Read Part One to learn about the origins of the R/Finance Conference in Chicago.
A Conversation with Jeff Ryan on the Origins of Chicago’s R/Finance Conference and the Challenge of AI
“I’ve always been uncomfortable with people stealing personal data from me,” says Jeff Ryan, founder of Chicago’s R/Finance conference https://www.rinfinance.com/.
He grins.
“Unfortunately, that’s one of the predicates for building an AI engine: you have to pretty much steal massive amounts of data that have essentially already been stolen. And it seems to me that when you take away the hype — the noise and the branding — there’s still no actual intelligence in AI. It’s souped-up Natural Language Processing, which some of us were doing ten years ago.”
He raises what he considers the core question.
“What is generative AI actually generating? At this point, it’s new glosses on old stuff — close-up magic, old parlor tricks dressed up to look new. In the end, we’re still just talking about information retrieval — much smarter than a card catalog, sure — but we weren’t very excited with card catalogs, were we?”
He pauses.
“Let me back up. AI’s good at putting things together. But that’s not problem-solving. When you give it an actual problem that hasn’t been solved, what does it do? It makes things up. That’s why, for now, I avoid relying on it at all costs.”
On the other hand, he says, there are definitely places where AI can be useful.
“The ability to scale up makes a difference, and AI can do that. It’s also pretty amazing with graphics, though at the moment, that stuff may actually be more dangerous than anything. And it also helps with code completion.”
In finance, though, Ryan believes that AI-driven quant and systematic trading face a difficult underlying challenge: trying to remove biases. In his view, almost all finance-oriented AI platforms are trained on the same data.
”In the end, they mostly wind up reacting to each other. It’s the old story: a new trading idea is great until somebody else figures it out, at which point it stops working. To me, that’s where AI is today – always ‘learning’ what its counterparts are doing at the same time that they’re learning what it’s doing. It all leads to a giant info loop. I don’t know how you get past that, even with a large language model. Outside the realm where an AI instance is trained, it will tend to fail. Things will break.”
One place Ryan does see strong potential is with signals.
“Over the last decade or so, we went from tracking 10, 500 or 1,000 meaningful signals to tracking millions. If AI and advanced machine learning can help combine signals – combine, say, 45 weak signals into a single meta-signal — it’s very possible there are things you’ll discover that might help with portfolio construction. I’m sure PM fundamental people would argue against this, but I suspect large language models could find ways to transform fundamental analysis into something more quantitative. A machine that can do highly nonlinear combinations could be really valuable.”
As for Ryan’s own efforts he says his goal remains what it’s always been: to find the simplest solution that works.
“An approach that’s reliable enough to perform at roughly 90% of what might be possible will give you more than enough edge, especially if the last 10% carries big risks — like the current generation of AI.”
Disclosure: Interactive Brokers
The analysis in this material is provided for information only and is not and should not be construed as an offer to sell or the solicitation of an offer to buy any security. To the extent that this material discusses general market activity, industry or sector trends or other broad-based economic or political conditions, it should not be construed as research or investment advice. To the extent that it includes references to specific securities, commodities, currencies, or other instruments, those references do not constitute a recommendation by IBKR to buy, sell or hold such investments. This material does not and is not intended to take into account the particular financial conditions, investment objectives or requirements of individual customers. Before acting on this material, you should consider whether it is suitable for your particular circumstances and, as necessary, seek professional advice.
The views and opinions expressed herein are those of the author and do not necessarily reflect the views of Interactive Brokers, its affiliates, or its employees.
