Sold At "Irrational Exuberance". Still Lost Money | Sam Ro on the Bubble Paradox

Summary

Excess Returns Podcast Summary

Episode Title: Sold At "Irrational Exuberance". Still Lost Money | Sam Ro on the Bubble Paradox
Date: January 10, 2026
Guests: Sam Ro (Ticker), Kai Wu (Sparkline Capital), Excess Returns Hosts (Jack Forehand, Justin Carbonneau, Matt Zeigler)

Main Theme

This episode dives into the complexities of market valuations, profit margins, the impact of technological revolutions (especially AI), and the paradoxes of investment timing—particularly as they relate to bubbles. Sam Ro discusses how these factors interplay to create both opportunities and risks in long-term investing, urging listeners to look beyond simplistic metrics and narratives.

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Key Discussion Points and Insights

1. Are Valuations Still Useful?

• Sam Ro (04:27): Valuations absolutely matter—but primarily over long-term horizons. Over short periods (1–2 years), they’re poor predictors due to market noise and behavioral factors:

  "If you're trying to time a really great entry point, valuations are probably not going to help you... If we're talking about long-term, you might want to put more weight into valuations. Otherwise, don't be disappointed when the market doesn't do what you thought valuations would suggest."

• Short-term market movements are too random for valuation metrics to be actionable.

2. Historical PE Ratios: What Do Today’s Elevated Numbers Mean?

• The S&P 500’s forward PE is about 22, versus a 30-year average of 17.1. This is over one standard deviation above average, prompting debate over whether the market is truly "expensive".
• Sam Ro (07:30): It’s a good conversation starter, not a conclusion. Changes in business efficiency, operational margins, and the overall business environment may justify higher multiples today:

  "Companies are structurally seeing very different things today... better operational efficiencies, better credit quality, and a more productive business environment... must therefore justify a higher premium we're paying for earnings."

• Historical averages might not fully apply to today’s high-tech, asset-light corporate world.

3. Profit Margins: Persistent Elevation and the "Santa Claus" of Mean Reversion

• Sam Ro (11:09): It’s not just tech or price gouging—increased margins are due to a mix of factors, including healthier consumer and business finances, and the ability to pass on costs:

  "Much to everyone's surprise, [companies] were able to pass those costs on and the customers absorbed it... For me, central to why that counterintuitive phenomenon happened is people have money."

• Despite expectations for margin compression, strong balance sheets and spending have kept them high.

4. The AI Revolution and Its Impact on Margins

• Kai Wu (15:24): AI is posited as a new, transformative force, with questions about whether it will structurally lift or compress profit margins.
• Sam Ro (17:00): Initial evidence is mixed; some firms report tangible productivity gains, others are experimenting. Crucially, AI investments aren’t free, and rising software costs could offset productivity gains:

  "We may see productivity unleashed, but... we have to understand how those costs are going to evolve. I'm bullish, but it's an unanswered question."

5. Valuations Adjusted for Margins

• When adjusting for structurally higher margins, current valuations seem less extreme—even logical—over the past decade-plus (21:18).
• But is this a "new normal," or a temporary anomaly? The jury’s out.

6. Tech Company Multiples and PEG Ratios

• Technology companies trade at higher multiples, but when accounting for expected multi-year growth, these valuations become more rational (23:41).
• Forecasting multi-year earnings adds uncertainty, however.

7. Bubble Paradox and Timing

• Sam Ro (26:14): Bubble discussions are complicated by semantics and investor psychology. Exciting paradigm shifts always generate euphoria, overshooting, and eventual corrections.

  "We will get to a place that in retrospect will be defined as a bubble... But the problem is, we don't know how to time any of that stuff."

• Reference to Alan Greenspan’s “irrational exuberance” and the .com bubble: Even perfect market-timers could lose money if out of the market too soon (28:45).

8. Comparing AI to Historic Paradigm Shifts

• AI’s impact likened to the Internet, or even the advent of automobiles—disruptive shifts that reconfigure labor and value chains (31:59).
• Sam Ro: "It makes things better, cheaper, or faster. That's the essence of meaningful tech advancement."

9. Overbuilding, Infrastructure, and Who Captures Value

• Kai Wu (41:25): Draws parallels with the railroad and telecom booms. Historically, those who build the infrastructure often don’t reap the largest rewards; rather, it’s the users or secondary adopters who benefit most.
• Sam Ro (43:46): Overbuilding and subsequent write-downs are inevitable. The graveyard of former "must-own" companies is vast; the key is diversification and humility.

  "There will be write downs because the ROI for something that they invest in doesn't deliver... This happens 100% of the time."

10. Mag 7 (Magnificent Seven) and Market Leadership Dispersion

• The market’s recent leadership concentration (Mag 7) broke down in 2025—dispersion increased, with outperformance shifting away from tech mega-caps (50:26).
• Bubbles tend to show indiscriminate buying; recent market action instead suggests selectivity and healthy skepticism.

11. Tech Shifting From Asset-Light to Asset-Heavy

• The move towards “asset-heavy” models (e.g., AI data centers) makes tech more capital-intensive, undermining old valuation justifications (53:18).
• Lower moats, higher depreciation, and more complex competitive dynamics may bring multiples down, but earnings growth could keep share prices resilient (58:38–60:49).

12. Turnover Among Top Companies Is the Historical Norm

• The top 10 companies by market cap change regularly; incumbents rarely remain kings forever (62:02).

13. Skepticism on Price Targets & Presidential Cycles

• Price targets are a largely pointless exercise, useful only for inferring bias, not for actionable investing (63:06).
• Presidential cycle returns are similarly unreliable—seasonal narratives may reflect underlying macro dynamics, but are not to be leaned on (66:39).

14. Sentiment & Surveys as Lagging Indicators

• When most investors view "the AI bubble" as the top risk, it may already be discounted—surveys often lag market realities (68:41).

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Notable Quotes & Memorable Moments

• On timing bubbles:

  "If you had sold out completely of the market when Greenspan said that and then perfectly timed the bottom in 2002 and bought, then you would have actually lost money."
  — Sam Ro (00:43, repeated at 28:45)

• On what technology shifts do:

  "Good tech... makes something we have better, or it makes something we have cheaper, or it makes something we have faster."
  — Sam Ro (32:52)

• On recurring overbuild:

  "I'm convinced that all these players will overbuild and there will be write downs. This is not me guessing. This happens 100% of the time."
  — Sam Ro (44:41)

• On structural market leadership:

  "The lesson of history here is it's very difficult to predict what will be the leaders in the future. But history also reminds you that the incumbents rarely stay there."
  — Sam Ro (62:24)

• On asset-heavy shift in tech:

  "It's a lot harder to run a capital-intensive company than one that's run by a lot of people putting code into the same computer... especially when you're thinking about things like valuation."
  — Sam Ro (53:18)

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Timestamps of Important Segments

