Eurodollar Talk: The AI Trade Is Entering Its Most Dangerous Phase | Lyn Alden

On an individual level, I think AI can be a savior in the sense that, I mean, it's never really been easier to start a business. The cost of doing so, at least for many of the industries, is lower than it has been. There are ways to get services and stuff like that at lower costs than there were 5, 10, 20 years ago because AI can really extend the reach of one person or a small team. We are very fortunate here at U of R University to have none other than Lynn Alden with us to talk about any number of things here. I think, Lynn, let's talk about the stock market because I think the stock market is on everybody's mind for good reason. This is one of the reasons I wanted to have you on. I wanted to get your take on what's going on with equities. We hear about everything, AI bubble, concentration risk. Should we worry about semiconductors? Is there a signal there? What do you think about equities maybe from a broader perspective and then maybe drill down into some more micro-scale topics? Yeah, big question. Happy to be here. It's been a long time since we had a chat. Yeah, equities obviously is a super broad topic, kind of a big focus of mine. I've been pretty bullish on equities just because of the fiscal environment that we're in. Now, obviously, there's certain areas that are kind of heated at the moment. But broadly speaking, when you look at the U.S. and globally, most of what we see in the equity market, I would say, is backed by fundamentals, which is that we have earnings growth. We have revenue growth for the most part. Obviously, there are pockets of excess. But in general, most of the moves have been rational. They occasionally get ahead of themselves. There certainly are risks. So the question is, how durable are some of those? I think that's a whole other topic. And I mean, even outside of the obvious areas, you know, the hyperscalers, the semiconductors, you know, the equity market's not as strong when you take out the winners. But, you know, I think that for quite a while, international equities were basically under-owned. You know, there's not a lot of reason to have just kind of excess capital in them, you know, especially globally mobile capital is mostly shoved into the U.S. It still is. So for some of them, just the fundamentals stopped going down. I mean, not many people would have guessed that. You know, during 2025, kind of the year of trade wars, that like Latin American banks would do amazing, right? But they were priced as though the world was ending and they just didn't. I mean, Brazil has super high real rates. Banks are priced cheaply. A number of other areas too, Colombian banks. I mean, you know, there's like weird pockets of the market you wouldn't expect that had like, you know, kind of crypto-like returns in a year you wouldn't think yet. So I think there's a ton of places to look in the equity market. And so I don't really treat it as just one big index, you know, just the NASDAQ or just the semiconductor. Or ETF or, you know, just S&P. Or just AI or just, you know, everything. I think maybe, Lynn, that's part of the problem here is that we hear only about a specific part of the market. It's sort of like the smallest little minority that's the loudest. So maybe our opinion or our view of the stock market is clouded by hyper-focus on one part of the marketplace. And as you're talking about, there's a whole other world out there. Yeah. I mean, so the biggest, like in terms of like the combination of size. And performance, you know, it's easy to understand why there's been so much focus on the AI trade. Because even though some pockets of the market have done really well, they're generally smaller parts. So the combination of some of the percentage returns that have come from the AI space combined with the starting size is truly remarkable. I mean, if you go back to, I think, you know, late 2022 or so, you know, if you kind of added together the top, call it 15 semiconductor stock. You're looking at something like a 2 or 3 trillion market cap with all of them combined. And then, you know, some months ago. I mean, when I compiled the data last time, I mean, that particular figure was well over 16 trillion, you know. And so you had both obviously a very big percentage gain in a pretty short period of time, a handful of years. And then you had just the sheer size of that happening in a lot. And then, you know, kind of the blow off top was that whole period from, say, autumn of 2025 into June 2026. I think some of the easier returns from that trade are over. I still think that some semiconductor names probably have a higher like to go before, you know, maybe the cycle's over. I think some of those bottlenecks. They still might persist for a period of time. But then even outside of that trade, I mean, for example, the equal weight S&P 500, while that's not been as high flying or exciting as some of the more concentrated areas, that's currently bouncing around all time highs. So even that is just grinding higher and you generally get, you know, you get more sector fusion, even though it's the same names as the market cap weighted S&P. You know, in general, because equal weighted, you're kind of more slanted toward the mid cap side than you are in the more concentrated, you know, the market cap version. So there are ways to have equity exposure that don't rely on being concentrated. And, you know, when when things are great, you're generally going to be underperforming. But if you do get kind of a big correction, some of the overbought areas, you're already more spread out. So I think, you know, if someone's looking to say a passive portfolio, as an example, they have an equal weight S&P 500 slice and a couple international slices and then other asset classes. There's not a lot to do over time. And of course, you know, if they want to be more active, they want to pick names if they want to get to where money's flowing in. They can. Maybe we're active. Yeah. So let's talk about maybe some emerging because I think that's probably a good segue. Right. I mean, if there is, is there a risk to the broader marketplace? So if all the returns are into this narrow segment, not all the returns, you know, being being oversimplified here. But if a lot of the returns, a lot of the attention, a lot of focus is in a narrow segment, does that potentially lead to, OK, we get into a capex cycle that starts to run into problems and then roll over, you know, the AI bust, AI bubble narrative that's out there. I mean, there's probably some truth. Does that threaten the overall marketplace because the overall marketplace hasn't participated to the same extent and therefore may not be as overvalued? Is there a sentimental channel where everybody just says, screw it, I'm out of stocks entirely? Is that the downside risk to the entire marketplace? What are the emerging things that you look at as far as, OK, it's been pretty good for the last couple of years. What could possibly go wrong here that spoils the party? Yeah, I think there's a handful of things and they're not surprises, but we're trying to get the