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- [00:00]
A
On this episode of Full Signal, I am sitting down with Anthony Pompliano to talk about Pro Cap Financial because I have just joined as the chief market strategist. I am very excited about this role because we are building Wall Street's first agentic AI research shop. And that means we're using an army of agents to produce world class research about stocks, macro thematics and much more. We get into all of that and more. I hope you enjoy this conversation.
- [00:29]
B
All right, Phil, now that we got these supersonic tsunami of AI working on our side, we got this whole AI system, these little AI agents going and putting their little prickly fingers all throughout financial markets, going through heaps and heaps of data and trying to figure out where are their hidden insights. The people want to know what the heck type of research is this thing going to be publishing? So let's start maybe with the first report that we're going to talk about today. This idea of actually stacking different trends or different insights so some people care about, hey, what companies are going to benefit from the oil shock. Obviously, if energy prices are higher, then we're going to figure out that some people that are selling energy, they're probably going to make more profit. But then a whole separate different trend is tariff refunds. And so if you put those things on top of each other, that's pretty hard for a human analyst to do, is start to try to think through multiple things stacked on top of each other. AI is great at doing this kind of complex thing. So what kind of research did these AI agents come up with here?
- [01:23]
A
So I will say there are teams and teams of Wall street analysts that spend all their time looking into the data, looking at markets and what we have essentially done, as you're saying, we have armies of agents doing that for us while you and I maybe record a podcast or, you know, do other work. And I'm working.
- [01:40]
B
I don't know what she talked about.
- [01:41]
A
We're working. Of course we're working. The catalysts that I thought were most interesting, there are three stocks that our agents essentially came up with for this one report, which is called the Stocks that Will Win from Both Tariff Refunds and the Iran Oil Shock. The three stocks are Baker Hughes, Valero Energy and Cheniere Energy.
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B
So that's by Alpha, right?
- [02:03]
A
That is alpha.
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B
And I certainly thought process behind why those two things stack together are so powerful.
- [02:09]
A
So they all three benefit from the Supreme Court ordered tariff refunds. And then they're also very, very tied to the Iran oil shock. So between those Two catalysts. I don't know if there's any other stocks that kind of fit that Venn diagram that fall in between.
- [02:27]
B
So it's like a dual catalyst where higher energy prices, pretty easy. All the companies in energy, like, this is one of the things I think people don't really understand about higher energy prices is as a consumer, it sucks. You go to the gas pump, gas prices are higher. You're like, this sucks. You worry about inflation. Oh, there. All these other things that need gas or energy going to become more expensive, they. That sucks. But for the country and for these companies, actually, they're profiting from this. The US Is a net exporter of energy at this point, and so higher prices mean that the United States is. We're filling up the bag full of money right now. And so it's this weird dichotomy of, like, what's good for the country may not be good for the citizens and vice versa. But you're saying these three companies in particular are really benefiting from higher energy prices?
- [03:12]
A
Yeah. So I think the oil shock, generally, the obvious trade would be buy something like Chevron or Exxon Mobil, maybe, because they are just oil giants and there's sort of the explicit play on this. But they don't have the second catalyst of tariff refunds coming their way, unlike these three companies. So according to the research here from ProCap Insights, an equally weighted basket of the three has returned 39% year to date, outpacing the S&P 500 energy sector by 9 percentage points. And the S&P 500 energy sector has been far and away the number one sector in the benchmark this year. I think it's up maybe 20, 28% as of this morning. So just getting these three stocks, you're crushing the best sector. And I don't think we would have been able to find these stocks or highlight them without using our agency.
- [04:04]
B
It's a little fishing for, like a needle in a haystack there. And the AI can obviously go do that. Now, what's interesting is up 39% as soon as I hear that, I'm like, oh, hold on, that's up pretty big. But none of the refunds have hit yet. And so the companies have not actually captured that refund revenue, if you will. And I think if I remember correctly, when I was reading the report, some of them actually have called out what was the drag on their revenue because of tariffs. And in some cases, I think it was like 100 to 200 million dollars. Obviously, if they get that back, that's a pretty big boost to their revenue. You know, if you're getting nine figures of what you thought was going to be an expense, now all of a sudden becomes revenue.