• 00:43 — The bubble paradox: "Irrational Exuberance" and why even correct bubble-calling/timing can still lose you money
• 04:27 — Are valuations still useful? Nuances beyond headlines
• 07:30 — How higher profit margins and tech evolution justify higher multiples
• 11:09 — Persistent profit margins: supply, demand, and economic health
• 15:24 — The AI revolution and its potential impact on profit margins
• 23:41 — PEG ratios and tech multiples: rational or not?
• 26:14 — On bubbles: semantics, cycles, and lessons from history
• 31:59 — How AI ranks with prior paradigm shifts
• 43:46 — Who really wins in tech buildouts? Overbuilding and inevitable write-downs
• 50:26 — Mag 7, market leadership, and sector dispersion
• 53:18 — From asset-light to asset-heavy: implications for tech's fundamentals
• 62:02 — Why turnover among top companies is the norm
• 66:39 — Presidential cycles and market seasonality: fact or fiction?
• 68:41 — Why most sentiment surveys are lagging or contrarian indicators

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Final Thoughts & Recommendations

• Kai Wu’s relevant piece: “Surviving the AI Capex Boom” (Sparkline Capital)
• Sam Ro’s chart roundup: “27 Charts to Watch as we enter a new year” (Ticker)
• Core messages:
  • The market’s apparent excesses or “bubbles” are often more nuanced than they appear.
  • Timing bubbles is almost impossible; maintaining broad diversification and a focus on fundamentals is essential.
  • Technological shifts create as many losers as winners. Don’t get star-struck by current incumbents.
  • Valuation, growth, and narrative all matter—but none are infallible.

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“We can both agree that we’re in a bubble, but also agree that it’s going to be incredibly difficult to time how this bubble works. Because... it’s not just about selling during a bubble, but if you’re a long-term investor, you also have to figure out when to come back in. So that’s two incredibly difficult decisions you have to make.”
— Sam Ro (29:33)

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For a deeper dive:

• “Surviving the AI Capex Boom” by Kai Wu (Sparkline Capital)
• “27 Charts to Watch as we enter a new year” by Sam Ro (Ticker)

Transcript

[Kai Wu]

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[Sam Rowe]

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[Sam Rowe]

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[Sam Rowe]

Slack business plus I can tell you with 100% certainty that we're either in a bubble or this will eventually be a bubble. But I can't tell you if prices will, if we're near a peak, or if we're going to find ourselves in a place where prices ultimately end up lower than where we are today. I'm convinced that all these players will overbuild and there will be write downs. This is not me guessing this happens 100% of the time. One of the most popular figures and phrases to come out of that whole.com era was fed Chair Alan Greenspan saying, questioning this possibility of you know, but how do we know if there's irrational exuberance in the market? If you had sold out completely of the market when Greenspan said that and then perfectly timed the bottom in 2002 and bought, then you would have actually lost money.

[Excess Returns Host]

You're watching Excess Returns, the channel that makes complex investing ideas simple enough to actually use for better conversations come from better questions. Kai Wu from Sparkline Capital, he's co hosting with me today, and our guest is none other than Ticker's own Sam Rowe. Sam, welcome back to Access Returns.

[Sam Rowe]

Thanks for having me.

[Excess Returns Host]

So we're jumping right into the deep end here. We're talking market valuations and before we do that, are valuations even useful anymore? Does anybody care? Can we just throw them all out the window like a White House press conference? Can I get some couchy odds on this? Does anyone.

[Kai Wu]

Does it matter?

[Excess Returns Host]

Should we even be having this conversation? Can I go home?

[Sam Rowe]

Absolutely. Absolutely. They better having said that, you know, it's it. I think, I think the way to think of it is they absolutely do matter, but there's caveats to that perspective. Or we could say they don't matter, but there's caveats to that perspective. Right? Like understanding what Valuations actually tell us. Well, it tells you the premium you're paying for a company's earnings. Or if you want to get really into the theory, the future cash flows, the net present value of the future cash flows of a particular company. The challenge there being, well, what is this company going to earn not just this year and next year, but into the rest of its existence? How is this company going to actually be in existence 30, 50 years from now? And that's where things begin to get a little bit treacherous in terms of things like valuations, on how much weight you want to put into those things. But in terms of using that information as something that's actionable, the history tells us that it really depends on your time horizon. If you're trying to time a really great entry point or something, valuations are probably not going to help you because they won't tell you. Or historically there's very little reliable signal when it comes to where prices will be over short term periods, like one or two years. So you can have elevated valuations where prices continue to go higher, but you can also have low valuations where you think that might be a good time to buy, but prices actually sink further. So I think in the context of maybe longer term thinking, you might want to put more weight into the valuations, but otherwise don't be disappointed when the market doesn't do what you thought the valuations were telling you they would do.

[Kai Wu]

So what I'm hearing is valuations matter over a longer time frame, but on any given day, who knows, it's not a meaningful signal.

[Sam Rowe]

Yeah, and I, I think the other thing too is, you know, maybe at extremes and maybe at like the stock level, you know, things like PE ratios. Right. It's very simple what those ratios are telling us the price you pay versus for, you know, one year's worth of earnings. So if you're paying 20 times earnings and you're, you know, you're making the assumption or you can extrapolate that, you know, you can get your investment back in 20 years assuming earnings go sideways or something. And so 20 or 18 or 20 versus 22. It's like if you're a business owner and you think about it in terms of that this is a rounding error, it's great that you made your money back in 18 years versus 22 years, or let's say it takes 22 years to make your money back instead of 18. Well, that's not the end of the world either. So I think in terms of long term investing, like 90% of these debates with valuations is mostly about things like, you know, is 22 too high relative to historical average of 17 or is, you know, 12 now attractive relative to historical average of 17? From my perspective, I think it's a good discussion to have, but from my perspective, I think we're, you know, sort of dealing with what ends up becoming a rounding error over the long run. But yeah, if we're talking about a 1 PE versus a 200 PE at those extremes, and I think, yeah, let's actually take a closer look at what we're about to buy because you might not want to buy at 200 and you know, I don't know, maybe it's like at one pe, but the company's finances are really great. Yeah, maybe you buy the whole damn company.

[Kai Wu]

So you mentioned a 22 pe relative to a 17 historical average. Well, so it turns out that that's exactly where we are today. So entering this year, the S&P 500 forward PE ratio sitting at 22 times earnings against a 30 year average of 17.1. And so I'll put this chart up as well for the viewers, but we can basically describe this, you know, in one sentence, which is we are currently sitting over one standard deviation above that historical average of 17 times. Does this, what does this tell you? I mean, you have, you know, plenty of folks on, on TV saying, oh yeah, this is one of the most expensive markets in history. Do you agree or disagree? You know, what, what are we missing here? What are these guys missing?

