Top Questions: Eagle Alpha Unbound and NYC Data Week
We're back in New York for the Autumn Data Conference Season with Eagle Alpha's Unbound NYC Alternative Data Conference on Oct 9th and Data Week Oct 8th-10th.
Welcome to the Data Score newsletter, composed by DataChorus LLC. The newsletter is your go-to source for insights into the world of data-driven decision-making. Whether you're an insight seeker, a unique data company, a software-as-a-service provider, or an investor, this newsletter is for you. I'm Jason DeRise, a seasoned expert in the field of data-driven insights. As one of the first 10 members of UBS Evidence Lab, I was at the forefront of pioneering new ways to generate actionable insights from alternative data. Before that, I successfully built a sell-side equity research franchise based on proprietary data and non-consensus insights. After moving on from UBS Evidence Lab, I’ve remained active in the intersection of data, technology, and financial insights. Through my extensive experience as a purchaser and creator of data, I have gained a unique perspective, which I am sharing through the newsletter.
In addition to its flagship conference, Eagle Alpha organized Data Week.
#DataWeekNYC will bring together data suppliers, data experts and data consumers for a dynamic series of specialist events and meetups either side of the Eagle Alpha Conference. Brought together by Eagle Alpha, the inaugural Data Week aims to rival established weekly gatherings in other industries. https://www.eaglealpha.com/2024/08/06/join-us-for-dataweeknyc-october-7th-11th-2024/
In addition to providing questions for it’s Unbound NYC Alternative Data conference, I provide questions for the various Data Week NYC events.
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Connect with Flywheel Alternative Data at Eagle Alpha’s NYC conference, where Director of Research, Jeremy Scott, will be participating in a panel discussion on data trends. Flywheel will be sharing deep fundamental use cases and modelling using the eCommerce Insights dataset.
A recent example of such analysis is on StockX, showing the sales and units sold in the footwear category. Resale and 3P marketplaces have become a growing focus for Flywheel, not only because of the growing importance in the eCommerce landscape, but because what these marketplaces can reveal about product mix, buyer trends and brand momentum.
Three themes from my questions ahead of Data Week NYC
Generative AI1 and Investment Process
Industry Consolidation and Evolution
Emerging Data Trends and Insights
Eagle Alpha Unbound NYC Alterative Data Conference, October 9th 2024
Agenda: https://www.eaglealpha.com/2024/05/12/unbound-alternative-data-conference-2024/
09:15 - 09:30 Auditorium: Opening Remarks
Eagle Alpha Team
Question: How do you envision the data industry evolving over the next 5 years, and how is Eagle Alpha evolving in response?
09:30 - 09:45 Fireside Chat: Alternative Data Strategy In An AI Centric World
Jason DeRise, CFA – Liberty Mutual Investments
Question: What questions would you like us to cover?
09:45 - 10:15 Auditorium: How GPT4 & AI Is Changing The Buyside
Brian Peltonen, Founder, Parcosm.AI
Sudip Gupta, Professor of Finance, John Hopkins University
Question: Which generative AI use cases have made it out of the proof-of-concept stage and are currently in full production with consistent usage across the buyside2? What impact are they having on decision-making?
12:00 - 13:30 Part of Data Week: SQA Alphathon
Please Register Here
The Society of Quantative Analysts (SQA) hosted a competition: Alphathon2024, a quantitative finance competition, organized jointly with the Center of Excellence in Wireless and Information Technology (CEWIT) at Stony Brook University. The agenda for the session hosted at the Eagle Alpha conference is the final presentations by the winning entries, and a panel on the State of the Quant Industry.
Question: Is the future of alpha3 generation more about refactoring quant4 models with existing data already in use, or is discovering entirely new datasets the key driver of alpha opportunities moving forward? Also, congratulations to the finalists!
13:00 - 14:00 Breakout Room: Analyst Lunch: Q3 Data Trends From Category Leading Vendors
Apptopia
EventVestor
Fable
S&P Global
Question: With interest rates easing from their peaks, what changes in consumer and corporate behavior are you observing in your datasets? Are there any early indicators of potential new trends emerging? I’d be curious if EventVestor and S&P’s data covering corporate and analyst signaling differs from the consumer behavior signals covered by Apptopia, Placer.ai, and Fable.
15:30 - 16:00 Auditorium: Forward Looking Insights With Leading Data Vendors
WeatherTrends 360
S&P Global
Flywheel
Question: Based on your datasets, what inflection points or emerging trends should we expect in 2025, whether at the macroeconomic level or within specific companies? I would be curious if WeatherTrends sees a highly probable global weather shift in 2025 vs 2024 and based on that, if S&Ps data would signal supply chain implications in response and then related to that, which companies covered by Flywheel could potentially be negatively affected based on their current inventory and pricing trends.
16:00 - 16:30 Auditorium: CCO / COO Session - "AI" Compliance Implications For Vendors & Buyers
Jessica Margolies, Special Counsel, Schulte Roth & Zabel.
Paula Weill, Chief Compliance Officer, Citadel.
Brian Digney, Research & Content Director, SBAI.
Question: A common theme this conference season has been licensing in the age of Gen AI. The consensus has been that existing licensing agreements should be sufficient and there wouldn’t be a need to create brand new licensing contracts for Gen AI use cases. The question is: Even if core licensing agreements remain valid, are there specific legal nuances related to generative AI that must be updated or rewritten?
16:30 - 17:00 Auditorium: B2B Technology & Software Insights With Leading Data Vendors
RepVue
Data Provider
JetNet
Question: Across each B2B data company’s unique data, what trends in business activity—acceleration or deceleration—have emerged over the past year, and do your datasets reveal any potential inflection points ahead? I would be curious if the RepVue angle on the sales forces aligns with the digital business activity that Data Provider covers and the aviation activity that JetNet provides.
