The Power of Humility in Investing with Dan Rasmussen (EP.216)

0:28We all need to make smart decisions with our money. a firm renowned for its rigorous data-driven approach to investing. Dan has made a name for himself in financial circles, really for a long time just by challenging conventional investment wisdom and advocating for humility and empiricism in financial decision-making. He's here to discuss his latest book, The Humble Investor, which reveals some really compelling insights into how investors can find an edge by recognizing their own limitations and the unpredictability of markets. Speaking of new books, you can go to theperfectportfoliobook.com and you can get updates on my new book, The Perfect Portfolio, which comes to your inbox every other Saturday.

1:10When you subscribe, you get early excerpts, you get access to subscriber-only webinars. So again, that's theperfectportfoliobook.com or you can find a link at the top of the episode description. him. Now, let's dive in and explore how embracing humility can lead to smarter investment decisions with Dan Rasmussen.

1:32Welcome to The Long-Term Investor. Today with me, I have Dan Rasmussen, author of The Humble Investor. Dan, thank you so much for joining me here today. My pleasure. Thanks for having me, Peter. The Humble Investor, I was curious what it was going to be about. I followed you on Twitter. Well, I still follow you on Twitter. I just don't use it that much. But I have followed you for years. You were one of the key contributors to FinTwit or Financial Twitter, for those who don't know, in what I consider to be the peak Twitter years. And Twitter's changed a lot. And so I was really excited when I got to read, know that you had a book and read it.

2:06And the central premise is really built around humility in investing. So I was hoping maybe we could start with you explaining why humility is crucial and how often investors are going to mistake confidence for competence. You know, one of the central challenges of investing is how unpredictable the world is. We see through a glass darkly. There's a famous study on predicting earnings growth, revenue growth and earnings growth. And one of the interesting findings from it is that historical earnings and revenue growth has no predictive power on future revenue and earnings growth. So if you say, hey, if I looked at the top 10 % of fastest growing firms, you know, what's their future one, three, five year growth rate?

2:49Well, it's no different from flipping a coin what it's going to be. So there's this break between the past and the future. But our brains are wired. The same mechanisms in the brain we use to forecast are the ones that we use for memory. I think if you think back to like the Stone Age, right, if you go and find a spring or a place where there are lots of rabbits, and then you want to forecast tomorrow where a spring or a bunch of rabbits are going to be. But you're going to use your memory as to where that spring and those rabbits are. But the same tools mislead us when it comes to investing because the future, in fact, is so discontinuous from the past.

3:23And I think that we don't want to just throw up our hands, however, and say, oh, gee, the future is totally unpredictable. So there's nothing that we can do. We want to rather harness that unpredictability because there are things that are predictable. One of those is the behavioral errors of people who think they can predict the future. One of my favorite stories or studies is by my colleague, Sam Hansen. He studied Greek ship owners. One of the things that he found is that when shipping prices are very high, Greek ship owners plug all of these inputs into their DCF models. They say, wow, current shipping rates, the shipping market is vastly profitable.

3:58I can go build a new ship and earn like a 30, 40, 50 % IRR on building this ship. So let's go out and order a bunch of new ships at the South Korean shipyards. And then two or three years later, because that's how long it takes to build a ship, they get the ships delivered and they excitedly call their captains and say, hey, gee, how are our new ships doing? I said, oh, it's not very good. I said, not very good. You know what happened? And they said, well, shipping rates have cratered. I said, why have shipping rates cratered? And they said, well, it turns out there's a glut of new deliveries on the market.

4:25I said, a glut of new deliveries on the market? You know, how did that happen? And what they don't realize, right, is that in a competitive market, the inputs to the model that they were using with the same inputs everybody else was using. And this is the phenomenon Sam Hansen calls competition neglect, which is a wonderful term. And I think there's a lot of competition neglect in markets. We don't realize that the same things are driving us to make decisions or driving everyone else to make decisions, that investing has to be meta-analytic about what it is that we know relative to what everyone else knows.

