching for the foundations of specific trade ideas vs ‘playing’ with new and interesting concepts
  • Best data sourcing practices

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Olga Kokareva

Head of Data Sourcing and Strategy
Quantstellation

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Robert Morse

Head of Data Strategy and Sourcing
PDT Partners

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Lisa Schirf

Former COO Data Strategies Group and AI Research
Large Global Hedgefund

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Stewart Stimson

Head of Data Strategy
Jump Trading

STREAM A

2:15 pm - 2:25 pm Innovation in Alt Data
Tammer Kamel - CEO & Founder, Quandl

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Tammer Kamel

CEO & Founder
Quandl

STREAM A

2:25 pm - 2:40 pm Innovation in Alt Data
Daryl Smith - Head of Research, Neudata

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Daryl Smith

Head of Research
Neudata

STREAM A

2:40 pm - 2:50 pm Innovation in Alt Data
Greg Skibiski - Founder & CEO, Thasos Group

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Greg Skibiski

Founder & CEO
Thasos Group

STREAM A

2:50 pm - 3:30 pm Panel discussion: What are the next hot data sources/ regions? What are the different business models that are emerging?
Tammer Kamel - CEO & Founder, Quandl
Rado Lipuš - CEO & Founder, Neudata
Greg Skibiski - Founder & CEO, Thasos Group
Kristen Thiede - SVP, Two Sigma
  • We’ve had sentiment analysis on social media, car park image processing, mobile positioning, video, credit card transactions… Where or what is the next big alt data source?
  • Evaluating the global demand for data
  • Data, data everywhere. But how can you find the signals?

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Tammer Kamel

CEO & Founder
Quandl

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Rado Lipuš

CEO & Founder
Neudata

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Greg Skibiski

Founder & CEO
Thasos Group

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Kristen Thiede

SVP
Two Sigma

STREAM B

1:30 pm - 1:35 pm QUANT FUNDAMENTAL
Paul Rowady - Director of Research, Alphacution

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Paul Rowady

Director of Research
Alphacution

STREAM B

1:35 pm - 1:55 pm Introducing quant methods into your fundamental approach to enhance alpha capture
  • How this fundamental house took a considered approach to introducing systematic methods
  • Presenting the business case, investment required & time frame for returns
  • A culture change: embracing the value that technology can add
  • Using algorithms to optimise your position sizing: can you eliminate the human bias?

STREAM B

1:55 pm - 2:40 pm Panel discussion: How best to integrate your portfolio management, research and data science teams to deliver alpha
Tom Doris - Chief Data Scientist, Liquidnet
Poul Kristensen - Managing Director, Economist, and Portfolio Manager, New York Life Investment Management
Arun Verma - Head of Quant Research Solutions, Bloomberg
  • Embracing the culture: What is needed to make the changes
  • Practical insights into effective integration
  • Evaluating the success: How can you measure the benefits of a successful integration
  • Understanding the risks of a market saturated with the systematic approach: when will the models fail?


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Tom Doris

Chief Data Scientist
Liquidnet

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Poul Kristensen

Managing Director, Economist, and Portfolio Manager
New York Life Investment Management

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Arun Verma

Head of Quant Research Solutions
Bloomberg

STREAM B

2:40 pm - 3:30 pm Fireside Debate – When hedge funds ate their own
Paul Rowady - Director of Research, Alphacution
One side believes a blended, “quantamental” approach will consistently outperform a purely systematic approach. The other side favors an increasing level of automation. Recent empirical evidence supports both arguments. Come and find out what happens when two heavyweights battle it out.

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Paul Rowady

Director of Research
Alphacution

STREAM C

1:30 pm - 1:35 pm AI/ML CUTTING EDGE ACADEMIC RESEARCH
Vasant Dhar - Professor, NYU

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Vasant Dhar

Professor
NYU

STREAM C

1:35 pm - 2:00 pm Utilizing AI/ML to lend predictive/adaptive capability in continuously changing market environments
Yoshinori Nomura - Director, Simplex Asset Management
  • Understanding correlation between momentum & mean reversion
  • Overcoming lack of volatility without DOP
  • Applicability to other markets: the “walk forward test” 

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Yoshinori Nomura

Director
Simplex Asset Management

STREAM C

2:00 pm - 2:20 pm Cutting edge applications of AI
Mohsen Chitsaz - Founder & Chief Investment Officer, Alpha Beta Investments