[Sam Rowe]

Yeah, I mean, I, I think, I think it's a good place to start conversation about value in the market. It shouldn't, it certainly shouldn't be where discussions end. Right. You shouldn't end with whether or not you're going to buy into the market or buy into a particular stock because of the PE ratio. I think you start with the PE ratio and then try to figure out, well, what else is going on here. And something that is being increasingly, I think, appreciated in the analyst and the strategist community is this idea that, well, it's not just sort of the mix shift of the makeup of the stock market or the S&P 500, but across the board we're talking about companies where structurally they're seeing things that are very different today than what we might have seen, know, seven or eight years ago or 15 years ago, or, you know, however far back you want to go when it comes to calculating what these historical means are. And you know, broadly speaking, you have better operational efficiencies and operating Margins, the financial structures are much more healthier with companies with much better credit quality. And then there's things that are sort of even external to the businesses themselves, like just the business environment, broadly speaking, like being able to conduct business over cameras and webcams. Think about how much productivity we would have lost if we all had to meet in one place to record do this podcast. That's productivity that is no longer being lost. And I think we take that for granted when it comes to everything that happens in business. Right. So maybe just the very fact, like, you know, let's say, for instance, operational efficiencies and credit quality and all that stuff has actually been fixed for the last 30 years. Well, little things like this that we're doing right now where the business environment and the available apps and the Internet and all these things make us that much more productive must therefore justify a higher premium we're paying for earnings and cash flows, which, by the way, that in itself is very much rooted in theory. Things like, you know, higher return on capital very much justifies things like higher premiums that you should pay for a business when you go shopping for investments.

[Excess Returns Host]

Well, before we assume too much economic value in this podcast, which I assure you we're all making lots and lots of money on in the private jets that would otherwise put us in person. Are there somewhere, I'm sure, if we just study the accounting. And to be fair, a big part of this conversation came out of your piece 27 charts to consider as we look forward in the stock market. So we're going to pull more of these charts up, but make sure you check that out if you're watching this online. The next place I want to go is related because it's the ultimate. And what I think higher valuations are supposed to come from and where there's supposed to be mean reversion and that's profit margins. Like, is Santa not coming this year? Santa? Profit margin compression. Sam, what's going on? This one really gets at me and I think it gets at the core of the technological revolution that you were just hinting at before. But what the hell is going on? Profit margins?

[Sam Rowe]

Yeah, I think there's. There's a couple of things and it's, it's definitely not one thing. It's definitely not just tech. It's definitely not necessarily just price gouging or whatever you want to call it. It's definitely not just, you know, companies, you know, squeezing more out of the few workers that they have. I think it's a combination of all those Things that we're. We're seeing right now. But yeah, to the point about elevated profit margins and thus waiting for those cows to come home. And why aren't we seeing some reversion to some historical average? I do think that while we haven't seen it, I do think that there is some merit in understanding that that could be a risk. We live in a competitive business, extremely competitive business environment, and one of the easiest ways compete against one of your peers is to undercut them on price while delivering something similar, if not marginally inferior. I don't know. But yeah, this has been the question that we've all been wrestling with for at least five years. Coming out of the COVID pandemic, you know, there was this issue with supply chains and inflation was starting to creep up. And there was this idea that with cost inflation, profit margins would inevitably get crushed because companies would not be able to pass off, you know, 20% increase in egg prices or whatever to their customers. But much to everyone's surprise, they were able to pass those costs on and the customers absorbed it. Now, what's going on here? Again, I thought we were in a competitive society and all these things and people shouldn't be willing to stomach those price increases. But they did, and they knew they were coming. And they responded to the consumer sentiment surveys. They voted and they all expressed outrage to all these higher prices that were passed on from these companies who had these really big, gigantic, fat profit margins. So what are we to make of that? For me, I think central to why that sort of counterintuitive phenomenon happened and why it continues to happen is people have money. It is still the case that household finances, you know, some people are doing better than others, but in aggregate, household finances still continue to be very strong, if not healthier than they were, you know, pre pandemic. And there's the same thing with, you know, a lot of businesses, too. Balance sheets are much healthier. You know, companies have a lot more cash. You know, some. A lot of this stuff is normalizing, but in recent years, they've been unusually flush with cash and have had very little leverage. Which actually goes back to some of the stuff we're talking about with valuations, right. Financial resources have. Not to mention the fact low interest rates and all this kind of stuff. So, yeah, I think it's as simple as an important part of this equation is that consumers and businesses have had money to absorb the higher prices that companies have been passing on. And so I think that's a very important part of this profit margin story, which is to say that maybe this is the year that maybe things go sideways with margins or maybe that they contract. But we're also entering the year again with finances, household and business finances generally quite healthy. So yeah, again this is, I basically started every year with this sort of same discussion where it's like I think this could be the year where people start to rein things in. But you know, I have, I'm like you guys, I follow the data and the data is saying that people are still spending.

[Kai Wu]

So this is kind of the trillion dollar question, right? Because if valuations are premised on elevated margins and being structurally higher, the question of where margins go will be kind of a double whammy. Should they mean revert? So here's kind of the question then, which is we talked about the pandemic which obviously is starting kind of subsided by now. The next big trend in the economy of course is the AI revolution, right? So you have folks who are saying look like this AI technology is game changing and surely that will have an effect on margins, whether it's through the kind of labor versus capital imbalance, the competitive landscape amongst big tech and other previously kind of monopolistic, oligopolistic market structures around efficiencies potentially to be gained. You mentioned the mix shift of companies as kind of technology has eaten in the world, profit margins have gone higher. So there's a lot of things I just brought up here, but I'd be really interested in your view, Sam, on how you view AI kind of coming into play on this trillion dollar question.

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[Excess Returns Host]

I was worried we'd bring back the same team.

[Sam Rowe]

I meant those blackout motorized shades. Lines.com made it crazy affordable to repl replace our old blinds. Hard to install? No, it's easy. I installed these and then got some for my mom. She talked to a design consultant for free and scheduled a professional measure and install hall of fame son. They're the number one online retailer of custom window coverings in the world. Blinds.com is the goat. Visit blinds.com now for up to 45% off with minimum purchase plus a free professional measure. Rules and restrictions apply. Yeah, it's, it's, it's a trillion dollar question that's got lots of issues that, where it's also very incredibly difficult to measure this in a very comprehensive way. And I'll be very clear, like in a comprehensive way. I mean historically it's always been very tricky to try to measure or even define what productivity is. But as someone who is mostly focused on the stock market, I don't go out there and do economic policy and I don't write an economic policy. I write a stock market newsletter for people who are long term investors in the stock market. So the North Star again, like sort of what we were talking about earlier is earnings. And then if we're talking about corporate earnings and company earnings, we have to go back to the conference calls and the individual earnings reports and the 10Qs and the 10Ks to see what the companies are actually saying at that ground level. And the anecdotes so far is, I would actually say that characterized as mixed in that a lot of companies will give you really tangible examples of how AI has materially increased productivity and improved the performance of their operations and all these kinds of things. And then there's others that are saying that we're still exploring or we're training and we're trying to figure this stuff out. So I think it's still pretty early to understand exactly what this looks like. I think in theory everyone wants to say that this is going to unlock a lot of productivity. It's going to be able to convert a lot of man hours into, you know, robot hours or whatever. And I think that side of it makes sense. But yeah, it just, it does come down to like how the economics of this thing actually work because not because this stuff isn't free. Right. I mean some people are using the free versions of ChatGPT or whatever to, you know, write memos and things. But you know, the enterprise version of this stuff is not, know, isn't free. And there's honestly, there's no reason to think that things will continue to be free and, or cheap for a very long time. Like, you know, at some point, you know, I think these AI companies are going to start saying, oh, you really like this product and you've unlocked $100,000 worth of productivity last year. Well, we're going to raise the price of this thing from 20,000 to $50,000 a year and it's like, how does that look? So I think from like a top line perspective, yes, we may be able to see productivity unleashed, but you know, in order to really understand the economic value of that productivity, we have to understand what the, how those costs are going to evolve. So yeah, it's an open question. I'm, I'm bullish on the possibilities on technology, but I do think it's an unanswered. Two unanswered question. Two unanswered questions are to what degree do you get productivity? And two, what do the costs look like over the long run?

