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Excess Returns
30 Times Earnings Isn't Expensive | Chris Mayer & Robert Hagstrom on the Labels That Destroy Returns
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We are excited to announce the launch of a new podcast, the Hundred Year Thinkers. In a world where most investors think in quarters, this new show offers insights from investors who think in decades. Hosted by Matt Ziegler and Bogomil Baranowski and featuring Chris Mayer and Robert Hagstrom, this monthly roundtable will tackle many of the issues that all of us face as investors, but look at them through the lens of investors who operate over very long timeframes. We have included this episode in the Excess Returns feed, but if you want to keep receiving new episodes, you can subscribe to the 100 Year Thinkers on all major podcast platforms or our YouTube channel. Thank you for listening. We'll hope you enjoy the new show.
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E
30 times earnings is not, it's not expensive. It's not overvalued. Even Warren said this. He goes you can buy a high multiple stock, much higher than the market multiple, if you've got a pretty good deal of confidence that they can maintain a high return on invested capital for five or 10 years. If a company's earning, I don't know, 25, 50% return on invested capital, go ahead and pay 30 times earnings.
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A
We use income statements and balance sheets and cash flow statements. Those are our maps. But what are the reality that they really reflect? There's actually a business behind it with people and customers.
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E
What I like about Google and AWS and Microsoft thus far is that they're doing it in cash flow. If AI went away tomorrow, yes, Microsoft would get hurt. Google would hurt, you know, Amazon would get hurt. They'll still be in business tomorrow.
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A
So people say a company is a compounder and really, you know what we're saying is what we should. If we wanted to be more honest about it, we would just say something like a company. You know, it seems to have compounded capital well in the past under certain conditions. Right. It's not, it's not a thing. It's an ongoing process.
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You're watching Excess Returns. I'm Matt Zigler. Bogumill Baranowski is with me. This is the Hundred Year Thinkers. We've got Robert Hagstrom in the seat along with Chris Mayer. And let's be honest, Chris wrote this book. It's called General Semantics. It doesn't sound like an investing book, but it's, it's an all of life book and it's definitely an investing book, which is why we're going to unpack some of this today. The idea is it's basically a, it's a framework that goes all the way back to the 30s. Chris, you're going to correct me when I'm wrong on this, but it's about how our language shapes our reality now in the world of narratives, in the world of markets, in the world of thinking about how we assess companies, and companies communicate back to us, their peers, their competitors in the nine. If you don't already understand that language shapes reality, let us try to catch you up to speed with this one. So we're going to take Chris's thinking, but we also have Robert Hagstrom in this too because he's built a career on mental models, cross disciplinary thinking and all sorts of ways that these philosophies just go like this. Which is why Bogovil and I are so excited to be slies on the wall with you in the audience for this one. So, Chris, I'm starting here because it's my favorite word from this whole body of work. Tell me what a time binder is. Let's just start there and then we'll move it into investing.
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A
Yeah, so a time binder was. A time binder is a human being. It's Korzypski's word for human beings. And the reason he used that is because he thought that time binding reflected our unique ability to human beings. And what that is, is time binding is our ability to accumulate knowledge across generations. You know, add to it, pass it on. So it's like, you know, we are, we inherit this treasury of the past, this knowledge from everyone is before us, and then we can add to it and, and carry it forward. So it's why we can, you know, we don't have to learn to build computers from Scratch. We don't have to learn how to build houses from scratch or bicycles from scratch or whatever it is because we've built this accumulated knowledge that we continue to pass on. So it's why we can read, you know, Einstein and Darwin and Plato and all this, that that's the essential feature of, of what time binding is all about. So you might say that, you know, a big difference between us and human beings 500 years ago is that we benefit from 500 years of time binding. So that, that's kind of the essence, that really is the essence of the idea. And for Krasybski, who was the guy who created this dilemma of general semantics, that was his way, it was his thought about what was unique about human beings.
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F
I read this idea that more people are reading some of the ancient wise people today that were people are reading those works of, you know, those books at the time, like Plato, which is mind boggling to think that more people are reading Plato today than had exposure to him at the time. I think that's what I'm trying to say. Yeah, but. Right. Isn't it fascinating that he's now no longer of course around, but we can still experience it. I want to ask you about market concentration, time binding. There are certain moments in time when the s and P500 had very few stocks represent 30% and actually people think that it hasn't happened before. I looked up somewhere in the 60s, 50s, it was the case. Can you do a time binding experiment with us here? What does it mean? What can we learn from the past on that front?
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Yeah.
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So first, you know, think about it. You know, what does it mean when we say the S and P is concentrated? What we're really saying is that there's one group of firms that have vastly outperformed the rest over some stretch of time. And so they, they have become a much larger part of the weight. So it doesn't necessarily say anything about what will happen next. Although history does tend to show that you have these concentrations kind of in late cycle markets, but you can also have concentration in perfectly fine markets and these conditions can persist for years. So it's not really, I wouldn't use it in any sort of timing mechanism, but I think if we were to think about it more in terms of, you know, general semantics type thinking, we might re recast that question a little bit. So instead of saying, you know, is concentration somehow a warning sign? We might say something like, you know, what assumptions have to remain true for this concentration be justified. And so for that Then you would look at, you know, this particular merits of the case today. So what are, you know, the particular companies today at this particular time, are they worth investing or not? Are they going to be able to maintain their growth and their margins and their capital discipline and, and all that sort of thing. So I think it sort of, you know, thinking in this general semantics framework would maybe change the nature of that question a little bit. And I'm not saying those are necessarily easier questions to ask, but that sort of brings the abstraction level down because now we're not talking about just as the index too concentrated and that a bad thing we're looking about, well, why is it concentrated? These firms are the ones that have made it concentrated. And can those firms continue to perform the way they have performed?
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Robert, in your work with all the mental model focus, I'm curious a time binding and the work that Chris is highlighting just as a concept, as a mental model and then tie that through to what he just said about concentration in markets from your perspective.
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Yeah, I'm not sure I can attack it from Chris's framework, but maybe if I speak, Chris can lasso me back in. But I find this whole argument about concentration to be at sometimes silly and sometimes we don't recognize that really this is the fault of the s and P500 committee who decided to do a market cap weighted index. You got nine people on that committee that make decisions about what goes in and out of them s and P 500 and, and, and they assign weights or they basically we get. And they, and this committee can make changes, right? They, they can just say no, Nvidia doesn't need to be 8%, it can be 4% because you know, you get that Russell does that Russell makes changes on their index, MSCI makes changes on their index. But S and P is one of the few that I can recall that actually don't change the weights in their market cap indices. So I think, you know, I propose the question which is if there was no market cap indices and we just had equal weight indices, will we even be having this conversation which would. Right. You know, it'd be an equal weight S&P 500, and we wouldn't be all aghast that, you know, Nvidia because Nvidia still would have performed well last year and you know, the Mag 7, whatever the case may be, but it wouldn't be such a topic of conversation. So what you get down to is separate market cap and, and all that stuff is are the stocks overvalued? Are they not, you know, I don't care if you're 8% of the S&P 500 or you're 1% of the S&P 500, you should be still making the same decision, which is, are you undervalued, you're overvalued, and you know, what are your thoughts about competitive advantage?
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Period?
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And when you do that, you know, the whole idea of this market capitalization sometimes, you know, gets distilled down into something that's really not important to me other than the fact that other than the fact that there are enough people talking about it, they're going to make decisions about stocks to buy and sell, not so much about the economic returns of those business, but, but because they're a big part of the index. And we look back in history and know when things get so concentrated in the s and P500, that's probably the time to ring the bell and move on. You know, that's a decision that investors makes. But at the end of the day, whether you're 8% or 1%, you got to figure out if it's overvalued or undervalued. And, and to me, that's what I spend the most time on. I just spend most time, you know, what, what are you worth and what's the stock price? And let's go from there now. You know, there are a lot of other people that would disagree with me on that, but that's just how personally, you know, I attack it.
