The Bull Case for 2026 — ft. Tom Lee

31:14so the telephone companies and the long-distance providers, including MCI, would do everything to protect their existing businesses and use regulatory strengths to make sure cellular never really grew. Now, look back. That was, of course, the wrong bet. And remember, cellular companies had to spend$50 per pop to build out a cellular system. So if you took any city of 10 million people, you had to spend$50 per person just to build a basic system. It was enormously expensive, and cell phone penetration was 6%. You had to make a bet that you would have a lot of penetration. I think that I'm seeing people make the same arguments against AI, and I think one of the things we have to say is, which lens are you using?

32:08If you're using it through the lens of a 40-year-old, really wealthy person, no new technology looks interesting to you because you're more interested in protecting your wealth and incumbency. But young people are the ones who change the world. Look at Chase Institute. Credit card spending growth only comes from people under age 50. And what are young people doing with AI? I mean, my daughter is, one of my daughters is in college, my youngest. They have adapted to open AI and chat GBT in a way that I can't even fathom. And so those people represent the future vintage of AI adoption. Just like cellular adoption in the 90s, it was 70 % of 20-year-olds had a cell phone.

33:01and it was like 5 % of 60 year olds. So of course all my clients who are in their 50s and 60s said, you know, who needs a cell phone? They didn't realize that those 20 year olds become 60 and that 70 became 90 and soon everybody had a cell phone. So I think we have to be more, we have to think about how the 14 year olds using these models compared to us because we're already, you know, We've already lived our lives and we've established our regimes. It doesn't mean that AI stocks are correctly valued. I'm just saying we have to really understand that the future change is coming from young people.

33:43We'll be right back after the break. And if you're enjoying the show, send it to a friend and please follow us if you haven't already.

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36:17We're back with Prof G Markets. You said something, Tom, that really stuck out to me. You said that we're in this labor shortage cycle from 2018 that will last through 2035. And you can't avoid the catastrophizing around the destruction in the labor force from AI. Do you still believe we're going to be in a cycle of labor shortage even with AI? I vacillate because there's times where I'm like, when I read a book like The Coming Wave, I panic and I realize like, wow, like we need to re-educate society. But one thing that gives me hope is that we did at Funstret study another technological wave that wiped out at least 20 % of the labor force in the 20th century, which was frozen foods.

37:10So what many people don't realize is that when Charles Birdseye created Flash Frozen, which, by the way, was a venture backed by Goldman Sachs. It was a VC backed company. I love this. And by the way, his name is Birdseye because he was an ornithologist. He actually was studying birds. But he found that the Inui tribe in Alaska had kept their fish super fresh because they were putting it in a frozen saltwater solution that flash froze the fish. If we look at the labor tables from the 20s, 40 % of the U.S. labor force was employed on farms. It was literally, we spent, most of the economy was people working on farms, and most of the service sector that was defined back then were household servants, people working for someone else.

38:03Food was over 25 % of the wallet prior to frozen foods being widely mass market because most food spoiled on the way to the supply chain. And so grocery aisles were mostly fresh. And what was frozen back then had a freezer burn. It was terrible. So flash frozen allowed suddenly the cost of food to drop dramatically because you had less spoilage. And the number of people working on a farm today is down to, what, 2 % of the U.S. workforce? so flash frozen was the really the key innovation that brought down the cost of food from 20 of the wallet to what is it five or six percent today and reducing farming labor from more than i think it was 40 of the peak down to two an economist in 1920 okay let's just pretend on cnbc in 1920 there is none but let's say there was a CNBC in 1920 and these economists were saying frozen food if it comes along and it's going to wipe out 95 percent of all farmers this is going to wipe out the U.S.

39:15economy the U.S. economy can't survive frozen food and instead it freed up time right and it created it allowed people to be repurposed and it created a completely new labor force so So I, Scott, to your point, I think that there is an adverse outcome. But then when I look at past episodes of huge labor disruption, it's actually had positive outcomes. Every technology thus far has followed the cycle you're talking about, some short-term destruction of labor and then profits and innovation get reinvested and we reinvent ourselves. But I want to, we're about the same age, Tom. I want to walk down memory lane.

39:53in the 90s. I think you were a telco analyst with Kidder and then Solomon. Is that right? Yeah, that's right. And I was raising money for internet companies, the internet company that started e-commerce companies in the 90s. And I can't help, but this smells a lot like teen spirit. I feel like I've been to this movie and I have this certain muscle memory. And I might be wrong, but I'm curious if you think my timeline trues up with where you think we are, and that is the economists perfectly called the dot bomb. They said how it would happen, how it would unwind. They were exactly right. But they called it a 97.

