Welcome address from Quandl CEO Tammer Kamel.
Brian Koppelman is the co-creator, executive producer, and showrunner of the Showtime hit drama series, Billions. He's the man who created Axe, Taylor Mason, and Wags, among many others. How did Koppelman come to understand the unique and sometimes baffling zeitgeist of the hedge fund, and how did he get inside the heads of some of the most powerful investors in the world to drive his creative process?
In this fireside chat, Brian tells us whether his characters are heroes, villains or both. He explains the psychology of the investment manager and he helps us understand the perception of "hedgies" in popular culture. As a bonus, we will learn about his incredibly fluent creative process as something we can all apply in our lives to be better professionals.
Data science in general and statistical methods in particular are very powerful tools that can be used responsibly towards the pursuit of empirical truth. But all too often this does not happen at all. Analysts use statistics either sloppily or worse, couch flawed analysis in the language of statistics to confirm some bias or advance some preconceived notion. This talk sees Matthew Rothman, our data-driven contrarian, confront this problem head on.
Managing Director, Goldman Sachs
Join us for light refreshments in the exhibit hall.
It wasn't so long ago that data hunting was a one-man job; a feet-on-the-street, outbound process that felt a bit like detective work. Not anymore. Today investors are nearly crushed with the volume of datasets put in front of them; each holding the elusive promise of alpha. Funds and vendors alike have, out of necessity, had to develop tools, technology and processes to dramatically speed up the data productization cycle. We rounded up the toughest challenges facing data-driven investors today and who is solving them best, across sourcing, extracting, mapping, validation, idea generation, and compliance. For each of these areas, Bill will present ideas and firms with the most ingenious approaches to tackling these thorny problems.
Head of Alternative Data Research, Quandl
It is common for financial services firms to leverage alternative sources of data to gain an advantage in the market. The data is often massive, real-time, and spatiotemporal and/or graph-oriented, posing significant challenges for traditional analytics and data science software stacks. OmniSci enables practitioners to query, visualize, and train models over billions of rows of data at the speed of thought, allowing hedge funds and investment banks to rapidly determine the quality of new data sources, correct for deficiencies, visually find key correlations and anomalies across space and time, and leverage machine learning to determine optimal trading strategies.
Founder and CEO, Omnisci
VP, Product Management, Omnisci
Natural Language Processing (NLP) is nothing new. It has been applied to financial markets for more than a decade with several proven use-cases. Still, we are seeing new and interesting applications emerge as investors are becoming more familiar with what works and what doesn’t. NLP expert Peter Hafez will discuss:
• How news sentiment is being combined with traditional factors to extract value that goes beyond short-term horizons.
• How news sentiment is being applied to ESG investing, proving value on top of traditional ESG ratings data.
• How investors are taking advantage of co-mention networks to better understand relationships and information dissemination effects.
• How NLP is being used to extract orthogonal value from internal content such as analyst reports, investment notes, newsletters etc., value that goes beyond public news.
Chief Data Scientist, Ravenpack
Join us in the exhibit hall for lunch and networking.
A candid, intimate conversation with three of the pioneers in our industry contemplating the future of data-driven investing. You won't want to miss a second of this session, where best practices meet inside baseball. Please note: This is a live, exclusive session at QDC that will not be recorded.
Head of Proprietary Research, Point72
Head of Data Strategy and Sourcing, Quandl
Quantamental exists across a spectrum, from almost purely machine-driven to almost purely discretionary. The four panelists here ably cover that spectrum. One is developing algorithms that function like an analyst, but without the subjectivity and the emotional thinking. One is using machine learning to reduce her world to 60 stocks that are most likely to see significant dividend growth, but will then hand this list to fundamental analysts to build a portfolio of 22 stocks. One offers data science on demand, as a service to investors. And one believes that there is still much value to be found in personal conversations, the reading of body language, and other human elements that simply cannot be replaced by a machine.
Co-CIO, O'Shaughnessy Asset Management
Innovation Strategist, Bristol Gate Partners
Managing Director, Ancora Advisors
Moderator: Abraham Thomas,
Chief Data Officer, Quandl
P Street Advisors is undertaking highly specific, bespoke alternative data research on behalf of its buyside clients. Through these engagements they’ve learned that the buyside’s expectations of remotely-sensed data have been largely unmet. Ed will show us how imagery -- remotely sensed, as well as privately sourced aerial and ground data -- can be effective in the research process and uncover insights that are actionable, objective, and opportunistic.
President and Co-Founder, P Street Advisors
Please join us in the exhibit hall for refreshments.
The Investment Management industry is experiencing rapid and profound changes which challenges business models and changes the very nature of work. Firms are likely to find that simply enhancing the ways that they have traditionally sought to attract, retain, and engage an increasingly diverse, multi-generational workforce is not enough; a new, more individually-focused strategy where the organization makes it a mission to optimally leverage their talent may be required to unlock innovation and compete in a changing industry. In this talk, Matt will present the results from Citi's 2019 Industry Revolution Report and show investment managers can welcome a new opportunity to realize alpha through human capital practices.
Head of North America, Business Advisory Services, Citi
Millburn is one of the world’s longest-running systematic firms, with a legacy back to 1971. Millburn’s co-CEO Barry Goodman explains how and why the firm was an early mover in adopting a machine-first approach to continuous return and execution cost forecasting, with research starting in 2011 and implementation beginning in 2013. He demonstrates how their framework was successfully applied to billions of dollars trading global futures and FX markets, local China futures markets, and now, most recently, to active securities trading. He also discusses what role market experience and human judgement continue to play.
The Efficient Market Hypothesis (EMH) has become associated with the supposed impossibility of forecasting price movements of exchange listed assets. The availability of Alternative Data offers an elegant path at deconstructing this simplified view of the market. After demonstrating that Alternative Data should improve our forecast quality, we then dive into the details of the forecast building process, and consider how the various aspects of alternative data offer benefits in making reliable forecasts, and on the flip side, lay traps for the unsuspecting practitioner. Sample size, frequency, publication delays, revisions; availability of surrogate data sets, quality of data and meta-data; specificity, uniqueness and market awareness; relevance and asset liquidity -- these and other factors commonly found in the Quandl Database Report Cards, will be discussed in the context of placing a value an Alternative dataset for the end user. Finally, the (non-)stationarity of the resulting forecasts will be discussed using a well known example from the oil and gas industry.
Senior Portfolio Manager & Director of Research Process, Teza
There are few who know more about the legal intricacies of data-driven investing than Peter Greene, who starts off this session with a current précis of the legal and regulatory landscape, including the impending CCPA, web scraping and the public domain, and fair use of consumer data. He will then be joined by Business Insider's Bradley Saacks for an engaging discussion on what the judicial future might hold for this brave new world.
Partner & Vice Chair of the Investment Management Group, Lowenstein Sandler
Please join us in the exhibit hall for cocktails.