Transcription
Bankless Nation, a relevant topic for crypto investors at the moment. I think actually the most relevant topic, the most important question for us right now. How long will this AI boom continue? Are we in an AI bubble? What's going to be the outcome for our crypto assets? I have Michael Nato from the TDR podcast and uh the TDR research on the episode today and we're going to discuss this. Mike, how you doing?
>> I'm doing great, Ryan. How are you?
>> I'm doing great, man. Hey, uh, this episode really came from a discussion that we were having after we were done recording the TDR podcast last week, and you showed up this slide, which was Bitcoin versus NASDAQ, the correlation by year. You said that crypto has never been more correlated to the NASDAQ uh, than it is right now in 2026. And we see right now crypto prices were kind of being pulled upwards it seems by incredibly strong tradey market in particular tech stocks have been booming. So is it like up 25% the QQQ >> since um the was it March or April lows?
>> Yep. Yeah. It was like March 30 lows or so. Yep. I mean, so all of this led me to believe in our discussion, we were talking about this, um, it just seems like crypto is being pulled up by the stock market, by the AI trade, specifically by the NASDAQ. And so if that's the case, if our future, at least right now in this current regime, is dependent on the AI boom, I think the most relevant question for us is like, is that going to continue? How long will the AI boom last? and you prepared some materials to help answer that question or look at let's say both sides of the equation here. Well, let's start there. I mean, do you think that is the most relevant question for crypto investors right now is kind of where's AI going to go?
>> Yeah, I mean, you know, we we're mostly focused on the crypto markets and the crypto markets have been in we we believe we're in a bare market on the crypto side and really the the error has come out of these these markets. We've seen this rally from Bitcoin since early February, which has corresponded with a a major rally also, you know, in the NASDAQ over this period. There was some uh disruption in the NASDAQ prior to the the big rally we started um in in early April. Um but yeah, I think I think if you're focusing on crypto right now, the there there's sort of like a narrative that's going that we've already bottomed and that we're we're going into the next bull market. And while this is playing out, we have, you know, an extreme sort of situation happening in NASDAQ and kind of the AI sector. And there's a lot of discussion around is this a bubble, right? This is the big the big question right now. And if it is a bubble, what does that mean for for crypto markets? And that's kind of the the question I've been asking and why I'm doing some of this, you know, deeper research on the AI side of the equation right now and just trying to have a view on if that is is actually sort of in the ninth inning of potentially, you know, that this bubble scenario, which nobody knows. It'll be obvious in hindsight, but but nobody can predict this stuff.
>> I guess there's so many, I guess, mixed feelings when people use the word bubble. Some people say we shouldn't use it at all. It's kind of meaningless. What does what what is a bubble actually? Others say, you know, you can use the term bubble, and by the way, bubbles are are good. Uh, somebody by the name of author by the name of Burn Hobart came on the bankless podcast. He has a book called Boom talking about the value of bubbles historically throughout history.
>> Others use the term bubble as almost an insult. Uh, and they sort of have negative connotations when it comes to a bubble. So, it's another way to look at it. Let's maybe be precise on the definition of bubble as we're going to kind of use it in today's episode. So, when you think about a bubble in markets, what does it actually mean to you? What's the more objective uh perspective on on what a bubble actually is?
>> Yeah. And and like you said, this is all, you know, everyone has their own definition and kind of when you're entering or exiting these periods. Um, this is kind of how I think about it. you know, there's typically a breakthrough technology, right? This is kind of through the framework um of Carleta Carlo Perez's book, Technological Revolutions and Financial Capital, which is a fantastic book to read right now, I think, in and how it's relating to what's happening in AI. It's a book that I was very focused on trying to understand how that's actually impacting the crypto markets and the, you know, the crypto bubble as well. Um, but you always have this this introduction of a new technology that really captures people's attention. Um and there's usually broad acceptance, you know, that this thing is real. And we start to see, you know, a narrative start to form around how this is going to impact the future of business, the future of productivity, the future of efficiency, um new new business models, you know, different disruptions to various, you know, sectors of the economy. Um and so this starts to get baked into the sort of um the the psychology of the market, the narratives within the market. Um, and if you start to see some interesting growth behind that narrative, which we are absolutely seeing on on AI, we've seen uh the new models that are coming out. Each one is stronger than the last one, the uh earnings of some of these companies. We've seen anthropic uh reporting just the growth in revenues that they've seen. So now, you know, this sort of narrative that's already gotten kind of baked in um is now being validated by growth and the numbers. So now you have sort of this reflexive movement on top of that. I think we're in that uh phase of this you know right now at at some point typically you you get like the valuation detachment uh and and that's when you know maybe things start to get a little bit more wobbly. We can get into we're going to get into some of uh what's happening with with the data out there. Uh what's interesting right now is there's a a big discussion around um the these growth figures and and and analysts are reporting you know forward forward growth is continuing to tick up for Q1 27% earnings growth which is just an incredible uh incredible number when you factor that into the price of the assets. the price of the assets can be rising very fast, which they are, but if your your earnings growth is rising in line with that, then the the PE ratios aren't blowing out the way, you know, you might expect and and investors can sort of um you know, kind of validate a bull thesis even when, you know, valuations are are really high. So, we're seeing some of that start to play out. Um and this tends to happen with, you know, easy capital, lots of leverage, lots of FOMO. Um, and the the narrative just usually gets stretched too far and we tend to overbuild. This is just something we've saw we've seen this in the crypto markets. You know, a new technology comes out uh it looks like it's going to be a breakthrough technology and then you have all these copycats rush in and they start building. There's tons of capital gets thrown at that sector. You tend to overbuild the capacity. We saw this um in the dot era which which we we're going to get into today. Um and that's the big question. you know, at what point does does sort of this expectation of future growth, at what point does that story start to roll over? Um, and we can kind of get into the data, the narratives, what we're seeing and all of the things and how this looks similar and also different from what we saw back in 1999.
