Reflections on the Investing Process with Michael Mauboussin
If we are looking for a
Note: Compound helps tech employees work through capital allocation decisions. None of this article is financial advice, but if you are looking for modeling tools or human advisors to help you invest, we can help. Get started here.
"This is the nature of what we do. It's the intersection of business, people, psychology, sociology, and numbers. It's just inherently fascinating. There's a lot of macro factors and stuff that make sure you never have the game beat. Never."
Michael Mauboussin has spent more than three decades studying companies and the investment process. He has published a voluminous body of work combining traditional security analysis, corporate strategy, and concepts from a wide variety of disciplines (a new full archive is now available). In 2020, he joined Morgan Stanley’s Counterpoint Global unit and serves as Head of Consilient Research, a reference to the idea of consilience, the “linking together of principles from different disciplines.” Consilience, he explained in 2021, as “put forth by Harvard Professor Emeritus E. O. Wilson” is about a multidisciplinary approach to problem-solving because “many of our most vexing problems are at the intersection of disciplines.”
Mauboussin is also a trustee at the Santa Fe Institute (and was chair of the board for eight years), a research institute dedicated to the study of the complex adaptive systems (such as the stock market) which Mauboussin called the “unifying theme” of his work.
In his latest book, Expectations Investing, originally published with his mentor in 2000, Mauboussin advocates for a counterintuitive approach to investments. Rather than establishing a valuation first, he explains the power of investigating expectations embedded in the market’s valuation:
“Most investors act as if their task is to figure out a stock’s value and then to compare that value to the price. Our approach reverses this mindset. We start with the only thing we know for sure — the price — and then assess what has to happen to realize an attractive return.”
"The most important question in investing is what is discounted, or put slightly differently, what are the expectations embedded in the valuation?"
For an easy introduction to his work read this 2021 profile. Another excellent piece is his "Reflections on the Ten Attributes of Great Investors" which incorporates many of his key frameworks.
"Great investors do two things that most of us do not. They seek information or views that are different than their own and they update their beliefs when the evidence suggests they should. Neither task is easy."
I decided to ask Michael about the implications of his work for operators, the dynamics between analysts and portfolio managers, lessons from studying feedback and elite teams, and what gave him conviction to hold Amazon stock through the dotcom bust.
We’re excited to share this conversation which we split into two sections: the core conversation and an additional deep dive on investment process.
A conversation with Michael Mauboussin:
- Holding Amazon through the dotcom bust. “I was very influenced by a wonderful book by Carlota Perez that came out probably in the early 2000s where she talks about the interplay between technological revolutions and financial capital, one of the points she made was, it's often the case that the hard work happened after the financial bust.”
- On feedback and learning. “In every domain elite performers tend to practice. Every sports team practices, every musician practices, every comedian practices. What is practice in investment management? How much time should we be allocating to that?”
- On elite teams of superforecasters. “There are three important things. How big should it be? How do we compose the team? The third and final piece is how you manage the group. And this is usually where the mistakes happen.”
- Lessons for operators from Expectations Investing. “Executives of public companies in particular should absolutely understand the expectations priced into their stock. The first reason is that if they believe something that the market doesn't seem to be pricing in, they have a communication opportunity.”
- “Very few executives really understand how capital markets work. This is almost like our analyst portfolio manager conversation. When you get to that seat, all of a sudden you have responsibilities and skills that become important that you may not have ever dealt with before.”
- Why has Expectations Investing not caught on more? “Understanding what has to happen for today's price to make sense is just such a fundamentally attractive proposition. And then evaluating whether you think that those growth rates in sales and profit margins and capital intensity and return on in capital that's implied, whether those things are plausible or not, it just makes enormous sense as an approach.”
- On Stanley Druckenmiller, legendary hedge fund investor. “When you observe very successful people over very long periods of time in these probabilistic fields, they tend to have certain attributes that are worth all of us paying attention to.”