timing right as far as one of them would be a more acute energy shock. You know. A lot of people are monitoring for risks of that. And two would be kind of the exhaustion, I would put it, of the AI cycle, or at least this part of the AI cycle. And, you know, any sort of technological trend can be early or can be overdone for periods of time. I mean, the dotcom bubble is the one everybody thinks of. And, of course, the irony with that was that, you know, 10, 15, 20 years later, almost all the things they expected came true. It's just that it was front loaded by like 10 years and not all the names they thought would win would be the winners. And you kind of had that next cycle come along. And, of course, some of the same winners like Amazon. And so, you know, there's a risk somewhat, I think, of that happening here, which is you overbuild certain things. You get too much capacity. You get overbought in certain areas. And then a lot of the bullish things come, you know, maybe not 15 years later, maybe five years later even. But you've already kind of done five years of gains in, say, a nine month period. And so that's, you know, that's one of the risks. And, of course, just like any new trend, there are unprofitable layers here. So, I mean, I want, you know, the kind of the end of the chain, the semiconductors. For the most part, they're doing free cash flow growth. So money's pouring in. They are doing CapEx, but they're making more than they're investing. So they're just kind of they're stacking cash. They're doing great. Are generally still trading at kind of pretty benign price to earnings ratio just because they have a long history of being cyclical. So they're kind of priced more like commodity names, for example, even though they've grown in a very larger market cap. The hyperscalers are generally growing without free cash flow for the first time in a very long time. I mean, for the longest time, like throughout the 2010s or the 2020s, these mega cap. Tech companies had really high ROI growth as they had network effects. They, you know, they had searched. They had kind of lock in, you know, like Microsoft lock in environments, just really kind of like low friction growth. And so they didn't have to do a lot of CapEx, at least relative to their size. I mean, by by sheer numbers, they did a lot of CapEx, but as percentage of the revenue, it was pretty much in check. And so they could plow their cash into share buyback, some of them into dividends and just having a fortress balance sheet. But now they're in more of this hardware era. And AI. Has less switching costs, you know, than the network effects or, you know, social media networks or search or or operating systems. They're a lot more competitive. And so they're plowing their money into into CapEx. And so they're betting that they won't have to repeat this too frequently. It kind of comes down to the debate of how long do some of these investments have, how long should the depreciation cycle of them be before they have to replenish their semiconductors and things like that? And that's why, for example, when you look at their earnings expectations, it's still good for their free cash flow. It's still going to be good. And so it's not going to be good. It's going to be bad. It's not going to be bad. Right. Right. Right. you know, you have this kind of flywheel to the upside, but then it can get exhausted over a period of time when VC investors, you know, go back for another round in some of these companies or these companies try to go public. And they start to, you know, if some of the numbers start to stagnate from these open way models, investors can say, maybe I shouldn't be paying this multiple of sales, or maybe I should ask more about, you know, what year do you expect you might possibly start to break even on this? Which again, I mean, VC companies do run unprofitably usually, but, you know, they still want to say, okay, what is the path here? You know, what does this look like eventually? And so I think that's kind of the biggest risk is when does that exhaustion cycle kick in? I'm curious, I wouldn't invest, for example, in the frontier labs themselves. I think that there's very low switching costs. You know, there's one that's kind of ahead for a period of time and everybody switches to using that. And then the other one kind of, you know, locks in and kind of catches up and surpasses it and people switch right back. It's not like an operating system. It's not like a social network. People will change tools. One of them's giving them more bang for the buck. Which that's a really hard investing environment, especially when you have companies priced at, you know, over a trillion market cap or so in that competitive environment. The hyperscalers, I think, are still a question mark at the moment. The chip stocks, it's consensus, but I don't, I don't, I'm not sure that that trade's over yet just because they are the genuine bottlenecks. Generally hard to build a new foundry property. There is really strong, there are, you know, a lot of good traits there. And so that, in my opinion, most becomes an issue of how much you pay for the risk. If you think the cycle is another three years and ends up being, one year, you could get in trouble. If it ends up being five years, you could, you know, you could get wildly rewarded. So I think when those consolidate for periods of time, they're still interesting, but a lot of the other parts of the market are, are risk. And of course, if there's other parts of them, you know, if eventually the VC funding dries up, if eventually the profitability of this whole thing's challenged, it can eventually hit the demand side of the chip stocks. I just think they, I think that still has probably time to hit them would be my base case. Yeah. So sort of like juggling tails here, right? I mean, on one side, like you're right, there's still an upside. There's still an upside here because, you know, AI is, I think we all agree AI is going to be a potential game. It's not a potential, it's going to be a game changing technology. So you've got that dangling out there, even for the VC firms, you're right there. The reason why they're absorbing losses is because they see massive returns on the upside. And then the downside is, I think you just hit the nail on the head. We've all used AI. We know that it's not quite ready for prime time just yet. It may be in a couple of years, but it's not there. And so does that friction potentially drag on growth and then lead to the VC stocks first, maybe getting hit into the frontier model? Yeah. I think that's a good question. I think it's a good question. Maybe some of them start to struggle and does that, does that erode sentiment in the hyperscalers? And since the hyperscalers are front and center and everybody's face on social media and every other form of media, does that potentially, I think the, I think a lot of people have gotten themselves resigned to the fact that this looks a lot like the dot-com era, but does that necessarily mean that the rest of the stock market has the same, the same potential vulnerability? So let's, let's think about this a little bit