>> Okay. I guess the way you are grounding then this uh this this bubble word is through the lens of Perez's framework um who talked about in particular technology revolutions and how they go from kind of this um eruption phase to a frenzy phase to sort of a a turning point phase a synergy and maturity type phase and you've seen I'm sure and listeners will have seen bankless listeners will have seen the hype cycle It's really the exact same thing that Carlettto um Perez is talking about, right? Where you have kind of this trigger period. You have this inflated expectation horizon and that's the top of the bubble and then you have a deflation troth of disillusionment slow slope of enlightenment plateau of productivity and it kind of goes on and every major technology revolution has this. I mean crypto has had maybe four of these maybe five of these. The internet had this, the radio had this, electricity had this. I think Perez talks about um railroads in particular, automobiles, >> 1800s, automobiles, you know, some industries and have multiple of these kinds of cycles, but it's very clear that we're in one.
>> The problem is you don't know where exactly you are on this slope here.
>> Yeah, exactly. >> Like how close are we? Because for any major technology revolution, I mean, it seems like if you believe Perez's framework, and there's no reason not to. It seems to be almost always the way this plays out, we're going to hit a top at some point. There's going to be a period of time where expectations are just discordant with the reality on the ground and we get way over our skis on this. We just don't know when that's happening, right? And when we're in it versus when we're kind of like traveling up it. Uh because there's no timeline really on uh the axis here. It's like that's the unknown part is how steep is this curve.
>> Yeah. And there's so many factors, you know, that that play into this. What's happening, you know, broadly in the economy? What's happening with liquidity conditions? you know, there's what's happening, you know, on the political side of things and, you know, regulation and and where that's going. So, there's many many factors and I think that's why it's just so hard to predict, you know, how how things are going to going to shake out. And we're not trying to like call the top or anything in this episode. We're really just kind of laying it out to then say, okay, you know, how should we be thinking about this? And we'll we'll get to that at the end. But yeah, I think, you know, I think this is the right framework and we're clearly in, you know, we had the eruption period. I think you could say that that was, you know, chat GPT coming out back in late 2022. There was obviously a lot of work that went into AI before Chat GPT was released, but that was kind of the eruption. And I think, you know, you can make an an argument that, you know, 24, 2025 have been sort of the the frenzy periods and we're it feels to me like we're we're really pushing into like maybe later stages of that frenzy period. Uh right now,
>> later stage frenzy. We're definitely in frenzy. later stage frenzy possible, but who knows how long the the later stage could actually last.
>> You know, Nate Silver has an interesting tech um model for this in his book too. He talks about each um technology having kind of a a different order of magnitude almost like a technical RTOR scale. And sometimes you have like a you know a six that might be a technology like the the mobile phone or something like that. Maybe the internet was like a seven or an eight. Maybe AI is a nine. We don't know. We don't know if it's a six or a seven or an eight or a nine or how world shaking this actually could be. And so we don't know the slope of the line. We don't know how long the frenzy period will actually last. Could be months, could be years. And it all depends on what this technology is actually able to deliver. Let's take a look at some of the data because I'm hearing different investors right now say different things. Um, famously Warren Buffett, he had some clips last week, uh, saying, you know, he's been in the market for 60 years. There's only been five years, at which point he thought the market was cheap enough to buy. Right now, he said it's kind of operating a bit more like a casino. Um, and Berkshire Hathway is stacking cash. Uh, they're they've sold into this market the last few years. They've been net sellers of stocks. Um and then he'll look at probably a metric like this which we have on the screen which is uh the Schiller PE cape uh ratio. Let's talk about some of the data and try to get to a sense of how valued the current equities market actually is. So what does the Schiller index tell us?
>> Yeah, this is the the Schiller Cape ratio. So this is uh giving us like more of a view of the cycllically adjusted you know PE ratio. So, it's taking the average of the last 10 years and it's adjusting that for inflation. So, you know, it's it's trying to strip out like we just had this period, you know, where uh NASDAQ went up 25% or so over like 5 weeks. So, it's trying to average that. It's not it's not giving too much uh weight to like what's happening recently. It's trying to average that out over the last 10 year period. Um and so, you know, right now when you look at that chart, we're at 42 or so. We're very very close to where we peaked back in um 99 which was uh right right over 44. We are well you know north of where we were um back in 1929 and we also you know
>> north means higher right. So 1929 we peaked what this looks at like 33 or
>> 33 or so. Yeah. Yeah.
>> And right now we're 42.
>> We're at 42. So we're well past that. I mean this people were pulling this chart up also back in 21. um where we had a a big rally and we got to about just under 40 back in in 21. Um so we're clearly like just from a very high level like we're clearly at these like very elevator levels just from very high level right.
>> Oh my god. So the only time in history Schiller PE has been higher was in the year 2000 basically the the dot boom and it was only mildly higher at the time 45 or something rather than rather than 42 right now. And remind us what Schiller PE is actually telling us. It's a ratio of price to earnings or it's some sort of index of of price to earnings, inflation adjusted.
>> It's Yeah, it's the PE ratio of the S&P 500 based on, you know, averaging out the last 10 years and adjusting for inflation. So, um,
>> when I look at this, I'm just like, how do you buy how do you buy in this into this market?
>> It's tough. I mean, you know, this is the this is the big question. We've obviously seen a lot of disruption, you know, within the technology sector as AI stocks have outperformed. We've seen SAS stocks, you know, there's bare markets happening at the same time, which is which is sort which is sort of interesting.
>> Um, but from a broad perspective, you know, we're clearly, you know, in sort of what you would what you might categorize as a bubble, you know, territory.
>> It's safe to say that when you look at this, you have to come away with a conclusion, which is stocks aren't cheap right now. Can you say that?
