In their latest episode of the VALUE: After Hours Podcast, Tobias Carlisle, Jake Taylor, and Dan Rasmussen discuss:
- AI: Will the Innovation Wave End in Overbuild?
- The Casino Mentality in Modern Markets
- Minsky’s Four Conditions for a Bubble: Do They Resonate Today?
- Is the US Holding Back Value Investing?
- The Hidden Opportunity: Why Europe is Undervalued and Misunderstood
- The Humble Investor by Daniel Rasmussen
- The Power of Non-Conformity: Lessons from Asch’s Experiments
- Speculation Redux: Are We Reliving the 2021 Market Boom?
- Optimizing Portfolios with Multi-Asset Risk Models and Volatility Insights
- Small Cap Value and the US Market: A Tale of Divergence
- Unlocking Japan’s Value: How Balance Sheet Optimization Could Transform Markets
- Japan vs. Europe: Can Corporate Reforms Bridge the Valuation Gap?
- Hidden Quality in Japan: Can Balance Sheet Engineering Unlock Value?
- Gold in Modern Portfolios: A Quantitative Perspective
- Systematic Macro vs. Cowboy Macro
- Competition Neglect, and the US Valuation Dilemma
You can find out more about the VALUE: After Hours Podcast here – VALUE: After Hours Podcast. You can also listen to the podcast on your favorite podcast platforms here:
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Transcript
Tobias: This meeting is now being livestreamed. It means it is Value: After Hours. First one for 2025.
Jake: Oh, my God.
Tobias: I’m Tobias Carlisle. Joined as always by my cohost, Jake Taylor. Special guest today, great name to kick off the new year, Dan Rasmussen. How are you, sir?
Dan: Great. Great to be here with you, guys.
Jake: Toby, I only agreed to do three of these. And now, we’re in Season 6. What the hell happened?
Dan: Oh, my gosh. [laughs]
Tobias: Is this Season 7, I think.
Jake: 7? Oh, my God.
Dan: I’m noticing a lot of gray hair on two of these panels, so I’m suspecting–
Jake: First of all, how dare you, sir?
[laughter]Dan: Wait till we get to Season 13.
Jake: Oh, my God.
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The Humble Investor by Daniel Rasmussen
Tobias: This is an expensive touch of gray job that I have here. [Jake chuckles] I’m actually jet black otherwise. It’s very expensive. Dan, you’ve got a new book out, The Humble Investor. What is it about?
Dan: Well, it’s mainly me bragging about being the most humble investor. [Jake [chuckles] And then, there’s a whole section on how I would have called it the arrogant investor, but I chose to be a value investor instead. So, now, I’m the humble investor.
Jake: [laughs]
Dan: The book is really the summation about a decade of writing my weekly research pieces. So, it’s a mix of our greatest hits and underlying theme of all of my writing, which is this idea that the future is so hard to predict and what follows from that. If you start from that premise where you say, “Hey, gee, it’s really hard to predict the future.”
And so, any analysis that’s going to be about what’s going to happen in the future and any decisions that are built on analysis about what’s going to happen in the future are likely going to lead you in a bad direction.
And so, then the next step is if you’re an investor and my favorite motto of investing is that investing is not a game of analysis, it’s a game of meta-analysis. It doesn’t matter what you think. It matters what you think relative to what everyone else thinks and what’s priced into the market that the best investment opportunities would therefore be found in looking for places where other people are too confident, where they’re arrogantly over optimistic or arrogantly pessimistic.
And so, I explore a variety of these types of themes of where can you find excessive optimism? Where can you find excessive pessimism? How do you trade on these ideas? What are the implications of that, and how do you apply this humble worldview to counteract a lot of the discounted cash flow models and the long-term planning and these excessively sophisticated models that just assume too much knowledge about the future that we don’t have?
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The Hidden Opportunity: Why Europe is Undervalued and Misunderstood
Tobias: Where are people being arrogantly pessimistic right now?
Jake: [laughs]
Dan: I think that–
Jake: Stop asking about your portfolio, Toby.
Tobias: I’m trying to get– just go straight to small value.
Dan: Yeah. Yeah. Yeah, exactly. Your three largest holdings, Toby. I’d say, broadly Europe. I think Europe has really been the focal point of excessive pessimism. I think it’s for a few reasons. One, we’ve had a series of events. We can talk about why those events maybe weren’t as bad as people said they were. But you’ve had Brexit, you’ve had the war in the Ukraine, you’ve had the subsequent energy crisis and then you’ve had the ongoing over regulatory, excessive government intervention that has left investors being very, very pessimistic on Europe and very pessimistic on the UK.
I think what they’re missing– Yes, by the way, the corporate earnings growth in Europe has been lower than that of the US. But so is everywhere. Pick any country, and it’s been lower than the US. Pick Canada, pick Europe, pick Japan, the US has been exceptionally good. It’s not that these other places have been exceptionally bad.
But the narrative has gotten so extreme that Europe is a museum, that there’s no innovation in Europe, that government regulation is going to strangle all these companies. But if you actually look at the fundamentals of the businesses in Europe and in the UK, they’re actually very well run, they’re generating very high return on assets and they’re extraordinarily cheap relative to the United States.
And so, I think today, if you want to buy really high-quality businesses and you want to buy them at reasonable valuations, it’s actually pretty easy. You just go across the Atlantic, and you can find these things in the UK and in Europe. I think that that’s the most exciting opportunity to me now, because it feels relatively safe. It feels supported by valuation, supported by business quality, supported by intelligent aligned management.
I think if you look at where Europe’s trading relative to history, where you think of European value trading relative to history or European small caps trading relative to history, you’re probably talking in the 40% to 50% discount relative to long-term averages for European small cap value, which just seems like a huge margin of safety for, again, what are fundamentally good businesses.
I think you’re starting to see private equity move there. You’re seeing an increase in take privates, an increase in M&A activity. And that’s because the math is just so easy to pencil out the Acquirer’s Multiple math works in Europe at the moment for a very broad swath of the small cap market. So, I think that’s probably the place where excessive pessimism has gone too far.
My two quick side note facts to anecdotally put exclamation points on that are the fastest growing developed economy last year was Spain. That’s point one. And point two, is that since Brexit, the UK economy has grown GDP faster than continental Europe. So, those are my two surprising anecdotes to illustrate why things just aren’t quite as bad as you think they are in Europe.