- [04:43]
A
Yeah. And I think the, the pairing of getting all these refunds at the same time as sort of a geopolitical macro catalyst. I have not seen anybody pair those things together or even get anything close to, hey, let's take these two outlier scenarios or like tail risks and put them in the same stock analysis.
- [05:03]
B
So you're saying it's like bing boom bong.
- [05:05]
A
Yes.
- [05:05]
B
Right, right. To put them two together and we go up. Okay, got it. What's the second report you got?
- [05:10]
A
So one of the most.
- [05:11]
B
I like that you liked bing boom Bomb.
- [05:12]
A
You know, that's part of our strategy. So one of our most popular Wall street narratives, I would say, is that when a company cuts headcount, their stock will go up. And we saw that with the block.
- [05:24]
B
Why? Because lower expenses.
- [05:26]
A
Lower expenses. The idea of efficiency. So Meta had this thing a couple years ago, right? Their year of efficiency. And that sort of kicked off the narrative of hey, the more you fire people or shrink your headcount, the better your stock returns. But the.
- [05:41]
B
You mean when Zuck was going to put them all in the metaverse? Well, I can say that as a former employee, he's the man. But I had to say it.
- [05:47]
A
We know what happened there. The story is not so clear in the data. There's actually very little correlation between headcount reduction and stock returns. Oh, interesting. And we essentially found in ProCap Insights the four biggest headcount cutters in big tech, which was Meta, Shopify, MicroStrategy, INTC. Yep. Averaged 181% three year return. But the nine most aggressive hiring companies, which includes Nvidia, averaged 173%. So it's very similar.
- [06:19]
B
And here's my take on this, right? You cut headcount for one or two reasons. You can cut it because you're becoming more efficient. You got great technology that means more profits. Or you can cut it because you're getting your face punched in by the market and things aren't going so hot. So cutting doesn't always mean that you're cutting for positive reasons. It could be cutting for negative reasons. Now that's with the benefit of hindsight buys, because I read the report. The second thing is that you could be hiring and that could mean that your margins are collapsing because revenue is not growing as fast as you're hiring and therefore you're making less money. But also, I don't know if you've seen these reports from like Nvidia. Nvidia is talking about they got a gazillion dollars of backlog. I mean, some of these companies are just like, yeah, we could try to service this revenue for the next, you know, century. And we still can't keep up with, with Anthropic, they just went, I think in one month from 19 billion in annualized revenue to 30, they added $11 billion in revenue in a single 30 day period. Now what's interesting about that is that's after they got in a little tussle with the Department of War. So maybe that's good marketing for them. But they ended last year, anthropic did, at $9 billion of revenue, annualized revenue, and now they're at 30. We're not even four full months into the year. It's crazy. So for them, hiring actually probably is a positive sign because they're printing cash right in terms of revenue. And so, hey, that means that this is good. And so I think what the AI is able to do, which is really interesting, is it basically can question these narratives and you don't come at it with this like, previously formed framework as to what happens. You know, a lot of people got in trouble in 2024 or 2025 because tariffs are inflationary. I don't know if you read that in your textbook in economics class. They're not. And all the people who got caught up in what the academics had told them, then dissent gets outlawed. And so no one's allowed to say that tariffs, what if they're not inflationary? And so you just get this big herd. It's like a bunch of cows all just going in, you know, looking for food together. But you know, sometimes the farm animals, they go to slaughter. You don't want to be with the herd in those moments. And so I think that AI is pretty good at trying to question these narratives.