>> I think so. Yes. I think that's correct. Yes. And and that also means that if stocks are not cheap, then your forward returns are not great. You know, if you buy if you buy stocks when the PE is over 20 or so, there's a lot of evidence to suggest that like your 10-year returns aren't going to be that great from those levels.
>> How about uh revenue growth forecast? That's another dimension of this.
>> Yes. So this is I think you know this is an interesting thing to show here because I think the big narrative and I think this is one of the things to really be paying attention to right now are what are the narratives what are the primary narratives from the bull side of the equation and do those line up with what what the data is showing and so I think one of the big narratives out there is that well this is a little bit different today because from from a few perspectives one the companies that are financing this buildout the big hypersale ers. These are extremely profitable companies. They're well capitalized. Uh they were using free cash flows to to to uh to build out the capex up until uh more recently. Now they're doing some debt financing. So I want to understand like is it true that okay yes earnings are are really strong and forward earnings are really strong. This is true and this chart shows that. So even just looking at Q1, this is a blended um growth rate for Q1 because not all companies have you know reported earnings just yet. So it's blending what analysts had expected for Q1 plus actual um actual reporting and we're at 27.7% right now. Uh the big narrative is that this was not happening back in 1999. Uh that is not true. Uh so
>> wait wait wait the big narrative is that in 1999 we had a bunch of fluff
>> uh unprofitable companies pets.com no bit like no business model substance you just had to launch a dot and then you could raise billions of dollars but there was no revenue growth underlying it really or and certainly no earnings growth yeah underlying it. Now this time it's different. There is earnings growth. We're seeing this in in um earnings growth forecasts and the current reporting from from equity companies. So this time is different from that perspective. That's the narrative. That's the narrative. And I think you know it's sort of a lazy because a lot I think people are looking there was a lot of fraud. There were the pets.com and just like these domains that popped up and didn't really have a business model and and got really high valuations. So that is true that that did happen. But what's not true is that uh earnings estimates were ramping up the same way that they are right now. So we were the earnings estimate in Q4 of 1999 was the same as it is today. So there was actual like the companies that were financing this were they weren't the hyperscalers that we have today but it was kind of similar. It was the big telecom companies. It was AT&T and Verizon and they were spending they were the ones spending the money. Those were profitable companies. they were ramping up. Everyone, their earnings were looking fantastic. And so it was a very similar setup where the valuations were were ramping up aggressively, but so were the earnings uh estimates for future forward earnings. So it's it's the same exact thing that we have going on today. Yes, you had all this extra froth in Pets.com, these other things, but the actual companies were strong that were actually financing this and they were reporting really strong earnings at the at the same time. So, this is like, you know, this is a little different from what the the narrative is out there. And you can see, you know, we have some notes just on the side here. So, we're at 27.7% just to give you an idea of how high that is. The 10-year average is about 10.3% in terms of uh earnings uh earnings growth estimates. The 5-year actual is uh 16.4%. So, we've been in a a period here where we're we've been above average and that just keeps ramping up. And, you know, again, same thing happened back in in in 99. We were at the same level of expected earnings growth in Q4 of 99, which was right before the peak. It actually went up a tick higher in Q1 of 2000 up to 32.7%. In Q1 and then when you talk to people that were in the markets at this time, we were, you know, I was uh I was not not an investor and and and not even old enough to be participating in the markets at this time.
>> Yes.
>> Um but a lot of people say like, you know, what broke it? Was there some catalyst? Like how could that how could it just break because earnings were so strong? I you know people people will tell you like it's not a good idea to just wait for these quarterly earnings to come out and then just be complacent because it looks good because there wasn't really much that that broke it at the time. It just kind of started to roll over and then the narrative start to shift. So it was really price that led not fundamentals and I think that's the most important takeaway. This is something we focus on in the crypto markets that price leads fundamentals. Um and we see this same thing also happen with crypto investors where you get into a bull market in crypto onchain activity peak you know ramps up uh the chains start to you can the price to sales ratio of like Salana was coming way down as the valuation was going way up last cycle right so if you start to extrapolate that out you can tell a story about why this valuation makes sense but you're using like the the peak sort of activity on chain to to to extrapolate out. The question I have is like, okay, if if these are real earnings, right? We're not saying they're not real earnings. The question is like, can you can you extrapolate out from there? And we'll get into like where is all this coming? We've got some flowcharts to show kind of where the money is flowing through.
>> I think that's a really subtle point and a really important point as we look at these markets. Um, let's grab some more data though before we come to some conclusions here. So, here's a chart of Ford PE ratios. There's another chart of S&P 500 Ford profit margins. What are these data sets adding to our story?
>> Yeah. So the the forward P ratios uh right now if you look at like the MAG7 it's you know 26.7 or so. If we look at the large large cap S&P 500 we're about 21. So this is not like insane. you know, we've seen higher valuations and the reason is because the E is just going up just as much as the price, right? We the if the earnings keep keep going up and the and the price is going up at the same time, you know, the the ratio is basically going to going to stay flat. So, I see. So this is this is um a breakdown of forward PE ratios again and it's showing there's the these um vertical bands I guess indicating uh down markets bare markets maybe recessions I'm not sure.
>> Yeah. So the yeah the pink ones are uh S&P 500 bare markets and the blue ones are are are corrections. So corrections 10% bare market 20%.
>> All right. Very good. And the breakdown, the reason we have different lines is there are different segments of the S&P 500. So you got MAG 7, you've got large cap, you've got midcap, they actually have S&P 600, some small cap as well. Y
>> and so you see kind of, you know, I guess different uh indicators here. Now on this chart, different than our Schiller PE on this chart, we're actually not seeing all-time highs. I guess I guess for for Mag 7 Mag 7 is doing pretty well, but it was higher in 20 2021.
>> Is that right? Ford P.
>> That's right. That's right. Yes. Because the earnings weren't as strong in 21. That that's the key here is the earnings.
