Amassed Insights

Amassed Insights #4: MacroVolatility

How Trump’s Tariffs Just Flipped Data Sourcing on Its Head (Plus M Science v. Yipit Drama)

Jordan Hauer

Jordan Hauer

— 15 min read
Funny image of Trump and a word bubble in front of a bunch of money
Photo by Igor Omilaev / Unsplash

Sourcing Data in this Era of Macroeconomic & Geopolitical Volatility

This year's rapid shifts in public policy and the global political landscape, particularly the yo-yoing of proposed tariff rates, have highlighted the necessity for most organizations to keep track of unique macroeconomic news and events in real-time. Most companies aren't well-equipped to monitor policy changes that are highly impactful to them, especially for those that are esoteric or nuanced, as gathering information from external sources hasn't been a priority historically. It's incumbent upon those companies to at the very least identify and monitor the governmental organizations and policy groups that can drive their outcomes. Even better to keep a keen eye on macro-level consumer pricing and transaction trends as well as supply chain-related datasets to build a well-rounded viewpoint on how consumers and businesses are responding to tariff-related trade shocks.

Large, data-driven asset managers typically already have the infrastructure, relationships and culture to be able to quickly shift their data sourcing priorities along with these changes. But some, particularly long/short equity investors, haven't historically prioritized macroeconomic data sources as they may believe all beta has been hedged out of their portfolio. All of a sudden, I've been seeing this mindset finally crumble since news of Trump's tariff whims shift markets daily. However, sourcing and employing unique data that focuses on countries, hard-to-find government filings, and election predictions/results isn't easy. It's super important to understand the trustworthiness of your sources and their timeliness.

In our taxonomy, the main data categories relevant to this topic include "Macroeconomic", "Supply Chain", "Public Policy", "Open Government", "Government/Regulatory Risk", "Government Financials", and "Elections". We've sourced ~3,646 data providers focusing on at least one of those categories! Besides the largest well-known financial market data providers, here's a small sample of the macro-focused data providers that should be on every asset managers' radar:

How actual ‘fake news’ caused the market whiplash | CNN Business
An errant post on X may have just shaken the stock market, showing how influential — and irresponsible — the social media platform can be.
CNNHadas Gold, Brian Stelter

"In an era of volatility and uncertainty, what datasets can investors employ to understand how potential tariffs could impact them, their suppliers, and their portfolios?"

Upcoming Events I'll Be Speaking At

  • Boris Liberman from Lowenstein Sandler LLP and I will have a fireside chat about alternative data compliance onboarding, taking into account the novel effects of AI, at BattleFin in NYC at 9:25 AM next Wednesday, Jun 11. We'll delve into legal best practices for data vendors as well as asset managers when monetizing or procuring new datasets, as well as the newest questions to expect in due diligence questionnaires (DDQs) regarding the evolving AI or web scraping concerns. My summary of Lowenstein's article about this topic in the next section below (as well as in my previous post) serves a teaser for what to expect in this talk.
Description of a panel at the BattleFin event with Jordan Hauer and Boris Liberman about Alternative Data Due Diligence
  • I'm co-hosting the second edition of the Alternative Data Breakfast Series tomorrow, June 10 at 8:15 AM in NYC. Boris Liberman from Lowenstein Sandler, Evan Reich from Verition Fund Management, Michael Watson from Hedgineer, Richard Rothenberg from Global AI and I will explore using AI within institutional investing. The panelists will discuss the past, present and future of AI's impact on alternative data and asset management, ranging from the front to back offices and from data providers to data buyers. Let me know if you'd like to receive invites to events like these.
  • In my last two posts, I've commented on the ongoing Yipit & M Science civil litigation. To catch you up: M Science poached a couple high-level salespeople, Pinsky & Emmett, from Yipit and Yipit later accused them of stealing confidential client information and attempting to steal their clients, particularly at the end of those clients' subscription periods. Thanks to my friends at Glacier Network, who have been dutifully attending the court hearings on this case (in addition to other relevant alternative data-related cases), I was told the latest hearing went very poorly for Yipit. "The judge seems to broadly accept that employees did steal information from Yipit and bring that info to M Science, but is skeptical that Yipit has shown/can show that the malfeasance was the reason for client churn. The judge was also frustrated that the parties haven't been able to enter consent judgments (settlements) with Pinsky and Emmett - and mostly placed the blame for that on Yipit." The judge was very critical of how much Yipit has been spending to pursue this case, instead of finding a reasonable settlement. So far, Yipit only identified 5 clients they believe churned because of this, but M Science pointed out that most of these have either already been clients of theirs for a while or had begun discussions with them well into the past. And at least one of them isn't even an M Science client anyway! Clearly, it seems a settlement is coming and while there is clearly some smoke here, there doesn't seem to be much fire.
  • Key Considerations for Alternative Data and AI Vendors to Investment Firms: Demonstrating Compliance in the Face of an Evolving Regulatory Environment by Lowenstein Sandler
    • My Summary:
      • State regulators may step in to impose regulation if the federal agencies like the SEC shift towards deregulation and take a step back from active enforcement.
      • This regulatory uncertainty means that investment firms should maintain their diligence practices, and comply with regulations like Section 204A of the Investment Advisors Act of 1940 covering insider trading.
      • Vendors should do the following:
        1. Prepare a DDQ.
        2. Details on data provenance, such as all the sources of their information and the various parties' rights and licenses
          with AI systems, consider having a training cutoff date since stale data is less likely to include material non-public information (MNPI).
        3. Understand Insider Trading and MNPI Concerns.
        4. Have an escalation plan for Legal/Compliance issues.
        5. Consider adopting a formal set of compliance policies, covering confidential information, data privacy, insider trading and MNPI.
        6. Conduct Regular Compliance Training for Employees.
        7. Prepare for Followup Questions, particularly about your rights to your data.
        8. Be Prepared!
      • In data license agreements, vendors should be ready to:
        1. Accept firm reps and warranties about their data's provenance, with a keen eye on relevant local laws and regulations.
        2. Notify clients of adverse events affecting the data or AI systems.
        3. Include the same reps and warranties in a trial agreement, but only covering stale data.
        4. Forego auto-renewals.
        5. Forego broad on-site audit rights in the event of a suspected breach in favor of reasonable cooperation with the client.
        6. Enable clients to firmly protect their own confidential information.
  • CFPB Quietly Kills Rule to Shield Americans From Data Brokers by Dell Cameron, Dhruv Mehrotra
    • My Take: Not at all a surprising development considering this administration's cost-cutting measures and disdain for the CFPB. Data brokers in America will continue to be able to operate in a laissez faire manner.
  • DOJ Rule Restricting Sensitive Data Transfers Takes Effect by Miller Canfield
    • My Take: If you're a data provider selling or transferring data to Russia, Iran, North Korea, Cuba, Venezuela, or China (including Hong Kong and Macau), take a very close look at these new restrictions that already are in effect! Most data products I know of would meet the very loose requirements set forth, such as precise geolocation data on 1,000+ U.S. devices or personal financial data collected on 10,000+ U.S. persons. Even if you're not selling to these countries, you may want to update your data license terms to ensure your downstream partners aren't as well!
  • Did OpenAI train on copyrighted book content? by Asimov’s Addendum
    • My Take: The AI Disclosures Project studied the extent to which OpenAI's LLMs were trained on copyrighted O'Reilly Media books without proper authorization. In summary, it seems that GPT-4o was materially stronger at recognizing paywalled content than previous models or smaller models. This suggests that OpenAI has started including the LibGen database in its training (which includes copyrighted content like O'Reilly books), significantly increasing the risk to highly-regulated users of this model.