Jake: And what free cash flow yields are you seeing in a well-constructed basket in Europe these days?
Dan: 15 plus percent free cash flow yields for companies that are generating, 35% gross profit to assets. So, it’s just shockingly good. This market has been left over– You think of like where people are putting their money, it’s all the S&P.
I even saw one of my analysts– I have analyst who’s Japanese. He sent me a list of the top traded individual stocks in Japanese NISA accounts, which is their equivalent of an IRA. And if you look down the list, it’s Palantir. It’s every US [crosstalk]. The global attention is all in the US. And as a result, you see these great, great opportunities the minute you step outside of the New York Stock Exchange and the Nasdaq.
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Is the US Holding Back Value Investing?
Tobias: Given that it’s been a long time since value’s really driven the markets, why do you think that would– Cliff Asness wrote this great piece over the weekend. He said–
Jake: That was hilarious.
Tobias: He imagines what the world will be like in 10 years’ time. I read that. I thought the [chuckles] only problem was this, is that it assumes some return to sanity over the next decade. And if I look back over the last decade, there certainly was no return to sanity then. So, why do you think now might be the time?
Dan: Yeah. Well, I think you have to segment out US international, because value actually has worked quite well internationally. Really the dramatic slap you in the face and kick you into the curb underperformance of value has all been in the US. I think that’s because the extraordinary outperformance of growth has been concentrated in the US. Bitcoin seems to be primarily, or at least originally to a large extent a US investor phenomenon. All the Mag 7 names. AI, ChatGPT, you name it.
The only thing that you can think of that isn’t that way is Novo Nordisk and the GLP-1s. But Lilly has one too. So, I think the bulk of the innovation has come in the US and the bulk of the irrational, in my mind, exuberance around these certain ideas has been in the US. The rise of meme stock trading. All the meme stocks are in the US. There’s no European meme stock or some company on the Paris Exchange is a 5000X, because some random Jacobin and had eating croissants [Jake laughs] at in a cafe is pumping the stock on his video blog. It just isn’t happening.
Tobias: [laughs]
Dan: And so, I think that you got to say value still works. Value is still working. We just have an extraordinary set of specific things– And not a huge number of them in the United States that are driving those factors to not work in the US right now.
Tobias: The problem with the French is they haven’t been able to come up with a competitor for FARTCOIN.
Dan: [laughs] Yeah. My primary portfolio is now 50% FARTCOIN, 50% Nvidia.
Jake: Is that the innovation that they’re lacking in continental Europe?
[laughter]Dan: Exactly.
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Unlocking Japan’s Value: How Balance Sheet Optimization Could Transform Markets
Tobias: Japan is a country that has been undervalued for a long time. After soaring to incredible heights in 1990, it really hasn’t come anywhere near where it was in 1990. It’s a long period of time now. It’s 35 years. But Japan, I think, has looked cheap on and off for the last 5 years or 10 years maybe. But it doesn’t seem to have been a place– hasn’t really got much attention, hasn’t really ever returned to the boom. What does it take to see Japan turn around?
Dan: Yeah. I think it’s a lot easier than you think it is. And the reason it’s a lot easier than you think it is, is because we’re used to the United States where valuations are dependent on future free cash flow. The classic discounted cash flow models. If you want to value Nvidia, it matters what earnings are in the2030s.
Okay. if you go to Japan, and you liquidated basically the entire small cap market and sold it for book value, you’d Increase the amount of money you had. [chuckles] So, it’s a balance sheet question. Because if your assets are worth more– If your book value is twice your market cap, it doesn’t matter what your free cash flow generation in the future is. All that matters is that you do something even reasonably intelligent with your balance sheet.
Now, in a reasonably constructed portfolio of Japanese equities, you might find cash running at 50% to 60% of market cap for a pretty broad basket of cheap value names. And so, you say, “Well, what do you need to do to make the stock go up to book value?” Well, you could start by buying back shares. Buy back 20% of your market cap and shares, which you could do overnight. And then, you look at depreciated real estate is probably another 150% of market cap. So, you’re saying,” Well, do you need all that real estate? Could you maybe borrow against it at 0% interest rates? Get a 0% interest rate mortgage from your local bank for 100% of market cap, which would be two-thirds of your asset value of your PP&E asset value?”
And then, the average Japanese value stock has 50% of their market cap in cross shareholdings of other publicly listed Japanese companies, so you could just sell the cross shareholdings. So, you could actually double the value of a large number of Japanese small caps simply by reducing cash and selling cross holdings, would get you pretty far to getting to book value.
So, the question is like, does Japan need to grow again? Do they need to start bringing in migrant workers to revive the economy? It’s like, no. They just need to do simple, obvious things their balance sheet. And the good news is they’re starting to do that already. So, the Tokyo Stock Exchange put in place this great initiative, and they’re naming and shaming, they’re forcing companies to put up plans.
The culture is really shifting. And you’re seeing those conversations start to take place where all of a sudden, people want to talk about balance sheet optimization, they want to talk about getting to book value, they want to talk about increasing dividends and doing buybacks. And I think once that ship has turned, it’s only going to accelerate.
So, I think we’re in the early innings, but we’ve already seen the results. It’s already happening. This isn’t a pie in the sky. The corporate governance reforms are already taking effect. Companies are already issuing dividends, already increasing dividends, already initiating more buybacks, already starting to sell cross shareholdings. I think those things will only accelerate as they become more popular and widespread.
Jake: It seems like it’s started at the top as far as the size of company and it’s been working its way down. Does that feel right?
Dan: Oh, yeah. Absolutely.
Jake: The smaller ones have not fully– just hasn’t gotten there yet, but it seems like it might be coming.
Dan: Yeah, they’re more conservative. They want to see things work at the larger companies, but they’re ultimately their followers. If Toyota is doing it, they’re going to do it. It’s just a matter of time.
By the way, once Toyota is doing it, what excuse do you have if you’re a Toyota supplier for not doing it? What are you going to tell your board? What are you going to tell your investors? Toyota’s doing it. We’re a supplier of Toyota, and we’re not doing what they told us to do and what everyone else is doing. They’re not going to do it. They’re going to change.
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Japan vs. Europe: Can Corporate Reforms Bridge the Valuation Gap?
Tobias: One of the things that we’ve talked about on this show and we talked about just before we came on, is that the Japanese seem to focus more on longevity rather than optimization, which might explain some of the choices that they’ve made to get to this point.