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Mohsen Chitsaz

Founder & Chief Investment Officer
Alpha Beta Investments

STREAM C

2:20 pm - 2:40 pm Practical applications of AI/ML
Jamie Wise - President, Periscope Capital
  • Once a qualitative “factor,” sentiment around individual stocks with scale levels of online discussion can now be measured 
  • Applications of ‘task-specific’ vs ‘general’ artificial intelligence
  • Is sentiment predictive or contrarian? 
  • Implications for portfolio construction
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Jamie Wise

President
Periscope Capital

STREAM C

2:40 pm - 3:05 pm Neo-cybernetics: New and developing AI techniques
Paul Bilokon - Founder, Thalesians & Senior Quantitative Consultant, BNP Paribas
  • Extending the ideas and principles of classical finance to change the foundations of the use of AI in modern finance
  • Practical examples: How to recognize and avert catastrophic phenomena like market crashes
  • Understanding the applications to finance and beyond


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Paul Bilokon

Founder, Thalesians & Senior Quantitative Consultant
BNP Paribas

STREAM C

3:05 pm - 3:30 pm FED AI: Applying AI techniques and macro economics
George Lentzas - Manager & Chief Data Scientist, Springfield Capital Management



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George Lentzas

Manager & Chief Data Scientist
Springfield Capital Management

3:30 pm - 3:55 pm Networking refreshment break in the exhibition area

STREAM A

3:55 pm - 4:00 pm NATURAL LANGUAGE PROCESSING
Gary Kazantsev - Head of the Machine Learning Engineering Team, Bloomberg
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Gary Kazantsev

Head of the Machine Learning Engineering Team
Bloomberg

STREAM A

4:00 pm - 4:20 pm Hanging on every word: Natural Language Processing unlocks new frontiers in corporate earnings sentiment analysis
David Pope - Managing Director of Quantitative Research, S&P Global Market Intelligence
How can NLP be applied to corporate earnings call transcripts? Can you dissect the tone, complexity, and overall level of engagement with analysts as indicators of earnings sentiment?
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David Pope

Managing Director of Quantitative Research
S&P Global Market Intelligence

STREAM A

4:20 pm - 4:40 pm Practical uses of cutting edge NLP: what is the current state of play, and how can you benefit from incorporating it into your investment strategy?
Mike Chen - Portfolio Manager, PanAgora Asset Management
  • Defining the value you can add from overcoming language barriers and maximizing your translation services to processing unstructured data from around the world in a variety of formats
  • Enhancing your systems abilities: overcoming the translation barriers: an insight into unsupervised learning of rap, slang and unusual language structure
  • Other practical NLP hints and tricks to set you on the path to alpha generation

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Mike Chen

Portfolio Manager
PanAgora Asset Management

STREAM A

4:40 pm - 5:20 pm Panel discussion: Understanding the very latest developments in NLP: what is the current state of play, and how can you benefit from incorporating it into your investment strategy?
Peter Hafez - Chief Data Scientist, RavenPack
Alejandra Litterio - Co-founder & Chief Research Officer, Eye Capital
Gurraj Singh Sangha - Global Head of Risk, State Street Verus
  • Rule based NLP vs deep learning, i.e. relying on human intervention and ingesting touches of augmented AI rules to better detect key elements of languages in a proper NLP system
  • Using proprietary deep tech and being early adopters of new technologies as opposed to relying on open source
  • The challenges of adapting an English NLP engine to different languages, public sources (such as Twitter that almost has its own language), or thousands of different types of file formats (proprietary textual content from clients)

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Peter Hafez

Chief Data Scientist
RavenPack

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Alejandra Litterio

Co-founder & Chief Research Officer
Eye Capital

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Gurraj Singh Sangha

Global Head of Risk
State Street Verus

STREAM B

3:55 pm - 4:00 pm QUANTAMENTAL & RISK
Yin Luo - Vice Chairman - QES, Wolfe Research
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Yin Luo

Vice Chairman - QES
Wolfe Research

STREAM B

4:00 pm - 4:20 pm Building a unique, fully quant-driven strategy on fundamental principles: Lessons learned, pitfalls to avoid
Mikhail Samonov - Founder, Two Centuries Investments
  • Great quant models are built based on a deep, refined and experience-driven understanding of some processes in asset pricing. 
  • There are many such in-depth fundamental investment philosophies that can provide robust frameworks for great quant models. 
  • Most important benefits of a fundamental framework are the insightful questions it poses. Quants with data and computing tools are great at answering questions, but not at articulating them.  
  • Example: Dynamic Contextual Alpha Model based on a Fundamental Investment Philosophy. 
  • Other potential examples: Industry Models, Stock Specific Models, Macro Sensitivities on Stocks. 
  • Things that don't work: Making fundamental analysts do quant things like rank stocks. Making quant models do fundamental things, like screen a small group of stocks for fundamental analysts to pick from; Quants using 'of the shelf' 'academically tested' 'fundamental' approaches. Fundamentals using 'textbook' security analysis. Alpha comes from innovation, uniqueness in style, refined and customized competitive edge in the investing process. 