4:54I think my argument in The Humble Investor is that the one thing that we know that perhaps everybody else doesn't, is that the world is much more unpredictable than people think. So what we want to do is bet against hubris, bet against consensus, find the things where the vast majority of people agree and where that agreement is priced in and bet against correlated beliefs. You know, one of the interesting angles that you spoke about that I'd never really thought about before is just how sometimes both the confidence in our forecasting ability, as well as the fact that we have some of these models that we all agree upon can directly contribute to volatility in markets.

5:31Do you mind explaining that for the audience a little bit? So Robert Schiller won the Nobel Prize for his work on excess volatility. And what excess volatility is, is basically, if you think at any given point, stock is worth future cash flows discounted back to the present. The only problem with that is that we don't know what future cash flows are. We don't know what future discount rates are. But if we look back into the past, we do know. So we can know what the true value of the market was in 1931 or 1935 or the value of any individual stock on the market for that matter. And so what Schiller does is he looks and calculates what the true fundamental value of the market was over long periods of time and then compares that to the market prices.

6:07And he finds out that changes in the fundamental value, the true value, including future information, which obviously they didn't have, explains only 5 % to 20 % of market volatility. The other 80 % to 95 % is not explainable by the fundamental data that should be, in theory, driving market pricing. And so the challenge to us is to say, well, what drives that excess volatility? Because it's a challenge in some ways to efficient market hypothesis, right? Because we're to extreme forms of that, which say, oh, the price is always right. Well, the price can't always be right because clearly prices are too volatile relative to fundamentals.

6:42So price isn't always right. Now, the sort of weaker form of that efficient markets hypothesis is that markets are really hard to beat. You know, it doesn't challenge that, obviously. The interpretation that I think best explains excess volatility comes from a sort of obscure professor at Stanford, Mordecai Kurtz, who has a theory of rational beliefs. And his theory of rational beliefs is that at any given time, there are a variety of potential futures. And based on historical information, it's totally rational to believe in any of those potential futures because we don't know the future. So you can't disprove any one of them, right?

7:16If you're in December 2019, you said, I think 2020 is going to be defined by some massive, you know, contagious disease that's going to spread from China and force the country to go crazy. So what are you talking about? You know, there's no reason to think that that isn't even a possibility, but that would have been the right one. So sort of surprising things happen all the time. And again, we can't disprove anyone else's view of the future. And I think if you think to political disagreements or business disagreements, so many of them are better interpreted through this rational beliefs lens, right?

7:43You say Trump's tariffs are bad. I say Trump's tariffs are good. You know, what we're really doing is making a forecast of how the tariffs will impact the economy. But because neither of us know, because we don't know what the future is, actually, both our views are rational. Neither of us is wrong or right. We can't know. Six months from now, we could know. But then what's going to happen as the future basically forecloses, as the future happens, it forecloses these alternative histories. And these many people who had bet on these alternative histories coming to pass. And so then all those people, having made a forecast error, have to go and revisit their forecasts.

8:15And that's what creates market volatility. And I think that's the right interpretation. And so it's funny, but you don't see the term forecast error in any economics textbooks. But any of us who have ever invested in markets know that this is a defining attribute of life in markets. We're always making a forecast errors. Otherwise, you're not betting and not a participant. So the question is, logically, right, those forecasts are a component of markets. And of course, they're a driver of market volatility. It is such a nuanced perspective and such a well-stated one. And I think it probably applies even to investors, whether they're doing it themselves or they have an advisor.

8:50Just the viewpoint of the world, understanding, people seek to understand. They make mistakes during periods of volatility, something I do want to ask you about. But I want to pull on the string that you just gave to me a little bit more. you manage a large hedge fund. And I think this viewpoint of the world must impact how you make investment decisions. Do you mind digging in a little deeper there and explaining how that might impact the way that, or at least the lens through which you are both making an investment decision to start as well as evaluating an investment decision after the fact, whether that's five months from now or five years from now?