from the perspective. Okay. VC, the frontier models get into a little bit of trouble. Maybe the semiconductors, they, you know, they start to show some weakness, the hyperscalers. Okay. Maybe not everybody's going to win there. Some of the cashflow numbers don't make sense. The debt cycle maybe shifts a little bit more unfavorably. Does that lead necessarily to something like, you know, a full-blown correction or even a full-blown kind of dot-com crisis or dot-com bubble 2.0 or dot-com bust 2.0? Is there, is there really that kind of thing? What is the kind of risk from what is really a concentrated sector? My expectation would be less of a total drawdown risk than the dot-com bubble. I mean, you know, with equities, anything's possible. I mean, they go up, they go down. My base case wouldn't be, you know, 2000 or 2008 type of, of massive equity drawdown. I view a bigger risk of more of a stagnation where you have somewhat of a more moderate correction and then something like sideways chop as fundamentals catch up. You know, one of the kind of instructive things might be from the dot-com bubble. So, you know, we, we think of the crazy tech stocks, but then there are even other stocks like Coca-Cola or Walmart that back in the late nineties, they, at their peaks, that both of them were trading at something like 50 times earnings, right? And they were, they were both of these kind of blue chip, non-tech growth stocks. They were doing well fundamentally, but investors were paying 50 times earnings. And then what happened after the dot-com bubble is not that Coca-Cola and Walmart went on to crash, but instead they, they basically churned sideways for depending on specific name, like a decade or more as basically earnings had to double just to bring the existing price down to say 25 times multiple, which was somewhat more appropriate. And it won't be a Walmart at some point, I think got only done like 15 times earnings. So you had some, you had something like an earnings triple before you basically paid for your, your prior 50 times earnings multiple, even without the stock going down per se. And so I think that, I mean, there's certainly a risk of that type of price action in some of these names. Of course, individual names can, can, you know, crash pretty hard. And then the question is, what does the index do? In some of my portfolios, I do use the equal weight version of the S&P just because it does diffuse that risk a little bit more. I mean, there's still plenty of kind of reasonable quality companies trading at 12, 15, 20, 25 earnings, depending on how, you know, how premium they are, what their balance sheet looks like and things like that. There still are basically reasonable price parts of the market. You know, generally speaking, when, when you have major corrections, they go down in sympathy with it. You know, you have broad-based selling, you have algorithmic selling, you have just overall kind of capital flows coming out, but mostly the dot-com bubble, you'd have kind of the non-excessive sectors get hit less. And so it depends on how, how kind of priced they are. And I think one of the, I think, you know, unlike, so in the 2000s and the early 2020s, when you, when there was the rise of these mega cap tech companies, they were the primary beneficiaries of kind of the whole mobile internet wave. Like I said before, a lot of that was high ROI network effect growth. So a lot of the market cap consolidated into them. I think kind of the, the good side of, of, of how this resolves is I think actually a lot of the value of AI is going to eventually end up in the, in the end users, you know, right now, like I mentioned before, that most AI services are being underpriced basically due to that VC subsidy. So companies that are on the forefront of making use of it are basically getting more AI than they're paying for, for the most part. So they can benefit from that if they're, if they're rationing it well. And then even when this ends, I mean, they're, they're companies who their, their end product is still very much in demand in a post AI world, you know, it's a physical product. It's, you know, it's something that's kind of AI resistant while their backend could still get costs, streamlined opportunities from AI. And so, you know, that's, I think one of the parts of the market that can do pretty well is that even if the AI companies eventually suffer or at least certain parts of it, some of the end use companies still might just benefit from what is basically a technology deflationary, you know, trend and benefit. There, there are some kind of early studies that show that the companies that adopt AI ironically tend to have faster headcount growth than companies that, that are slower to adopt it probably because they're kind of taking market share. They're able to be a little bit more competitive if they're on top of these things, if they're, if they're using the macroeconomic benefit, the story here, I mean, yeah, set aside the dystopian nonsense about how, you know, AI is going to eliminate jobs. I mean, if AI works as it's designed and it's probably going to over time, it makes people in companies, makes workers and businesses more productive. And in a competitive environment, if you're more productive than your competitor, you can offer better services at lower prices. You would think that over time, that would be, as you said, headcount positive. So contrary to the horror stories of dystopian futures, actually, I love that you brought that up. Cause I think it brings in a, you know, sort of a real world elite, you know, early stage example of how this can go positively rather than focusing on so much of the big time negatives. Yeah. I think a lot of the negative assumptions come from assuming it's kind of a zero sum game, whereas, whereas tech shifts, I mean, obviously there are disruptions. Anything that moves quickly causes disruption. There's winners and losers, but the pie expands, you know? So yes, the losers, we all focus on the losers and we learn. Lament the jobs that disappear, but the pie expands, everything gets better and bigger. Yeah. And I think, I mean, one of the earliest examples is just basically when, when humans harnessed hydrocarbons and made the tractor, you know, before then, like over half of people worked in farming, it took, you know, half the population to feed the whole population. And, you know, with, you know, with, with a tractor and other kind of automated tools, you basically 10X or more the productivity of each farmer. So it takes, you know, 2% of the population to feed everyone. The other 98% of people can work in non-agricultural fields. They can make new medicines and new engineering products and be influenced on social media, whatever the, whatever the case they're doing, they get anything other than farming. And then of course, yeah, because there's high value to that. Yeah. And so, you know, media, we call it, but anyway, then, you know, with obviously the rise of automation, you know, kind of the, you know, the whole IT wave when, when you could replace factory workers with mostly robots and then a few factory workers to oversee and fix the