How Funds Use AI to Beat Rivals
episode
Making Billions: The Private Equity Podcast for Fund Managers, Alternative Asset Managers, and Venture Capital Investors
35 min
2 speakers
4 chapters
transcribed 1 month ago
Transcript
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Transcript generated automatically by AI and may contain errors.
What is the main topic discussed in this episode?
Hey, welcome to another episode of Making Billions. I'm your host, Ryan Miller. And today I have my dear friend, Jan Salati. Jan is the CEO and co-founder of Reflexivity, the AI investment analysis platform used by firms, including some of the largest funds like Soros Fund Management, MUFG, and a lot more just like it. He holds the fastest economics PhD in Harvard history, earned under Ken Rogoff, along with a BA and MA degrees in mathematics and economics from Yale. Over a two-decade global macro career, he traded alongside Stanley at Duquesne Capital and managed portfolios at Fortress Investment Group and served as the co-CIO of Global Macro at Glombard ODA, running a $15 billion book. Reflexivity has raised over $40 million with a $30 million Series B led by Greycroft and Interactive Brokers and personal backing by the man himself, Stan Druckenmiller and Grey Coffee.
So what does this mean? Well, it means that the man who builds the AI tools that the biggest funds in the world are using right now is about to show you how to use them too. So you can better find trades, protect your portfolio, and compete with funds 100 times your size. So with that said, Jan, welcome to the show, man. Thanks for having me. Looking forward to it. It's good to have you here, man. I've been a big fan and I remember the first time that we met, you absolutely blew me away with what you've created at Reflexivity and how it helps a lot of hedge funds and traders just really understand what's going on in the market to a degree that it just synthesizes a lot of data. And I know I'm not doing it justice.
You're probably the smartest guy I've ever talked to in my life, but I'm excited to get into this, man. So with that said, Jan, you ran a $15 billion macro book. You traded alongside the legend Stan Druckenmiller at Duquesne. and you hold the fastest economics PhD in Harvard history. And today, your platform, Reflexivity, powers research at firms that are some of the biggest in the world. So walk us through exactly how a fund manager uses AI to surface a trade idea that the human eye would easily miss.
Yeah, first of all, thank you. You're super kind. The main keyword here that I would emphasize is the knowledge graph. So we at Reflexivity use a combination of the reasoning layer of large language models like Claude or, for example, ChatGPT. And then we combine that with a knowledge graph, which is really a very comprehensive mapping of all sorts of relationships in the investing world that matter. So giving the system some degree of understanding that if the yield curve is steepening, that could be good for banking stocks, that if there is a rise in oil prices, that might change the ethanol-gasoline blend and so on. What portfolio managers will therefore do is use this capability to be able to better understand ripple effects from a number of
market events so something happens in the market could be a macro event a micro event a geopolitical event and what everybody is racing to find out is what are the implications for my portfolio are there downside risks are there potentially opportunities that are arising from this and a system like reflexivity and i think ai at large is extremely well placed to be able to very quickly ascertain some of these implications and give you an edge that way brilliant
So when you and I first met, we talked about placing trades and really just how do you form thesis in hedge funds? And you definitely experienced that. And we kind of landed on, really comes down to the trade idea and that expression of that idea. And so I'm just curious, based on that, how does reflexivity and the software that really helps these traders, how does it tie into both of those very fundamental things as far as building a hedge fund?
Yeah, that's a great question, actually, because I think a lot of focus often when it comes to investing is on idea itself. And the reality is that I think a lot of people will come onto the same idea, but where those who are extremely, extremely good at this, but usually excel is the actual expression of that idea.
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Chapters
4 chapters
1
What is the main topic discussed in this episode?
0:00–10:45
2
How does Reflexivity use a knowledge graph and LLMs to surface trade ideas?
10:45–18:43
3
How does AI help express a trade idea differently than the idea itself?
18:43–27:48
4
What did trading with Stan Druckenmiller teach about sizing and price-action validation?
27:48–35:33
Speakers
2 identifiedMore from Making Billions: The Private Equity Podcast for Fund Managers, Alternative Asset Managers, and Venture Capital Investors
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