>> I look at this chart and I don't see anything like it doesn't look crazy. I mean the the Schiller PE looks crazy. That looks like you're buying the top if you're buying right now.
>> This doesn't look that bad. And you're saying the reason is because earnings are really keeping up like the earnings are actually >> being shown in the uh the reports and and kind of the the financials right now.
>> Exactly. And so if you're bullish and you're saying this is not a bubble like look at these earnings valuations are not you know we're below we're significantly below where we where we were in 21. You can sort of make the argument that hey look at look at all these earnings like this is not a bubble. this is just like, you know, the market's just really hot and this technology is incredible and all these companies are implementing the technology they're spending. So, you can make the bull the bull argument, I think, based on based on this the question, but going back to what we were just talking about, what is the leading indicator if you're focusing on earnings and you're waiting for it and you're going to you're going to say, "Okay, well, I'm bullish. All the earnings reports are coming out really strong right now and I'm going to just wait until Q2 on that." Like that's the that is the key thing is like are the does is price following fundamentals or are fundamentals following price and that this is the this is really we know in crypto it's price that that is a leading indicator. I think probably in all hype cycles res framework frenzy territory price is going to >> you know lead and then fundamentals are going to follow right that's probably going to be true here I know you've got some slides where we're going to look at the particulars of of how that might work in this market
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>> Let's get to this S&P 500 Ford profit margins. Is this a similar story?
>> Similar story. So, again, this feeds the narrative of the power of AI. You know, it's it's creating efficiencies. It's creating pro productivity. It's driving um these, you know, forward uh margin margins are rising. So, we're at about uh 15.3% right now. That's the highest, you know, we've been since in the history of this chart going back to 2004. Um, again, this was also a true back in 1999 where margins were actually rising as well and we got up to about 12.2%. So, not as high as as as we are today, but it just this charts here just to show that, you know, if if you're making the bull case, this is part of this is part of that margins are improving, earnings are improving.
>> Th this looks like a a bullc case could be like this looks like the AI boom productivity miracle here, right? We increased margins for everybody because AI is automating things away,
>> right? And the the question I have on this piece of it is like we haven't really seen any uh studies or at least I haven't seen any studies on the companies the the S&P 500 companies the large enterprises that are implementing um open AI and they're implementing anthropics enterprise products. They're spending a lot on this right now. We have not seen a study come out to say that, you know, showing that they they know for a fact that the spend that they're putting in there is is equating to two employees, right? That's basically what this has to do if this is going to um be durable long term is all of that spend. Like if you think about a large insurance company or something, travelers insurance is is implementing this internally into their systems right now. Massive company spending a ton of money. Most of that's going to the um companies like Anthropic. Now, what could possibly slow down the spend that they're putting in is like if they start to do study, they start to say, "Well, wait a minute. Is we're spending like crazy and we feel like we're just in this rush to do it because everyone else is doing it. What happens if the studies show that maybe the ROI is not as good as they thought it was going to be or like
>> isn't that getting priced into this? Like, you know, if I'm looking at forward profit margins, isn't that basically showing what you just said that, oh, these companies must be adding AI, incorporating AI, and becoming more productive, becoming more profitable. I mean, if it was costing more than it kind of like brought in, you'd see margin compression, wouldn't you?
>> Yeah, you should. We we Yeah. So, if the margins are increasing, it's a good thing. We just don't know if that's like 100% driven by AI. We don't know exactly what's what's driving that because uh like I said, I haven't I haven't seen the studies. I think we're we're we're kind of in the process where this is starting to be implemented, but I don't know like at what scale it's like really impacting it. It's we know the margin of improvement. We just don't know like it's not clear to me if that's like definitely AI just yet. What else would it be?
>> I don't know. I don't know. uh not hiring. We haven't seen really any hiring over the last year. So, if your revenues are growing and you haven't hired, your margin's going to your margins are going to improve there.
>> Isn't part of the bullish story that they're not hiring because they're able to backfill with AI. I mean, you look at kind of like um some of the layoffs that we've seen even crypto, Coinbase laying off 14% of its uh workforce. Brian Armstrong says, "Hey, we're doing this because of the cycle uh and also and you know um trading volume down, all these things. also because we can, you know, replace some of these jobs with AI effectively. That at least is the narrative.
>> That's the narrative. I I think there's definitely probably some truth to this, but I also think it's a it's kind of a you can you can use AI to, you know, maybe Coinbase was going to have to do layoffs anyways, and then they can say, well, we're restructuring our internal systems around AI and stuff, and we think this is going to be the way to do it. So I think there's probably a combination of productivity and it's an excuse, you know, they can sort of say, hey, we're going into a new world and we're implementing AI. So we'll see. Like to me, I don't know. I don't know. I think we need to we need more time on this to know for sure. But when I think about like what would if you were trying to figure out what would sort of change the narrative, I think it would be something like this where pe people start questioning the spend and whether or not there's real real um ROI on the other side of that. For me, as somebody, you know, running a small business, it's it's definitely making my life more efficient and I can see a path where we can just do more and not have to hire behind.
>> I think that's the same the same for me is I see it in spots sometimes, but I don't always see it. And I'm not sure how much like I can actually automate in the things that I do dayto-day versus how much I'm just kind of spending tokens. and
>> uh it's not leading to actual productivity gains and kind of revenue increases. Anyway, let's continue this story. So, the short term looks frothy of course. So, we have a 26% move on the NASDAQ
>> over 5 weeks.
>> Yeah.
>> So, I mean that's that's it. You say this is historic historic 28 uh day trading trading day. This is Has this ever happened
>> again? And so trying, you know, this is just me zooming out, trying to put this in perspective, like, you know, how many times has this happened in history and like what were the circumstances that that had it happened. It's happened uh a total of eight times going back to 1971. And if we kind of just go through these, so back in 1991, we had a 26% uh rally over a similar, you know, number of days that was after uh that was coming out of a cycle low. So I'm trying to understand like what was the context of these rallies that was out of a cycle low.
