The Battle of the Quants – BIG DATA brings you carefully selected BIG DATA Providers, Quantitative Hedge Fund Managers and Systematic Institutional Investors, who are leading the way into the new world of Artificial Intelligence, Alpha Data Sets and Machine Learning. With data becoming the “New Oil” or the “Currency of the Future” the DATA Forum Breakfast provides Quantitative Hedge Fund Managers the opportunity to meet BIG DATA providers in a pleasant two hour breakfast. The remainder of the day includes presentations and panel discussions with the most successful and innovative minds in quantitative finance and data. Additional topics include: the impact of Blockchain/Crypto, Quantum Computing and the future opportunities as disruption accelerates. A One-on-One meetings scheduler facilitates highly sought after meetings for attendees. Kicking off with an Evening Welcoming Reception on November 14th, the also event includes plenty of networking breaks from coffees to meals and a post cocktail hour. We hope you can join us and join “Leading the Discussion in Quantitative Finance and Connecting the Humans Behind the Machines”.
Sample of Past Attendees:Two Sigma, MOV37, Winton Capital, Citadel, PAAMCO Prisma, Nasdaq, Millenium Capital Partners, WorldQuant, RailPen Pension Fund, Aspect Capital Limited, Norges Bank Investment Management, Factset, Goldman Sachs, Point72 Asset Management, Raiffeisen Capital Management, RavenPack, IBM Systems, Citibank, QuantBot Technologies, Crabel Capital Management, , Planet, MANA Partners, Union Investments, Quoniam, Partners Capital, Intel Corporation, PRIME Capital, Orbital Insight, GAM, Bloomberg News.
Attendee Quote: ”I found the Battle of the Quants high quality and productive because everyone I met was a decision maker”
|8:00AM||Investor Breakfast (Contact us for details)|
|10:00AM||KEYNOTE: How Systematic Trading uses Machine Learning to Predict Markets
Dario Villani, Ph.D., CEO, Duality Group
Dario Villani, Ph.D. and Quant Machine Learning expert, had the largest launch ever for a Machine Learning based Hedge Fund in 2018. The visiting lecturer at Princeton University, former Global Head of Portfolio Strategy and Risk at Tudor Investment Corporation also shared the 2016 Risk.net Buy-Side Quant of the Year Award. Dario holds a Ph.D. in Theoretical Physics from Salerno University and a Master in Finance from Princeton University.
|10:20AM||Data Buyer Panel: How I Like my Data! From Raw Unstructured to Refined and Alpha Signal Ready!
Quantitative hedge fund traders have specific needs when it comes to their desired type of data. Each hedge fund has a unique ingestion requirement, infrastructure and market data they trade with. Are data suppliers meeting all the needs of the data buyers? What is missing? What unique characteristics would you like to see to improve the efficacy of data sets? What are the warning signs that data is not going to be predictive?
Moderator: Andreas Zagos, CEO, InTraCoM
Christian Schwarz, Executive Director, Head of Quant Research, Focus on Machine Learning and Algo Trading, Mizuho
Conor Taggart, Managing Director, NASDAQ Europe
Abhijeet Gaikwad, Portfolio Manager, Trium Capital
Hammad Khan, Co-Founder and CIO, QuanVolve
Morgan Slade, CEO, CloudQuant
|10:50AM||Data Provider Panel: BIG DATA Providers and How to Find Alpha Generating Data Sets
We are in the “Golden Age of BIG DATA” according to Igor Tulchinsky, CEO of WorldQuant and data companies are providing a tremendous variety of data types. Unique data sets continue to proliferate and quantitative based hedge funds are eager customers provided that the data reflects predictability of financial markets. How are data companies finding and providing the most valuable data to quantitative models? Self-generated? IoT? Purchased? Other? What is the most expensive and highest quality data the you have seen? As data sets begin to flood the market, will alpha decay ultimately render most data sets obsolete and ineffective? When will we see that happen?
Moderator: Matteo Testi, CEO & Founder, Deep Learning Italia & Icaro Artificial Intelligence
Katya Chupryna, Chief Strategy Officer, Thinknum
Salvatore Licata, Director of Strategic Initiatives, ETF Global
Thomas Kieselstein, CIO, Quoniam
Peter Hafez, Chief Data Scientist, Ravenpack
|11:20AM||Networking Coffee Break|
|11:30AM||Presentation: News Sentiment: Insights From Top Investment Banks
Alternative data has become a “must-have” for Quants and Fundamental investors to stand out in an incredibly competitive market. Focusing on short- and long-term investment strategies, Peter will discuss the latest use-cases on RavenPack Sentiment from Citi Research, J.P. Morgan, and Empirical Research Partners, that enable new ways of constructing alpha signals around alternative data.
Peter Hafez, Chief Data Scientist, Ravenpack
|11:55AM||Panel: Winning Quantitative Hedge Fund Strategies in 2018 and What to Look for in 2019
Moderator: Bartt C. Kellermann, CEO & Founder, Global Capital Acquisition
Scott Kerson, Senior Managing Director & Head of Systematic Strategies, Gresham Investment Management
Damian Borth, Ph.D., Deep Learning Lab, Amplitude Capital
George Sokoloff, Ph.D.,Founder and CIO, Carmot Capital
Kevin Shea, CEO, Disciplined Alpha
|12:20PM||Presentation: Can we use Machine Learning to Figure out the Smart Humans?