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Mikhail Samonov

Founder
Two Centuries Investments

STREAM B

4:20 pm - 4:40 pm Explainable AI: A fundamentally systematic approach
Aric Whitewood - Founding Partner, WilmotML
Combining fundamental knowledge and quantitative techniques into an explainable AI framework for investment decisions:
  • We use a fundamental macro framework to guide data selection and curation, in combination with AI
  • Combining fundamental and quant, how to balance the two

How we approach the prediction problem: 
  • Definition of market regimes
  • Accounting for investor behavior
  • This includes human and machine, as well as machine-only modes of operation

Interrogation versus explanation:
  • The former is used by our team, the latter to provide information to investors
  • What is the best way of surfacing explanations to investment professionals?
  • Investor mental models

Use of the system for:
  • Investing
  • Risk Management
  • Indicators
  • Dealing with new and uncertain regimes

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Aric Whitewood

Founding Partner
WilmotML

STREAM B

4:40 pm - 5:00 pm Utilizing a blended man & machine approach to generating Alpha
Manoj Narang - CEO, MANA Partners LLC
Integrating data, machine learning and fundamental insights to drive alpha
  • Finding patterns in data to aid your strategy
  • Automatic feed: immediately processing news and live market updates to your portfolio to accurately maintain risk

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Manoj Narang

CEO
MANA Partners LLC

STREAM B

5:00 pm - 5:20 pm Model risk management for investment strategies with deep learning
Ben Steiner - Global Fixed Income, BNP Paribas Asset Management
  • Understanding the challenges of using machine learning to build your alpha generation strategies
  • Ongoing monitoring for model risk when using machine learning strategies to make your decisions
  • Can you ever model all circumstances in an undefinable and constantly moving market? How can AI make a decision on data it hasn’t seen yet?

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Ben Steiner

Global Fixed Income
BNP Paribas Asset Management

STREAM C

3:55 pm - 4:00 pm PRACTICAL APPLICATIONS OF AI/ML
Benoit Mondoloni - Director, Bank of America Merrill Lynch

Benoit Mondoloni

Director
Bank of America Merrill Lynch

STREAM C

4:00 pm - 4:20 pm Practical applications of machine learning in investment banking
Charles Elkan - Managing Director, Goldman Sachs

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Charles Elkan

Managing Director
Goldman Sachs

STREAM C

4:20 pm - 4:40 pm Applications of deep learning in portfolio management
Calvin Yu - Managing Director and Head of Multi-Asset Solutions, Qplum
  • How deep learning can help CIOs with common portfolio management challenges
  • Business drivers when considering an AI-driven approach to asset management
  • An end-to-end deep learning model for portfolio allocation
  • Deployment and scalability related practical challenges for a deep learning strategy

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Calvin Yu

Managing Director and Head of Multi-Asset Solutions
Qplum

STREAM C

4:40 pm - 5:00 pm WALLACE: The self-taught fully functional investment system
Adrian de Valois-Franklin - CEO, Castle Ridge
WALLACE is a genetic algorithm based on the concept of survival of the fittest. Constantly growing and developing, it is currently analysing about 10,000 securities across 42 dimension space features. As a self-learning system, the team at Castle Ridge offer it new features and data sources, and WALLACE decides what will add value from these, adopting and learning itself to build a highly liquid market neutral strategy.
  • Survival of the fittest: An insight into the process and journey of creating WALLACE 
  • The burden of unsupervised learning: enabling the machine to decide what inputs are more or less useful
  • Becoming social: How WALLACE explains its decisions and exposes its thought process to overcome interpretability issues

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Adrian de Valois-Franklin

CEO
Castle Ridge

STREAM C

5:00 pm - 5:20 pm How to utilize reinforcement learning for hedging options
Petter Kolm - Professor, Courant Institute of Mathematical Sciences, NYU Courant


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Petter Kolm

Professor, Courant Institute of Mathematical Sciences
NYU Courant

5:20 pm - 5:30 pm Closing remarks

5:30 pm - 7:00 pm Drinks reception and networking in the exhibition area