>> So that wasn't a technology revolution. That was just cycle low recovery basically
>> recovery rally basically mean reversion rally. Um and we had another one in 1998. So this was kind of like early earlier in the kind of like AI bubble. This was also coming out of a correction. Um so kind of early cycle um move back in back in October of 1998. And then we had the big late cycle meltup. Um October 27th, this was Q4 of 99. That was a 28% rally. That was the late cycle uh kind of meltup. And then you had the bare market rally um in J in January of 2000, 30% rally that was kind of, you know, coming out of out of some of the lows and and we had another one another bare market rally in 2001. So now you're in you're in the sort of like well destruction phase and you're getting some of these kind of bare market rallies. Uh and then the other the other two were um coming out of the lows from 2009 and then we had the big sell-off COVID selloff and we had a big rally a V-shaped rally coming out of that. So the takeaway for me I think is just uh these tend to happen like coming out of like a mean reversion after a correction is like one way these tend to happen and then they tend to happen um at like the top right so possibly possibly that's where we are
>> all so okay so as I look at this chart this is really fascinating all of these are mean reversions after cycle lows except for the three that happened during the tech revolution of.com 1998 you said a plus 32%.
>> Uh 1999 December a plus 28%.
>> And then the final blowoff top in March of 2000 of a 30%.
>> So there were three there were three in.com.
>> Yeah. Yeah. It's true. Yeah. Yeah.
>> So like this could be I don't know the first or the second.
>> We could be early. We could be early. That's the challenge. I think that's the this is the challenge. we could see another 30% move. You know, we maybe we have a little 5% correction and then another 30% move. I think this is the this is the this is the challenge of being in a in in a bubble. And I think if you're a trader, you probably love this, right? Traders probably like this. There's more volatility there. You can make, you know, kind of short-term bets. And I think if you're a long-term investor, it's a little bit uh trickier to to to navigate. Um, but yeah, I mean, this is kind of the I guess the if you zoom out on on this, it's to me it's either the final blowoff or it's just like we're in the final blowoff and maybe we have another one to go.
>> So guys, we could either be in 1998, 1999 or 2000. We're not sure.
>> We're not sure, but we're in one of those probably. And it probably is going to because of it's a a technological change. It probably is going to blow off top. I mean, that's pretty much a given at some point in time, whether it's this time or the next one or the one after. Uh, concentration levels. This was a fascinating metric. I saw this all over my timeline on uh on Twitter. So, peak concentration levels of major bubbles. Anytime you get over 40% of what some sort of concentration metric, I guess when you had the Nifty50 run, was that in the 1960s? um you had 40% Nifty50 were 40% of the market.
>> Uh when you had Japan going crazy in the 1980s, it got up to 44% of the total world market.
>> When you had railroads back to the 18 1800s, that got up to 63%. That was the mother bubble of all bubbles. Right now we're at 40%. And that's measured by the big 10 AI companies as a percent of S&P. They dominate. they have 40% of the S&P. When I look at this data though, I can't tell if they're just kind of picking some data sets to tell a concentration story because these aren't really apples to apples comparisons. But but what do you see when you look at this?
>> Yeah, it's, you know, this is really just like a high level to understand the concentration in the market, how that lines up with other periods where there were where there were bubbles. And we we've known this has been this has been going on for a while. The the the MAG7 really led uh most of this rally. What what I'm starting to pay a little bit more attention to now is, you know, we've seen we saw this about 12% correction or so in and NASDAQ in March and and we've seen the big 25% move coming out of that over the last 5 weeks or so. What's sort of interesting to me is that uh MAG 7 there's like there's not like full leadership amongst Mag 7 in that move back to all-time highs. So only four out of the seven. So still still more than half of them are now back to all-time highs, but but you still have a few of them that are not participating. When things broke down back in 1999, that's kind of what it looked like is you had like this broad, you know, leadership amongst the winners and then like a few fell off and then a few more fell off and then there was like one that was still like kind of everything was concentrating around. So I'm kind of paying attention to um how Mag 7 is performing. We've got a chart in here just showing like equal weight and this is not back to all-time highs of the S&P 500 which is interesting because the S&P 500 is back to all-time highs and it's sort of showing you that there's not like broad breath broad participation. So last Friday the S&P 500 closed 7.7% above its 50-day moving average but only 52% of the components of the S&P 500 uh finished above their 50-day moving average. Uh, in the past 30 years, the S&P 500 has never had fewer than 55% of its components above their 50 50-day moving average when the index was at least 7% above it. So, it's kind of just, you know, it's a little odd that the index is is back to all-time highs, but MAG 7, not all of MAG 7 is not, and you're not really getting this broad participation from from the rest of the market, which tends to align with like kind of bubbly type periods uh in the past.
>> I see. And I guess that's because the leaders, the ones that are pulling ahead are
>> embracing more of the the narrative story and kind of the you the price story as well. The the story around AI exuberance that the market really wants to hear
>> and like of later we can go to a few of these stock charts. I mean just looking at like Sandis like some of these memory stocks.
>> Oh that's true. Yeah. So into Intel from April 1st up 200%. Intel
>> Intel. These are this a big business. This is not a
>> Intel has like traded flat for like 10 years or something, hasn't it?
>> Right. Right. So, you know, they're this is a big business. It's not a penny stock. It's up 200% in in 5 weeks. That is that's a huge huge move. Um the memory stocks we've been seeing just absolutely rip as well. Like SanDisk is up 540%. Okay. Year to date.
>> Um which is pretty pretty wild. you know, uh, we've seen Micron, another memory stock, you know, up 130% or so since April 1st. So, um, you know, these are this is where the the bubble is starting to concentrate in different parts of the AI stack. Um, we've seen Mag 7 a little bit, you know, less participation there and, you know, the rest of the market is kind of lagging, lagging behind.