robots when they run into issues, you basically extend the productivity of each, you know, worker that's, that's, that works in that field that again, freed up people to do other types of work. And I think that this is kind of like that for certain, especially certain types of white collar work. They're just very kind of intensive desk type work. In many cases, you can extend the reach of each person doing that. I mean, an accountant using AI can do more accounting work than an accountant that's not using those types of tools. For example, an editor, you know, you can get all the proofreading out of the way with, with AI kind of like super spell check. And then you can, the parts that benefit from human judgment can come in. And you can, you know, you can do more books or more articles per unit of time by getting some of the busy work out of the way, you know, to, to steel man, the concern of the bears on that sense, I think that they would say that there might be some point in the future where technology is so good that there's a certain, there's a, there's a bigger share of the population that can't contribute in any economically meaningful way compared to a machine. So instead of just moving around what people do. So instead of just, you know, getting people off the farms and into the factories or out of the factories and into the service sector, that, that at some point is the combination of either automated tools or robots that say some percent of the population that, you know, whatever the percentage is now that's effectively unemployable would be a larger gap. That, I think, is a genuine longer-term, you know, social-political concern to be aware of. I generally think that that point is further out, and it's unclear what that number would look like, you know, when we run into certain ceilings. There's also the fact that technology is often viewed as kind of linear and smooth, when really it's stepwise. An example I like to use is, like, human effort at flight. For thousands of years, we got nowhere. Then, you know, with, like, you know, gases, like, you know, with, like, balloons, we got a little bit of flight, but still really poor. And then when you put together, like, basically oil and aluminum, which were fairly recent in human history, you know, you go from Wright Brothers to Man on the Moon and Human Lifetime. But then we kind of hit, like, a stall. Like, we kind of hit, you know, like, a lot of the low-hanging fruit was picked. And then you actually don't get a lot of rapid improvement anymore in most types of commercial aviation. You know, even. Even more advanced aviation, you know, a lot of the improvements in flight, for example, have been in the electronics of airplanes rather than the physics of how to fly. And so I think. It's sort of like better flight rather than necessarily more types of flight. Yeah, incrementally safer flight. Yeah. Ironically, it's like we don't have the Concorde anymore. You know, it's like we're trying to reinvent the faster-than-sound commercial flight that we once briefly had, in a sense. So in some ways, we hit hard ceilings. Otherwise, other areas, we just got incrementally safer. Ironically, people would say less complex. We were more comfortable in flying than we were maybe decades ago. But the point is, we kind of just. We put a couple pieces together we were missing. We had a rapid, like, exponential gain in that area. And then we hit a pretty hard ceiling of what is just possible until we have some other breakthrough, maybe. And I think AI can run into that, where you put the pieces together, we hit certain critical mass thresholds. And then it's like a handful of years of just absolute takeoff and disruption and new ways of doing things. But then eventually, we hit kind of a. Either a. Or a hard or a soft ceiling, where those tools are out there now, and they stop kind of rapidly getting better, compared to the early phase of going, you know, to use the term zero to one. From October 9th through 12th, I'm bringing together a group of roughly 40 serious investors and financial professionals, along with some special guests and friends like Hugh Hendry and Mike Green, George Gammon, Brent Johnson, and a couple of other ones, where we're going to spend four days asking the questions that truly matter. What happens next? Where are the biggest risks being mispriced? Where are the opportunities? What should change our minds? And how should we think about positioning around it? This is not a conference built around speeches. It's a small room built around discussion, some disagreement, and actionable advice. So if you manage some meaningful capital or you're seriously interested in all of these questions and finding answers to them in a very small, intimate setting, apply below. Isn't that kind of what happened with the dot-coms, too? You mentioned that earlier. It was a time difference, right? The dot-coms. The dot-coms was right on. Well, mostly right. Mostly right on the nose. I mean, they described the new economy future that we actually live in, but it took a couple, you know, 15 years or so to get there. And a lot of it was it hit that sort of technological ceiling or functional ceiling, right? It was, in many ways, especially the e-commerce, e-commerce needed something like the iPad or the iPhone, really the iPhone, which came along, that unlocked e-commerce. So is maybe potentially something there for the AI that, you know, there's some kind of technology or, you know, evolution or innovation. That's waiting down the future that really unlocks the secret of AI because it kind of plateaus out. But then thinking that, you know, taking that a step further into the investment theme, wouldn't that necessarily then present, again, timing difficulties and timing challenges? And wouldn't it be funny if there was a possibility where, you know, you have all these AI stocks that are zooming way ahead. And as you described of, say, Coca-Cola and, you know, Walmart, rather than having them crash, they kind of plateau for a while and just kind of hang out and do nothing while they wait for, you know, the adoption cycle to. Overcome its short-run technological limitations. We really don't get much of a downside from AI at all. It's sort of, you know, as you mentioned, this maybe the more typical model is the fundamentals underneath the AI, the AI build-out start to become more and more realistic. And then you have a very different future where we're into, you know, we're past the adoption cycle. We're actually talking more about macroeconomics of AI than we are necessarily investing of AI. That's really how I view it. I think that a lot of low-hanging fruit's already been picked. I mean, when you go from kind of the semiconductor industry as a whole. Being worth under $3 trillion to, you know, approaching $20 trillion, you know, like another multiple of that type. Obviously, it doesn't just, you don't just grow out of the sky. You hit a certain percentage of like global GDP or global assets and you just, you know, you can only grow so far so fast. So you start kind of hitting into that wall. And then it just has to show more results. I