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F
I think it's a great reminder that the benchmarks are man made, they're not God given. And it leads me to the another question for Chris, the map and the territory. Because the benchmark was supposed to help us observe something, and now it became a guidance, a guide or maybe even an expectation of where things should be or how much we should own of certain stocks. So can you explain the concept of map of the map not being the territory?
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Yeah, map is not the territory. Korzybski didn't come up with that phrase, but he popularized it. And it, it's how we confuse our maps with the underlying reality. So another one I like is the menu is not the meal. So, you know, it's the same concept, but what does that mean practically as investors? So there's lots of things, I think, where we confuse our maps with reality. So as investors, we use income statements and balance sheets and cash flow statements. Those are our maps. But what are the reality that they really, you know, reflect there's actually a business behind it with people and Customers and you know, there's, there's that customer, that business has a culture and there's pricing power and there's competitive pressures and there's all these sorts of things. So I'll give you an example where we can get confused. If you look at the map and you, you might say a business has sales went up 20% and their margins expanded and ROIC is great. So business is healthy and it's doing well. But then when you really get into it, really why did revenues go up? I mean it might have been that a bunch of sales were pulled forward for some reason or why did margins go up? Well, maybe they under invested in, you know, R and D or maintenance or maybe they cut people in an unsustainable way. You know. And ROIC can be affected by all kinds of accounting treatment. So that's an example where you're again, we're losing sight. We're focusing too much on the map. We're losing sight of what it really reflects. There are a lot of other examples. My favorite always comes down to valuation. When people say something like stock is cheap because it trades at, you know, X times free cash flow or it's expensive because it trades at X times free cash flow. And again there's a lot that's being ignored in that basic map. You know, you're not, what, what are we really looking at? You know, it ignores things like capital intensity, it ignores leverage, it ignores a bunch of real world world facts, factors. Most of the time I think comes valuation questions come down the time horizon. But I think we'll talk a little more about that later. But other ways, I mean any kind of back testing is always, you know, one place where people can confuse maps with territories, risk measures using things like beta or volatility and, and losing sight of something like, you know, permanent capital loss was what we're really worried about. So those are, you know, some examples of confusing map and territory. But that's the basic idea.
- [13:47]
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And a free professional measure happening right now@blinds.com. robert, what about you? Map and Territory is something that you've talked about directly and indirectly quite a bit.
- [14:53]
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Yeah.
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Add to Chris's point.
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E
Yeah, well, now I think, you know, this reminds me of a book that, that we read at like Mason. We had a book club that, that Bill Miller started with Michael Mobison way back when and when Michael was with us. And we read a book by John Lewis Gaddis know, called the Landscape of History. How, you know, history, how historians map the past. Right? And so this dogtails right into Chris's point about general semantics and other things, which is, you know, people write history, but, you know, these are people, right? And they're coming up with their descriptions of what they thought happened, you know, to, to. To offer an explanation. But as Chris's work, you know, rightly points out, you know, there's lots of different ways that you can describe something, right? And the words you choose and how you think about it. So, you know, we have a tendency to think that, you know, history is, you know, etched in stone on the temple Pilate at the top of the mountain. But there could have been a couple of different other interpretations of what happened in history. And John Lewis Gaddis book, you know, points out that, you know, historians write it, but. And sometimes it's the loudest historian or it's the historian that had a lucky break and had a good book or whatever the case may be. But, you know, this is not. The finger comes down, you know, from the cloud and God says, this is what happened. You know, these are, these are all fallible interpretations of what happened. But, you know, we got to move on, you know, and people latch on to what the general description is. But I'm repeating myself. But Chris's work points out how perilous we are and it can become when we start getting into descriptions to form the explanation. Because when we look back and look at all the errors that we made in explaining, Chris would agree, you know, nine times out of 10, we had the wrong description because we use the wrong words. So, you know, here we are.
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Yeah. I mean, that's why, like, history has to be rewritten every now and then. It's generation. Every generation brings its own, you know, tools and things. And so you could take any event like American Revolution, you can tell it through five different lenses or maybe a dozen different lenses. You know, you could tell it from the one political point of view, a libertarian point of view. You could tell it from a. Yeah, more Karl Marx clacks, you know, class point of view. I mean, there's lots of ways to tell the story. So that's why it's, you know, the new biographies come out all the time. And how many biographies are written about certain famous figures? And again, same updating is going on. Different things are being emphasized. So, yeah, when. You know, Kipski, this is one of the things too. People say history never changes, of course, changes all the time.
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You know, to Chris's point, it reminds me of listening to Ken Burns, and maybe it was a couple weeks ago, but he's got a new, you know, history documentary on, on, because Chris mentioned it. The American Revolutionary War. It's totally different than anything that I ever read about the American. And I'm going, well, that was 250 years ago. I mean, where did you come up with this? Here's an, you know, here's a historian who's basically come up with a different description about what happened during the American Revolutionary War that I never read in high school, I never read in college, and I don't remember from my, you know, having thought about that, that, that things like the treatment of indigenous people and slavery and other things that were going on were big deals back then. But they, they didn't quite get the light in the book that we were, you know, told to read about the American Revolutionary War. So Chris's point is, right. We're rewriting the American Revolutionary history right now with Ken Burns. Can you believe that? How many times have we done that?
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F
So many thoughts come to mind, and they're random, but I was thinking of Ramses ii, the Pharaoh. I read about him years ago, and they show different pictures of a battle from the early days of his rule. And the battle of Kadesh, that was apparently a pretty even battle with a peace treaty. But by the time he got older, and I think he was the longest ruling pharaoh for a lot of history, the battle became a bigger and bigger success. So by the time he was an old, old dying king, this was the biggest success of his lifetime. Depicted on the Walls of the temples. Which makes you think, you don't have to wait 250 years to rewrite history. History gets rewritten sometimes in a day, but I don't want to get too political about it. But Anyways, fast forward 3500 years, AI, we're looking at it, we're observing it. And I feel like I have the same sense that Chris was talking about the map and the territory. Huge investments, hundreds of billions of dollars. What are the business models? How do we make money? I feel like I'm trying to connect the dots on both ends. Chris, how do you look at it?
- [19:35]
A
Yeah, I mean, it is a map, territory thing, because these people are using these words to carry a lot of freight, Right. So AI covers a lot of things. So, for example, if you look like software, I think probably there's few sectors that are more hated right now, I think, than software generally. Looking at stock prices of a number of different software companies, because there's this narrative that AI is just going to destroy software. It's very general. But if we were to break it down again using more of these tools of Kimski's, we would have to think about individually. Well, what do we mean when we're talking about AI? And of course, there's lots of different things. We'd have to think about how it was going to be used and how it's going to roll out and which company is going to affect. And it's not going to. You know, it's not just this blanket thing that's going to happen instantaneously. And those large companies that are spending so much money on it, you have those large, huge gobs of money. It's hard to imagine a reasonable return on that capital. In some ways, the companies involved are in kind of a classic prisoner's dilemma, because they have to. They can't afford to not be involved or they'll just get passed. But not all of them are going to be able to recoup that investment. So it'll be really interesting to see how it plays out. And so the way I look at it is the same way I would look at anything else. You know, just sort of start to break it down into its little parts and pieces. So all of software is not created equal. There's lots of different kinds of software. You know, vertical market software is very different than horizontal market software, for example. And those companies are going to be using the AI tools themselves. So then you start thinking about, well, where is it going to impact specifically, you know, is it going to impact the Union economics of the businesses. Is this going to change switching costs? Is it going to affect retention? And so you start to break it down that way. And I think you get a more nuanced picture than just saying, you know, AI is going to destroy a lot of software companies or, or the AI itself is going to be, you know, a boon as an investment.