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>> Let's talk about in more detail maybe the mechanics um of today versus the the do bubble. So when you look at the AI money flow today, where is all of the money coming from? I mean it starts with demand, doesn't it? like your demand
For tokens, AI tokens, my demand for AI tokens, large companies' demand for AI tokens in an interface like Claude or ChatGPT or some agent somewhere. That's where it all starts. And then what happens?
Yeah. So, you know, all that demand, you know, and I think 80% of Anthropic's revenues are enterprise revenues. So almost every major company is integrating AI into their systems. They're doing this, you know, they're not just using these things. They're integrating that inside, like a sort of walled garden within their businesses. But basically, what I think is happening is everybody is rushing to integrate this right now. They see the potential for this technology and how it can help them improve margins, improve efficiency. So everybody's rushing in. That's, you know, subscriptions, APIs, software, all that's mostly flowing to the models and the application layer. That's OpenAI, that's Anthropic, that's Perplexity. So most of that's going into those companies. These are the businesses that are not profitable, right? We know that Anthropic is scaling revenues aggressively. I can't remember what the latest that they reported is, but it might have been a $30 billion annual run rate that they've already achieved, which is incredible.
Um, but they're not. Actually, I think I've got some numbers here just to take a peek at. Look at this right here. Anthropic's extraordinary rise from December 2022, $10 million in revenue, all the way to May 2026. This is annualized revenue. We went from $10 million to $45 billion on this. Yeah.
This is log scale.
Okay. Yeah. Yeah. That's an insane ramp. All right. So, this is like this is feeding the narrative, right? They're everybody is plugging into them right now. Um, and so that's, you know, that's where the cash is going. They are spending on the hyperscale, right? So then they are spending money with the cloud providers, right? This is Google, this is Amazon, this is Meta to some extent. So that is going there. So then when those companies report their earnings, everyone's like, "Oh my god, look at all the revenue that they're producing." Um, they are also, there's a little bit of like a circular thing going on where some of those companies are investing in OpenAI and Anthropic, um, and then they're paying them revenue. So there's a little bit of a circular thing going there.
I just saw, was it last week or the week before? Anthropic was basically out of compute, and XAI had overprovisioned. Elon made all these data centers, but their model wasn't as used as Anthropic. And so Anthropic cut a deal, cut a deal with XAI to just tap into their hyperscale resources so they have the compute.
So there's a lot of allocation, let's say, to the leading apps where the demand is actually taking place.
Interesting. I think that's really interesting. Um, so yeah, so right now, like the demand is there. I think it's very clear the demand is there. Um, so if we just keep following this, so then the hyperscalers, right? Where is their cash? They're spending on chips, right? Nvidia, data center buildouts. So then the capital's flowing, you know, to those types of companies. What's Nvidia spending its money on? It's spending its money on TSMC, all the things that go into those chips. Most of that capital, I think, is leaving the US and going to Asia, where a lot of those chips are manufactured. Um, so this is like the kind of the flow of capital. And it all starts. The only thing you really have to understand here is that this first step is the demand. Um, and where is that coming from? I think every time a new model comes out, we just, you know, Mythos came out, kind of blew everyone's expectations away, and then that maybe creates even more demand for the next new model. Um, so as long as that stays there, in this sort of FOMO-driven race to implement these solutions internally within these large businesses, as long as that's there and they feel like they're getting ROI on that, that I think this can continue. But it's sort of a Goldilocks type setup where, what if there's a drop? You know, we know there's other risks in the economy. Um, what if China comes? We know China's building out lots of these models. What if they introduce a model that's just way cheaper to use than some of the stuff that's already out there? So, you know, you just got to kind of think about what would break the demand. Is there some change in the technology that could potentially come? Is there some unexpected thing with return on investment that people aren't projecting that would potentially reduce some of that demand at step one? And then that's what would make the capex investment and everything else look like it was getting frothy and maybe overbuilt. I don't think we have signs of it being overbuilt just yet because the demand's there and there's so much demand for the compute itself that there's no, I don't think there's a glut of supply here just yet. The demand is there because the models and their capabilities just keep on getting better. Like, I'll tell you, just my own experience. So a year ago at this time, I was probably subscribed to maybe two models, $20 a month. So my spend was, you know, $40 a month, let's say. Now you fast forward to today, over the past month or so, I probably averaged about $50 a day maybe in terms of token model spend. Uh, and that's just because the tokens have become more valuable for the research and work output that I'm producing. Um, and so my demand has continued to ramp up and it will continue to ramp up until they stop being as useful, or I suppose they get a lot cheaper. So I'm sure that's just a microcosm of what every person is doing, every company is doing. And it all depends on how useful these AI tokens actually continue to be.
Yeah, I agree. And then, you know, what's the next phase of demand potentially? You know, we should start to see more sophisticated agent-type products come out and start to really start to do more stuff. So, um, so we'll see. I think the real important thing is like the models have to keep improving and keep getting people excited, and then the demand just has to be there. And if that continues, then I think this can just keep going for a while. But we know that, you know, just to me, the reason these types of cycles rhyme is just more related to human behavior, chasing things, chasing narratives. And there's usually just not a clean sort of adoption to these things. It tends to be lumpy, kind of all at once, and then we have to sort of reset. I think that's why Carlota Perez's framework has largely held for almost every major technological advance, and that we just throw too much capital at the problem. We waste a lot of capital. There's some sort of a reset at some point, and then you kind of go into the golden age of the technology. It would be very rare, I think, to just not have a reset at some point. And that's, like I think, really hard to project because there's an element of this that's actually related to geopolitics and just positioning. Like we're kind of in a race with other countries, you know, in terms of security, national security. All of these implications, and you have to factor in what does that mean for policymakers, and how are we allowed to have a correction this time? Are we allowed to have the reset this time? And is it possible that we don't, because it's such a national security concern? At the same time, it's a lot to factor in here. But I think hopefully this just kind of lays out what's really going on under the hood and why it's working right now.