Data Being Requested

If this request reasonably matches with a data product you represent or are aware of, please respond.

US Credit Card Transactional Data

  • In light of the recent consolidation of Earnest into Consumer Edge (referenced below), we've been hearing from data buyers looking around for novel sources of US credit card transactional data. We've put together a landscape of 14 data providers, covering:
    • The most popular, well-known and/or respected vendors.
    • New entrants or offerings to explore or, at least, be aware of.
    • Biases and skews inherent to each panel.
  • Are there any US credit card transactional data providers we are missing?
  • Are there any companies sitting on valuable US transactional data that have yet to monetize it? Now might be the best time in a long time to pursue this.

If you'd like us to source data that fulfills your unique requirements:

Submit Your Data Requests & Preferences

Data Providers & Products

If any of the following data providers piques your interest for any reason, respond and I'll share additional materials & directly introduce you, if necessary.

New Data Providers

  • SOV.AI (Data Profile)
    • Main Data Category: Financial Data-Driven Investment Research
    • Brief: Provides AI-driven financial datasets, including government filings, lobbying data, clinical trials, institutional trading, and sectorial insights.
  • Derivox (Data Profile)
    • Main Data Category: Financial Market Data
    • Brief: Provides daily end-of-day interest rate curves, including spot, forward, and discount factors for risk-free rates designed for use in valuation, accounting, and risk systems.
  • Whoisology (Data Profile)
    • Main Data Category: Company Information
    • Brief: Database that archives and indexes domain ownership information, enabling users to search, track, and analyze connections between domains and their owners for cybersecurity investigations, corporate intelligence, legal research, and brand monitoring.
  • CostQuest Associates (Data Profile)
    • Main Data Category: Location - Consumers & IoT
    • Brief: Provides geospatial broadband infrastructure data, including serviceable locations and network cost models, supporting investment decisions in telecommunications and infrastructure sectors.
  • Bond Radar (Data Profile)
    • Main Data Category: News - Finance
    • Brief: Provides real-time news and analysis on global primary bond markets, covering new issues, pricing, and market trends.

Partnerships + New or Updated Data Products

M&A + Funding

TipRanks, the Israeli market research aggregator, has acquired Main Street Data, a visual-first equity research platform, for an undisclosed sum to meet the dataset needs of its “enterprise clients” and also traders...
“The unique company KPI data and charting abilities of Main Street Data further position TipRanks as the leading research platform for non-institutional investors." - Uri Gruenbaum, CEO of TipRanks

  • Boardroom Alpha (Data Profile)
    • Main Data Category: Accounting and Governance Risk (AGR)
    • Brief: Provides data and analytics on governance, executive performance, insider trading, board composition, institutional voting, and SPACs for all U.S. public companies.
  • StockTwits (Data Profile)
    • Main Data Category: Social Investor Network
    • Brief: Social media platform designed for sharing ideas between investors, traders, and entrepreneurs. Tracks social/sentiment data from multiple primary sources to generate signals on various equities.
    • My Take: This data product was reasonably popular with hedge funds many years ago, but hadn't been a focus of the company for a long time...until now.

Recent News, Blogs & Podcasts

Information-Services-Insight-new
Information-Services-Insight-new.pdf
5 MB
download-circle

"These aren't places to build a career usually," said one former portfolio manager who has worked at several of the biggest multistrategy hedge fund firms. "It's a place to survive and get paid while you can,[...]because you don't know when things will turn against you."

  • The Ben Cohen Episode by The Alternative Data Podcast
    • Ben Cohen, former Global Head of Data Strategy at WorldQuant and now on gardening leave before his next opportunity[...] talk[ing] about the data sourcing role, how it has changed, who to hire for a team, how the data world is changing and the impact of AI.

10 Upcoming Events, including:

7 Recent Events of Interest, including:

Read more