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B
Makes me think of that if software is eating the world thing, it's like, you know, you're in the world, right? Like it's, it's, it's eating. Yeah, you have to think about this from different directions, Robert, inside of this too, because you've thought so much about growth and just the delusions of crowds as we move forward in time. How are you making sense of this?
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E
Well, you know, I would, you know, I have to take a nod to Bill Miller. It was nice to be sitting by his side in 1995 and 94, 93, when he started buying Dell computer and added AOL and stuff like that. So here was a value guy that got early in tech and you know, that was the beginning of the great 15 year track record. It's amazing to me though, people don't think about this too much, but Bill outperformed the market with those tech investments because he re weighted them, reweighted them. Importantly in 2000, he outperformed the market. In 2001, he outperformed the market. In 2002 he outperformed the market and all they did was complain about that. He was not a value investor in 1997 owning Dell and he wasn't a value investor owning, you know, AOL and stuff like that. And so, you know, you, you're, you know, you, you've done a terrible job. Now he still owned them in 2000, but he just reweighted them because the risk reward at the price and economics were such that it didn't, you know, deserve to have, you know, 8%, 10%, 15% bets. He pulled that.
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B
So you're saying that, you're saying that the value investor title is not the track record. Is that what I'm hearing here?
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E
In the end of the day, we're supposed to all be value investors, whether you're buying slow growing companies or rapidly growing companies, you know, whatever the case may be. So, you know, one book that had a huge influence on me that, that we read in book club was Carla Paredes book called Technology Revolutions in Capital Markets. And she goes back, you know, to the water wheel and then we, you know, we go to, you know, the Manchester, you know, railway system and then we went into steel mills and we went into the automobile business. And you know, you go on and on and on through all of these technological revolutions and every single one of them up through the dot com, every single one of them had a bubble episode at the end. And so you'd have to say with this AI, there's going to be, you know, some problems here in the end. And I, and I think it comes down to there will be a lot of things that get funded, as Chris pointed out, and get market caps that aren't going to get that rate of return. And that happened during the dot com period. I mean we did sock puppets, we did all kinds of stupid things and they never grew into that valuation. Right. And, and so when the market gave back, you know, it was a pretty good get back. Now my, my, you know, issue with AI today and thinking about bubble is when I look at the, you know, let's look at the market concentration. Take Tesla out. Okay, I'm not doing Tesla. You know, I don't, I don't understand the market's infatuation with that company. It is a car company, guys. I don't, you know, here's a perfect. I don't know how many times people redescribe Tesla. And I say, you know, Tesla's an auto. No it's not, Robert. It's a technology company. Okay, so what are we talking about here? Well, you know, they, they know all the miles you do and how you drive. They're going to sell that to insurance companies, they're going to have their own insurance company, blah, blah, blah. Okay, okay, well that's never happened. Right. So no, it's not a technology company now. It's an autonomous vehicle company. Oh, okay, well how's that working out? Well, we still got a driver sitting in the seat of Teslas in Austin. Okay. That, you know. Okay, so where are we going with all this? So as a side, there's a bad description of Tesla going on with people trying to justify the market cap. But if you absolutely look at the economics of Google today, Nvidia today, Microsoft today, just look at the market value, look at the earnings, do a reasonable, I'm not saying they're growing at 50 to 60% per year, but if you said, hey, I think they can do 15% for five years, maybe they do 12% from 5 to 10 and after 10, maybe they do, you know, the normal, you know, 7, 8, 9% earnings growth that the S and P does. They're not overvalued. They're not overvalued. So, you know, I get it that in, you know, we got an S and p market cap, 30% weighting, we've got a tech situation that ends in bubbles. You know, there are some things that are in bubbles, there are some things that are not in bubbles. The thing that I'm wrestling with, Chris, is, you know, the market is not very discriminating when it wants to sell out a perceived bubble. It's going to take the good guys and the bad guys down at the same rate. And that's tricky. That's the tricky part because when Tesla craters or app loving craters or Palantir creators, all great companies, but wildly overvalued in my interpretation, you know, the Googles are going to go down too. The Dell computers are going to go down too at 15 times earnings and those stocks will go down too, although I don't perceive them to be overvalued. That's just, you know, that's the business that we're in. So I don't know how to think about that. Chris. Sometimes.
- [26:39]
A
Well, I'm tempted to roll into the, to talk about the discussion about is.
- [26:46]
F
So let's, let's do that. General semantics. The use of the verb is how do you think about it? Such an innocent word, right? But it's not.
- [26:53]
A
Well, yeah, Korzytski. Yeah, he flagged this as a problem because he thought that people use the word is and then they sort of snuggle in or smuggle in, I should say, not snuggle, smuggle in a lot of hidden assumptions about that. That word that that then may pass unexamined. So again, I think, I think it's good. Probably talk about example. So you say something like. And if you say, you know a business, business is risky, you're kind of treating it like it's an attribute of the business. Like, like a, like you would talk about something that has a color or something has a weight instead of saying, you know, thinking about the relationship or what risk means. So you're talking about the business versus maybe the price you pay for it versus maybe, you know, the balance sheet, is it highly leveraged or not versus time horizon. So you might say, you know, again, speaking in a general semantics way, you probably drop the is entirely and just say something like, you know, the business seems risky to me because it's highly leveraged or something like that. Rather than just say it is that so that's number one. Is it? Using is in that sense sort of collapses your description into the identity as if it's bound together like it's a. Like it's an attribute. The other thing that's interesting is that, you know, they can hide, hide certain assumptions. So when we say a stock is cheap, you know, again, Korzypski would flag, that is for me, when I hear it, I always want to have a question, you know, like, stock is cheap, cheap relative to what? You know, what do you mean? Or this is a great business, you know. Well, great in what sense? You know, what was it great for? Or we say this is a bad industry. And I say, well, you know, is it always a bad industry, I mean, or what? So again, you know, the way Kipski General Semanic teaches this is anytime you hear that word is, you sort of pops, you know, ask a little question about it as a flag. And I find myself, even when I use it, I'll think, my brain will think, oh, you really mean seems, you know, it's what you're saying you seems to be or something. And then the last kind of example I'll mention is, and this because it's interesting because in investing, the way we talk, we have a lot of verbs that are just like pretending to be nouns kind of thing going on. So people say a company is a compounder. And really, you know, what we're, what we're saying is, well, we should, if we wanted to be more honest about it, we would just say something like a company, you know, it seems to have compounded capital well in the past under certain conditions. Right? It's not, it's not a thing. It's an ongoing process. And that process can strengthen over time. It can weaken over time. Depends on the investment opportunity. So if you say something is a compounder, you're again, you're treating it like it's melded together, like it's some attribute inherent in the company. That's not what's happened. When you really mean, when you're saying that is that to this point in some period in the past, it has compounded capital well, but again, under certain conditions, and that will prevent you hopefully this is the idea of this kind of thinking. It'll at least make you think about is that also true in the future, what sort of conditions? And so you won't say that anymore. You'll say capital seems to be good compounder. So those are some ways I think that you flag is and. And brings up questions to ask after.
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E
You know what? I knew I was going to learn something from this. And let me tell you something, this whole hour is got is going to be worth me now saying from now on. Nvidia seems to be. That's my word for the day. Reformed man.
- [31:26]
B
A reformed man.
- [31:28]
E
I love it. You're absolutely correct. And Chris said something very, very important, which is context dependent. Right. You've got to get the context right. So. And when you say seems, you can kind of begin to describe your context of it, but he's 100% correct. We use that damn word is as if it is chiseled in marble. And this is what it is. And that probably opens you up for mistakes and errors and, you know, over, you know, overconfidence and all the things that we know we get wrong. Seems is my word of the day. I'm going to put it on my computer and I'm going to put it on a card up here and I'm going to use instead of is. So thank you for this, our podcast. I learned something really very important.
- [32:14]
F
I think we all did.
- [32:16]
B
All right, I want to actually jump from is to, because this is related. This is dating and indexing. And I don't mean dating on match.com I mean actually putting dates on these things, which is part of the nuance that you just referenced, Robert, which I think is really important. So Chris Korzybski's dating and indexing. An example might be Apple or Nvidia or whatever. Today is not Apple or Nvidia or whatever from 10 years ago. And that, that little thing that the stream that you step in is never the same stream in a really eloquent way here in Korzybski's work and the way you just.
- [32:54]
E
Eric Lidis. Yep.
- [32:55]
B
Yeah, yeah, tell us, tell, tell us what dating and indexing is in this framework.
- [33:00]
A
Yeah, so again, this comes from Kybski thinking about how we treat things like they are unchanging. And so we have these identities when we talk about, you know, like you mentioned Apple today is a lot different than Apple 20 years ago. Different products, different companies, different competitive set. So what Krasimski suggested you do, at least initially, and this is why I did do this initially, but then I now I just mentally do it. It was. You just put a date by it. So you say Apple subscript 2025. So you know, you're talking about Apple now. And when you're. And versus Apple in 2015, you know, so you actually put a little date by your assumption that keeps reminding you that your view of that company is a point in time view. And it might be different next year or two years from now or maybe different two or three years ago. That works for people too. You see people do it all the time. And even like in academics or like when they talk about a certain thinker, they'll say, you know, Albert Einstein thought X, but, you know, he thought X at a certain point in his career when he was younger, he didn't think that, you know, so if you put a little date alpha, you know, Albert Einstein in 1936 thought this in 1945. Whatever, whatever. The thing is. So that's, that's the date part and the index is similar, but it applies to things within a class. So if we say, like we talking about earlier, all software companies are not the same. So you'd say, if you were talking about software, you would say, you know, software one, because in your mind that reminds you that there's lots of different companies and different things that have that software label. So software company one is not equal to software company two. Or when Robert was talking about, you know, car companies, obviously Tesla, car company one, it's not equal to car company two, which may be. We're talking about Ferrari or Ford. They're very, very different. Even though. And we all mentally. They're car companies. So those are the two tools. And that, that's really all it's meant to correct.
- [35:09]
E
Well, yeah, One of the things that we'll use just to pair off of that, that we do, you know, is when you do comparative systems analysis, which is kind of what we're doing, right. We're comparing something today and comparing it to what it was back then is the tendency that we look for those things that are in common of those two episodes, right. And if we find a couple things that are in common, then we automatically assume that it will have the same outcome as it did 20, 30 years ago when that same commonality was there. But when you do comparative systems analysis, oftentimes it's not what's common. That's important to figure out. It's the differences. So you begin to go out and this kind of speaks to Chris's work which is you begin to go down and say what's different about today than it was, you know, Apple in 2016 or what's, what's different? You know, you've got to do the differences. I think people are lazy thinkers and the tendency is that they just take the quick route, you know, maybe system one thinking and say, oh, this looks just like this 20 years ago. This looks like the dot com bubble, right? So you find a couple things that are in common and you go, oh, this is the dot com bubble. It's going to turn out like the dot com bubble. I'm spending most of my trying to figure out what are the differences between today and the dot com bubble. I already know what the big narrative is about AI in the dot com bubble. I got it. But I've got more things that are not in common with the dot com bubble that are in common with the dot com bubble. But people don't really spend enough time doing that kind of work in my opinion.
- [36:38]
F
So Chris, speaking of dating, the dating that Matt described the U.S. today, the U.S. 10, 15 years ago we got used to the U.S. being the leader in so many metrics. But last year, interesting thing happened. So the market was up however you want to look at it. But the international index MSCI was up 29, twice as much as the U.S. the dollar fell 10% which is the worst year since 2017. What, what's going on? Are we comparing the U.S. today to the U.S. from 2009, that it's a different U.S. and maybe I'm asking for a prediction here, but no, but I.
- [37:16]
A
Think that's, I think that's interesting because well, for one thing the index does change over time. Robert mentioned it before. So I mean I think every year there's something like 20 companies get dropped in and out. And so over a period of a decade, that's a lot of companies. That's number one. Number two is, you know, the index is much more multinational now than it was before. I mean what percentage of the earnings today of the S&P 500 come from outside the U.S. i would say it's probably a pretty healthy percentage compared to what it was, I don't know, 25 years ago. But again when people, you know, they do these long term charts, it's the SCP of 100 and it's, and it's as if the implication there is you're comparing something that's very close to being the same thing. Right. But even though it changes a lot, so that's partly reflected in those indexes. Yeah, I mean, I think that's a, that's a big one.
- [38:09]
E
Yeah, for sure. The Chris, you know, thing that I find is, you know, the data is non stationary and this is what we're talking about, comparisons.
- [38:17]
D
Right.
- [38:18]
E
So, so Warren, you know, who's, you know, brilliant on all episodes, he made a mistake many years ago when he said that, you know, 15% return on equity was now the permanent high bar of what, brick and mortar, whatever return on capital. So when prices got to levels that, you know, return on capital was 15, it couldn't get any better and stuff like that. And he always poo poo, that could do. But the data set changed. Right. So the data set that Warren was working with in the 60s, 70s and 80s, which was largely brick and mortar, it changed a little bit when we kind of moved into Charlie Munger's world of better businesses. You started to get higher returns on capital. But then it really exploded when we got into technology, network economics and stuff like that. So when you say, well, the market is expensive anytime, you know, it's, it will, I should say, it's never going to get above 15, 15% return on equity. You're working with a data set that was appropriate back then. It's not the same data set today. So you've got to make that adjustment. And I'm glad I have you guys here too, because Warren is saying, you know, he thinks the market may be fully valued or overvalued, who knows, based upon the percent of S& P profits. Right. You know, market cap, I guess. Do I have that right, Chris?
- [39:34]
A
Yeah, I know he has that. The market cap, the GDP stat that he loves. That's a classic example of, you know, that maybe was relevant whenever he said it. It was a long time ago.
- [39:45]
E
But, but, yeah, but Chris's point, he just pointed out that 60, I think it is 60% of the revenues of the S&P 500 are outside the US so we're not talking about market cap to US GDP. We're talking about market caps of the, you know, operating in the world that are generating revenues and earnings around the world, not just in the US So would it make sense to say when the market cap reaches this level as a percent of gdp, we're overvalued? No, it doesn't. The data set's not the same. So, you know, you got to watch those things. You know, people latch on to those descriptions or analogies or comparative systems that, you know, it looks like it's common. But if you don't recognize that the data set. Bradford Cornell did a lot of work on this. If the data set is non stationary, using historical averages will give you the wrong answer. Unless a data set is actually identical today as it was 20 years ago on all aspects, you cannot draw any historical comparisons and say it's a truism because the data set changed. And Bradford Cornell wrote a lot about this. Moby's on this as well. So Chris is spot on. This is good stuff.
- [40:55]
F
As I'm listening to you and connecting dots throughout this conversation, I'm thinking of a Runway that a business has. And when you look at the early investments of even Buffett, those businesses had a fairly limited, almost regional Runway. Only that many, many stores, that much presence. Combining this with AI or software or the tech, you have a business that can be a global business in its first year, which is unheard of. Right. And it can be in 200 countries in the next three years without physical presence in those countries. Right. I mean, you have to ponder for a second. So when we talk about what Chris was explaining, the, you know, handful of stocks representing 30% of the market cap of the S&P 500, that's the natural outcome of what we're seeing, isn't it?
- [41:45]
E
Well, you would argue that the market actually has Nvidia, right?
- [41:49]
F
Yeah.
- [41:49]
E
I mean, it's. Here's a company that is generating 200%, I'm sorry, 100% return on invested capital. I'm going to say that again. Nvidia generates 100% return on invested capital. It's going to generate 200 billion in sales next year. It has 200 billion in free cash flow in which to do something with. It can give a dividend, it can reinvest in its own business, it can buy back stock, or it can make investments in other companies that are in the same ecology that you're in. And by the way, guys, this bridge financing between companies has been going on for a century. If you go back to the Model T and the Ford business and the oil companies, they were all cross investing. If you look, it's the Keiretsu in Japan. They all cross invest. It's called the Cabal in South Korea, they all cross invest. All right? This cross investing in the same ecology has been going on for a century. It's not considered to be voodoo economics, although Jamie Dimon said, you got to look at them each individually, one off some of them will make good investments and make sense, others won't. But just because AI and these guys are investing in each other is getting to be funny, accounting and hiding things and stuff like that is actually untrue. If you kind of look at how this worked out throughout history now, some will work and some won't. We've got to get that part right.
- [43:18]
B
I go back to this experience I had college age, and I buy this van, Ford van, 15 passenger, taking friends and band stuff around the country with it. And I buy it and the guy's like, oh, this is the best van ever. Wonderful. Everything that you need, Ford. You can't beat a Ford. And like six weeks later, the radiator's blown up on the side of the highway somewhere. And, you know, we're standing there waiting for the truck and the tow truck guy comes and he goes, ford. You know what that stands for? Do you guys know what Ford stands?
- [43:47]
F
Yeah, yeah.
- [43:49]
B
Found on road dead. And I'm like, well, that's a different story than the one I heard from the guy who sold me this thing.
- [43:55]
E
Yeah.
- [43:56]
B
The pace of change.
- [43:58]
E
Yeah.
- [43:58]
B
I'm just curious, especially with date and indexing, I feel like The Nvidia of 12 months ago might not be the Nvidia of today. How do you, how do you understand that? Yeah, how do you understand the pacing? Does that make for red flags? Does it just make deeper work? What do you think?
- [44:15]
E
It's, it's tough to keep up with Jensen. I mean, the guy's moving, lightning speed. He's, he, he wants to be vertical in this thing. He wants to own everything in the stack from the software all the way down to the chips all the way down. I think he wants the whole thing and he wants to have a. That, that's his edge. And so he's making these investments. Yeah, Nvidia's. I mean, when we bought Nvidia in 2022 during the, you know, the growth market sell off, when they were. Now here's a case where when the Russell 1000 growth was going down, it was down 38%. No, 28% that year. I mean, they were taking everybody out and shooting everybody, the good guys and the bad guys. Right. And that's also, you know, if you want to have a great, you know, put this on your tickler list. I'd love to do an episode in the future on the changing structure of markets because markets have changed in such a phenomenal way and how they're behaving, the actors, the ecology of markets are totally different today than they were 20 years ago. I think in technology, the rate of change is a very fast moving animal. And that's natural. Right. So if you kind of think about, if you go back and think about the evolution of markets, when technology becomes the center point, things move very, very, very fast. And you do, you know, we said earlier that it's a survival. Everybody has keep moving pretty quick or you could be the last man out and you don't want to take that risk. And so things are moving very, very fast. But I think Nvidia is interesting at how well it's been able to broaden out into other turfs. And, and it's, it, it, it's a fat. It's going to be a fascinating case study. And this case study on Nvidia is not over. This has got a long way to go here. But I was saying about 2002. When we bought Nvidia in 2002, we had an idea that AI was coming. We just didn't know it was coming in two months after we bought it. We just got lucky, you know, we bought it in, I don't know, September, October, and chat GPT came out the first week of November and it was off to the races. But, you know, when we bought Nvidia, at the time, we didn't. Our description of Nvidia is nowhere near what the description of Nvidia is today. It's a totally different animal. Just in what, three years? Not even quite three years. So, you know, it's pretty amazing what they're doing.
- [46:34]
A
And on that, on that pace of change, I mean, there's probably some objective data points you could find to support that. I mean, one that comes to mind is the average lifespan if an S and P company has fallen and keeps falling.
- [46:44]
E
Yeah, yeah.
- [46:46]
A
That would then indicate that things happen much faster now than they did before. And it's more difficult for companies.
- [46:51]
E
It's unbelievable. Unbelievable. You know, Schumpeter wrote about this a hundred years ago and we kind of went, yeah, that makes a lot of sense. And it didn't happen for about 20, 30, 40 years. And all of a sudden it happened. You know, it's when that transistor came out at intel and you know, the microprocessor in 1977, if you want to, you want to put a line in the sand and say, how did the world change? You know, when that intel processor showed up in 1977, that was the change of a new world. And everything from there has just exploded. But, you know, Charlie Munger said no, no chance, no chance. He didn't warn, would have ever imagined that people could put together billion dollar plus companies now, trillion dollar plus companies earning hundreds of billions of dollars each year with so little capital. Think about that, right? I mean, if you go to Harvard today and you do a Harvard business case study, 99.9% of them is how to make as much money with as little capital as possible. Yeah, capital is the demon, right? That's the hurdle, you know, that makes returns harder to get. You want to figure out a business that doesn't need capital. The more you can get to there, the higher your returns are, if it's sustainable. But that's what technology allows, you know, allows you to do. And he said, you know, we studied Rockefeller, we studied Carnegie, we studied Ford. That's how they saw the world. And when the world changed in the 70s, he goes, we didn't get it. We just didn't figure it out. We didn't, we didn't understand it. It was changing so rapidly. And Buffett hates change. I mean, you know, he wants certainties at discount, he wants long term certainties at discounts. And you're operating in a space that's moving pretty quickly to Chris's point. It's amazing the number of companies that are dying off in the S and P and being replaced. And to that point, I don't know if you guys want to go down this rabbit hole. There's an infatuation with the Russell 2000 today and it's off to the races and it's due and it's reversion to the mean, whatever. But 40% of them are banks, right? I think the other 40% haven't even earned positive EPS in the last year. Okay? This is not the same Russell 2000 as the Russell 2000 in the 1980s. Right. The Russell 2000 in the 1980s was the cradle of innovation. That's where biotech went, that's where tech went, that's where everybody went. And you had to go public to get money to stay in business, to grow your business. Right. You had to go public. What's going on today? All these companies are coming public at 10 billion, 50 billion, 40 billion. 6. They never even, they, they don't even see the Russell 2000. They go, they go right to the S&P 500. The private equity doesn't want venture capital. No, don't go public here at, you know, a billion. Just wait, just wait. So some of the best innovative companies out there are not even in the Russell 2000 anymore. So there's another, you know, that is not stationary, not the same animal anymore. So there's a lot of things to think about in the Russell 2000. It's taking off, it's going to the races, the economy is going to do well, earnings are going to be up. And so it's a no brainer to go into Russell 2000. But you know, I don't see that lasting too long because of the economic returns of those businesses. And they're just not going to, you know, support that much longer.
- [50:04]
F
You're touching on so many things. And I thought of Peter lynch one up on Wall street, the first book that I read about investing and the kind of investing that he practiced 40 years ago in the small cap, buying those companies before they're discovered. They have 100 locations instead of a thousand locations and on and on. Those companies are not publicly listed these days. But that's a whole topic for another episode. Chris, I want to ask you about general semantics again. True and false. We look at the world and we kind of want to say this is true, this is false. You tell us that it can be either of the two, but there are other options to, to consider.
- [50:39]
A
Yeah. So I'll be interested to hear how Robert takes this because for, so for example, we'll use one that have come up a number of times already in this conversation. You know, if we say a company, you know, is the company overvalued or not?
- [50:53]
B
Yeah.
- [50:53]
A
And the implication of course is that it's a yes or no answer. But really I would say there's at least four different possible, you know, ways you can answer that. The first one is just to say that there may be something with the question that it's not really a meaningful question. In other words, something undervalued, you know, compared to what, what do we mean? So most of the time, like when people say something's overvalued, it's always, to me, it's always like a time horizon difference. Like I'm thinking of something over, you know, a five year model or whatever. And they're looking at, mostly what they're looking at is a present multiple based on what earnings or cash flow was the year before and what it might be in the year ahead. And they're saying it's overvalued because it's whatever, 30 times. And whereas I might be looking at it and saying, well, you know, I'm looking at it five years from now what the return's going to be and what the multiple is going to be. And what the IRR is from then. So it looks cheap, even though it's at seemingly, you know, 30, sometimes multiple. So a lot of times, you know, that's one option. You say, you know, you have to give it some context. So you say the question's meaningless. That could be one answer. Is it overvalued? Well, you know, I need to know more before I answer that. The other, the other one. I think that where most companies fall for me is we just say it's indeterminate. You don't know. I mean, most of the time, that's where I wind up, actually. I just don't know is it undervalued or not? It's too hard. I don't know enough. I haven't studied it enough. Or it's in a realm that's just kind of hazy. You know, it's not clearly overvalued. It's not clearly undervalued. It's just in this sort of, you know, gray area state, so that, you know, a lot of times I think things wind up there. And then there's the obvious answer to say, you know, is it overvalued?
- [52:36]
E
Yes.
- [52:37]
A
Or you say, you know, is it cheap? Yes. But way I would. The way general semantics might come in here, too, is it wouldn't just. You wouldn't just say yes. You would say yes, you know, under certain conditions. So I would say, like somebody was saying to me, you know, that stock looks expensive at 30 times cash flow. And I would say, no, it isn't, because. And then I'd give out, you know, whatever my assumptions were on my time horizon. So, again, like Robert said earlier, you're just kind of enriching the context of that. So anytime you know that yes and no are the true or false, those ones you just sort of buttress up with, you know, what are you assuming?
- [53:16]
E
What.
- [53:16]
A
What are you saying when you're saying it's cheaper, expensive, what sort of the conditions as part of your answer? That's, again, part of that training. And Krasybski talks a lot about this. Either or. He calls it either or, thinking. Most people tend to think of questions in terms of binary yes and no answers. And he's trying to get you to think of at least these four buckets, that there's a more of a multivariate way to answer those questions. So, Robert, what do you think?
- [53:44]
E
You've got it down pat. Which is. So Charlie would say there's certain things that we were going to say no to immediately. So there's A no pile. And so you just move on, right? And then there's something that's kind of interesting, but it's too hard to figure out. Well, if it's too hard to figure out, put it in the no pile, get that stuff over here and then work on the things that you have some reasonable capabilities of making estimation. Chris is spot on, which is when we do valuations, we just do do central tendency of value. You know, we say it's a pro, it's worth approximately this, and the inputs are if it grows at this rate, if it grows at that rate for this many years, and we change the growth rates and we don't, we, we don't try to do the math too hard on it, but we kind of do different scenarios to get to an approximation. We say we think it's approximately this and then we move on from there. The thing that I keyed on says 30 times earnings. It's not expensive, it's not overvalued. Even Warren said this. He goes, you can buy a high multiple stock, much higher than the market multiple. If you've got a pretty good deal of confidence that they can maintain a high return on invested capital for five or 10 years. If a company's earning, I don't know, 25, 50% return on invested capital, go ahead and pay 30 times earnings, you'll get your money back in more. Now the question is, are they going to be able to do it right? So there's the trick, right, the sustainability of it and, you know, how long can this last and stuff like that. But you know, you find these great companies that, you know, look expensive but have high returns on invested capital, if that lasts for a long time, they're actually very cheap. That's what Buffett said. But the trick is, how long is it going to last? You know, what sustain, you know, what's the competitive, you know, who's going to come in and take their lunch away and how long does this last before something else happens? But Chris is spot on. He's got the thinking model right.
- [55:39]
B
Robert Peel, Peel this strategy back. And I'm almost thinking of it from the capital allocation standpoint, at the company level, I'm thinking about, I'm going to use Oracle, just because they're the poster child of this right now. But at the strategic level, from the company and then certainly from the investor seat, when we watch companies change, when we literally watch them go like, oh, I was asset light yesterday, but today I'm asset heavy. And we think about how they try to Communicate through that. What are they thinking from a capital allocation strategy and communication? What should we be taking that to be as, as investors?
- [56:13]
E
Well, you know, luck. Luck played a great role in Oracle. You know, things came together pretty quick. I apologize to the individual that, that is heading up the cloud business at Oracle. He came from aws. His name escapes me at this moment, but he, he basically went to Oracle maybe 10 years ago, 15 years ago, and said, you know, I worked at AWS, you know, do you guys kind of want to get into that? And they flirted around a little bit with the cloud, but never got to the size of Azure or, you know, or Google or AWS and things like that. But it was there, there was a nucleus inside of Oracle. And then when this AI thing hit, they went, okay, you know, we've got a chip, you know, we got a couple of chips in this space that we can play. And they just levered the hell out of it. I mean, you know, they, they said, let's go for it. And they had good political associations and they just kind of went all in. And you got to admire Larry Ellison. You know, if you go back and look at his stuff in the 1980s, I saw interviews, you know, he was just sick and tired of IBM and all this other stuff. You know, he said, there's a better way to do it. And so he, you know, he was somewhat of a disruptor and he grew Oracle into a, you know, a really great company. Before AI though, this is, this was kind of IBM single digit business. This, you know, it was, it was pretty much maxed out, but AI gave them a lifeline. What, what unnerves me a little about Oracle and everybody knows it is, it's just a leverage. What I like about Google and AWS and Microsoft thus far is that they're doing it in cash flow. And, and just think about that. Those hundreds of billions of dollars, that's just money that I'm making on my existing business, you know. And you might say, well, you know, you may be flushing that down the toilet and you say, well, yeah, I could be, but I'm not putting the company at risk. If AI went away tomorrow, yes, Microsoft would get hurt, Google would hurt, you know, Amazon would get hurt. They'll still be in business tomorrow, right? They'll still be selling product and services. They'll still be making a lot of money. As Charlie Munger said, I just love this quote and written it down to share with you guys. He was talking about risk. You said risk isn't what makes you Uncomfortable that being variability risk is what makes recovery impossible. Okay. When I think about risk in the AI space, I like, all right, so if we go through a dot com bust, we get punched in the nose who is not recoverable and who is. And I want to hang out with the recoverable guys, with somebody who still has a business, has profits and sales. And I don't want to be in a business where I think maybe you don't come back from this. And that makes it easier for me to maintain the investment through the variability and all the hype and all that stuff is I've got a good business. Even apart from the AI business, I got a good business. So that's kind of, that's kind of how I kind of wrap my hands around it.
- [59:13]
F
Chris, I'm thinking of you and 100 beggars. It's a long period that takes a company to get to 100x. Some things are true, some things are false, some things on this journey we'll never find out, and some of them are absolutely meaningless. How do you think about it, framing it together, watching a company go up 100x?
- [59:34]
A
Yeah, I mean, you know that it was eye opening to do that study because then it. You do sort of think about a lot of the things that we focus on turn out not to matter very much. You know, you know, investors spend a lot of time thinking about the economy, whether it's going to be a recession or not, or they obsess a lot over about, you know, next year's earnings guests, for example. Well, we know that, you know, next year's earnings guests don't really matter very much to the overall value of a company. If you do a, you know, discounted cash flow, you can do just even more basic multiple analysis where you look out 5, 10 years, 1 year isn't going to really make much difference. So it really forces you to think like, what really matters over the long term for this? And he just come down, just sort of boils down some very basic essentials. And Robert talked about these. I mean, what's the return on invested capital, you know, and what's that growth rate going to be over time? And, you know, what's the, what's the multiple at the end, at the end of the rainbow there? And that they're not easy to answer, but at least they get you to think about the things that matter. And then from there you sort of back into it, say, okay, well, for every business there's different sensitivities, right? So, you know, margin may be very important for one business, but margin's not that important for another business. Like Walmart had very thin margins compared to Microsoft. But they successful in different ways. There are different ways to get there. But, but for every business you sort of have to figure out what are the essential KPIs if you will, that you have to focus on and that have to be there. And then a lot of the other stuff is just noise. It's short term noise that you can ignore.
- [61:18]
B
Chris, if people want to read more about Time binding about Korzybski's work, I'm telling you already there's a part two coming in this conversation. So if you're watching this, just know.
- [61:27]
F
Yeah, there's more, there's more.
- [61:28]
B
Chris, plug the new book, talk about some of the older books and where they can find you in general.
- [61:34]
A
Yeah, I mean I think the best way to kind of get into this general semantics way of thinking, I, I read I, you know, my own book. And how do you know that that's kind of a good, you know, entree into that world? Because it's, it's written applying it to investing. It's, you know, it's, I hope I wrote it to be entertaining and fun so hopefully you'll, you'll come away with some handful of ideas you can use. So that's, that would be the way I, I would say is your entree into that. And then you know, after that you'll find, you know, other books and but tackling Korzynski directly is a tough, is a tough task.
- [62:11]
E
So I might not start with him starting.
- [62:19]
A
Yeah.
- [62:20]
B
Robert, what about you? People want to check you out on the Internet where you want to send.
- [62:23]
E
Yeah, you know we, we got a homepage Equity Compass. That's where we'll do our writings on my global leaders portfolio. And you can go there and get the commentaries, the annual reports and things of that nature. You know, that's probably the best way to keep up. And all our literature is there and you know the, the books on, on Buffett there, investing, the Last Liberal art are all there. So you know, we got to continue to learn. This thing doesn't stop. Markets do not stop learning. They do not stop evolving. And if you stop learning and stop evolving, you'll be behind, you'll be behind the eight ball before you know it. So you got to keep going.
- [62:59]
B
Love, love, love that sentiment. Robert and Chris, thanks so much for joining us. You're watching Excess Returns. Bogomil, you're going to hang out with me for another minute. Let's Talk about this.
- [63:07]
F
Okay, I'll be here.
- [63:09]
A
Great. Good talk with you guys. Yep.
- [63:12]
F
Thank you.
- [63:17]
B
Any better than being a fly on the wall for these two? Right?
- [63:20]
F
Like, I mean, you know, the. The privilege of spending time with Chris and Robert and talking about anything is. It's just a blessing. And for us to be able to ask about things that are on our minds and go deeper than what we read in the book and have an audience that will enjoy it, I mean, made my day.
- [63:39]
B
All right, so I know we both took some notes as we were having this conversation. Yeah, the. The part I'm jumping right into the middle of, the danger of is that segment where that segment is. It's a really powerful thing to me because that forcing of the nuance and the back into the conversation, I. I really love the way that Robert reacted to that, where he went, I'm not gonna say this the same way anymore. You've. You've just given me a new. A new construct for doing it. Just curious, like, you and your work. How. How do you apply. I mean, any of this? But I'm curious how you apply this.
- [64:20]
F
So. Even before I read Chris's work about general semantics, I felt like my. The nuanced aspect of what I do has expanded dramatically from the days when I left university where I thought the answer is 2 or the B, and I realized the world is much more complex for us to operate that way. So discovering Chris's work, and I introduced him to. Well, I invited him back on talking billions, and I talked to him about general semantics. And the first time I asked him to come back and talk about it, he said, well, this book didn't sell that well. And I said, it's not about that. I think these ideas belong in more homes and even our heads out there. Anyways, he gave me the vocabulary to see the world from a different perspective. And you talk about the word is that Robert pointed out that he's going to look at the world in a different way. I think we're. So. We're operating in the world of absolutes, very categorical, like, this is it. This is the answer. That's a cheap stock. That's an expensive stock. That's a tech stock. And sometimes it opens the door, but sometimes it shuts the door for us to even explore. Like, this is not a value stock, or this is definitely a growth stock. And we limit ourselves on the investment side, on the client relationship side, instead of looking at things. It's a range. It's something for us to experience, observe it may seem this way now, but it may be different if we shed a different light on it. How did you think about it?
- [65:50]
B
In the same way. And I had the experience too, of when I encountered. So, number one, you're the reason that I read the Time Binding work and everything from Chris. You were like, yeah, 100 baggers. Fine, move past that, Matt. Go straight to this.
- [66:04]
F
It's a great book. Ye.
- [66:05]
B
Yeah, it is great. And what's crazy too is that's probably the first book since. Since reading Robert's book Investing the the Last Great Liberal Art. Both of those right away were wet in my mind because both of them basically say, like, you need to bring these outside things in and forget the absolutes that you see in headlines and all the other places. So whether it's on an investment committee meeting or meeting with somebody and talking about their finances or an investment in the portfolio, this idea of that, you constantly have to couch things in a much broader framework. And I feel like I was already doing that in some just, you know, probabilistically waiting. A lot of the stuff from Mobison actually really shaped my thinking on this too. But it's like probabilistically waiting. Well, this is the good scenario, this is the bad scenario, this is the middle of the road scenario. Then how do we want to place weightings on each now to be able to go, here's how we understand a headline in the context of all these things. Here's how we understand what this might have meant a year ago or 10 years ago to you versus what it means now. It just helps enrich our ability to communicate what this was specific to this. And because it kept popping into my head, I remember working with this family who had amassed a massive McDonald's position. And it was a McDonald's position that was started in, I'm assuming, the 60s. And it was just like from the 60s through the 70s, through the 80s, through the 90s, and then somewhere in like the early to middle 2000s, maybe even a little bit later, you know, it had already passed on from one generation to the next. And I'm working with this family and looking at it and just marveling at the company as a compounder, but also marveling at about how different of a company this has been even in my own lifetime, from when this person started investing it before I was born. How do you think about stuff on those timescales? I know you do.