9:25I think there's an element of which this view is freeing in some ways. And one of my mentors has a great line that he taught his kids, which I love, which is, you know, when you know what your principles are, it's not the decisions that are hard, it's the consequences of your decisions. And I think there's a truth to that. I think of quantitative investing or systematic investing, which is what we do in that context. So how do we make investment decisions? What I think is that if you look at Phil Tetlock's work, and Phil Tetlock is probably the world's leading expert on forecasting. And of course, one of his big findings is that nobody can predict anything with any degree of accuracy.

9:57And experts in the field are actually really problematic because experts tend to be no more accurate, but much more confident. And so they're sort of the worst of the breed, right? Like don't go to the Yale foreign policy school to figure out what's going to happen in Russia next year, right? Like you're just going to get some overconfident person who's going to tell you something with great degree of certainty that sounds really right, but it isn't at all. So instead, what he advocates is this tool or method of thinking called historical probabilities or base rates. And the way to think about historical probabilities or base rates is think about you're doing a renovation on your kitchen, okay?

10:28You ask the contractor, you know, how long is it going to take to renovate this kitchen? And they say, oh, four months. That's their forecast. You're getting an expert forecast. Now, you then say, well, have you done kitchen renovations like this before? And they said, yes, we've done about 10 of them. And you say, well, what's the average time it took you to complete those 10? And they say, well, 17 months. And then you say, well, wow, I'm seeing a big difference between the historical base rates and your own forecast. And which is more reliable? Well, of course, the historical base rate is more reliable.

10:59Now, that's an example for kitchen renovation. But what about for investments? One way you might think about in a cross-section or in a time series. So in a cross-section, we're thinking about ranking stocks. We might say, oh, gee, what I really want to buy is high quality stocks. I'm going to come up with my favorite metric of quality. And then I'm going to rank stocks by quality. And what I want to know is if I choose stocks based on quality, how well am I going to do and what's the spectrum of outcomes? What that is going to lead you to a conclusion is going to be like, hey, over the long term, this quality stock thing outperforms by one or two percentage points, but with a 5 % standard deviation such that over any given year, I really don't know, but over any three to five year period, maybe I can expect to earn something consistent.

11:38You just start to frame your conclusions much more probabilistically. But you're going to spend a lot less time thinking, oh, I've spent six months understanding one company to make a really complicated discounted cash flow model on it, because you're going to know intuitively that's an impossible task. And so I think a lot of it is sort of saying, let's stop doing the things that aren't going to work. You know, discounted cash flow models are a great example. They're just not helpful. They're not going to work. They're going to mislead you. They're going to make you overconfident. And let's start doing things that do work, like how has X predicted Y in the past with what historical probabilities?

12:11And if I'm betting on X, therefore, I can now understand the probability that Y will happen. I have to mention, so I started my career as a stock analyst. And when you do a discounted cash flow model, for those who are not familiar, I mean, you're putting everything about a company's financials onto a spreadsheet. And when the first time you see one and you're taught how to build one, you do feel like you have precision and knowledge of the company's inner workings. But the thing that really blew my mind, like really never made sense to me, and I think ultimately informed a lot of my philosophy on investing is most of the model came down to what you predicted the cost of capital to be.

12:46Yes, you do have to predict a sales growth rate. You do have to predict where margins go. But man, this one variable that you can't possibly know was where the big predictor was. Now, using that to transition, you've actually highlighted valuation, though, is a pretty effective tool for predicting equity returns. Why do you feel that low valuation stocks in particular consistently outperform? And how can investors practically implement this insight? First, I'll quibble with the word consistently. I hate adverbs generally. That's fair because it depends on the timeframe. Yes, my clients might challenge that too.

13:20I'll particularly challenge that one. I think they outperform, but not consistently. But I'll talk about that more. So valuation is such an interesting thing. The way I think about valuation, right? As you think about what is a discounted cash flow model, you're valuing a company and the biggest input to that company's valuations are its future growth rate and the discount rate, the cost of capital assumption that you're putting in there, right? And the cost of capital assumption measures how risky you think it is. And the growth rate is how much you're going to grow. And you look at those two numbers and you're going to come to a conclusion about what the company is worth.