Data Week Events, October 8th-10th
For more info and the evolving agenda: https://www.eaglealpha.com/dataweek/
TUESDAY, OCTOBER 8th, 9am – 10am
Executive Search Firm The Search For AI / Data Talent, Roundtable, Chatham House Rules
For: Buyside & PE Focused. 15 to 20 people.
Location: Rockefeller Plaza
Question: Over the past few decades, the investment industry and tech industries have competed for top talent in data and technology. How has the competition for top talent between investment and tech industries shifted since the rise of generative AI? Are there new skills or roles that are now in higher demand?
TUESDAY, OCTOBER 8th, 12pm – 1.30pm
Society Evolution of Data & Data Science
For: The Fundamental Analyst Society Focused. 100 people.
Location: Times Square
Question: What advice and strategies do you have for early-career fundamental analysts to use to bridge the gap when working with senior colleagues who may be less comfortable with the latet data science and technology?
TUESDAY, OCTOBER 8th, 4pm – 5.30pm
Archedata Inc: Market Data vs Alternative Data Convergence: Best Practices Workshop
For: Sourcing and Managing Vendors, Buyers & Vendors. 20 people.
Register Your Interest Here
Location: 5th Avenue
Question: With industry consolidation accelerating and market data converging with alternative data5, how should buyers evolve their data sourcing strategies to stay competitive?
WEDNESDAY, OCTOBER 9th at the Eagle Alpha Conference
SQA Data Alphathon (At Eagle Alpha Conference)
For: SQA Members Prioritized.
Register Here
Location: 360 Madison
Agenda: The Society of Quanative Analysts (SQA) hosted a competition: Alphathon2024, a quantitative finance competition, organized jointly with the Center of Excellence in Wireless and Information Technology (CEWIT) at Stony Brook University. The agenda for the session hosted at the Eagle Alpha conference is the final presentations by the winning entries, and a panel on the State of the Quant Industry.
Question: Same as covered in the conference agenda above: Is the future of alpha generation more about refactoring models with existing data already in use, or is discovering entirely new datasets the key driver of alpha opportunities moving forward? And still, congratulations to the finalists!
THURSDAY, OCTOBER 10TH 9am – 10am
ADI & Code Willing: GenAI’s Impact on Data Productization
For: Buyside & PE. 20 to 30 people.
Register Interest Here
Location: Grand Central Area
Question: Is generative AI having a greater impact on streamlining data pipelines6 or on transforming the insights generated from the data? Which area offers the most value for data buyers?
THURSDAY, OCTOBER 10th, 11am – 12pm
Roll-ups, M&A, and Consolidation in the Data World
Emmett Kilduff, Fortia Group
Evan Schidman, Outrigger
Jason DeRise, Liberty Mutual Investments
For: Vendor & PE. 30 to 40 people.
Register Interest Here
Location: Hudson Yards (EY Offices)
Question: What are the key forces driving consolidation in the data industry, and how sustainable is this trend? What ROI metrics should companies prioritize after consolidation?
By the way, check out a Data Score post on the subject from earlier this year:
THURSDAY, OCTOBER 10th, 12.30pm – 1.30pm
EY: How Are Corporates Approaching Data Assetization?
For: Buyside, PE & Corporate Focused. 30 to 50 people.
Location: Hudson Yards (EY Offices)
Question: What are the main obstacles preventing corporations from monetizing their data assets, and how can the data community help address these challenges?
THURSDAY, OCTOBER 10th, 2:30pm
System2: US Consumer – Deep Dive Into Behavioral Trends With Transaction Data Capacity
For: Buyers & Vendors. 15 to 20 people.
Register Interest Here
Location: Park Avenue (East 59th)
Question: Investors often look at highly aggregated trends of the US consumer, but the reality is there isn’t an average US consumer. Based on granular transaction data and more advanced data science techniques, which consumer cohorts are showing behavioral changes which signal coming headline trend changes for the US consumer?
What questions would you ask? Leave a comment below.
If you think this is useful for someone attending the conference, please feel free to forward it on.
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- Jason DeRise, CFA
Generative AI: AI models that can generate data like text, images, etc. For example, a generative AI model can write an article, paint a picture, or even compose music.
Buyside typically refers to institutional investors (Hedge funds, mutual funds, etc.) who invest large amounts of capital, and Sellside typically refers to investment banking and research firms that provide execution and advisory services (research reports, investment recommendations, and financial analyses) to institutional investors.
Alpha: A term used in finance to describe an investment strategy's ability to beat the market or generate excess returns. A simple way to think about alpha is that it’s a measure of the outperformance of a portfolio compared to a pre-defined benchmark for performance. Investopedia has a lot more detail: https://www.investopedia.com/terms/a/alpha.asp
Quant funds: Short for "quantitative funds," also referred to as systematic funds. Systematic refers to a quantitative (quant) approach to portfolio allocation based on advanced statistical models and machine learning (with varying degrees of human involvement “in the loop” or “on the loop” managing the programmatic decision-making).
Alternative data: Alternative data refers to data that is not traditional or conventional in the context of the finance and investing industries. Traditional data often includes factors like share prices, a company's earnings, valuation ratios, and other widely available financial data. Alternative data can include anything from transaction data, social media data, web traffic data, web mined data, satellite images, and more. This data is typically unstructured and requires more advanced data engineering and science skills to generate insights.
Data pipeline: A set of data processing elements or tasks connected in series, where the output of one element is the input of the next one, converting raw data into cleansed and enriched data, typically managed on an automated schedule.