- [67:58]
F
I do. And the time binding, the infinite time horizon, the family perspective, it's something that really speaks to me as you know, and probably this audience knows, I manage money for families in a similar way that you do. And we interact. I interact with generations, many generations of a family. And I have those moments of the time binding experience that I brought up on the show when I would open a banker's box with statements from years ago, from before I even started working with the family, and I would see what they held, you know, 45 years ago, and how big the account was. And you're touching history in a way that I can't explain. I think on a human level you can. And I've done with family members, with my wife's family, too. Pick up a birth certificate of your great grandparents, if you have one, or, you know, a passport or any document. And when you're touching it, you see their signature from, like 1912, and you're thinking, wow, where was this form filled out? Where were they? What was their state of mind? Maybe they just arrived in this country. Maybe they were learning the language, the customs. They were trying to figure out the first stop, the first opportunity. Maybe they came with a loved one. Maybe they just saw, you know, a beautiful woman on the boat thinking, is she going to the same town as me? Maybe this will be the mother of my kids. I don't know, but I call those thoughts pop in my head. But the time binding phenomenon, it's not just the investment in the stock, but the human experience of us touching history. You know, if you're reading Plato, we're talking about Ramses ii. We're touching history. Like, for a moment, we feel like I was there at that battle that's depicted on the walls of the temple, the same way I was there with the great grandfather filling out that form. I wish I was there in the room with them for a moment. What was it like? Did they know where I'm going to be? I don't know. Like, do you have those thoughts sometimes?
- [69:56]
B
Oh, I 100% do. And I have the thoughts in the way that I'm clicking to E sign on a DocuSign, and I'm like, what's the record of this? Like, if this exists in a hundred years, is just this, my embarrassing computer screen or smartphone, like, scribble, that's not even my name or recognizable. Are we destroying these artifacts? How do those matter? Yeah, because all that nuance is like, our lives today are as full of detail and nuance as somebody's life 100 years ago.
- [70:28]
F
But, yeah, the records today, it's so efficient and so easy, but at the same time, it doesn't have the physical connection. And I love the digital, as you know, I love the virtual. I love that we can host this show in a way that we can today with technology. But I think that the physical aspect, I think we all need it in some way or shape or form. And holding a statement, it's not enough. Holding on to a story, it's a little bit more. But picking up a physical expression of something. Maybe I'm childish here, but I wish I had shared certificates of all the holdings I have, actually. Lauren Templeton, the great granddaughter of John Templeton, told me how her parents would give her paper certificates instead of just sending money between accounts, and she would put them in a frame and then put them on the wall in her bedroom. And I thought, it's such a symbolic commitment to ownership of a stock, of a business, of a share of a business. Instead of you just having a line on the app in your phone thinking, I could sell it tomorrow. No, it's a commitment. You can't actually sell it. It's. You have to take it out of the frame, go to a broker, have it, you know, placed in your account, and then you can sell it. I don't know, maybe we need those physical hoops.
- [71:50]
B
Maybe we do. Maybe this is something that actually popped into my head multiple times in the conversation. And I know that Robert brought it up of talking about how the indices have changed over time. And I couldn't help but think it's also how capital allocation and corporate strategy has evolved too. Yeah, because the kind of pre and post Mark Benioff world of just how you talk about a company, how you guide towards the metrics that you decide you should be measured by and the fluidity that that affords you. That type of storytelling shifted because 50 years ago, 100 years ago, the stock certificate was a physical representation, like, of that trust. I think of those old Disney certificates and I think of people where I've seen them who have framed them because they are literal works of art and you have all the cool little things going on. An office I worked in, they had old stock certificates framed on various parts of the wall as just cool pieces of history. I remember marveling at them because that was the end of that actually existing as a thing people would do. People come in with a bunch of shares and we'd have to convert them, you know, into the digital equivalency. We've been in the business long enough to have done this. But I think about how, how quickly we've moved away from that and how much that's representative by who the leaders in the markets are, are the people who can tell these stories with a minimal physical commitment. And that's a. That's a fascinating part of the transition.
- [73:18]
F
So let's look to the future. And it's something that we touched on and, and I called it the Runway. You know, the. The Runway for a business, the Runway for an idea, even the Runway for this podcast episode. If this was a radio recording in the 1960s in a local, I don't know, Pennsylvania radio, we would.
- [73:36]
B
We'd both be drunk and smoking, probably.
- [73:39]
F
There's that going on that might be happening. But we would have reached, you know, the hundred taxi drivers and bus drivers and whoever's still at home, whoever has arrived at work. I don't know who else was listening at the time. And that would be it. But now you and I record this episode and I know it from Talking billions. It reaches 180 countries. And I think it's still in its early stages of what it could be. But 180 countries, and many of them I can't even name. And I've heard from listeners from many countries that I haven't visited or I need a minute to find them on the map. It's mind blowing what we can do. And, you know, we think about a business that develops, a service that can be offered, as we spoke in this episode, within a year in, you know, 50 countries. But you and I are creating something here with, you know, Chris and Robert. You guys will air it in the coming days. And think about the minute you press Go Upload pops up on devices in maybe 200 countries. I don't know. It gives me chills. How do you feel about it?
- [74:47]
B
Yeah, take that, Gutenberg. That's the way I feel about that. And it's also funny because if this was just a call and talk radio show in beautiful northeastern Pennsylvania, you'd still reach a couple of Polish grandmothers, probably. I can tell you, man, the kielbasa and pierogies are strong in my backyard.
- [75:05]
F
That's my target audience anyway.
- [75:07]
B
But yeah, it is special and it's fascinating to be reminded of, not just back to the nuance idea, how it works in the past, how it works in the future, and our perception of the future and how that reflects on how we understand it right now in real time. I'm excited for the next one of these. I think we're going to do a part two, and then I know we have some more stuff to wrap in here with what Robert brought up midway through the episode too. What do you think?
- [75:35]
F
There is so much, and I know that we have to pace ourselves, but one of the topics you brought up, and maybe just a teaser here for this audience, the structure of the market has changed and it's something that I know people think about, but we haven't talked about it. Even if you look at the Russell or whichever index, these are different companies. Speaking of dating, the dating that Chris talks about from even the 1980s when Peter lynch was having his successful decade or two and writing a book about it, we have to think about it. It's a different market. And it's not just that. It's the passive index participation. And now AI is changing the dynamics. I hope more people are paying attention, doing the research, learning about businesses and seeing it as ownership of businesses. But also our time attention span has become so short that it became really, really hard to do what we talked about, actually owning businesses over long periods of time anyways, we can take it in so many directions, but the structure of the market has changed what Robert pointed out and I'd love to explore it with him, with them at some point.
- [76:44]
B
Well, that's where we're going next. I am long 100 year Thinkers podcast episodes in 2026. How about you?
- [76:50]
F
Me too. I'll be back.
- [76:52]
B
Fantastic. You're watching Excess Returns. Like subscribe all the things below. You know what to do. We'll talk to you real soon.
- [77:00]
D
Thank you for tuning into this episode. If you found this discussion interesting and valuable, please subscribe on your favorite audio platform or on YouTube. You can also follow all the podcasts in the Excess returns network@excessreturnspod.com. if you have any feedback or questions, you can contact us@excessreturnspodmail.com no information on.
- [77:19]
B
This podcast should be construed as investment advice.
- [77:23]
C
Securities discussed in the podcast may be.
- [77:25]
B
Holdings of the firms of the hosts.
- [77:27]
F
Close your eyes.
- [77:28]
B
Exhale, feel your body relax and let go of whatever you're carrying today.
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C
Well, I'm letting go of the worry that I wouldn't get my new contacts in time for this class. I got them delivered free from 1-800-contacts. Oh my gosh, they're so fast.
- [77:42]
F
And breathe.
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C
Oh, sorry. I almost couldn't breathe when I saw the discount they gave me on my first order. Oh, sorry. Namaste. Visit 1-800-contacts.com today to save on your first order.
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F
1-800-Contacts.
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C
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