mean, right now, I feel like at most macro charts, if someone said, when did AI take off? You wouldn't be able to, like the dates are removed. You wouldn't be able to point and say, this is where it happened. You know, it's not really showing up in the data. I've seen, you know, the analytics. I forget, Bob Elliott has pointed that out multiple times. He's kind of like, he'll show a chart and be like, where's the AI books? And, you know, there's mixed results to the extent that it's showing up in business ROI. Like I mentioned the study before that showed that earlier adopters tend to take market share from slower adopters. That's one pretty extensive study. But other studies are showing, you know, when they kind of poll companies and say, you know, have you seen positive ROI from your AI? It's not, are you using AI, but are you seeing positive ROI? You tend to get more mixed results. So far, it's been obviously easier to implement on the individual level because people can use the tools and the process that benefit them. Whereas trying to roll out a system that, you know, all employees at a company are going to use. Is that, it's just like an experimental phase where nobody's really sure how to use it yet, right? There's no, you know, manual that you can follow and say, okay, this is how we adopt AI. There's no procedures that companies follow. Is it really just the unproductivity of the experimental phase, right? And you almost have to be unproductive when you're just kind of throwing everything against the wall. Yeah. And I think that's it. The irony of it is people are still doing their jobs while they have the second job of learning AI before it actually makes their real job. It's kind of in the way it's productive, right? Because they're learning something that just won't pay off until the future. So that actually is productive. So yeah, in that gap, it seems unproductive because they haven't yet saved time with it, but they have this extra burden. And, you know, there, I mean, there are, you know, there's ironically, there are consulting companies that are at risk of being disrupted by AI. But in the meantime, are trying to pivot toward helping other companies implement AI. So they're trying to solve that problem. Every company having to figure it out on their own to say, hey, you know, we, we have AI experts and, you know, we've helped these 10 businesses and we can help you. You don't have to invent it from scratch. So there's services like that, you know, at the, I'm a partner at Ego Death Capital. So we do venture type work. And one thing we do is we get our, our portfolio founders of companies together and we have them talk to each other and say, okay, what are you finding success in with your AI implementation, your company? What frictions are you running into? And another person will say, well, okay, here's how we solve those frictions. But then they learn something from the other founder and you, you know, you get networks of, of information sharing as we kind of work through what is a pretty disruptive period. And other than that, I think it's just, it's, it's trying to invest where the low hanging fruit is. I mean, one of the ways I've expressed the view that the end user might benefit here is, you know, we started a private equity company where we, you know, we're looking to buy kind of low multiple real world private businesses. But then be able to bring in AI talent to figure out, okay, how can we bring this company from a, say a low adopter to an early adopter and be on the right side of that curve that goes out and takes market share from, from others. So I think that there are opportunities out there, but a lot of it just comes down to basically sharing information that companies encounter, at least in ways that are not harmful for their own types of businesses. Okay. Let's switch gears here. Cause you mentioned something earlier that I definitely want to talk about, and that is the energy shock. So set aside AI technology, all that stuff for, for a moment. Here, let's talk pure economics and it looks like the energy shock isn't going to go away anytime soon. At least that's my, my thoughts. I'd love to get your thoughts on this as well. So you got energy prices, really, you know, you look at crack spreads, diesel is going to be an issue, gasoline prices. We got food. That's potentially a problem moving down the road, potentially shortages. Where do you see the energy shock playing out? Maybe first for the stock or, you know, either way you want to take it for the stock market. If you want to talk about macro economy and then the effect on the stock markets, because I think the energy shock is going to be here for quite some time. Yeah, you mentioned the guy, I think the key issues, which are the crack spreads and diesel really, you know, early on in this crisis, people were worried about, you know, the, the mythical $2 barrel of oil, right? So what if oil goes 200 and, you know, fortunately that hasn't happened yet. I mean, we're pretty far into this issue and that, that hasn't happened. We haven't, you know, we haven't even gotten like the, the 150 level or anything close. But because of the really high crack spreads, you know, they're, you know, gasoline and especially diesel are being priced kind of as though oil is a lot higher than it currently is. Because I, you know, right now what's proving to be the bottleneck is the refining capacity, specifically the combination of refining capacity, some of it's been outright damage, both in the Middle East and in, in Russia, but then also even ones that are not damaged, some of that can't get through the strait, right? Just like the oil itself can't get through the strait, some of the refined products can't get through the strait. So both from damage and from physical bottlenecks, the refining capacity right now is the issue. There doesn't seem to be a relief anywhere in sight over the, over a long enough time. Time frame, obviously more refiners can be built, pipelines around bottlenecks can be built at great time and cost to do so in many cases. You can shift from seaborne trade to rail and other, other ways of doing things that generally a higher cost and more frictions and inefficiencies. So that's, that's how they take the edge off over time. You know, the world's a dynamic system, so it adapts to major bottlenecks, but those are frictions. So where this ends up showing up is obviously diesel used for everything. It's used for transporting everything. So then you end up with higher average inflation than you'd otherwise have because you just have this inbuilt friction that this, you know, that things that otherwise be benefiting from technological deflation, uh, you know kind of going down from maybe demographics and other issues you have all those things but then you have an actual you know kind of energy bottleneck and refining bottlenecks you have just higher diesel prices and then companies their margins squeeze so they have to incrementally raise prices on the consumers for things that have nothing to do with energy you know a bag of chips for example just because getting that bag of chips to to where the