[Excess Returns Host]

Embedded inside of this is what parts of these profit margin increases are structural. You had this really great chart from Truist that I think is fascinating. I'd love to have you unpack it. It's basically valuations are less extreme when you adjust for structurally higher profit margins. What's going on in this image?

[Sam Rowe]

Yeah, so, you know, this actually, this is basically tying everything we've just talked to together, right? You know, looking for an explanation as to why things like PE ratios are, are, you know, more than a standard deviation above their historical average. Well, you know, how many standard deviations above historical average are operating margins and net margins? They're elevated. And so there's a, you know, you look at a chart like this where, you know, you know, at least over like the, you know, past 10 or 15 years, there's this upward trend when it comes to things like profit margins. And you know, there's a lot of noise along the way, but you know, valuations have been trending higher over this period too. Now, you know, of course we can also talk about things like interest rates and all these things over this period which of course contribute to net margins. But the bottom line being that there is this. Seeing profit margins trend higher helps you understand why you have higher valuations. Is it an actual structural thing or is it just sort of a 15 year. Because that's another thing too. It's like 15 years very much feels secular and structural. But maybe 30 years from now we realize, well, that was actually an anomalous period, I don't know. But for now I do find it satisfactory that valuations have been increasing alongside profit margins.

[Kai Wu]

And so I guess the next question relates to the questions around composition. Right? We're talking about the, the U.S. market, which of course has become increasingly tech dominated over time. And you know, we've, you know, one of the things we've seen is that tech companies tend to trade at premium multiples relative to their non tech peers. So, so the question is this, which is, you know, to what extent is this justified? You actually have an interesting chart here showing PEG ratios, which I believe adjust P ratios for expected growth. Can you maybe walk us through what this is telling us? And you know why this may or may not justify the kind of higher multiples at which tech companies tend to trade?

[Sam Rowe]

Sure, sure. So, so, so this chart comes from JP Morgan's Michael Semblist, who, you know, adds one more dimension to this PE ratio discussion, which is extending out that earnings forecast by an extra year and saying, because when we're talking about 18 PE versus 20 or 22 PE versus 18 average, we're actually only talking about based off of one year forward EPS estimates. This one adds one year and it's an average of two year forward EPS estimates. And when you have 20% earnings growth followed by another 20% earnings growth, maybe it makes sense to think about those sort of stacked earnings forecasts. And so what he's showing here is that when you do look out a little bit further with what the expectations are for, let's say 20, 27 earnings, then the valuations do become more rational because it looks like, you know, like what we were talking about before, it's going to take 22 years to earn back one year's worth of earnings. Well, if the next, if, if the year after next, the earnings level is much higher than, it's going to take far less than 22 years to earn back that earnings. But as with everything, there are caveats, right? As much as this helps us understand why valuations might be elevated, we also have to understand that when you're forecasting two years out, there's a lot more uncertainty. Like we don't know what's going to happen next week. And now we're, and we already put so much faith in what happens on one year's worth of earnings. And now with a measure like this, which again helps us understand why we're trading at a premium, we also understand that there's going to be that much more uncertainty attached to the measurement because we're now forecasting earnings that we won't know about for two years.

[Excess Returns Host]

So we love banking on things that aren't here yet. Which is a very short way to say, what's your thought on bubbles? What's your thought on the AI bubble question? Is that even a question worth asking in the face of just you're couching the whole future as uncertain as you should? But is that bubble question even fair?

[Sam Rowe]

Yeah, I think it's, I think it's totally fair. And I think it's, it's also the only reason why I don't like talking about bubbles per se is as soon as you say invokes certain memories and imagery in people's heads, they all go.

[Excess Returns Host]

To tulips right away. That's the.

[Sam Rowe]

They all go to tulips. But some got a tulips, some go to South SEAs, some go to.com, some go to, you know, depending on their age, they're going to look at, you know, crypto a couple years ago and, and I think that's an important point, right? Everyone sort of defines what a bubble is differently. And so I think from that perspective it's not helpful to, to start by saying, you know, are we or are we not in a bubble? I do think that history tells us that when there is something exciting happening, when there appears to be a big paradigm shift, whether it's technology or whether it's industrial uses for certain things or maybe a new pharmaceutical or something happens, there's a lot of excitement and when there's a lot of uptake. And by the way, Everybody from age 3 to 80 are telling you different ways that they're engaging with AI when you have this kind of excitement. Yeah, I think it's inevitable that you overshoot when it comes to things like investment activity and valuations and all that stuff. So my view is I am very confident that we will get to a place that in retrospect will be defined as a bubble because we know that the prices shot way beyond what was actually a justifiable valuation. Problem is, and this is the other trillion dollar question is when is that going to happen? And we just don't know, especially when we're thinking about stuff that's going to upend a global economy with 8 billion people and tens of trillions of dollars worth of economic activity. And all these numbers that we hear about every day about capex investment and all this stuff, it's all mind boggling. But when you begin to normalize things with the potential impact, it becomes much murkier. But of course that's the kind of language someone who's hyping this stuff will say. But the last thing I'll say about this though is the problem again is we don't know how to time any of that stuff. I can tell you. Let me actually put it this way. And this is one of the lessons from the late 90s, by the way, one of the most popular figures and phrases to come out of that whole.com era. Was fed Chair Alan Greenspan saying, questioning this possibility of. But how do we know if there's irrational exuberance in the market? Whether or not he was talking about bubble specific, I don't know. But people go back, even looking at history in retrospect will point to that as a sign. But what people sometimes forget is the market continued to go up for four years after he said that. And when the market eventually bottomed, 2001, 2002 or whatever, post bubble, the S&P 500 at the low then was still higher than when Greenspan made that statement. So if you had sold out completely of the market when Greenspan said that and then perfectly timed the bottom in 2002 and bought, then you would have actually lost money. So it speaks to this whole challenge of this timing. And listen, it's great that people want to try. Listen, we're not always talking about all in and all out, right? Maybe you take some risk off, take some profits off or whatever. But the point being is we can both agree that we're in a bubble, but also agree that it's going to be incredibly difficult to time how this bubble works. Because, listen, because it's not just about selling during a bubble, but if you're a long term investor, you also have to figure out when to come back in. So that's two incredibly difficult decisions you have to make.

