Alternative Data Weekly #165

December 22, 2023

John Farrall

Dec 22, 2023

Thanks for being here!

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Announcement(s):

Merry Christmas Edition!

Vertical Knowledge will have a presence at two upcoming conferences:

Eagle Alpha’s January 18^th data conference in NY
BattleFin’s January 24-26^th data conference in Miami

Let me know if you plan to be in attendance.

Theme that emerged in this week’s email is … AI will create more “data people” as data is made more accessible.

QUOTES

“The raw material consumed by all AI approaches is data — lots of data — and the reality is that markets for the most part are data-poor, and frustratingly fickle.“ – FT Article: A Quant Winter’s Tale

“It’s important to set expectations for what you can achieve with machine learning. If you have lots of data points, you can make better predictions. But the only way we can get more real data is actually to just let time pass.” – Bryan Kelly, AQR

News Articles
Podcasts
Cool Charts
Final Thoughts (2023 Books)

#1 – HBR Published 5 Forces That Will Drive the Adoption of GenAI. December 2023.

My Take: Progress with AI is advancing rapidly. Companies are rapidly moving from talk to action. One of the biggest problems to solve is protecting internal data. Companies are rightfully concerned that their internal data will be made public, but the majority (78%) of execs continue to think the benefits of AI outweigh the risks. The hype is slowing as firms start to recognize what is feasible and what is unrealistic…bottom line, customers want the benefits of AI.
Of most interest to me was the falling impact of digital interactions. Given the massive volume of content, ads, etc … “the value they attach to the content is strikingly low”. AI will help customize/personalize & break through the noise…customers will expect no less. My prediction for Word of the Year 2024 = Hyper-Personalization.

#2 – Informa published The best of QuantMinds 2023: 10 Things Every Quant Needs in The New Year. December 2023.

My Take: Of course, I was hoping that #1 was going to be a reliable source of web data, but alas, that did not make the list. I do not want to simply share a list since QuantMinds puts this document behind a sign-up. Of most interest to me was #8, LLM & GenAI Applications with Quant Finance. I say that because I am now seeing quant funds more activity interested in alternative data, an area historically reserved for “quant-a-mental” or pure fundamental analysts. This is due to higher quality, more robust, ticker mapped, more frequent “alternative” data being made available.

BONUS: Google’s Gemini Team published Gemini: A Family of Highly Capable Multimodal Models. 2023. “We find that data quality is critical to a highly performing model, and believe that many interesting questions remain around finding the optimal dataset distribution for pretraining.”

What else I am reading:

Matthew Rand published Better Decisions, Faster: How AI Will Change Industrial Real Estate. December 2023.

FT’s Robin Wigglesworth published A Quants Winter’s Tale. December 2023.

Crosshatch’s What if you could have Spotify Wrapped every day?

Ethan Mollick’s An AI Haunted World. December 2023.

Hamish McKenzie published The AI revolution is an opportunity for writers (the human kind). December 2023.

Andrew Nadin of DecaSim published Are marketeers reticent to use AI? December 2023.

Source: Deconstructing Data Podcast interviewed Facteus Co-Founder Jonathan Chin. October 2023.

My Take: Enjoyed this conversation. Consumer transaction data is the OG among alternative data sources and Facteus has been doing this for a long time. Some interesting takeaways include the idea that barriers to entry are falling. AI will create more “data people” as data becomes more accessible to everyone.
Interesting conversation around spending trends & inflation (minute 22:00).
Lastly the idea that the ‘specific crowds out the general’ as larger companies service the average consumer & people with want more customized offerings.

Highlights (45-minute run time):

Minute 02:00 – intro & Facteus background
Minute 06:00 – how is Facteus helping people understand US consumer spending?
Minute 08:00 – who is Facteus customer? Today HFs? Moving toward corporate entities
Minute 11:00 – context is important for competitive intelligence
Minute 12:30 –trends you’ve seen that are particularly interesting? Spending patterns b/w income levels
Minute 15:30 – examples of market and wallet share
Minute 20:00 – breaking down by category or geography
Minute 22:00 – discussion of inflationary pressures (“fun-flation” example)
Minute 26:45 – combing consumer transaction data & AI
Minute 33:00 – make it easier for small businesses to compete against larger businesses
Minute 35:20 – favorite tools in the tech stack (Snowflake)
Minute 37:00 – advice for younger self

BONUS: Barry Ritholtz’s Masters in Business: Mike Rockefeller

Source: cnverg.io (an Intel company) published the results of a survey: The state of Generative AI and Machine Learning at the end of 2023. December 2023.

Lots of good charts in this 30-page document.

Summary:

“Overall, the 2023 ML Insider revealed that AI maturity has not changed significantly over the last few years. The rise in GenAI technology has shifted the industry in some ways, but organizations are slow to adopt it. Despite the hype, only 25% of organizations have deployed any genAI models to production in the past year.”

I was surprised more progress wasn’t made: