Joining us now, Art Amador. Art is the CIO at QuantumStreet AI. Art, it's really good to have you on the show today. Grateful for your time. Let's start by talking all about QIS. That's QuantumStreet's new AI investing system. What is it, and what is it actually looking for?
Yeah, so QIS is actually Quantitative Investment Solutions. This is the unit that sits within large banks. And the interesting thing is QIS has actually doubled since 2020 and now sits over $850 billion of assets. So what we do is we're an index provider. So we use artificial intelligence to help bring different strategies to life. And so we combine macro, fundamental, technical, and news in order to drive better data-driven investment decisions. And we have about $8 billion currently tracking our index assets that is powered by AI.
So I find this interesting. Your models turned bullish somewhere around the Liberation Day lows, the Liberation Day sell-off around April of last year. What do you think the AI saw then that too many investors missed at the time?
Yeah, so I think it goes back to really the advantage of using AI and specifically our AI. We specialize in the combination of macro, fundamental, technical, as well as news. And so Liberation Day was really interesting because actually at the trough, when the market was down nearly 20%, our system was actually predicting that the market would go up about 7% over the next 30 days. In reality, it actually rallied closer to about 14%. And what our system had actually seen was that there was some solid guidance as it relates to fundamentals. Some of the technicals were overdone. But one of the most interesting things is that it had seen how Trump had spoken about trade in his prior term. And so what the system was able to do is to recognize that, hey, this is a very similar pattern. And that's essentially what AI is, pattern recognition. It said, hey, when markets sell off, when they have sold off in the past based on trade talks, they quickly rebound. And so the system was able to kind of see through that and make that prediction where a lot of CTA strategies, trend following strategies, continue to de-risk and miss the huge upswing in the marketplace.
Alright, everyone seemingly out there wants exposure to AI. How does your system separate the actual winners from the hype? Separate the signal from the noise?
Well, that's that is always the that's always the challenge. And the way to think about it is we don't just process information for the sake of processing information or trying to process the most information. It's exactly what you just said is separating the signal from the noise. And so the way to do that is we build unstructured data side to really kind of understand the trust in the unstructured data in the news, for example. So what sources can be trusted, what sources cannot be trusted, and then take that information and effectively combine it with different combinations of different data sets, so macro data, fundamental data, technical data, in order to understand where markets are headed. And really, that's what AI does. AI is not a crystal ball, but it's meant to understand when relationships are changing and then essentially adapt to those changes.
Art Amador, CIO, Quantum Street AI. Art, grateful for your time. Thanks for joining us today.
Thanks, JD.