[Excess Returns Host]

In the forthcoming DeLorean ETF suite, we're adding the 3x reverse Greenspan trade in honor of Sam Rose.

[Sam Rowe]

I'm sure we'll find demand for that one.

[Excess Returns Host]

I'm sure we will.

[Kai Wu]

So it sounds like, you know, you think that euphoria is kind of a part and parcel with any technological revolution yet. The challenge is that, you know, knowing in real time if you're in a bubble, and it's even just unclear what the intervention might be. So let's put aside the kind of price action bubble discussion for a second and instead focus on the real impacts of this technology. Right. Where would you rank, and this is maybe an unfair question, but where would you rank AI relative to the other inventions of history, the Internet, electricity, the automobile, so on and so forth, in terms of how you anticipate it transforming the economy? You have folks in Silicon Valley saying this will be the last invention, that basically this will obviate the need for human labor. That's obviously an extreme view and they're talking in their own book, of course, But I'd just be curious when it comes to the real productive impact of AI putting aside kind of any of the questions of whether shareholders will make money or not. Where do you think this ranks?

[Sam Rowe]

I think it ranks with. Maybe it's kind of a cop out, but I do think it kind of ranks with the Internet. Actually, let me change that a bit. I'm sort of thinking on the fly here. Maybe we go back to automobiles because you know what, automobiles replace horses. And there was a whole horses, you know, horse, horse drawn carriages and all that stuff. That used to be pretty big business. There used to be a lot of horses that, that took people around and there were a lot of businesses that supported horses. Everything from blacksmiths, you know, making horseshoes and cobblers and people bailing hay and cleaning up shit on sidewalks, you know, all day long or whatever. It's incredibly disruptive. And, you know, that put a lot of people out of work. I mean, my goodness, like that entire, like think about all those attached industries. But then, yeah, you had the uptake and then, oh, and not to mention speaking of bubbles and overshooting, you know, there were hundreds, you know, maybe even thousands of automakers in the wake of that, the whole dawn of that paradigm shift. And then of course, there were some winners and losers or whatever. But yeah, I think maybe that's it. But in terms of the sort of the nature of the transformative impact, I think it's as simple as when you do think about what does good tech or a good technological development really offer. I think fundamentally it has to be some combination of it makes something we have better, or it makes something we have cheaper, or it makes something we have faster. I think when you start to think of things in terms of that, people who write interoffice memos love these chatbots and stuff, who will draft a memo for them in 30 seconds as opposed to them having to write, work this from scratch for 45 minutes or an hour or something. Every lawyer and paralegal on the planet will tell you about how this is absolute miracle. If they're not telling you that they're lying. They understand how this stuff works and it is changing the way people who work on paper are doing business. I don't, I'm not convinced, I'm definitely not convinced that it just replaces all people because, you know, there is some intangible value that, that people have to offer when it comes to, I don't know whether it's the sale of a product or the delivery of information or, you know, something else people are looking for when it comes to the interaction that the AI might be replacing. So I don't think this is the end of people. But I definitely do think that it does replace a lot of work that used to be done by people. Like, you know, an example that the analogy or example in media is often, or the first, the first sort of skeptical take is, well, hey, wait a second, we can't trust a robot to report out a story and write an article and send it out. Who's fact checking this? Who's quality controlling this? Who's going to confirm that these sources actually exist? Well, here's the thing. AI doesn't have to be perfect. AI doesn't have to be good at any of those things, by the way. It just has to be better than what you have. And with entry level reporters or even experienced reporters, you have an editor who does have to do the fact checking, who does have to. This reporter has to earn the trust of this person to know that these anonymous sources actually exist. And all the things that should go in vetting the work of whatever the AI is replacing, you know, all those steps will continue to exist. But the difference between the human reporter, the junior writer or whatever and the AI is AI will file the copy in 30 seconds as opposed to the junior writer who might take four hours, six hours to put this graph together. And it's the same thing that you have to go through the same rigorous editing process. And there are examples of this across the board where it doesn't fully solve all of your problems, but it does certainly save you time in the process of doing things that are the normal course of business.

[Excess Returns Host]

Inside of this, there's a lot of money being spent on AI by these companies. And I do think it's interesting, especially taking it back to the bubble analogy of these companies are not only just spending absurd quantities of money as investment, research and development, capex spending and expensing it off. How do we reconcile if this is ever going to be worth it? Or go, oh no, this is thoughtless spend that's happening right now?

[Sam Rowe]

I don't know, I don't know.

[Excess Returns Host]

That's probably the right answer. But how do you think through that? Because I mean, some of these numbers.

[Sam Rowe]

I think the starting point, I think the starting point is appreciating that this isn't like pet rocks or something where it's very difficult to see the tangible value that you get out of what you're investing in. All this discussion about replacing man hours, which cost a whole lot and come with health insurance and all these things, you can begin to measure that stuff out. What's really tricky is actually nailing what that ultimate productivity and the value of all that looks like. I'm not sure anybody who was working on the Internet in the late 90s understood where we would be today in terms of what that technology has offered in terms of the value add. And there's good and bad things that have come with, with all this. But it's like, I think the point being that we, it's just so hard to envision what things might look like 10 years from now. But as far as like the spend, you know, there's some companies that are, are sort of at playing around in sort of treacherous financial debt territory a little bit more than others. And then there are some of these bigger companies that are financing almost all of this with their free cash flows from their existing businesses that are already massive. Whether that turns into some big credit event that ripples through the markets, I don't know. Maybe that's not what we're talking about right now. But in terms of the economic value of like all this capex spend. Yeah, I don't know. I think we see it in hindsight. I do think though that a lot of the folks who are working on this, whether they are at Google or Meta or Amazon, a lot of the, maybe the engineers themselves are not, weren't around back then, but they're coming from a culture that was established during this period where they know that, you know, what if you can win, you know, whoever wins in, you know, 99 or 2000 or 2001 will dominate for the next 20 years. And you know, you go from, I mean, like think about search engines back then, like think about all the different search engines, like starting to forget some of those. But like ask G. Altavista. You know, no offense to one of my former employers, but I mean even Yahoo was massive back then and had a huge valuation. And then a couple years later, you know, everything gets blown out by Google and then Google just keeps improving on their product and they never stop improving on their product and you know, they add all different things alongside whatever that search was and they figure out how to monetize it better. And now we're talking about trillion dollar companies. And so I think that's what people see at stake here is not just the AI, but there's going to be all kinds of things that are going to be attached to the AI and the software and the services that come about here. But yeah, maybe it's not winner take all or maybe not to be number one, but you definitely want to be out front and the way to do it with any kind of investment is you got to throw a lot of money at this thing.