- [08:24]
A
Well, to your point, if you only bought stocks that were having company announcements that they were cutting headcount, you wouldn't have performed that differently than if you bought companies that were hiring. So we have this chart from the research here. The top 12 performers include companies that cut, held steady, and hired aggressively. And there's pretty much no predictable pattern. So this is the narrative violation that the AI kind of parsed through and discovered. Because if you look at this chart, you have all these top performers, but there's no clear, okay, all of these were firing at the same time. There's nothing like that. So it's really about business management, business strategy separate from headcount size. Some of you may not have heard this, but our partners at Public just launched something called generated assets. It brings AI into investing in a way I've honestly not seen before. Here's how it works. You type in an idea like AI powered supply chain companies with positive free cash flow, or something like defense tech companies growing revenue over 25% year over year. Publix AI then dispatches a swarm of agents that can scan every single stock, evaluate them, and instantly build a custom index around your thesis. What really stands out is how clearly it explains why each stock is included. And before you invest, you can even backtest your idea against the S&P 500. So you're making decisions with real context and not just guessing. Beyond generated assets, Public lets you invest in stocks, bonds, options, crypto, all in one place. They'll even give you an uncapped 1% match when you transfer your investments over from another platform. If you want to build a portfolio that actually reflects your thesis, visit public.com openingbell that's public.com openingbell now, let's get back to the conversation before we get
- [10:17]
B
to the third report. If any of you are sitting at home and you're listening to this and you're like, what the heck are these guys talking about? I want you to understand that we're using artificial intelligence to go and find these hidden insights all throughout financial markets. But then once they find it, they bring it back and they sit and they argue with each other, which is actually pretty interesting. Imagine if you could have a friend. And I'm going to use a hypothetical situation. Imagine if you got a Republican friend, a Democrat friend. You got an optimist, a pessimist, maybe you got somebody who's domestically born and raised. Then you got somebody who came from an international market. You all sat in a room and you talked about a topic and then you argued about it. You probably would come away with a very different view of that topic after hearing all these different perspectives. And it may question some of the assumptions that you had, but you also may be able to implement your assumptions or teach them something from your perspective. The artificial intelligence agents are able to do this in a way that humans just can't do. I can't call up every single one of my friends every time I want to do something, right? But having these agents that come with certain perspectives and argue it, or steel man arguments, is really valuable. So they go and they find the Insight. They then do this whole little, you know, pressure testing and then my, my favorite part is then they wr and there's a lot of people out there that do not yet understand what's going to happen here. But if you write for a living, there could potentially, potentially be trouble on the horizon. What do I mean by that? If you're a research analyst, if you're a reporter, if you work in the media space, etc. I basically think in media there's three things that are safe. Scoops, long form profiles and live coverage. AI ain't going to do that. AI is not going to the straight or who moves and taking pictures on a secret camera of a ship that's on fire. AI is not going to be able to go and get the scoop. AI is not going to be able to write this long form profile with anecdotes and interviews and all this kind of stuff. But what AI is very good at doing is pro cap insights, which is it can go through all this data, can argue, can figure out what the actual information is and then it can write an entire report and only have one human boss. Which by the way, I was thinking about the other day, you're basically the boss of the agents.
- [12:09]
A
I have one of the biggest companies, got like 500 employees.
- [12:14]
B
You should just have a car that you know. Do you ever tell the AI like
- [12:17]
A
I'm your boss, listen to me, I should more often. They're starting to have some attitude here.
- [12:22]
B
All right, what's the third report?
- [12:24]
A
So we came up with this idea that what if the market rotation can actually be told in a story through insider selling? And that thesis, we pressure tested it with a bunch of AI agents and that ended up to be true. So we took all the SEC filings for insider selling and buying and we've essentially found that with the big tech sell off this year, tech insiders have indeed been selling at a unusually high rate. And at the same time everyone's talking about this broad market rotation into health care, energy, other sectors. And it turns out that energy insiders, health care insiders, are all buying to start the year as well. So I think the story of let's say rotation or broadening out in the market, that's what you're going to see in headlines everywhere. But then if you tell the story through actual SEC filings that show who is buying and selling on the inside, executive CEOs, things like that, then it gets really interesting and I think it gives a little more weight and insight to the broadening out story. You know, I'VE been writing about it a lot in my newsletter, but it wasn't until Pro Cap Insights that I got the insider data, which I think makes it much more robust.
- [13:32]
B
So what you're highlighting here also is like, if you go on any one of these lms, you could go, you could, you know, ask some questions, whatever. But a huge part is having access to real time accurate data with which is also fact checked source, you know, all this kind of stuff. And so a big part for those that don't know how these systems get built, that we had to spend time on, is trying to figure out where are we going to get the data from? What are the live feeds? How do we know it's accurate? How does the system actually double check what is the source of this information? How does it fact check that the source is actually giving accurate information? All that stuff is pretty important. But then if you add all that up on top, you look at something like insider selling and it's not actually usually that helpful to know, oh, a bunch of people are selling, okay, what do I do with that information? And so I think maybe the part that I enjoy the most about what you're doing so far is trying to make every single research report super, super actionable. Right. The goal being, how do you help people make money? Well, if you write a research report that's like, you know, the street or her Moses, water temperature is 37 degrees, who cares? But if you read a research report that says, yo, there's this one company and they're the ones who are taking the fee to get everyone through the straight right now, and nobody yet knows that probably in Q2, their earnings are gonna skyrocket. That's not a real company. But I'm just saying if that was
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A
true, we should find it.