40:33And the NASDAQ doubled between 97 and 99. And what you said also that really struck was that the market seems to be climbing a wall of worry. And that is in 97 and 98, we were just very anxious. These things are overvalued. There's no way we can sustain this. And the markets kept going up. And then in 99, we had this zeitgeist where all the short sellers, all the hedge funds, I mean, Julian Robinson just like threw in the towel and gave up and said, I can't predict this market. And then there were all these articles. I remember one specifically in the Wall Street Journal saying, maybe we have moved to a new economic model that the internet has ushered in and we should be thinking about things differently.

41:17And then wham, the market crashed. So if I were to look back in trying to equate this to the 90s and the internet, you know, the internet timeline, it feels like we're more like 97 to 98, a ton of catastrophizing that might indicate a surge up. My sense is when prices are, PE multiples are crazy, which I would argue they are right now, they go insane before they crash. Does this timeline, A, is that even useful to think about, this economic history? And does that timeline sort of where 97, 98, not 99, true up with what you're thinking? It does, Scott. We both have experience of 35 years or more in markets and in technology.

41:59And we have to keep in mind that the median tenure of a portfolio manager today managing a fund is nine years. So they've experienced the markets really only since 2015, you know, being generous. So to them, the 90s is only a legend that their bosses talked about or things that they heard and it's become second and third hand stories. Now, when I was a wireless analyst, there was so much meat to the stories in the 90s, and then like by the in the 97 period, like real things happening, TDMA, adoption, the quality of the customers were good. There was real spending taking place. It wasn't startups paying for everything, you know.

42:55But by the late 90s, the customer quality had already essentially, you exhausted the post-pay world. You had to suddenly go into a prepaid model. And, you know, technology, we called it bleeding edge. There was innovation coming, but there wasn't apps and services to support it, like, you know, picture messaging. And, you know, these were still years away. So I'd say that there is going to be a moment where we've all gotten so accustomed to stocks going up that we insisted that that's the new regime. That's what you're talking about in 2000, right? That's when everyone capitulated. But that's not what I encounter today.

43:41When we talk to our institutional investor clients, this is a market that's frustrating to them because They don't really want to be buying expensive stocks. There's a lot of discipline in place today. And I think that that discipline is the reason markets are climbing a wall of worry. Because I think there's, as you know, a lot of cash on the sidelines. Sentiment is still really bearish. And a lot of people are claiming that we're at a top. But again, I just, you know, in my experience, you know, people are not bearish at the tops. They're bullish at the tops. And I don't really find that many bullish people.

44:17When people talk about the types of jobs that AI will, quite frankly, destroy, I think they're describing the analysts at Fundstrat. So tell me what is actually happening on the ground at Fundstrat. How are you using AI and what, if any, impact is it having or do you think is going to have on your human capital? Wall Street itself has actually been a victim of technology because, you know, first, many investment firms have been using essentially versions of AI systems for a long time, right? They've been investing in quant systems and models. And the sell-side firms have invested in technology to replace labor constantly.

45:02I don't think there's been a year in my career on Wall Street that money wasn't being spent to actually reduce the labor intensity of the job. I mean, I remembered when I was at J.P. Morgan, you know, in the 90s and the early 2000s, trading occupied a huge percentage of the cash equities business real estate. You know, it was a couple floors. and then one day went to electronic systems and like the number of traders went to like, you know, a 10th of a floor. So I think that's the nature of Wall Street that every job is eventually automated away and so value capture is shifting around. In the 90s, when I started, equity research was a back office job.

45:51You know, it wasn't like, Because I went to Wharton undergrad and I graduated. I wanted to get into research. Firms weren't really actively hiring for research. Research was an apprenticeship industry. You had to find a job and find an analyst that would hire you and take you in. Of course, research has become a much more important business today as other parts of Wall Street became commoditized. But when I graduated in the 90s, traders were the highest paid people, the sales trader. They were like the masters of the universe. And of course now it's just computer code. So I think you're exactly right.

46:29In the future, a mediocre research person is not going to be any better than a mediocre open AI or LLM, right? So Wall Street needs to constantly evolve. I know that at our company, we are using AI at so many levels. It's not just research, and we are using it to ingest data, but it's really how we manage our data now and even how we manage our customer service experience. Because Fundstrate has 11 ,000 RAA and family offices plus around 400 hedge fund clients. But the way we manage them and identify their needs, we are using AI. So I would say I have not found any of the AI models that have been shown to us and that we trial because everybody wants Fundstrat to adopt one of their models has not been good at stock picking.