[Kai Wu]

So, Sam, what I'm really interested in understanding is how we see the value of AI accruing through the value chain. Right? Because obviously the AI ecosystem is not a monolith. There are data center companies, hyperscalers, chip makers, RAM producers, there are the electricity component and then there's the users, the adopters of technology. Now one interesting thing we've seen, you know, when we study historical episodes like this, you know, think about like the railroad build out in the 1860s, right? There are hundreds of railroad companies built that were founded in the us Most of them went bankrupt in the dot com boom, right? The telecom index. These telecoms, like Global Crossing, AT&T, spent, you know, billions of dollars building out the fiber optic infrastructure for the Internet. That index, the telecom index, went down 92% and has never recovered. Even today, it's still below its high watermark. Right. So one of the interesting patterns you've seen historically is this kind of irony where the guys who are actually building out this infrastructure, who are kind of building the future, literally, they are the ones who do not actually capture the value of their creation. Instead, it's the users, right? The fact that we all get to enjoy subsidized AI inference, or the enterprises, the customers of these infrastructure builders who have actually stood to benefit. And that's just a historical pattern. Maybe this time will be different. But I'm just curious. We talked a little bit just now about the competitive dynamics amongst big tech, where these big tech leaders view the market as winner take all because of their experience in the cloud and mobile and the browser war, so on and so forth, and as a result, they're willing to commit insane amounts of money with the hope that they will lock up the market. Right. Like, does that, you know, kind of game theory dynamic, you know, potentially lead to an overbuild, potentially lead to a situation where there's too much capital at the infrastructure layer and, you know, maybe the profits don't end up there, they end up becoming commoditized. Instead they flow down to the users of this kind of subsidized infrastructure. The Netflix, you know, and Facebook's who benefited from the cheap bandwidth, you know, that happened due to the stranded assets in the, in the dot com bust. What are your kind of thoughts on this argument which I think people are increasingly making?

[Sam Rowe]

Yeah, I think that makes a whole lot of sense and sort of following up on what we were talking about earlier? Yeah, I think there will be tremendous. Overbuild. I think there's going to be, it's going to be sad, but there's going to be a lot of idle empty data centers and stuff gathering dust because we totally overshot. Maybe it gets used eventually. But yeah, I think that the promise of this from an economic standpoint and this even outside of the hyperscalers, the reason why there's this much excitement, the reason why there's putting this much money into this is because of the far reaching second order secondary benefits. Right, the users. Like you're saying, really the only reason why I would be excited about any of this is not because of how much money I want to make investing in Mag 7 stocks. The reason why I'm excited about this is because I think that My S&P493 should do incredibly well here. And again, anecdotally across industries, people are talking about unlocking value from using this technology that they're already deploying. There's a lot of experimentation, but a lot of these places are already deploying it. And some of it is starting to show up in labor market data in terms of how hiring and all this stuff happens. But yeah, to your point, you know, listen, there's a long, there's a very large graveyard of companies that were once the hottest thing on the planet and you know, maybe moved in to these sort of paradigm shifting areas where you know, the, the secret to being number one was to build and build and build until you reach the point where you realize, you know, you're the roadrunner that ran off the cliff or whatever. I'm never going to rule out the possibility because history always repeats this by the way. I'm not going to rule out the possibility that some, maybe all of the mega cap tech companies we're talking about today might not be around in 10, 15, 20, 30, 40. I'm going to keep increasing that number in 50 years. I don't want anybody smart yell at me if they're still around in five years. But that happens. And it's like in order to keep, I mean, because if there's one thing that investors want and the executives and the shareholders and the board and all these people want from any of these companies to see that perpetual earnings growth and the cash flow growth or whatever and as long as there's going to be demand for that, they're going to keep pivoting in directions where they're going to see the next year or two's worth of growth or whatever and then maybe eventually it leads them To a place where they can't come back and they become obsolete or the product that they help develop becomes commoditized and they no longer own the rights to it. Like a pharmaceutical company that loses the patent on the multibillion dollar drug and they have to find something else and if they don't, they end up going sideways and all this kind of stuff. So yeah, I think that's a very real risk. And this is why I preach things like the merits of being very broadly diversified. Even when you have confidence in who the market leaders are and when you see those two year earnings growth forecasts are much hotter for certain places. But maybe that just means it's a good time to be in stocks that are outside of that category. But yeah, to your point, I would never. I'm convinced that all these players will overbuild and there will be write downs. This is not me guessing. This happens 100% of the time. There will be write downs because the ROI for something that they invest in doesn't deliver and it becomes an impaired asset or a factory needs to close and all these kinds of things. And we're going to hear about oh well, it's just a non cash write off, blah blah, bullshit, you know, whatever. But yeah, I think that'll certainly happen. That's just the nature of when we have interesting things happen when it comes to technology and innovation.

[Excess Returns Host]

So another piece that's fascinating here, Sam and I want to bring up this chart from B of a s and P500 revenue per worker. A how flat this was for 15 years is really interesting to see. But B to what you're talking about like driving earnings. A big part of driving earnings is driving growth and actually seeing the revenue poor employee revenue growth increase now for the first time in a minute, this feels pretty optimistic. This feels like a good case.

[Sam Rowe]

Yeah, it's great. I mean as an investor in companies like this, I think you can't help but be thrilled. Of course, all things being equal. Right. Hopefully you're not burning more cash on something else to make this happen. But your employee headcount is usually one of, if not the most expensive thing in your cost structure. To be able to get more revenue per worker is a great thing because again everything from all the tools, whether it's the Internet and Google Meets and all these things that help us be more productive. Yeah, I think you can't be anything but optimistic and there's really no reason to believe that this is going to go in an opposite direction.

[Kai Wu]

So you mentioned earlier this Idea of what's happening with the Mag 7, the Magnificent 7 stocks. For the longest time, basically the market has been defined by one theme, which is, are you bullish Mag seven or not? Right. What's so interesting is the Magnificent seven aren't really a monolith or no longer a monolith. So 2025 was a really interesting year where there was kind of unprecedented dispersion across the different names in this category, with of course, Google leading the way and then Amazon lagging. Talk to me more about what happened this year, why this dispersion happened, and what you say, what does this portend for the future potentially?

[Sam Rowe]

Generally don't like to pinpoint too much on even, even, even a one year's price performance. But I will say that this is one of the more important things that happened last year. If not, it's maybe it's one of the most important things that happened last year in terms of signaling that it's possible for this idea of a Mag 7 to sort of break down a little bit. Most of the Mag 7 names last year underperformed the S&P 500 and forever. There were many people who are committed to this idea that the whole stock market is being held up by the Mag 7. And frankly, for a period of time, that was true. But when you speak in those terms, the assumption is, well, if this narrative breaks down, then maybe the market starts to break down. But no, that's not how markets work. It is possible for a set of leaders to boost returns, but it does not necessarily mean when those companies lag, that those returns start to lag. All that means is that it may be an opportunity that the narratives start to evolve. But yeah, I think there are two really great lessons here. One, that you can have a ton of these trillion dollar companies underperform and still have a market that does very well. And two, I guess sort of like getting back to the bubble talk. All right, One of the things that you do see or hear about with bubbles is indiscriminate buying. Right? Just keep bidding up the prices with anything even remotely attached to whatever that theme is, whether it's.com or AI or whatever. It appears to be the case that the investor trader class was not indiscriminately buying AI stocks. They were picking winners and losers themselves. And so I think that makes for a very healthy, if not more reasonable market than something that's just insanely bubbly. Which again speaks to my reluctance to try to time what may or may.