How similar is this in your mind to kind of, you know, the way the capital flows to the way it worked, or like how similar versus different is it, maybe the AI boom versus the dot-com boom?
So it's very similar. Uh, so this is a graphic kind of laying out. Um, so it's very similar. So step one is the end demand. So every household, business at the time was moving online, and the main thing that was being built out at that time was bandwidth. So you had the telecom companies, AT&T, Verizon, building out capex for the fiber optic and all of the bandwidth that then households and businesses were demanding. Um, and then you had the dot-coms and the telecom customers that were, you know, that's where a lot of that capital was flowing in the early days. What happened here was, you know, I think everyone knows this story where we had too much investment went into the infrastructure, the sort of fiber optic cabling. It was kind of a commodity. Too much went into that. We overshot the amount of demand that there was going to be in the near term. Um, obviously the internet was a really important thing. It still is today, and it was not the bubble was very real, but we just sort of overshot it. And that's the human behavior kind of element of this, I think. Uh, and the question is, is that same setup in place today? And if you're a bull and saying, "No, no, this is not a bubble," you would just point at the demand and the fact that people can't get their hands on enough compute. So there's no glut. There's no. And maybe until you see that happen, um, you know, you can just continue to be bullish. But I don't know if, like, I don't know if there was like a glut before the market started to sell off, and if it was more just the price just sort of led. Price just started to break down. We got too overheated, and then because of that, then demand, the reflexivity of that, all of a sudden people are less bullish, and there's just less demand. Um, so I think it's very similar. The key question is, like, we overbuilt bandwidth last time. Are we going to overbuild with data centers and access to compute this time? And right now, we don't see evidence of that. But it doesn't mean it doesn't mean that it can't.
As you say that, as we're looking at the numbers here, it seems like the answer to that question is like, yes, of course, we're going to overbuild. Of course, we're going to overprovision. We always do when these major technological innovations happen. The only question I suppose for those in the market right now and for investors is like, have we done that yet? Like, when will that happen?
Yeah. And so it's kind of back to the question of, is it 1998? Is it 1999?
Or is it 2000?
And if you don't know, because none of us do, really. If you don't know, then how do you position yourself?
Yeah. Uh, maybe we could start to get into the positioning that investors should consider under these current conditions. So, um, how are investors positioning right now? Is it primarily bullish? I mean, they're not doing the Berkshire Hathaway play. It seems like most investors are pretty, pretty well to fully deployed as part of their mandate. Um, is that correct?
It seems that way. We, you know, when we, if we go back to late March, when things were kind of heating up with the Iran war and markets were starting to roll over and sell off, there was a ton of hedging that had come into the markets. Um, and what we've seen since that period, and I think that's part of the reason why we didn't come down as much, but what we've seen since then is the hedges have come off. Retail call options have been exploding. Um, we recently hit 9 million contracts on a five-day average. Um, at the peak of '21, we were about six million contracts, and we've gone up three times, really.
Is this a good index of retail demand? Is that what this is?
Yeah. Uh, it's, you know, retail calls versus puts are, um, so calls, people going long, are two times, two times calls versus puts. So it's telling me that, like, retail since, you know, we hit those lows in late March and we started to reverse, like there's been a very reflexive move in terms of retail getting back into the market. And then sort of like just a mechanical thing where hedges come off, transaction volumes are lower, there's been some other technical stuff with CTAs and just mechanical buying that has to happen, and that's happening in like, kind of a low volume environment. And so I think this has played into this big move that we've seen of late. And, you know, like we were talking about earlier, like this could be it. It could maybe we just sort of kind of calm down for a little bit and then we have another big move. Impossible to predict. It'll seem obvious in hindsight, you know, but I think this is something to keep an eye on, just like this is the positioning in the market right now. This next chart just shows, you know, the VIX has come off. So, you know, we had a big rally. Um, hedges have come off, and it looks like markets are becoming a little more complacent. Uh, again, they were not very complacent back in March. We're getting a little bit more complacent. And then we can look at, you know, credit spreads, as another way to just look at access to capital, right, for businesses out there. Um, it's pretty easy to get a loan. So, um, markets look complacent. We just had a 25% move. We think we're in some type of a bubble framework here. We don't know, you know, it's hard to say, but the markets are kind of complacent at this stage.
So, when did it end? Um, how did it end? Were there any signs aside from markets going crazy, the frenzy, the euphoria, the massive price gains, you know, multiple times you had, you know, three separate 30% plus, whatever, 30 to 45 day events? Besides all of those things, were there any signs and how did it end?