47:33We actually run three ETFs. Fundstrat Capital has granny shots, GRNY, GRNJ, which is a small mid-cap version, and GRNI. But GRNY has a one year of history, has outperformed the S &P by 800 basis points this year. And none of the AI systems that have been shown to us have actually outperformed our own process for stock picking. What would you say makes a great researcher and a great analyst? And then I want to get into crypto. So this is one of my final AI questions. But when you talk about AI is going to replace the analyst, what are the kinds of skills that makes you irreplaceable as an analyst?

48:20What kinds of things should white-collar workers, working professionals in general, be trying to work on and be trying to hone in order to not be replaced by AI? AI is very good at looking at the past. So if you need to build a model, you need to recall data, even say, give me the last 12 times something happened. That is AI. But as you know, to do true training, then you need to have it work in the future. Now, future has not a binomial outcome. It's multiple forward scenarios. and the probabilities are unknown of each future event. Okay? So you're dealing with so much uncertainty that I don't know how a probabilistic way to give you a single-point answer would ever work.

49:18I mean, to give me an example, someone will say this is the fair value of a stock and they say this is the PE and this is the E. and I can never understand that because I'm always wondering which E are you using and you know what I mean because price is today but then which forward metric and then how do you discount it how do you explain to AI that you have to look at 10 years of future earnings but you don't know which future earnings will actually matter the most and then how do you assign the weights I mean that's really what we do at Fundstrat is we're constantly assessing the probabilities of future events and then deciding we do have to pick a direction, right?

50:01Then we say this is the path we're going to take, but it's a guess. So I think that the best qualities of a researcher, at least in my opinion, are you do need to be unemotional, but you also need to know the difference between conviction and being stubborn. Because stubborn is writing something and believing in something when all the facts have changed. Conviction is basically riding through the volatility. And it's not easy to tell the difference until history has already passed. And I think, you know, the third thing that's really important in markets is to know what's already priced in. I don't know if AI is going to really have a good sense for, like, if all, if AI is the only thing managing money in the future, I think a human will beat the market because all the AI systems will be predictable.

50:56You know what I mean? And then you can spoof them all. So that's really where I think human judgment matters because I'm constantly surveying our clients and I'm in constant touch with them. So I kind of know where the money is and what the bets are and how they react to the Fed. And I don't know how you can program AI unless it is, well, they'll get very good. But they really have to think not just on a specific outcome, but on a series of future outcomes. And that's what we're always sort of obsessing over. We'll be right back. And for even more markets content, sign up for our newsletter at profgmarkets.com slash subscribe.

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53:28it. We're back with Prof G Markets. Speaking of future outcomes, last month, I want to talk about crypto. Last month, you said you think Bitcoin could go as high as$200 ,000 in January. We're currently at $94 ,000. It's been a rough couple of months for Bitcoin and for crypto. Where do you stand on Bitcoin right now? Do you still believe that we could hit$200 ,000 in January? What do you make of what's happening in the crypto markets? Well, crypto's had a rough year. It was actually having a great year until October 10th, because on October 10th, Bitcoin was up 36 % for the year. And now it's currently, I think it's like flat for the year.

54:16So it lost a lot of its gains. I'm still very optimistic because crypto still has its best years ahead. But crypto should have had a good year this year and it was on track to until there was a liquidity crisis on October 10th. that was a bigger wipeout in terms of liquidation than any event in history. The most recent one before this would have been 2022 with FTX. And that wipeout pales in comparison to what happened on October 10th. But in 2022, it took eight weeks before crypto, the smoke cleared, the leverage wipeout was enough in the mirror that crypto prices began to recover. This week is the eighth week since that crisis.

55:09And I think crypto prices are beginning to actually recover. That's why I think Bitcoin can double from here by the end of January. Now, many people don't expect it because of the four-year cycle. And that's going to be the big question. If Bitcoin breaks$125 in January, there is no four-year cycle. What did happen on October 10th? Like, everyone knows crypto markets got hit. It seems unclear to people what actually happened. And as you say, it was one of the largest liquidation events that we've seen in the history of crypto. What happened? I'm going to give you what we've been able to piece together.

55:51And I would say that it's like a 90 % correct. Because, you know, there's going to be 10 % you don't know if there was something else. Just to clarify, is the reason we don't know what's happening because of the anonymity of crypto? We don't know who owns which wallets, and so it's harder to track what's actually happening? Well, it's that. And plus, you know, when we look at liquidation events in a stock market, 90 % of what someone will explain is probably correct. But 10%, like 90%, it would be 90 % to correct to say that the February to April decline was largely due to the Trump tariffs. But the other 10 % would be like, well, stocks were already expensive and they were overdue for erection.