[Excess Returns Host]

Not be a bubble inside of these Bubble mechanics. There's this evolution that's going on too that I think is fascinating. I'm putting one of Kai's charts up here, so a little extra shine on Kai for coming up with this one. This is fascinating to me. You have these asset light companies that have been growing like crazy and they're now transitioning towards basically asset heavy companies. Is that a negative in terms of them dominating the markets? What do you make of this evolution in really balance sheet composure?

[Sam Rowe]

Yeah, I thought, I mean, everyone should read Kai's report on this. Like this was a really a breath of fresh air in what has been a lot of sort of repetition in terms of the same narratives. But I think this is actually a really important story here. The idea that, and I guess it's sort of general theme of our entire discussion here. We can never just think in terms of price and earnings. It's like you start from those points and try to dig deeper into what's going on. And when you have something like this where we might be witnessing a major long term structural change in terms of operating structure and capital structure at these companies, then yeah, the way you think about valuations and things like that need to evolve because it's a lot harder to run a capital intensive company than a company that's run by a lot of people putting code into the same computer. So beyond that, I don't think I really have too much to add. I think I'd like to hear Kai's sort of bottom line on this. But the only thing I would add is, you know, over the last couple of decades every single one of these companies have evolved their business models and added businesses and gotten out of businesses, you know, you know, Facebook used to be a site where you, you know, click on, you know, your friends photo albums and now it's got, you know, WhatsApp and Instagram and all these kinds of things. You know, Microsoft, everyone had to buy Office, but now, you know, they're Cloud and LinkedIn and Xbox and all this stuff and it goes on and on and on. But yeah, the latest iteration of everyone building data centers and getting, you know, neck deep in hardware is, is something to absolutely be mindful of, especially when you're thinking about things like valuation.

[Kai Wu]

Yeah, I mean, I think, Sam, you pretty much summed it up. I mean, I think, you know, going back to my earlier point, I summed.

[Sam Rowe]

It up only because I read your note, by the way.

[Kai Wu]

Well, you did the most important thing, Sam, and you plugged me too.

[Sam Rowe]

So.

[Kai Wu]

No, what I was going to say is I think the main, the first thing you said on this talk today was capitalism is all about competition. And what made the Magnificent Seven so dominant and perhaps will continue, but at least we can say with certainty looking back was that they effectively kind of carved up all major digital services and said, hey you two got this one, you two get this one. Basically creating this impenetrable oligopoly built on network effects and ip, various digital moats that allowed them to earn really, really high returns on very little capital. It doesn't require much capital to write code and if you have the lock in of the ecosystem, then the profits are all yours, which is incredible. Now the concern is that these companies view AI as an existential risk and as a result they are saying we're going to go all in on this new category which we believe will collapse all markets into one. So whether you're doing shopping or search or chat or social media, it's all just going to be AI agents now. Okay. And if that is the case, and that's their belief, it could prove being wrong. But the point is that they're operating under this assumption, then what happens is the competition goes up a lot. And it turns out that the ability to build AI data centers is not like a unique thing that only Google and Microsoft can do. It turns out that Oracle is this legacy database company can just say, you know what, like I'm just going to roll the dice here, why not and spend money it doesn't even have on building our data centers. It turns out that Bitcoin miners, that companies like Core Weave, these so called neoclouds get entered the race as well. So basically it's not, there really is no moat as far as I can tell, aside from the ability to want to spend more money when it comes to building AI data centers. And that's what concerns me because we know the history of the railroads and the telecoms, they're basically utilities. Yes, of course we all rely on this critical infrastructure. If the Internet were to go down, that would be disastrous for the economy and for society. That being said, do these companies earn extra super normal returns on capital? Not at all. Right. They have to always be replacing their depreciating assets. There's obsolescence, there's wear and tear, not great businesses to be in. So to the extent that we are potentially seeing the Magnificent Seven rotate into what is, I would argue a much worse type of business, that is concerning just given the extent to which investors have been so conditioned over the past 15, 20 years to just assign them these really elevated multiples on the basis of them having these kind of asset like compounding machines, which they still have, but it's increasingly being diluted by, you know, what is more of a utility business.

[Sam Rowe]

Right, right. 100%. 100% agree. The one thing I will add is we could, it's possible, it's very possible that, you know, this evolution in business structure can continue to go in this direction. And it is also possible that the investor class does wake up to this and decide that they're going to assign a different multiple that's much more conservative than what it is right now. Before everyone goes out and starts selling all these stocks. And this gets into sort of the broad philosophical discussion when it comes to stuff like PE ratios and whether or not they mean revert or whatever. Let's assume that they do mean revert. And let's say for instance, these big tech companies see their PE ratios mean revert over what length of time, I'm not sure. But if during this interim period where their valuations get recalibrated, if during this interim period they're still registering double digit earnings growth, it is possible that you see them watch their multiples come down 1, 2, 3 times, whatever, and still see the prices either go up or go sideways because the earnings are still holding up. I think this story is one of the more interesting things that's going to be finance business school case for years to come because, yeah, I think as quickly as people were happy to put huge premiums on earnings of these companies, if they continue to go in this direction, where they get very capital intensive in this world where there's no moat, then yeah, I hate to say it, but it's going to be really fascinating to see Alphabet or whatever trade at 10 pe. And will he visit this on the podcast?

[Excess Returns Host]

We'll revisit it. And it's, I think of Apple, however many years ago, when you're looking at, on an adjusted cash basis, we have historic examples of like great, incredible companies trading at bizarro valuations. And that can happen again too.

[Sam Rowe]

I mean like, and you know, in, in Kai's chart here in his report, you know, it's funny to see AT and T on on there, you know, ATT once one of the hottest companies on the freaking planet. Like there wasn't a sexier tech company than Big Telecoms at one point and now we insert it into a chart to basically almost speak disparagingly of the hottest companies of today.

[Excess Returns Host]

Yeah, we beat on them and all Those baby bells that came out of.

[Sam Rowe]

It.

[Excess Returns Host]

It'S crazy to think about. I want to lightning round you through a few more charts from the deck that you put together, Sam. So let's just hit a couple of these because I think they are useful. Your quick take. Top 10 companies by decade. We're going to get this chart up on the screen. Top 10 companies by decade. It's supposed to change. It's supposed to turn over. Is there room for a paradigm shift here? Could we see this break?