13:51And then you can take that value and compare it to current book value or current cash flow or current profit or sales or whatever, you have a ratio of the sort of market valuation to some thing in the financials. And ultimately, what you're going to see is that valuation is a measure of optimism or pessimism of confidence in the company or skepticism of it. The richer the valuation relative to the current financials, the more excited other people are. And the more pessimistic, the worse the future valuation is. And you can think of a sort of a simple. Let's imagine the apocalypse is happening two years from now.

14:27And we have something, two companies, you know, that made$50 each last year. One of those companies is valued at$100 because it's going to earn$50 for each of the next two years. So that's person is just saying, hey, the same thing will happen the next two years that happened last year. And the other is valued at$1 ,000. So somehow they think it's going to earn, you know, massively more. And I think if you then think intuitively, like, well, well, if my view is the future is really unpredictable and we have no clue what the next two years are going to happen. Well, I'm obviously better choosing the one that's valued at a hundred than the one that's valued at a thousand because, you know, we don't know.

15:02And the only thing we know is price. Price you do know. It's the only certain thing you got. Price you do know. And of course, there are a lot of nuances. Okay. So let's start with some nuances, right? Would be some companies might be intrinsically worth more regardless of their future growth. Like simplistically, let's think of two businesses that do exactly the same thing, one that owns all their own real estate and one that leases their own real estate. The one that owns their own real estate is just more valuable. They own the real estate. Okay. So you're going to value the real estate and the company, right?

15:33So it's not like valuation is purely about growth rate and discount rates. There are a lot of other factors, or one is a really high return on assets and one is a really low return on assets, or one is located in Romania and the other is located in California. One is listed on the Budapest stock exchange, one is listed on the NASDAQ. They're all things that are going to shape your valuation. So it's not all about growth and discount rates, but that's the majority. And so what you're trying to do is isolate that. Like let's isolate the growth component of this from the stuff that's sort of intrinsically true about the company.

16:05And that will be a very clean metric of consensus optimism or pessimism. And then our intuition should be that we should avoid the things that consensus is too extremely optimistic about and prefer the ones that the consensus is extremely pessimistic about. And what you see then unfold in reality, if you sort of play forward value a year, what you see is that on average, the things that the market's really optimistic about have better fundamental results over the next year than the stocks that people are pessimistic about. However, fast forward to a year, you're making a forecast inclusive of that year, making a forecast about future years.

16:41And it turns out that the extreme optimism just fades, or maybe that some good things happen that year, and so fewer good things happen in the future. And the pessimism also fades. The multiples mean revert, and that creates the value effect. Another way to think about this, I think it's quite elegant. We did a study of Japanese companies, because Japanese companies are required to issue guidance. And so, you know, we divided the world into companies that had low, medium, and high growth guidance. And they're forecasting one year forward. So companies own CEO, forecasting one year forward. And the TSC requires them if the forecast is going to be, the results are going to be outside a certain range of the forecast, they have to issue some update to the stock exchange.

17:21So there's a lot of incentives for accuracy here. And everyone has to do it. So there's no sort of lemons problem like there is in the US. And what you find is that companies are at 50 % accurate at sorting into the categories. If they think they're gonna be high growth 50 % of the time, they're going to be high growth, which is better than 30 % or one third. So there is some ability to predict the future one year forward for companies, the management has some sense of what's going to happen. But then when you start to interact this with market pricing and returns is where it gets interesting, because it turns out that if you look at the companies that say they're going to grow really fast, that do grow really fast, they beat the market.

17:56And it turns out that companies that say they're not going to grow fast and don't grow fast, they underperform by a little bit. Sort of like, okay, gee, the world is sort of roughly right. But the problem is the other 50 % of the time when the companies forecast high growth and don't achieve it. Well, what happens? Well, the stock underperforms by a lot because you set them up for high expectations you didn't achieve. You told your wife you're going to be home at 530 and you're home at eight. She's not happy. On the other hand, you said you were going to do that business travel next week and then it's canceled in your home and can out with the kids.

18:24And that's the value stock where they said they were going to have slow growth and they had a high growth. And of course, the outcome is quite positive from the market perspective, such that, interestingly enough, knowing what the management's growth forecast is has no predictive power over the stock whatsoever, because it's priced in. And enough of the time it doesn't work that you don't make any money off the signal. So it's just one of those sort of ways of trying to change your perspective around value and growth and forecasts to understanding this sort of metacognition about what's baked into the market price and how to analyze your own view relative to that.

18:57Well, I think that people who have subscribed to value investing, which I'll say in kind of a nebulous broad way, because we could probably nail it down a little bit deeper, particularly in the U.S. have really had their religion tested because U.S. large growth has just dominated anything that is an investable asset class that you could put in one of those asset class return quilts. large cap growth is at the top. So people have doubts. And let me ask you, Dan, I mean, what do you feel like are some of the bigger misconceptions about value investing and the validity of it and why you still believe in the concept of it being persistent and working going forward again?

19:37And I'm saying working going forward in a pretty nebulous broad way. And you can go as specific as you want, but just recognizing that. So I'd say let's bifurcate the world in the US international value investing has worked just fine internationally. So if you look at the performance of small cap value indices versus large cap indices, they've done better internationally than large cap indices. So the value premium still works. It just doesn't work in the US or hasn't worked in the US. What makes the US special is really the question. What makes the US special over the last 10, 15 years? And I think there's a simple and obvious answer to that question, which is I talked about value being based on historical probabilities and betting on sort of consensus optimism being wrong.

20:15But something has happened in the US over the last 15 years. And what is that? A major technological revolution where consensus optimism about technological innovation was underestimating the actual impact of that innovation. We are living through an age akin to the Renaissance, the development of the railroad or the steam engine, something that will be in the history books for hundreds of years about what just happened in the United States over the last 20 years. Think of the technologies that have been developed, The cloud, mobile, AI, these are revolutionary tools and they've changed the way society is.

20:54Think about the impacts of phones on schools or phones on kids. Think about the impact that AI is going to have on a whole variety of professions. Think of the impact that internet has had on our day-to-day life. These are massive, revolutionary technological changes. And the companies that created those technological changes have made huge amounts of money. And the people that bet on those technological changes have made huge amounts of money. So, yes, this has been a period where buying boring industrial companies at single digit P multiples has not worked as well as investing in high growth, exciting technology and software stuff.

21:27Now, how long will that technological revolution continue? How rare are those technology? Like, has there ever been a time for music as wonderful as Vienna in the 17th and 18th century? No. Like, will there ever be a time again in our lifetimes where we see such massive technological change? Probably not. And so I think that my view is that, yes, we've lived through a special time. But should we forecast that that special time is always going to be special or that it's even special in other places, right? Like Japan didn't have a great AI revolution, nor did Europe. There are no great tech companies there.

22:00So these technological revolutions are often concentrated in very narrow periods of time among very narrow sets of people and very narrow places that sort of foster that innovation that Silicon Valley is to tech what Vienna was to classical music or Florence was to Renaissance literature and painting. And that's an exciting thing to live through, but it's not a very good thing for being a skeptical, pessimistic value investor who thinks that things are going to mean revert because they just didn't. Again, you travel outside of that special case to Europe or Japan and value investing is done just fine.

22:30And I think that thinking about the future, it's more likely that we're going to live in a more normal time than that these special technological revolutions will continue. That said, a special technological revolution could continue and Gen AI could become AGI. And then all of a sudden, all bets are off, which is certainly what our largest tech companies are betting on. You know, it's interesting, and I don't want to get too off track at the largest tech companies. I mentioned being a stock analyst when I was younger. And there was something about like the diversified industrial company that was fascinated to me, where they kept deviating from their core business to move the needle.