56:38So that's what I mean by 90-10. So give us your 90%. What do you think happened? On October 10th, there was two things that happened. One was a triggering event, which was Trump announced a re-escalation of tariffs with China, like a tripling of proposed tariffs. And because markets were closed, historically, crypto is what reflects reaction to a macro event when you're already after market hours. Like if the S &P was open, crypto probably wouldn't have been gut-punched as hard. But crypto prices fell. Now, crypto prices falling, system can handle that because, you know, crypto is a hypervolatile by nature.

57:24So large swings in prices shouldn't really overload the system. And even volume shouldn't overload the system because crypto trades, you know, there's so much automated trading. However, there was an algorithm in place that actually what I call a glitch happened on a specific exchange. Okay. Many people use leverage in crypto. I mean, it attracts leveraged trading. But people put up collateral so they can do leveraged trading. One of the collaterals is stablecoins, okay? And stablecoins are a pretty safe collateral because, hey, if it's Tether, it trades at a dollar, it's a pretty safe collateral.

58:11And so you can borrow a lot against safe collateral. And if it was USDC Circle, that's also a really stablecoin because it's backed by a dollar. However, there was a popular stablecoin called USDA. It was an algorithmic stablecoin. And on one particular exchange, because of the shock of Friday, internal prices, like people bid ask of that stablecoin actually got out of whack. Suddenly, the price went to$0.65, even though it's supposed to be essentially worth a dollar. But within one exchange, the quoted price dropped to$0.65. Well, that meant that all the collateral for every account that used that particular stablecoin to borrow money was now in deficit.

59:06Okay, even if it was just$1 that traded at that price, it was already putting every single piece of collateral at risk, into deficit. So then something called ADL was triggered, automatic deleveraging. And so in one exchange, everybody who had used that stablecoin as collateral basically got wiped. Their accounts liquidated. Well, what were those accounts long? They were long altcoins and all these different cryptos that suddenly got dumped onto spot exchanges. so then on all these other exchanges suddenly some crypt some alt coins suddenly went down 99 because there was a lot of selling from adl but it triggered a domino effect of all these other exchanges triggering other adls because spot prices of all these alts dropped so that to me was a glitch because it was like an illiquid quote that didn't represent a true vwap triggered an ADL that triggered a cascade of ADLs.

1:00:11And that led to millions of accounts being literally zeroed out. It won't happen again, I'm sure, because in the future, I'm sure they will use a composite set of prices, or if there's a variance between what's quoted internally versus on spot, or if it's a volume-based measure. So that's why I don't think it would happen again, but that's what happened on October 10th. Okay, we finally got our answer. I've asked this question to many people and i never get a proper answer uh my takeaways from that are that you know it seems vulnerable this this asset class that is it was supposed to be a hedge in a lot of ways um we are learning in in various ways is extremely vulnerable to to what seems to be almost nonsensical mechanical glitches um which i guess that is my takeaway in 2020 the price of oil went negative right i mean oil is the most liquid commodity in the world and it traded a negative price so these glitches happen in all markets but it does happen in crypto because it's it it's a gigantic place where people are trying to experiment and create you know uh what they view as free from censorship and interference but of course there's every event's going to bring something new and you're 100 right you know it's terrible that it happened um but again i remembered oil was negative you know and people actually were able to buy negative oil they were paid to like take oil i guess i'll wait for a negative stock price I'd love the opportunity to get, yeah, negative stock.

1:02:00Remember bonds? Corporate bonds had a negative yield in Europe. You were actually paid to own, like, an issuer was paid to issue a bond. Can you identify any sectors or geographies that you think are dramatically over or undervalued right now? undervalued uh i think is small caps because there is real earnings growth now coming but there is no money flows so small caps are a whole group that professional investors can afford to ignore because no one else is buying them you know the amount of active money in small caps is like at record lows uh i think financials are also dramatically undervalued, Scott, because, well, this is where we could be wrong.

1:02:49But in my view, I think the financial sector is actually becoming a tech sector, that as money is becoming more digital, and as AI implementations are heavily, heavily taking place in financial services, it's going to make, it's creating an advantage for the companies, the companies who issue capital. and in companies like JP Morgan probably as we just discussed earlier could really dramatically reduce their dependence on humans which is their largest expense so I think financial companies are increasingly going to look like tech companies and their multiples may become more like tech multiples so that that to me is one group that in the future could have a 30 PE even though they used to trade it 10 times earnings.