consumer picks it up has a cost and then partially what it contributes to here is the the k-shaped economy or the two-speed economy different names for it which is especially in the u.s right now if you map out where the deficits are going you know fiscal deficits they're going toward the entitlement programs so generally the older demographic that's wealthier they're going toward um you know the medical industry they're going to the defense industry which means these employees are getting paychecks and their and their contractors are getting paychecks and they're going out and spending into the economy it's going into interest expense which is at least some pockets that are spendable so they go out and I mean someone with their money market fund is earning more than it would be in a Zerp environment which is it's spendable money and so that money is kind of pouring out into the economy on the other hand if someone is on the lower end of the income spectrum if they're looking to buy a home for the first time rather than already having a home with a 30-year you know mortgage locked in they're facing the combination of still high home prices with high mortgage rates uh so it's increasing out of reach they're the ones that get more squeezed by you know the chips going up in price because the diesel prices at the store or you know high beef prices to use a more nutritious example but you know just basically across the board kind of prices are squeezing them uh so both just filling their own car up but but then just more broadly the price of everything and so that that's where you get this kind of K-shaped economy which I I think unfortunately is probably going to persist for a long period of time I think the deficits are going to continue roughly going where they're going I think that obviously you know what happens with the Strait of Hormuz is anyone's guess months you know out from now but I think for the most part the K-shaped economy is set to continue and we circle that back to investing it's basically that you want companies that are on the right side of either fiscal deficit spending one way or another you know it sometimes it's going directly to those companies sometimes it's going to consumers who buy those types of things you know for example one of the reasons I've been at least for a while so bullish on travel is because on average older wealthier Americans are receiving a pretty significant part of the deficit they're the ones with assets they're the ones with passive income they're the ones that have the time and and money to travel so they're traveling you know whereas uh you know stocks that are catering to the middle end of the kind of income spectrum are the ones obviously in general facing headwinds so I think the case you're kind of saying you got to follow the money right if we're talking about you know uh this K-shaped economy in macroeconomic terms so there's positive flows and negative flows like you know we tend to think of the economy as sort of like a big average where everybody kind of experiences the average but in the you know I think it was Chris Martinson that was in Arizona a couple weeks ago he called it the I-shaped economy which may be a better letter to use because people who are up here in the top part of the eye are experiencing a very different life than people down here at the bottom part of the eye and so what you're saying is when you're thinking about investing in in portfolio construction follow the money there's money up here and there's not a lot of money down here so you probably want to be up here and less exposed down here right yeah I think that's exactly it and with the caveat that valuations matter so you want to you want to follow the money you just want to be careful about not overpaying for the areas that are consensus or where monies are going I mean there's a you know something can be doing well but still be a bad investment if it's priced at 50 times earnings when it maybe should be priced at 25 times earnings but yeah basically I think that that's the main thing to be aware of is to buy things where the money's going with a mind toward you know bubble valuations when they when they pop up and try to avoid the most excessive areas so is there a potential risk there yes this is the thing that concerns me the most with an I shaped economy K shaped economy two speed economy put whatever label you want to put on it maybe that's not necessarily a threat to the stock market the macroeconomic climate because it has enough positive attributes and positive monetary flows and redistribution where it kind of keeps everything afloat but are you concerned that maybe the consequences are beyond the marketplace in the economy itself first of all because you know combine that with AI as you said before there's potentially a pool of labor that is possible that might be get bigger over time we already know how hard it is for people in the bottom part of the economy to get a job primarily younger people to begin with who have you don't have the ability to start their career therefore they're not investing in their own uh their own capabilities they can't buy a house which means they're not building wealth that way they don't get the 401k are you concerned about the social and the political impacts of the K-shaped economy just beyond investing where potentially we go into some pretty darker pretty dark areas I am I've written about this a handful of times which is and often I speak of it more in the deficit in the sense that because that's a fueling factor for the K-shaped economy which is people people don't get there right they they think you know that well there's a lot of a lot of misconception about the deficit but the deficit the government spending is making things worse not actually making things better yeah I mean obviously it depends on the country in question where it goes but yeah in a general sense at least in the especially in the current U.S environment I would say the deficit is you know if you were talking about kind of maybe post World War II spending that'd be a different environment than today's spending but basically the today's spending where it is for the most part I would say it's fueling the K-shape and the the challenge here is when people say well when will the deficit or debt matter as though it was like one mythical moment where the U.S misses a bond auction or something like that is that that's not it's more like that slow bleed of basically unrest populism and everybody kind of feeling that something's wrong and then not really knowing what the issue is and then depending on where they fall in the political spectrum they point at different things and you know after the global financial crisis you got the rise of both Occupy Wall Street on the left and Tea Party on the right that uh you know changed over time on the right you got more the MAGA side of things on the left you get you have more I mean like the now we have Mamdani in New York for example uh other things like that and I do think that you get the kind of a rise of in some cases more collectivist type of of ways of doing things whether it's socialism communism