Yeah, you know, you had the extreme concentration, you know, at the top, which we showed, you know, 40%, or so, for the leaders. And that started to break down. So that's one thing to keep an eye on is the concentration. We talked about how only four of the seven Mag 7 have gotten back to all-time highs on this latest rally. So that rhymes a little bit with what we were seeing. Um, lots of dispersion, right? There was tons of dispersion when you got into the frothy zone where things are up a lot. Also, things are falling a lot. We've seen this disruption with a lot of the SaaS stocks out there. Um, you had a restrictive Fed back then. The Fed was actually hiking rates into what seemed like a kind of overheating economy at the time. So they started hiking mid-1999 or so. Um, so the Fed was not, you know, loose. They were hiking into this. Um, and you know, when you hear people talk about what it was like to invest at the time, like there was, I don't think there was some catalyst that caused the prices to just kind of stop going up. They just kind of stopped going up. But then eventually, once you got into like March 2000, um, there was some concern around a recession in Japan. There was a Microsoft was dealing with an antitrust lawsuit. I think that started to shift the narrative in the market at the time. Um, and it kind of just broke the risk-on sentiment out there. I think. And NASDAQ ended up dropping about 78% from March of 2000 through October of 2002. You know, we had a very, I'm not even sure if there was a recession, it was a very mild recession. So, you know, this didn't cause like a 2009 style recession, but we took the froth out. And I think a lot of that was IPOs that had happened, and sort of we talk about token unlocks in crypto, right? In a bare market, you don't want to be in an asset that's sort of unlocking. And there were tons of that happening. So, um, this is something to pay attention to with like Mag 7, for example. Um, a lot of the Mag 7 is not able to do buybacks right now because they're using their free cash flow to invest in CapEx. So that is a shift. If you have some big IPOs coming, we're going to see a similar kind of unlock type period at a time when there's less buybacks happening in the market. So I think that's something to pay attention to. That sort of lines up a little bit with, so I think, you know, pay attention to the structure out there. Pay attention to the leaders, and sort of, you know, the equal-weight S&P 500 has not gone back to all-time highs. If we don't see more participation from the rest of the market, I think that also lines up with what we saw in the dot-com bubble. So, yeah, it's a lot of factors, but definitely something to keep an eye focused on.
The crypto markets and how that is sort of interplaying with what we're seeing in TradFi. Crypto has had a pretty big rally here. Bitcoin's had a, you know, 35% move or so since mid-February. And we're at a really interesting inflection point on the crypto markets. And so that's where I'm spending most of my time. And just really trying to understand, like, if this rally continues in NASDAQ and S&P 500, is that actually going to pull the crypto markets along with it? And I think that's the big unknown. Typically, Bitcoin actually leads the NASDAQ. So when we look at Bitcoin correlations, we talked about how it's most correlated during bare market years. We are at the highest correlation point right now in 2026. And Bitcoin tends to lead the market here. So that'll be interesting to see if Bitcoin rolls over. It's at its right around its 200-day moving average, which can be resistance in a bare market. So we'll be keeping an eye on that. If Bitcoin breaks down, is that a leading indicator for NASDAQ and the TradFi side?
So, if you sum all this up, I'm kind of hearing, maybe I'm reading between the lines, but of course, can't tell whether this is the top or not for NASDAQ. Um, definitely stocks are not cheap at this time. Um, but we could be in a period like 1999 where there's still greater gains ahead and blow-off tops. And it's always painful to be out of the market when that happens. Now, I know you're not an active investor in the stock market. You're more looking at the stock market in the context of the moves that you want to make in crypto. So, let's say it's like 1999 and there's still more growth ahead for the stock market. Where do you think this crypto goes? So, let's say the market goes up and then crashes. Does crypto get pulled along with it? And then do we have to reestablish ourselves in a new regime? Like, I guess maybe sum this up in terms of how you're playing it on the crypto side.
So yeah, we've never invested in the crypto markets through, I guess, a bubble type setup, you know, in NASDAQ. I guess, you know, 2021 we had some similarities there. And yeah, I mean, the best thing you can do is understand the relationship between Bitcoin and NASDAQ. Uh, we know that it's moderately correlated. It tends to be more correlated in bare market years. You know, my way that I'm playing this is, you know, my exposure to the TradFi side of things is like in index funds, and I'm just kind of, you know, I'm not selling anything. I'm just kind of letting that play out. I think what you can do if you think you're in a bubble is just try to stack cash and keep an eye on things. Um, we like to invest when, like, we think things are, it's a fat pitch, and things are oversold, and those opportunities. I think I'm not seeing that on the crypto side in terms of Bitcoin right now. We're kind of expecting things to potentially roll over. And if that starts to happen, and NASDAQ just keeps doing its thing, I think we can just say, like, the crypto markets are just going to do their own thing. And this is one of the things I like about the crypto markets, right? So, one of the best things about crypto to me is like, yes, there's bad things that can happen in crypto markets, but they're free markets, right? There's no, like, there's nobody in there doing stuff that you can't, you know, that you feel like is just against you. And I think on the traditional side, like every Trump tweet, if you're trying to play these markets and you have somebody just kind of tweeting stuff out that might not even be true, but the market responds to it. We know that the Fed has been sort of juicing the markets a little bit here. We think there's been some manipulation, there's been releasing of oil reserves, there's a lot going on that you don't control. At least in crypto, it's just a market. And maybe there's people doing things, but you can see it and you can just kind of navigate that yourself. The thing that frustrates me on the TradFi side is just there's just so many other things and so many other incentives and things at play. And maybe that's how we see this shake out, where crypto markets are just going to be independent. Um, and maybe this bare market just kind of plays out like we would expect a typical bare market to play out. And on the traditional finance side, it's just a lot more complicated with all these other incentives at play. So we'll see. Like, I wish I could give you a real concrete answer, but we are every week, we are updating the DeFi report readers on market structure and exactly how we see things playing out on the crypto side. I think it's a really interesting time to be focusing on crypto. We're at a really interesting inflection point right now.
Yeah, I know you and I have been talking on the weekly TDR podcast about sort of this battle between the bears and the bulls that's going on right now and who's going to win. And so we're in this interim period. I think you're about 50% deployed into crypto and 50% dry powder on the sidelines and waiting for the market regime to reveal itself further. So, this has been great, Mike. I will say for Bankless listeners, if you're not following the TDR journey on the TDR podcast, you should go subscribe to that because we are going to be releasing a new episode on Wednesday. This comes out every Wednesday. We go through the market cycle, so you can get an update on the way Mike is playing it and how he thinks the market cycle looks. So make sure you're dialed into that. There's a link in the show notes. And I got to end with this as we always do. None of this has been financial advice. We don't know where the NASDAQ is going, nor crypto prices. It's all risky. You could lose what you put in. But we are headed west. This is the frontier. It's not for everyone, but we're glad you're with us on the Bankless journey. Thanks a lot.