1:03:37We've been talking with a lot of different people in the markets. We've been talking with renowned professors, investment strategists, economists. We talk with a lot of people. Most of them are somewhat bearish right now. You are one of the only real bulls that we've talked with. I've seen you described online as a perma bull. That was what Bloomberg called you. What do you think about that label? And how is it that you are bullish right now in a sea of bears? And what do you think that says about who you are? I was first called a permable in 2009. In fact, it was major newspapers that were using it as a mocking term.

1:04:30Here's what's interesting. 16 years later, what was the right call to be? The optimists have won. And yet today, if I had to say what proportion of investors are bullish versus bearish, it's really risen in the last year. In fact, it's kind of close to the 2009 levels. I think people are already betting on the fact that we're in a bear market. And now many people were convinced of that in 2022 because of the Fed hikes, and they just never changed their views three years later. But as you know, what made people a lot more bearish is also because President Trump is a very unpopular president. He's a very divisive figure.

1:05:23I'm a registered independent, so I have never tried to let politics be involved in how I view markets. But I can't help notice that I think that political lens plays into many of our clients' views around markets that they tend to view. When Biden was president, there were a lot of people who were critical of Biden. I thought the economy—I've cared about the economy. I thought the economy was fine. I think the economy's still doing fine under Trump so that's kept me I use that as one level of coding that I think has kept people bearish but I think America as long as it's a place of innovation and we are because we're at the center of AI I think it's pretty bullish but you guys have raised the key point I mean, there's a chance that this AI is a disaster for labor markets.

1:06:24And if it is, the U.S. will be the least scathed, but everyone's going to go down. Tom Lee is the co-founder, managing partner, and head of research at Fundstrat Global Advisors, a leading independent research firm. He has more than 25 years of experience in equity research and has been top-ranked by institutional investor every year since 1998. prior to co-founding Fundstrat. He served as JP Morgan's chief equity strategist from 2007 to 2014. Tom, I wish we could do this for three hours. Maybe next time we will. Really appreciate your time. Thank you. Thanks, Tom. Good to see you. Yeah, next time.

1:07:10Scott, what'd you think? Yeah, I have a lot of respect for Tom, not just because I think he's a great analyst and does the work, but I just appreciate how measured he is. He basically says, yeah, that's a good point. You could be right. When these guys go on CNBC and sort of talk their own book and say, no, the market's going up 20 % next year and this is why, he's very measured around this is what I think, but I don't know. and he acknowledges the other side. He just strikes me as very reasonable and tempered. And, you know, I can kind of see why institutions like his research because I think he's probably got a track record of sort of, you know, I hope most of this is right, but I know some of it's wrong and buyer beware.

1:08:02He just strikes me as the adult in the room when he's making these recommendations. Look, I think it's good that we had the bull come on before the end of the year. We've had a lot of bears on. And I think all of them have presented really - He and Josh Brown. Josh Brown's a kind of a ball. We'll definitely get him on in 2026. But yeah, I think I love his analysis of frozen foods. I think that was a great example - That was really interesting, wasn't it? Of a technology that had real impacts on the labor force, but ultimately a freed up time and it left us with more productive things to do. I don't think that that means that we're not going to see an impact on individuals' lives.

1:08:40I mean, he talked about how, you know, frozen foods happen. Everyone thought that farmers would go out of business, and then we were fine. It's like some of those farmers did go out of business, and some of those farmers were not fine. But long-term, as an investor, yes, the idea of these technologies creating short-term destruction in the labor market shouldn't worry you too much. I think the question is, you know, he was talking about his children using AI and young people using AI, which I think is a fantastic point. We should be really looking at how are young people using it. I think the question is, what exactly is the market pricing in?

1:09:17Because it's hard to tell if the market is underestimating the potential or overestimating the potential. And it seems that we haven't really reached a consensus on this. And perhaps that's just the way markets work. We can't know. But I think that is sort of my big question. It's like, you know, just how optimistic or pessimistic or neutral on AI is the market really based on current prices? And then I think the final point that I think was a good point to end on for the end of the year is he says, you know, yes, he expects or he could easily see a 10 to 15 % correction next year. And I think that was a little bit scary hearing that.

1:10:00But then he also points out it's a long time a year, 52 weeks. So he expects that actually we'll see a rally after then. So I think it was a good way to end the year. Appreciate his perspective. And we'll definitely want to talk to him again.

1:10:21This episode was produced by Clyde Miller and Alison Weiss and engineered by Benjamin Spencer. Our research team is Dan Shalan, Isabella Kinsel, Chris Nogonoghue, and Mio Saverio. Drew Burrows is our technical director, and Catherine Dillon is our executive producer. Thank you for listening to Prof G Markets and Prof G Media. If you like what you heard, give us a follow and join us for a fresh take on markets on Monday.

1:10:56In kind reunion As the world turns And the dark flies In love

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