Dan: Yeah.
Tobias: Do you think there’s some cultural shift that needs to happen, or you think that these reforms will get them there?
Dan: I think the reforms will get them there. Now, get them there, meaning, getting to book value, which would be a huge win for corporate Japan. But will it get them to where the US trades, which is three and a half or four times book? No.
Japanese companies will still be lower margin, lower return on investment, spend more on employees. Those things are so big and so structural. Maybe they’ll change at a glacier pace, but probably not much. But again, those things are peripheral to the main question of, can you just fix the balance sheets, which is easy to do. Can tell every company to own 15% cash as a percent of market cap instead of 50 or 60, and the problem is solved. Or, tell people, “Gee, you need to rationalize your real estate, divest noncore real estate assets.” Just simple things like that. They are already having a tangible effect.
We invest a lot in Japan. We invest a lot in Europe. If you compare the two, Japanese companies from a US framework, US definitions– So, I’ll admit we’re applying some cultural hegemony here. You would say Japanese companies are poorly run. They’re run primarily for the benefit of employees. They never fire anyone. They never cut costs. They’re very slow to take obvious actions.
European companies are run almost exactly like US companies. Maybe they went to INSEAD instead of HBS, but they’ve worked at the McKinsey Belgium office instead of the McKinsey New York office. But they’re the exact same pedigree, they have the same philosophy, same worldview. The companies are run in exactly the same way. You see it in the margins. The margins are higher. The return on assets and higher. You’re not seeing stupid investment decisions being made. In Japan, you see all that stuff being done. It’s massive empire building, or real estate purchases or crazy spending on employees. That stuff is a permanent feature of Japan.
So, I’m not saying Japanese companies need to trade at the same multiples as the US. They don’t. But trade at something like one times book at least. I think if you’re looking for quality, there’s a much smaller opportunity in Japan for quality. Japan’s a value market. If you want quality, you got to go to Europe, and that’s where you’re able to buy really high-quality businesses for cheap.
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Hidden Quality in Japan: Can Balance Sheet Engineering Unlock Value?
Tobias: Does the balance sheet engineering reveal some of that quality? It just genuinely isn’t there or just it’s hidden, because it’s buried under unproductive building, unproductive cash at bank?
Dan: Yeah, it’s a good question. I think it depends on how you see quality. If you want the best French food in the world, go to Tokyo. [Jake laughs] But if you want the highest margin restaurant, don’t go to Tokyo. I think they have a meticulous focus on the customer experience. They have a meticulous focus on employee experience.
I think there’s this areas in which Japan is truly excellent. Like, Toyota’s are wonderful cars. Everyone understands the quality of Japanese manufacturing in its attention to detail and the beauty of that culture. But that attention to detail and the beauty of that meticulousness does not translate into high efficiency, high return on assets. [chuckles] This is not like the 3G cost cutters. It’s the exact opposite of that. It’s like, “Oh, we could spend $100 which would earn us a $1 of incremental profit a year, but that $100 would allow us to incrementally make our thing that much more beautiful. Let’s do it right.”
It’s an elegant thing. I admire it. But it’s not efficient. It’s not efficient. And so, it’s never going to and never does pass our tests of return on assets and return on equity type metrics.
Jake: I think one of the things to keep in mind, is that accounting is not perfect at necessarily describing every single economic situation. So, it’s much heavier industry in Japan, much more manufacturing. It requires more assets to do that, more physical assets, more tangible assets, which then are easier to put onto a balance sheet and easier to then measure an ROE on. Whereas more intangible things, those don’t end up on the balance sheet necessarily, so you actually look like you have higher ROA, ROEs in an intangible economy. And so, sometimes you’re comparing apples and oranges, but you go–
Dan: Yeah, that’s a great point.
Jake: -four times book value in the US and half book value in Japan. Well, those book values aren’t analogous. So, I think you got to take a little bit of grain of salt there.
Dan: Yeah, that’s a great point, Jake.
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Competition Neglect, and the US Valuation Dilemma
Tobias: I saw the chart. I haven’t done this analysis myself, but it said that the US has reached its highest ever level of price to book value. I know that price to book value is a terrible metric for all the reasons we’ve just discussed and have discussed ad nauseum for six or seven years on this show.
What do you think about the US prospects? There’s a composition problem with the market that it is materially different. And this is some of the criticism using something like Shiller or some of those other aggregated metrics for stock market overvaluation.
Jake: And comparing historical epics. They’re just not the same. The numbers don’t mean the same thing from era to era.
Tobias: What do you think about that, Dan? What do you think about the valuation? I shouldn’t say overvaluation. I don’t lead the witness too much, [chuckles] but the valuation, the metrics?
Dan: I think that my argument, is that what we’re experiencing in the US is not analogous with broad numerical averages as Jake was arguing and as you were arguing. Because what’s going on in the US is so specific. What is specifically happening, is that we’re going through an innovation wave. During this innovation wave, the innovation leaders are clearly earning abnormally high profits that are growing at abnormally fast pace. And so, the question is, what happens to these technology leaders?
That’s the only question that matters. Like, will CAPE’s mean revert is entirely dependent on whether AI CapEx spend has the return people think it’s going to have or not? That’s the question, right? If the $80 billion Microsoft is planning to spend next year on AI, does not have a good return on assets, then all of a sudden, CAPE ratios are going to mean revert. If, on the other hand, Microsoft spends $80 billion, and a year from now, they have accomplished artificial general intelligence and we have robots that can do everything that humans can do but better–
Jake: We are all unemployed.
Dan: We’re all unemployed. Your lawyer has been fired and replaced by a chatbot, and your accountant has been replaced by a chatbot and your kids are being taught by chatbots. A year from now, and Microsoft is making $160 billion of revenue in AI versus that $80 billion of spend, then all of a sudden, the CAPE ratio is going to go to 2x what it is right now. Not mean revert, and we’ll be having Value: After Hours again coming up with some other reason why some other market is cheap [laughs] and wondering why we didn’t just buy bitcoin. But I think that’s the dynamic.
I think that’s not a question which you can necessarily– You can answer it by analogy. And so, I would give a few analogies that to me resonate. One, I would say is this beautiful paper that was written by our consulting economist here for [unintelligible 00:22:04] about cycles in shipping prices. The paper talks about this idea of competition neglect.