[Sam Rowe]

Absolutely. Absolutely. I, I have pretty high, deep degree of confidence that in 2035, at least half of these names will turn over. I'm not sure what the other industries and sectors are going to look like. Maybe there's a world where AI replaces everything, but we also have a great distribution of wealth where half of us are in the leisure industry and Royal Caribbean becomes one of the top 10. I don't know. I don't know. But the lesson of history here is it's very difficult to predict what will be the leaders in the future. But history also reminds you that the incumbents rarely stay there.

[Excess Returns Host]

Wall street price targets, pointless exercise. Fun bingo card to throw up once a year. Best to forget after January 2nd when they're all stale.

[Sam Rowe]

Yeah, no, I've been reluctant to say this by. I'm getting more comfortable saying this. It's a pointless exercise. And I think increasingly it's getting out that even the strategists don't like this particular exercise. The only redeeming thing about price targets is it sort of helps you get a sense of a strategist or analyst bullishness or bearishness in terms of their interpretation of the fundamentals and what they are forecasting for fundamentals. The research notes that come with these price targets are actually, I find to be quite interesting.

[Excess Returns Host]

Those are the best parts. We did a episode just on a whole bunch of these for this year. I think we read 22 or 26 of them. But in every single one, because you see top line, bottom line, the profit margin projections, what they think the drivers are. Is the multiple going to change? Is it going to expand? Is it going to compress what's driving that?

[Sam Rowe]

Right, right.

[Excess Returns Host]

That doesn't show up in this chart.

[Sam Rowe]

It does not. It does not. It really is a shame because some strategists get a really bad rap because the price target is off, and then some strategists will have terrible research but somehow nail their number. I think one sort of anecdote I have here that I feel like is Just factually, just not covered. Is the chief strategist at Morgan Stanley, Mike Wilson became really famous two or three years ago because he was the most bearish strategist in 2022 or something. And I remember at the time I was following, they send me his research and stuff and I was reading through his note and I thought the most interesting thing that he had to say this was end of 2021, early 2022, was he had this really interesting view on operating leverage and how companies were structuring and all these things. During COVID a lot of companies have refreshed in a way where just a little bit of revenue growth leads to a lot of earnings growth and you're going to see profit margin expansion, all this stuff. So he had really great intermediate term bullish thesis when it came to fundamentals. But the reason why he lands on a bearish price target was because of his view on multiple compression, as we often do. But yeah, you know, we're looking back, you know, backwards and you know, talking about things like high profit margins and, you know, where they've been, why they're happening. And it turns out one of the people who had one of the more compelling arguments for this and who has predicted this was a market bearer three years ago. So, yeah, for my subscribers who are on some of these research lists, I tried to encourage them to look past those price targets because they're usually interesting things being said about the underlying fundamentals.

[Excess Returns Host]

All right, I've got two more fun ones for you here. S&P 500. During the presidential cycle, 1950 year to date, we all talk about this stuff. We talk about who's in office, we debate them endlessly online. Obviously in the midterm year, you go into another country and you take the president. This is included in all the data points here. This is a bunch of crap. Should we care about presidential cycle returns or is it actually useful?

[Sam Rowe]

I generally don't care for, you know, one, two, three year seasonal patterns. You know, most of the time. And I'll tell you why. Most of the time, any way you slice historical numbers by, you know, certain years or certain months or whatever, you know, it always comes out to, you know, either 70% or 90% of the time, you know, the stock market still ends up positive. And so but you have these precision numbers. What's interesting about like this midterm stuff, and again, I think you still take it with a grain of salt, but you be aware of it, is there is a relatively consistent pattern here and happens to be somewhat Rooted in something that makes sense to people in that midterm years are pretty uncertain from a policy standpoint. And so it's not crazy to think that as US Leaders are thinking about power dynamics later this year, that there is a lot of hemming and hawing about policy. And as a result, you get some policy uncertainty and that just gives you a force you to discount prices. So again, I don't think everybody runs to the exits, but this is just saying, you know, don't be surprised if, you know, we are down 19% or something at some point this year before things inflect higher again.

[Excess Returns Host]

All right, one more. This one's close to my heart because I think this is a enormously useful survey piece in the same way that the annual forecasts are. And I want to read the reports. This is the fund manager survey from Merrill Lynch. I love this because this is basically the boogeyman that we're all scared of. And so right now, it's the AI bubble. 38% of correspondents are basically saying that's the biggest tail risk information. Like this. Is it useful?

[Sam Rowe]

I think this is one of the great lagging indicators in that by the time a risk shows up here, it's usually either too late or it's confirmation that it's stale information. I mean, this is actually perfect, right? The fact that bubble is number one, that's not what you see in bubbles. Bubbles are when everyone says it's not a bubble and everyone's bidding stocks up. If you have 40% of the professional financial markets world saying this is a bubble, then it's probably not. You know, my favorite example of, of how this top risk list has evolved was before March of 2020. Pandemics and viruses were not even on the top 50 of these things. And then they show up in April, but that's when the market bottomed. So. And it was on that list for another year until, like, vaccines went on, we had inflation. But coronavirus dominated this list from spring of 2020 into maybe late 2021, while coronavirus was happening. But that was also the best buying opportunity in recent history. So it's helpful in that. Okay. It helps us understand what people are worried about. But yeah, it's either a combination of contrarian or stale or just an outright lagging indicator.

[Excess Returns Host]

Beautiful, beautiful stuff. I'm going to thank you both. Kai, you go first. Would you just say the name of the piece that we pulled that chart of? Because you've been thinking so eloquently about this. This is why we wanted to make sure you were here with Sam today. What's the AI piece that you wrote?

[Kai Wu]

It's titled Surviving the AI Capex Boom.

[Excess Returns Host]

Highly, highly recommend you go find that. Sparkline Capital is where you're going to find Kai. Or look them up online. Sam, same question for you. Plug this piece that you wrote for Ticker with all these charts in it.

[Sam Rowe]

Yeah, I think it's called 27 Charts to Watch as we enter a new year. Every once in a while I'll do these nice big chart roundups that sort of give you a nice cross section of sort of my broad thinking in terms of markets. And if anyone listening is interested in getting some free access, just reply to the free subscription email and let me know. And I'm happy to extend some comp months.

[Excess Returns Host]

You know you want it. And Sam, you get bonus points for not doing 26 charts for 2026 or something dumb like that. I loved when that said 27. Take that marketing brains. Fantastic stuff. Sam. We're going to have you back real soon. Kai, thanks for helping us today. You're watching Excess Returns. Like subscribe, comment, all the things below and we are out. Thank you for tuning in to this episode.

[Sam Rowe]

If you found this discussion interesting and valuable, please subscribe on your favorite audio platform or on YouTube. You can also follow all the podcasts in the Excess Returns [e-mail]. if you have any feedback or questions, you can contact [e-mail] no information on.

[Kai Wu]

This podcast should be construed as investment advice. Securities discussed in the podcast may be holdings of the firms of the hosts or their clients.