Sell-side analysts are a significant part of the investment ecosystem – they structure complex information into forward looking recommendations and predictions. The big question is, are there any good at it? And how do we harness their predictive power? In this talk we take a look at a real-world example of how machine learning techniques can be applied to a large alternative data set to optimise portfolio construction for a systematic institutional money manager.
Laurent Nguyen, Head of Quantitative Equities, Pictet Asset Management
Thibault Jaisson, Ph.D., Quantitative Analyst, Pictet Asset Management
|12:50PM||Fireside Chat: The Increasing Convergence of Quant and Fundamental Strategies Because of Alternative Data
Hosts: Michael Marrale, CEO, M Science
Kirk McKeown, Managing Director and Head of Proprietary Research, Point72
Kirk and Michael will be discussing how vital alternative data has become to quantitative and fundamental trading and how to manage the proliferation and effective use of data sets within an organization. Michael of M Science was an early market participant in the alternative data arena and his firm continues to evolve and innovate at a blistering pace.
|1:30PM||One on One Pre-Scheduled Meetings Break|
|2:00PM||Presentation: Using AI to Find Super Stars in Seemingly Low Credibility M&A Chatter
Through the use of specialized AI tuned to understand the language of M&A, credible market moving M&A rumors can be identified in sources with low reach before they propagate into the collective consciousness.
Prashant B. Bhuyan, Founder & CEO, Accrete.AI
|2:25PM||Presentation: Can Data Formations in Nature Predict Financial Market Regime Change?
A fascinating presentation on the analysis of data resulting from natural phenomena that occur in nature and how they can be related to finance. Real world examples include the physics and math data behind avalanches, fractals and bus arrival times in Mexico. By analyzing the data behind these occurrences one can begin to construct models on how change evolves, spreads and ultimately reaches a tipping point then a complete pivot or reversal. The same models can then be applied to financial markets relative to the herding characteristics of investors which ultimately result in a complete regime change. This analysis has been done on current markets and Edgar will reflect on where we are in the business cycle and what the models reveal.
Edgar van Tuyll van Serooskerken, CIO, Quantitative Arm, PAG
|2:45PM||Networking Coffee Break|
|3:05PM||Panel: Synthetic Data: Methodologies in Creating Synthetic Data including GAN (Generating Adversarial Network)
Data can be created to supplement markets when there is a dearth of information. Two main strategies can be employed to build data sets to help test against models that will improve accuracy and predictability. Still in it’s infancy, synthetic data continues to improve as multiple initiatives are active. What are the benefits of synthetic data? Which initiatives are the farthest ahead and when can it be used? What is GAN and how does it differ from other methodologies.
Moderator: Robert Hillman, CIO, Neuron Advisers
Thomas Crow, Analyst, MOV 37
Darko Matovski, Ph.D., CEO, causaLens
|3:35PM||Investor Panel: Do Data Sources Influence Investment Decisions?
Moderator: Erin Kogan, Founder, Beespoke
Markus Koch, Director, Prime Capital Management
Pierre Bonart, Group Head of Multi Management, Edmond de Rothschild
Frances Newton Stacy, Director, Portfolio Strategy, Optimal Capital
|4:05PM||Panel: From Quants to Cryptos – True Stories from the Digital Asset Ecosystem
Is the Crypto Revolution Real? Are we spending billions on a new “Ghost City” financial infrastructure with no inhabitants/usage? Get the truth from managers who moved over from the conventional financial system to the new “Wild West” of the revolutionary crypto world. Learn why they made the decision, their stories of transition and what they found. What is the new microstructure? What data is available and what is the quality? Is the infrastructure robust enough for Institutional level trading? What challenges do they face that they never faced before. Can “smart” contracts really work?
Moderator: Oskar Mencer, Ph.D., CEO, Academie De Europa
Jakob Palmstierna, Director of Investment Solution, GSR (Formerly at Two SIGMA and Winton Capital)
Shane V. Kehoe, Co-Founder, SVKCrypto (Ex-Partner at BlueCrest Capital)
David Fauchier, CEO/CIO, Cambrial
|4:35PM||Presentation: A View to the Future: What Strategic Moves to Initiate Today to Maintain Competitiveness in a Disrupting Financial World
The exponential growth of technology continues unabated and is increasingly challenging the status quo of global financial markets. What components of the financial world are most vulnerable to technological advancements and where will the opportunities be. A new breed of high technology data analytics companies are setting the stage for the ultimate robotic trader. By combining historical data with real time data then overlaying an artificial intelligent engine, new data entrepreneurs are recreating a human trader. What are these systems able to do today? Have these systems been able to generate alpha?
Matt Griffin, Futurist, 311 Institute
|5:00PM||Cocktail Reception in The Royal Automobile Club Long Bar|