And so, the idea is that when shipping rates are really high, shipping companies tend to– The heads of the shipping companies look and they say, “Wow, rates are really high. We should go build a bunch of new ships, because the IRR on building these new ships is very high at the current rates.” But it takes three to five years to build a ship, okay?
So, they go and they commission these ships. What they don’t realize is at the same time, they’re going and commissioning these new ships, five of their competitors are also running the exact same IRR math, because by the way, it’s not hard. Like, what are the shipping rates? How much does the ship cost? Okay. Great. Like, “I should also build ships.” And so, they all go out and they all build ships and so the fleet ends up growing much more than any of them anticipated, rates come down much more than any of them anticipated, prices crash and then the opposite thing happens.
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AI: Will the Innovation Wave End in Overbuild?
Dan: And so, my analogy with what’s going on in AI is the same. Like, how many AI companies are spending in the tens of billions of dollars building LLMs. All thinking that there’s this massive AI opportunity. Let’s put on the lens of competition neglect. Like, are all of them going to win or not? What has been the historical experience of big technologies like this? Well, the historical experience of the last 20 years has been that its winner takes all, that all the profits in mobile phones go to Apple, that all the profits in search go to Google, that all the profits in social media go to Meta. That’s been the experience.
It hasn’t been like that. Everybody earns a 20% share of the market, and yet you’ve got five or six different major companies competing with major LLMs, spending massive amounts of money and not all of them are going to win. There’s obvious competition neglect. It’s obvious. Now, what’s going to happen, which one to short, which one to go long? I have no idea. But that analogy makes sense to me.
The second analogy that makes a ton of sense to me is fiber. Everybody says the internet is coming, high speed internet access is a must. And so, we’re going to build out massive fiber networks to enable everyone to get on the internet. There’s no question that we’re going to make a killing, because the profits generated by the internet are so huge. Absolutely right.
All that fiber is now lit, all of it is now used, the internet is massively profitable. It’s just 20 years late, after every one of the companies that built the fiber went bankrupt, because they spent all this money, and the applications of the internet were 10 years away really from being highly profitable.
Jake: I thought I read actually somewhere that this might have been a couple of years ago, but it was something like only half of the fiber that was built is lit today still.
Dan: Yeah. That might be right, actually. Maybe it’s not even all of it is lit. It’s crazy. The overbuild was so massive. And so, I think you apply that second analog and you say like, “What is a really highly profitable application of AI today?” Not building the models or raising money off building models, but where a customer is actually spending billions of dollars on AI powered software that is actually helping them generate more than that in profit. It doesn’t exist yet, and yet everyone’s assuming it will. It probably will, but it might not until 2040. I think that’s my second analogy.
So, I don’t know enough about AI and G. Everyone has been skeptical of technological innovation in any way over the last decade has been wrong. And so, me certainly, obviously, don’t trust me on predicting the future of technology or technology stocks, because I’ve been wrong. But I’ve been wrong, because I’ve hearkened back to the historical analogies which just suggest that these things don’t grow to the sky, that we’re not going to magically develop humanoid robots that are going to solve all of our problems and put us all out of work. That every time we’ve heard those type of arguments, it’s been wrong. The world doesn’t change that fast. That five or six companies spending massive amounts of money on the same technology doesn’t end well, but we’ll see.
Jake: [chuckles]
Tobias: “ChatGPT continues to be one of the most downloaded apps in the App Store”.
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Small Cap Value and the US Market: A Tale of Divergence
Tobias: According to a tweet that I saw. Another tweet that I saw says that “Small cap values approaching its long run mean in the US.” Do you have any views on long run average valuation, which means that it’s not particularly cheap? If anything, it’s just– [crosstalk]
Jake: Really? Has that been a deterioration of the fundamental side, not the– I don’t feel like price has been– [crosstalk]
Tobias: I think it’s straight PE. Yeah, I don’t know.
Jake: Numerator or denominator here?
Tobias: Yeah. But it could be E deterioration, which would make the P more expensive, wouldn’t it? What do you think, Dan? You’re still immersed in that part of the world?
Dan: I am. I spend less time in the US. I find the value opportunity is better internationally, and so that’s where I’ve been focused. I tend to look at the value stocks that I see in the US and the ones that I tend to like, a lot of them are very cyclical. I think there’s a huge overrepresentation of oil and shale type businesses in the value names. There’s a lot of consumer retail type stuff, shoe companies and things like that. I don’t know, it’s hard for me to make as much clear sense of the US value market.
Large cap value, I think, which is not something I do at all. I’d say there’s quite an interesting dynamic going on there, where if you look at the correlations between large cap value and large cap growth, historically, they were like 99%. US stocks were US stocks and US large value very correlated to US large growth. But in the past few months, in the past year, US large value is now as correlated to US large growth as international stocks are to US growth. Like, US growth in stocks have decoupled from US value stocks, which is another fascinating phenomenon.
Tobias: Interesting.
Dan: I don’t know what to make of that going forward, but it just shows you how concentrated and how single issue this market is.
Tobias: That’s purely the– whatever they’re calling it now, BATMMAAN or whatever the–
Dan: Yes exactly.
Jake: What’s the new acronym– [crosstalk]
Tobias: Fan Mag. Whatever it used to be, because they’ve entirely decoupled. And so, there’s seven stocks that are driving the entire market, and 493 that when you aggregate them, they’re cheaper than Europe and Japan or something like that. Maybe not– [crosstalk]
Dan: Right. I think even if you take out Nvidia, the US equity market minus Nvidia has had the same returns as Europe or something like that. That was another chart I saw going around. I haven’t done it myself. Yeah, but again, I think it also comes– It’s troubling for large cap active managers, because it’s one name or a very small number of name. And if you didn’t own them, you’re screwed.
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The Power of Non-Conformity: Lessons from Asch’s Experiments
Tobias: JT, top of the hour. Do you want to [unintelligible [00:29:27] at your veggies? First veggies for the year.
Jake: First veggies of the year, huh? Well, let’s try to set the bar high. All right. Imagine you’re sitting around a table with 10 other people. And a researcher in a white lab coat comes in and he shows you two cards. One with a single line on it and the other with three lines of varying lengths. Your task is very simple. Identify which of the three lines one of the cards matches the length of the single line on the other card. Easy enough, right? If you’re like most people, you’ll get it right about 99% of the time. And if we showed you 12 card pairs in a row, you’d get it right 95% of the time. This really isn’t that hard.