whether it's uh certain types of fascist type of kind of tendencies that rise uh and I think that's kind of the one of the major risks is that when people perceive that the pie is growing there's a little bit more of a tendency to be harmonious when they feel the pie is not growing um that's when there's more more issues and eventually it can threaten rule of law it can threaten you know the economy itself they can it can threaten the attractiveness of capital assets uh in countries where the rule of laws you know not that's weaker than it was you know 10 20 30 years ago you know it's going to be 10 20 30 years ago and so I think that is a longer term danger to monitor and then obviously anyone who's holding assets has to be worried about risks of obviously on the extreme end you have something like asset confiscation on the other hand you have kind of a you know kind of targeted types of wealth taxes that you have to kind of move around and and you have to you have to pay attention maybe jurisdiction more than you did 20 years ago and and so it becomes investing and kind of protecting wealth becomes bigger than just you know blank sheet of paper but it's also you know what kind of safeguards do you have where are you deciding to live where you're deciding to uh you know have assets uh you know domiciled and things like that it's an extreme thing but it's imminent right I mean it's happening places like California it's only going to continue if it passes in California you're going to see it spread to other places around the world or other places around the country not just you know California but that's I think that's exactly you know the when the pie's not growing the easiest thing for a politician to do is say those guys that you don't like over there they're the reason for it and so it's very easy for everybody to become polarized because simply the pie is not growing we all want answers to it so then the question becomes what the hell do we do how do we get out of this mess so that we can move into a situation where the pie is growing now my own view is I think you know these are longer term Cycles when we go through these periods in history kind of have to wait them out but uh do you see any way for us to at least solve the macroeconomic problem macroeconomic part of it so that we can start growing wouldn't it be funny if A.I. is the natural answer here A.I. kickstarts the economy and suddenly solves the k-shape and that would be the ultimate Irony yeah it would I mean I think I'm with you that that there's a time-based component here that that there's very few ways to accelerate it on average that the most likely scenario is it just it takes time to work through this I mean it takes time to work through a demographic shift it takes time to work through kind of a debt cycle people have to often try a lot of wrong answers before they find the right answer uh and so you know I I can give you know kind of list of policy ideas but I just know ahead of time that they're just not going to be done they're not going to be the chance to implement them all correctly enough and getting enough political consensus to do that is extremely low which is why I say nothing stops his train in terms of the fiscal deficits you know it's like uh don't fight kind of momentum and for A.I. I think that I mean the the the kicker there is that on an individual level I think A.I. can be a savior in the sense that I mean it makes it so it's never really been easier to start a business for example you have you know the the cost of doing so at least for maintenance entries is lower than it than it has been I mean you can do you can there are ways to to you know get services and stuff like that at lower costs than there were 5 10 20 years ago because A.I. can really extend the reach of one person or a small team why I can be a small team right it's not just exactly you know as a business owner you've got an entire you know suite of A.I. bots at your fingertips exactly that's yeah that's what I mean is that you all these tools extend what what each kind of living breathing person can do because you have all these components and and ways of organizing things and doing things and so it becomes not just you know who has the assets and connections to build a startup business but also just who who has acquired the know-how and the ability to use these tools efficiently versus who is either technically unable to use them properly or culturally resisting using them because they believe they're bad for one or more reasons, environmental or whatever, whatever kind of might be causing that. And then you get a divide in terms of kind of early AI users versus slow, like later stage AI users more so than just other things. So I do think that at least on the individual level, AI can be a powerful tool. And, you know, in general, anything that's good for productivity, while obviously not uniform because they're winners and losers like we talked about, but in general, anything that kind of adds net productivity to society, for the most part, should benefit society. Anything that reduces productivity, like wars or bottlenecks or destruction of existing facilities, that will detract from, you know, societal benefit. And so that's kind of the challenge is that we have this new productivity. And. We don't yet know quite how big it is. Obviously, you know, the bulls will say it's huge. Bears will say it's all an illusion. Most, most angels are being somewhere in the middle that, you know, I'm quite bullish on it, but it's not magic. But either way, there's some unlock here. The question is how unevenly will it be distributed in terms of, you know, who it helps and hurts five, 10 years from now and what impact will it have on the economy. But I think that we have ways of looking at this. We can look at, you know, what did manufacturing of automation and manufacturing facilities. Do for the economy? What did it do for workers? What did it do for this? You know, we, we saw what globalization did, obviously both pros and cons. We saw what, you know, bringing hydrocarbons to agriculture did. You know, we have kind of historical analogs and none of them are perfect, but we do have analogs for what happens when you have a technology unlock that is not evenly distributed in terms of, of users or where it happens or who it affects. But I think we're in another era like that. I think, you know, I'm more positive than maybe most people are. I mean, not, not, you know. I'm more hyper positive, not, you know, singularity type of Elon Musk type of a talk here, but I think that solves a lot of the issues, you know, you have so much, so much economic power and economic activity is concentrated in the top. That's where a lot of the stagnation is coming from, you know, economic growth, historically speaking is small businesses have become medium sized businesses have become large businesses and we just don't have the type of formation. I think you just, I think you nailed it, Lynn, that when you said that AI unlocks the ability for people to start businesses and the real disruption is there the ability to, to. Introduce some badly needed competition into