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B
Yeah. Then all of a sudden that'd be a pretty helpful data point for investors who are trying to make money. So I think that's really the focus of, there's a lot of, you know, large research shops or big kind of financial organizations. They basically write what I think of as like, feel good reports. It makes the person writing it feel good, it makes the institution feel good. Right. But how does it help investors make money? And I think that's actually the place where me as an investor, that's what I want. I don't want a research report telling me, you know, the temperature of the water. I want to know, what's the company's name? Find me the company. And then, hey, I'll, I'll, I'll subscribe I'll do whatever you need. Right. As long as you keep feeding me information that would help me make money.
- [15:32]
A
And that's what these reports do, because I'm the one, you know, I read them very carefully and I look to see, okay, does this meet the bar of if someone reads this, is there an actionable trade to make here? And that's really what we're going for each day. And someone asked me this morning, actually multiple people asked me the same question. If you're running these AI agents to create research reports and you're saying there's alpha in them, trade ideas, couldn't anyone with ChatGPT say, hey, give me actual trade ideas about, you know, the Iran conflict or something like that? And anyone could do that. But I think what gets missed is that we have put in probably, you know, however many hundred hours in the last few weeks, building the prompts out, building the models out and figuring out how, okay, we have suddenly a 60 page prompt that is so specific and so niche to each type of report that we're producing, it's really hard to do that. Like, that is almost a proprietary edge in itself. Just the time we have put in to build out the thoroughness of the prompting and even the editorial strategy. And between you and I, we've probably written what, 10,000 articles by hand before AI even came out.
- [16:49]
B
You can call me a craftsman. Yeah, I mean, artisanal craftsman.
- [16:53]
A
There's a lot of, let's say, pre AI skills that come into the mix here, which I think gets lost in the idea that, hey, if I have chat cbt, I could just do what you guys are doing.
- [17:04]
B
If you're an analyst on Wall street you think is the future, you should hit me up. Because, you know, as I keep saying, imagine being an analyst that works at a big shop and you got like a boomer boss who came to spell AI. I mean, just crazy, right? You got to be so frustrated because also, like some of these organizations, they won't even let the people use AI they're worried about, oh, what if our data gets put in there? What do you know the crazy stuff people put into ChatGPT or, you know, Claude or. Come on, what are you worried about? Your secrets aren't really secrets.
- [17:35]
A
Yes. And I think one of the things that is certainly something that you and I don't deal with. There is a very old fashioned culture on Wall street that is not incentivized to innovate, I think, from the people I know on Wall street and people I speak with, all the time they are more worried about, hey, what is this quarter going to look like? Or who should I have lunch with to make sure I'm in touch with the right people to get this bonus this year things. And that's not exactly conducive or supportive of, hey, what's the fastest thing we can do today to move forward and beat everyone else on the street?
- [18:12]
B
Agents don't get paid bonuses, so we don't gotta worry about that.
- [18:15]
A
They might start asking for them, though. I don't know.
- [18:17]
B
They get asked, that's fine, just fire them. You know, bring their brother. All of a sudden, we'll have the next one. All right, that's it for today. Thank you guys for paying attention. Where can we send people?
- [18:26]
A
Procapinsights.com all right, and here actually, we got one little.
- [18:30]
B
Actually, if you stayed all the way to the end. See, this is when you watch the videos all the way to the end. You get a little bit sauce at the end. Pro Cap Insights is going to be for everybody else, $2,500 a year. It's cheap, right? One trade. But if you sign up in the next 48 hours, I think, or 72 hours, something like that, whatever's on the website, you'll get it for 9.99. That's $999. Is $1 less than a thousand because psychologically that makes you think it's cheaper. But the reason why that's important is because you get grandfathered in. So if you come in at 999, you get it for life at 999. It's like a sale that never ends. So go to procapinsights. Com, check it out there, and we'll talk to you guys next time.