And of course, our 10 audience is quite intelligent, so then they’re rather clever, so they know where we’re going with this. But as you guessed it, everyone else in the room is a plant, a confederate in the experiment. They’re in on it. You’re the only real participant in this. And all of a sudden, the confederates are confidently agreeing on the same incorrect answer. They’re saying the wrong line size and you start doubting yourself. Maybe your vision’s a little blurry that day. What’s actually happening inside your brain is your amygdala is firing like crazy, and you genuinely feel this primordial sense of dread as these lines aren’t making sense.
This was the setup of the Asch conformity experiments, which were conducted by this social psychologist named Solomon Asch. He was actually a real true pioneer of social psychology. Born in 1907, Warsaw, Poland, which was then under the Russian Empire. He grew up in a Jewish family, and he spoke fluently in Polish, Yiddish and English. And at 13 years old, his family immigrated to the US. They settled into New York City. And like many immigrants, he’d adopted this new country and language and way of life, he integrated. He went on to earn a bachelor’s degree from the City College of New York and he later pursued his PhD in psychology at Columbia.
While he was teaching at Swarthmore in the 1950s, he conducted these experiments. They were designed to answer a simple question, “To what extent does social pressure influence an individual’s behavior?” And don’t forget, this was a time not too long after World War II. Everyone was grasping for reasons why there were these horrific war crimes of that period, like how could these seemingly normal people become these murderous savages and what are we all capable of?
So, just to reset our scenario again, this task is straightforward. You identify which of the three lines match on the card. And in the control group, of course, it’s almost error free. And yet, in the experimental group, these confederates were instructed to give the wrong answers. The numbers behind it are relatively staggering. 75% of participants conformed to the majority at least once, giving the wrong answer that the group had also given.
On average, participants conformed about a third of the time. Huge difference from that 5% error rate when they were tackling the test alone. And incredibly, 5% of the participants, so 1 in 20 answered all 12 incorrectly. Now, they all went on to have children who became the crypto community. I’m just kidding. I love you, crypto guys. Send your hate mail to Toby, not to me.
All right. So, humans are a highly imitative species. Okay, this is one of the findings that flows out of this. Mimicry was actually might be one of our superpowers. It’s actually served us quite well in our evolution. So, imagine the skill set that’s required to live in the Amazon rainforest. You need to know how to build blowguns, medicines from plants, fishing for piranhas or something. I don’t know, I’ve never lived there.
And now, think about surviving in the Arctic. You have to be able to build kayaks, and warm clothing, and oil lamps and goggles for snow blindness and dog sleds. Completely different skill sets, and tools necessary for survival. And yet, humans had to adapt in less than 10,000 years as we migrated from the Bering Strait down to the Amazon. So, no animal that we know of could make that quick of an adaptation. Like, how did we do that?
The answer is that we learned to copy each other when one of us had figured out something that was working really well. It’s too hard to reinvent every single wheel by yourself. So, this gave us an incredible adaptability that helped with our survival, but there was a price to be paid, and it’s that we’re wired for credulity. We’re monkey see, monkey do, and there’s safety in the herd. And so, it’s little wonder that we’re so quick and ready to conform when others around us are doing something.
But there is a silver lining to all this, and this is why I chose this segment for when Dan was coming on the show, because I feel like, if anything, he’s one of my favorite non-conformists that’s out there. I still remember a talk that you gave at Capital Camp, Dan, where you– It was like the heresies of every single asset class, [Dan laughs] and you basically just blew everyone up, and it was hilarious.
Dan: Thanks, Jake.
Jake: Yeah. So, you already know these sobering findings of the Asch conformity study, but here’s a part that maybe you should pay attention to and that you might not know about it. 25% of the participants resisted conformity entirely showcasing this power of independence. So, one in four monkeys basically thought for themselves. Okay. But even more encouragingly for everybody, further studies found that having even one dissenting voice in Acsh’s room reduced the conformity by a whopping 80%.
So, it just took one other person who was willing to speak up and say the truth, and that was all of a sudden, people thought for themselves again. It just takes one. So, I’d like to think that this show, maybe I’m being a little hubristic here, but that we make a little bit of a small contribution of one dissenting voice in the room that maybe allows you the confidence to think for yourself. That would make me quite happy to actually believe that we’re providing that public service. I feel very comfortable saying that Dan has been doing this for a long time, and he is one of those voices that is really good at that.
So, there’s an incredible amount of noise in financial markets. There’s a lot of emotion swirling around. It’s an environment that’s ripe for conformity. We see that in every single bubble.
===
Minsky’s Four Conditions for a Bubble: Do They Resonate Today?
Jake: And speaking of bubbles, we’ll wrap up this segment here with a mental model I read about recently, which fits in with a lot of what we were talking about. This is Hyman Minsky’s four necessary conditions for a bubble. I don’t know if you guys have seen this before, but I just recently happened to stumble across it. Tell me if you see any of these four hallmarks in today’s activities around the world.
So, number one. Technological and financial displacement or paradigm shifts which can capture the collective imaginations and drive narratives. Number two, loosening credit as a raw fuel for the system. Number three, amnesia. Each generation has to learn their own lessons the hard way. It’s different this time, is the common mantra. And number four, abandonment of time-honored valuation principles, shifting from profit to revenue to clicks to eyeballs or whatever.
There’s always new math that’s required to see the future. If you don’t get it, then the world has passed you by, you’re a luddite and you’re a bozo who’s stuck in the past. So, those are anything feel like rhymes with those four today that you see in the world?
Tobias: We’ve had the paradigm shift.
Jake: It’s already shifted.
Tobias: Paradigm shifts happen. AI– [crosstalk]
Dan: Listening to all-time low credit spreads.
Tobias: Yeah. The credit spread is credit versus the higher-
Dan: Treasurys.
Tobias: -levered loans versus treasuries?
Dan: Yeah. I like to look at the high yield spreads. High yield relative to treasury restoration matched, which is– There’s actually been research showing the longer spreads stay abnormally low, the greater the risk of a financial crisis, which is basically proving Minsky’s second point.
Jake: Well, stability creates instability,-
Tobias: Instability. Yeah.
Jake: -which is the other big finding that he had.
Tobias: Which makes perfect sense. If you feel like you can borrow without risk to buy assets, of course, you’re going to do that until– [crosstalk]
Dan: Right. And if those assets don’t show any risk or volatility, why you can lever up to buy them?