a lot of areas we wouldn't even imagine just yet. If people can imagine it, create a business, a small business that challenges the existing orthodoxy, suddenly you get a whole lot of economic potential. You pile on productivity. You can see a wave of prosperity in the future where not only are the benefits at least somewhat shared, maybe we go to a four day week work week, a three day work week. We've got lots of business. There is definitely a positive way forward here, but I do want to ask you, we can continue to talk about AI. And, you know, long-term macroeconomic trends, but I do want to ask you before we go here, your thoughts on Bitcoin, are we seeing another kind of head fake in Bitcoin? Is there another leg lower there? Because I would kind of hope that there is a leg lower. I really want to buy Bitcoin around 20,000 per coin, but what do you see as far as Bitcoin? Has it, has it been, has it endured enough of a winter that, uh, consolidation we're getting more signs of buyers entering the marketplace? What's going on there? Yeah, good question. So my, my guess, and I don't know is my guess is that the bottom's in the way that I've been phrasing it before this review. So my guess is that the bottom's in the way that I've been phrasing it before this review. Is that I was hesitant to try to, I don't find a lot of value trying to call it a precise bottom. It's more like trying to figure out, are you in a bottoming range or the opposite? And so for example, when it was in the lower sixties for a while, after it kind of hit that capitulation back in February. My base case was the bottom is kind of roughly in, we ended up getting slight validation. We, you know, we went down to kind of the 58K level briefly, but not way lower. And so my view was, look, okay, we got a slightly lower low. I still think roughly speaking, we're in kind of a bottoming range. I would be the kind of level that I would find truly surprising would be if we do break kind of below the 50K level on a sustained basis. I think kind of the fifties and lower sixties are, there's a lot of support there in terms of, we look at on-chain indicators. We basically, we have somewhat of a difference. If it's that indicators for, for Bitcoin, then just stock, for example, we have all this, all the normal charts that people look at, but then we have on-chain data and you can see things like, you know, at what price levels that a ton of coins change hands. Not just on exchanges, but literally just physically, you know, go from address to address. And there's a lot of support in that kind of the fifties and the low sixties. I think that the micro strategy issue has been taken off the table for a period of time. There's a period there where they had say six months of dollar reserves and, and, you know, otherwise. Uh, you might be started selling a lot of Bitcoin to fund their liabilities. Now they've kind of front loaded that. So they already kind of diluted, they already sold some coins and now they have, you know, two and a half year plus dollar reserve to cover all of their, you know, preferred dividends, you know, for two and a half years, even if they never sell another coin. I think a lot of that kind of overhang has been at least, you know, for, for, you know, this, this calendar year, next calendar year kind of taken off the table, uh, as kind of for sellers. And so I think actually the Bitcoin place is in a pretty. Decent, um, trajectory here. I'm not one of those people that thinks, you know, two months from now, we're at all time highs, you know, it's kind of the, the permables, uh, I think it could take time. I think we could, you know, we could go back down to the sixties and chop for, for a period of time. But in general, I do think that the, the sixties and seventies are an accumulation zone that if someone is bullish on the asset, that looking back two, three years from now, this is probably a good entry point, but you know, it's, you know, I, I think that it's, I think it's a more mature asset. Now it's more liquid asset. Now, you know, I think this draws. Drawdown was smaller than prior cycle drawdowns, but that was after the fact that the, that the bull market was smaller than, than prior bull markets. And I think that's probably the trend to, to expect now that, you know, we have ETFs in the market, we have treasury companies in the market, uh, it's, it's in general, it's a larger, more liquid market. And so I, I, my current view is I'm, I'm kind of structurally bearish on a lot, several parts of the digital asset space. I think a lot of that ran its course. It was kind of a zero rate phenomenon. Uh, but I do think that Bitcoin, and I do think that stable coins. Still have a long runway of growth ahead. It was obviously Bitcoin being the more investable, volatile part of that and stable coins being, you know, there, there's some ways to invest, but for the most part, that's more of a macro story. I think, whereas Bitcoin is more of an investor story. So if Bitcoin is a more mature market, maybe it doesn't have as much beta. And therefore that actually would help out a lot because beta is one of the biggest drawdowns to it or biggest drawbacks to it. So wouldn't that be funny too? Well, Lynn, I really appreciate your time, uh, taking time, talked about, you know, so much here with the stock market AI. We, we kind of hit a lot of topics. Uh, really appreciate everything that you, all the insights that you shared. I was going to say, you know, in this part of the interview, I'll say, you know, we're Lynn, where can everybody find you? But if you don't know where to find Lynn Alden, I can't help you. Uh, it's very easy to find just Google Lynn Alden. You'll find her a tremendous amount of insight and research. Uh, so again, thank you for your time and stopping by for here at your Urodal University. I appreciate that. Thank you for having me on. Take care, Lynn. One thing I really care about with Urodal University live is not the speakers. I mean, we liked the speakers, but what we really care about is the people. The people who are in that room and especially the people who are sitting next to you as much as who might be speaking at any given time, there are only going to be 40 people there, and I want them to be people who are managing real capital, running real businesses, making real investment decisions, and who actually have something to contribute to the conversation because over four days, a lot of the value isn't going to come from me standing up and talking and doing PowerPoint presentations. It's going to come over intimate dinners in the small groups, in the questions that somebody asked. It's going to come over a podcast that you hadn't thought of, or meeting somebody who looks at the same problem completely differently than you do, and might actually come to similar conclusions. That's why we're not just putting out a checkout page. We're talking to everyone before they come in. I want to build a room where you can sit down next to anyone who's there and know that you're going to have a conversation that's worth having. If that sounds like the kind of room you want to be a part of, apply below.