Tobias: In some sense, that’s what MicroStrategy has been doing with selling debt to buy bitcoin. Bitcoin goes up, lets you borrow more. I don’t see any four in that thesis, whatsoever, that should just keep on working forever.
Jake: Yes.
===
Tobias: Let me give a shoutout to everybody who’s playing home and then–
Jake: Oh, boy, we are way behind schedule.
Tobias: We forgot to do that. Yeah. What’s up, Santo Domingo? Danny Beltran, first in the house. Winter Park, Florida. Warren Buffett from his Winter Park.
Jake: Oh.
Tobias: Toronto. Andhra Pradesh, India. London. Madeira Island, Portugal. Valparaiso. What’s up, Mac? Bellevue. Bremerton. Savonlinna. Always in the house. Bendigo. What’s up? Indiana. Bangalore. Jupiter, Florida. You’ve already won, Sam. Hurricane City. Lanús, Argentina. Mendocino, California. Mississippi. Cincinnati, Vegas. Rockland County. Banana, Queensland. How are you, Les? Longueuil, Québec. Gothenburg, Sweden.
Jake: The 51st state.
[laughter]Tobias: Waterloo, London, Mount Sinai. Helsinki. Sardis, Lydia. Monterrey, Mexico. Nashville, Tennessee. Sorry, I slipped over a whole lot there. I think I can go back. It’s a good spread.
Dan: No one from Greenland?
Tobias: Didn’t see anybody. The 52nd state.
Jake: Panama.
Tobias: Temecula. Sorry, I think I skipped over a whole lot, but good to have everybody here. Dan, do you do any macro as part of your analysis? I vaguely remember that– [crosstalk]
Dan: We do.
===
Speculation Redux: Are We Reliving the 2021 Market Boom?
Tobias: What’s your macro take on the US–?
Jake: That’ll humble you.
Tobias: Yeah.
Dan: Yeah. [laughs] You want my views on AI? Now, you want my views on macro? Oh, dear. I think the situation coming into the year, I think probably the most dramatic thing we’re seeing is in the highly shorted baskets where the true speculative stocks are in a totally nutty environment akin to 2021. I would say, again, we take all of our macro variables that we watch and we look at how distant that set, that vector is to equivalent historical vectors. We can say like how similar is this macroeconomic conditions. This period probably feels most like 2021.
Jake: Back to 2020 already. I probably would have lost a lot of money betting that we wouldn’t see 2021 type of behavior for another– Usually, the amnesia takes longer than that, right?
Dan: Right. But it just feels like we’re exactly back the same speculative boom, the same stock– [crosstalk]
Tobias: And it’s the same stocks too for the most part.
Jake: Some of it is, huh?
Dan: Yeah. In a lot of cases, the same stocks, although also the quantum computing and things like the AI, anything with AI in the name type stuff. So, I think that’s probably one big picture. I think another– [crosstalk]
Jake: Is there any other time periods where it rhymes closely? Like, how far back do your data go?
Dan: We can go back to the 1970s. I think I’d have to look at the longer dated ones. But generally, this looks like a lot of the pre-crash period-
Jake: Like, what you would have suspected.
Dan: -versus very low credit spreads, very low volatility. I think the other thing that you see in credit markets, is that you have this competing thing where both spreads are feeling really tight, and so there’s room for yields to go wider. And then, when you look at treasuries, there’s also fear that inflation might be more persistent than it is, which would mean rates would have room to go higher.
So, I see a lot of downside risk in bonds right now again, which is another 2021-like moment. You don’t know whether it’s from rates or spreads, but gee, it seems like there’s a lot of [crosstalk]
Jake: It feels like the bond market does not agree with the equity market right now quite a bit.
Dan: No. No.
Jake: Even less so treasury, but mortgage rates not come down at all, even though the Fed’s been lowering.
Dan: Right. One of the biggest booms, of course, the last few years has been private credit, which is, of course, all floating rate debt, which is what’s funded the entire buyout wave. And so, [chuckles] you wonder like how can that not be painful right now for all those people that borrowed huge amounts of debt with floating rate terms. That seems scary.
Jake: Yeah. What’s Michael Lewis’ next book going to be about from this time period?
Dan: Right.
Tobias: FARTCOIN?
Dan: Yeah. FARTCOIN.
Jake: What’d you say?
Tobias: FARTCOIN. Emblematic. Yeah, I find it amazing we’ve encountered 2021 behavior again so soon. I don’t know what drives that. Is it the Fed cutting when rates are rising everywhere else? I don’t know.
===
The Casino Mentality in Modern Markets
Dan: I wonder too if it’s not like so many things in life, the presence of cell phones, that it’s just fun to trade.
Jake: Like, activity and gambler.
Dan: People like gambling. Look at FanDuel or DraftKings. People like to gamble, and it turns out you can gamble on the stock market and it turns out that unlike these other markets right now it appears that you can actually make money gambling in the stock market. I think that’s a lot of what’s driving. It’s just fun. People just like it. They enjoy it. They go on their phones, they get a dopamine kick and they hold it or they buy a single day option or they buy, and buy for a month or a week. I think a lot of that is happening.
Jake: I try not to get on soapbox too often, but I’m relatively troubled by this gambling impulse and degenerate gambling that we see– We’ve really normalized it. I think it’s not a credit to our species to allow this kind of behavior. I think Munger would be quite upset with this level of casino like mentality that has crept into anywhere that it can get into.
Dan: Yeah. There’s no question it’s a vice, and I think there’s also no question that probably the people that get addicted to it are the people that can least afford to get addicted to it. And so, I think it’s predatory as well.
Jake: Yeah, there is almost a– You can see a path from a feeling of nihilism that eff it. I might as well try to double down over and over again, because it blows up. It wasn’t going to happen for me anyway, right?
Dan: Right.
Tobias: There’s a bit of a hangover from the poker boom in the early 2000s. That seems to have gone away now. But I remember there was a guy who did a– He did a trek across America after he blew up all of his poker winnings, lost all of his money. And so, to a tone, he had this sign and dragged it across the entirety of America, and it made news for a little while. It was like a–
Jake: Like a Haj? [laughs]
Tobias: Yeah, something like that. So, he would remind himself. I wonder what that guy’s doing now. He’s probably–
Dan: He’s now on Robinhood.
Tobias: He’s got a lot of FARTCOIN.
[laughter]Jake: I’m back, baby.
Dan: His P&L was up 200% last year.
Tobias: Yeah.
Jake: Yeah, he crushed everybody.
Tobias: 200%, that wouldn’t even register. People are thousands of percent. It cuts both ways though.
Jake: You are seeing the victory lap tweets are back, right?
Tobias: Yeah, portfolio. It’s my portfolio.
Jake: That’s usually not a good sign. It got quiet in 2022, and now it’s back in 2024 and 2025.
===
Dan: It’s also amazing to loop back to us talking about the value factor earlier. If you chart the US value factor and then mark where ChatGPT was released, it’s remarkable.
Jake: That’s what it totally turned it back around.
Dan: Oh, yeah. Oh, yeah.
Jake: Amazing.
Tobias: I felt it happen in real time. That was like early 2024, February 2024, something like that.
Dan: Yeah. There was a period where in 2021 and 2022, value investors were kings again. And then, ChatGPT comes out.
Jake: All of Toby’s journal entries start getting pretty dark again.
[laughter]Dan: Exactly.
Tobias: My Journalytic entries.
Jake: There you go.
Dan: [laughs]
Tobias: I’m starting to become like the Ted Kaczynski.
Jake: Yeah.
Tobias: That manifesto is making a lot of sense anyway. Whatever gets the value factor working. I’m interested in how you construct your macro–
Jake: Sorry to cut off your macro stuff.
Tobias: Dan, because you come at it from the perspective of– Well, you’ve got this humble investor approach to it prior to–
Jake: Maybe talk about de-payment a little bit, Dan.
===
Optimizing Portfolios with Multi-Asset Risk Models and Volatility Insights
Dan: Yeah. So, it’s interesting. We’ve spent a huge amount of time. So, I’d say the starting point on a lot of our macro stuff comes from risk models of the type that Barra and Bloomberg build. And so, I think the first step you want is to explain historical returns or can you explain historical returns. It turns out that using– Let’s start with equities. You use equity factors. It’s called their 10 or so style factors. Size, value, profitability, momentum, etc., and then there are the sector and region factors, and a well calibrated risk model can explain called 30% to 40% of day-to-day vol and then the rest is idiosyncratic to the individual stocks.
But if you own a diversified portfolio, you can reduce that idiosyncratic fall, so a larger share of your P&L is coming from the common risk factors. And so, what we did is basically take this giant risk model, you use it to explain returns, you’re scoring every stock every day on its risk factors and you’re running all these regressions to try to understand what’s explaining returns and then you try to then forecast returns and you say, “Hey, can I forecast the value factor? Can I forecast the quality factor? Can I forecast the momentum factor?”
And then, say for 85% of those factors, you can’t make a– The forecast isn’t time varying is a better way of putting it. So, for example, with stocks and bonds. We can say that the average return for stocks is X and the average return for bonds is less than X. We know that with a fairly high degree of confidence, but we don’t know whether tomorrow the return of stocks is going to be higher or lower than the long-term average or whether the long-term return for bonds is higher or lower. So, 75%, 80% of these factors, you have to just take the long run average, and then there’s maybe 20% or 25% where there are time varying.
Size factor, for example, is very driven by high yield spreads. So, when spreads are widening, size tends to do horribly. And when spreads are tightening, it tends to really well. So, there are those sorts of relationships. You can basically then take these big factor models and your ability to predict the returns in those factor models and you can try to sort and predict the returns for individual stocks. This is just classic factor investing, but with a lot of factors.
You realize that you can predict returns, but with a very low R-squared that it’s really hard. It looks like a scatter plot. If you sort it into deciles, yes, you’ll be able to rank, but it’s very, very rough and the R-squared is very low. However, what it turns out is that if you want to then predict volatility and Sharpe ratios are return divided by risks and volatility matters. A lot of value investors say, “Oh, volatility doesn’t matter. All I care about is returns.” But if you care about returns, you actually do care about volatility.
The reason why is this concept of volatility drag, if you have something that goes down 10 and then up 10, you’ve lost a dollar. And if you have it go down 20 and up 20, you’ve lost $4. And if you have it go down 30 and up 30, you’ve lost $9, so your volatility drag is at the square of your volatility. So, the more volatile things are, you square that. So, that drag is exponential. It’s really problematic. So, you do actually want to reduce your vol for the same return.
It turns out you can predict volatility with about 40% R-squared. It’s actually, fairly predictable, because it’s autocorrelated. Last month’s volume predicts next month, so you take the option market data and you can predict it even better. And even if you have say 5% R-squared on prediction of returns, but a 40% prediction on volatility, your prediction of Sharpe ratios is actually closer to 40% than 5%.
And so, what that leads you to do, therefore, if you think multi asset, you can say, “Okay, if I have the equity market and I know it’s going to return on average 1% a month, and I know that next month is a 10% vol month and this other month is a 20% vol month, well, I should have twice as much money or four times as much money in the market during the 10% vol month as the 20% vol month, because my Sharpe ratio is so much better and vol drag so much lower.”
I think then the next step is to say, if I’m not just betting on the stock market but rather on all these individual factors on value, on momentum, on quality, and if I can then go multi asset and also include gold or the Swiss franc or the yen, and I can go long and I can go short. You have even a long-term average type return forecast, a decent volatility forecast, but then if you know the correlation structure, you can build quite interesting portfolios, because correlations are even easier to predict in volatility.
And so, you can then build quite interesting portfolios, not making some arrogant, “I know that Nvidia is going to do well next month.” But just simply saying, “Gee, recently, bonds and stocks have been more correlated than they are normally, and therefore my portfolio should be tilted next way, maybe I should be shorting bonds or as a hedge against equities,” or something like that, which is not based on a return prediction, but it’s based on your model understanding the volatility and correlation structure much better. So, that’s really what I’ve been focused on from a macro perspective and not return prediction, but rather portfolio construction and portfolio optimization using sophisticated risk models. So, that’s been my project.
Jake: Does vol tend to cluster in every asset class?
Dan: Yes. Yes. It’s autocorrelated everywhere, which is quite cool. The thing I also like about that, is that it doesn’t defy efficient market theory in any way, volatility being autocorrelated or your ability to predict correlations. Efficient market theory doesn’t say anything about that. In fact, it praises diversification. But if something is 90% correlated, it’s not that diversifying, and so it’s logical that an asset is more valuable to you the more diversifying it is. And so, why shouldn’t we seriously measure correlations and include that thinking.
Now, if you’re equity only, none of this matters as much, because all equities have roughly the same vol. Obviously, there’s a spread, but you’re in the same realm. The same with correlations. They’re also highly correlated. Portfolio optimization within equities is not as impactful as if you go multi asset. That’s where macro means to me is saying, “Wow, when you add an uncorrelated asset class like bonds or Treasurys or gold or the Swiss franc into a multi asset portfolio. That’s macro to me. And that is just expanding the aperture of the things that you can do. And the more your ability to diversify, as long as you have somewhat of a good risk model, is going to improve your Sharpe ratio.
===
Systematic Macro vs. Cowboy Macro
Tobias: I’ve got two questions. One is, when you aggregate that up, can you look at another macro investor’s portfolio to the extent that those things are disclosed and say, “Well, I have an idea how they’re generating their– Like, I know what their thought process is, I know how they’re doing it. Is anybody doing it similarly to the way you guys are doing it?
Dan: That’s an interesting question. I don’t know, I think we wrote this piece recently about the pod shops, the citadels and millenniums of the world. I’d say what we have in common with them is their obsessive focus on risk models, because one thing we know about the pod shops is they’re all running market neutral and factor neutral. And to do that means they’re not letting an individual PM say, “I’m the value PM and I load up on the value factor.” That PM has to be value neutral. So, it can only be incremental alpha.
Jake: Plus, all those [unintelligible [00:54:44] got fired along the way a long time ago.
Dan: Exactly. But that’s got to mean that the risk model is at the center of all their decision making at all times. And so, I think there’s an analogy there. But I think for most macro investors I know, the systematic ones tend to be more event focused and the discretionary ones are all cowboys. So, I don’t know if there’s a good analogy.
Tobias: Yeah. I went to a macro conference with a friend of mine, Chris Cole, a long time ago now. I’d never done anything macro. I sat in the room and I just heard pitch after pitch after pitch for special situations, like here’s Turkish Central Bank’s going to do something and this is what we think the leader is going to do or something like that. I had no idea. I thought macro was more systematic than that, and it was clearly like a real cowboy convention.
Dan: Oh, yeah.
Jake: Everybody’s George Soros– [crosstalk]
Dan: Yeah. [crosstalk] lifestyle.
Tobias: They love those stories where somebody gets on a plane and flies somewhere else and the position’s moved against them X amount while they’re in the plane, they just get in, they land and then double down on their phone. That’s great. That’s what you want to hear is happening with your money.
Dan: I know. You get these great– I was in a meeting with the Taiwanese Central Bank last Tuesday and like, “Okay. Great. How can I compete with that?”
===
Gold in Modern Portfolios: A Quantitative Perspective
Tobias: There was a question in our comment stream about gold. I don’t know if you’ve said something about gold or– They wanted your opinion on gold. And so, you raised it. Do you tease them out individually? Do you have a view?
Dan: Obviously, gold’s been a huge winner of late. Our models have liked gold quite a bit, because its lack of correlation, especially when stocks and bonds get very highly correlated and you need a safe asset. Gold is the natural choice. And so, I think what you’ve seen over the last few years as stock and bond correlations have risen as more money is flowing into gold and that’s pushed gold prices up, gold volatility has been relatively muted. So, on all from a quantitative perspective, gold looks like a very attractive asset. But gold is also, again– We have no ability to predict returns. I can only tell you about its value to a portfolio which right now is meaningfully higher than normal.
Tobias: Yeah. So, it’s not valuation. It’s anti correlation properties to the rest of the portfolio.
Jake: Valuation? How do you get to any valuation for gold?
Tobias: How do you value bitcoin?
Dan: Well, actually, what you don’t realize, Jake, is that denominated in bitcoin, gold is approaching its cheapest levels ever.
Jake: Total loser. Yeah.
Tobias: [laughs]
Jake: Every asset is, right?
Dan: [laughs]
Jake: Did you try putting bitcoin into your models and just smoke starts coming out of your computer or what–
Dan: Yeah, exactly. Well, actually, what’s interesting about bitcoin, is that it’s very correlated with highly shorted stocks. So, the highest correlation you see with bitcoin is with a certain segment of very small, very growthy stocks.
Jake: Shitco. Is that the term you were looking for?
Dan: Yeah, the polite term for them. So, it actually is not as diversifying as you might think. People are buying it for the same reason they buy a quantum computing stock.
Jake: Because it goes up into the right? [crosstalk]
===
Tobias: Hey, Dan, we’ve got a couple of minutes left. Do you want to just remind us again– The name of your new book is The Humble Investor. [crosstalk]
Jake: Give us one more good pitch. Yeah.
Dan: Yes. So, The Humble Investor is my new book. It’s my greatest hits from my weekly research along with a bunch of new stuff. It comes out February 4th. Its available anywhere books are sold. Yeah, pre-order now. If you want to help me game the New York Times Bestseller list, buy it from an independent bookstore. [chuckles] But it’s also available from Amazon.com.
Tobias: Somebody says that one of your degrees is a little bit not quite hung straight. So, you just get the intern in with the bubble.
Dan: Yeah. So, I’m going to have to fire our office manager. If only we had one, they’d be fired.
Jake: [laughs]
Tobias: If folks want to follow along with what you’re doing or get in contact, what’s the best way of doing that?
Dan: I’m on twitter, @verdadcap. Website, www.verdadcap.com. You can sign up for our email list. It goes out every week on Mondays. Follow us on Twitter. But thank you for having me. And of course, buy the book.
Jake: Signed up for the weekly updates. I read them regularly. There are tons of good research that’s just always coming out. You guys are quite the research factory. So, it’s all good stuff.
Dan: Thank you, Jake. And thank you, Toby. Thank you for having me on.
Tobias: Pleasure. JT, any last words?
Jake: 2025 New Year, let’s have a better year than we did last year and everybody be kind to each other.
Tobias: A wise man said to me, “Whatever happens in the markets, let it be a good year anyway.” So, I like that sentiment. That was JT, just in case anybody–
Dan: [laughs]
Jake: Did I? I don’t– [crosstalk]
Tobias: He just talking me down off the edge. So, I said, let’s hope it’s a good year for value. He’s like, “Ah, don’t worry about that.” All right, folks. We’ll see everybody next week, same time, same bat channel. We’ve got Jim O’Shaughnessy, and then we’ve got Ian–
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