- On the idea of the hot streaks. "I thought that what Druckenmiller was describing was a little bit more like that creative field, where things seem to line up for you. You seem to understand what's going on. You seem to be very productive."
- What has he changed his mind on? “When you start to understand the fundamental components of complex adaptive systems, there's no way to look at the stock market the same way again, personally.”
- On being an effective teacher. “To be a great teacher, an effective teacher, it's about being a great student, be a great learner yourself. And I think that comes through if you're doing it well.”
- What does he focus on today? “In our industry this is the nature of what we do. It's just inherently fascinating. Because it's the intersection of business and people and psychology and sociology and numbers. I mean, there's just a lot of really macroeconomic factors. There's a lot of stuff that's always going on that makes sure you never have the game beat, never.”
Bonus section: Deep dive into the investment process
- On sizing. "Here we have George Soros and Stanley Druckenmiller, two legendary investors who say that this is the main thing that drives their returns and results over a long period of time. Whereas we look at the real world, we find that most people don't create a lot of value from sizing and it's all security selection. The question is can we bring those things together to some degree?"
- On analysts and portfolio managers. “A very good portfolio manager will be able to focus on the two or three issues that matter most for a particular company. And they're very good at identifying those and honing in on those."
- On common mistakes among analysts. “There was a letter from Seth Klarman at Baupost to his shareholders. He said, we aspire to the idea that if you lifted the roof off our organization and peered in and saw our investors operating, that they would be doing precisely what you thought they would be doing, given what we've said, we're going to do. It's this idea of congruence.”
- On selecting investment managers. “Excess returns are a function of skill times opportunity set. If an investor hopes to generate some sort of an excess return, you might use that as a guideline to break down the fundamental law of active management and ask if they've got the components in place."
- On the shift from public to private markets. “This mirage of lower volatility creates essentially what ends up being an effective psychological technique to keep people in their seats.”
Frederik: Thank you so much for joining me today. I love that we can finally record this.
You've been a long-term shareholder of Amazon and once tweeted that you "didn't add but didn't sell" when it was down 90% from the dotcom peak. What was that experience like? How did you think about conviction and holding a stock through that kind of drawdown?
Michael: By way of background, I first learned about this company from Bill Gurley who at the time was part of the underwriting team at Deutsche bank who did the IPO. Bill was an analyst, now he's gone on to be a well-known venture capitalist. Bill just said, you should meet these guys because the way they think about things, even though this is a completely nascent industry doing completely different stuff, the language they're using is the language you're going to be familiar with. You're going to be excited about it.
In the late 1990s, I met Jeff Bezos and Joy Covy, the CFO. That 1997 letter, which they repeat every year, I think Joy played a large hand in writing that letter. I think Jeff certainly bought into it conceptually and I think that's really been their guiding light. Joy would just say to me, we’re big fans of Warren Buffett and Charlie Munger. We think about return on capital. We think long term. She's like, we're making investments that appear to be bad, but when you pencil out the numbers, we think we're going to generate really attractive returns. I bought into that.
The other aspect to Amazon, which has been much better than I would've ever dreamed, we wrote about it in the first edition of Expectations Investing, is this concept of real options. You can value a business based on what you can touch and feel today. But certain types of businesses have optionality; they may be able to use this business to get into ancillary operations that can be value creating. And we argued that you have to have a management team that's really attuned to creating and fostering and exercising these options appropriately. It helps to be a market leader. It helps to have financial flexibility and so on. Our original case study was Amazon. We said, they seem to have these qualities. And of course, you now look at the value, AWS, Amazon Web Services, is probably a big component of the value, which wasn't even a twinkle in Jeff Bezos's eyes when we wrote that back in 2001.
On the drawdowns, look, everything was down. It was down more than other stuff, but it is mostly because I'm lazy. I just thought like, it seems dumb to sell when it's down this much, if this is all true. And I was very influenced by a wonderful book by Carlota Perez that came out probably in the early 2000s where she talks about the interplay between technological revolutions and financial capital, one of the points she made was, it's often the case that the hard work happened after the financial bust.
The dotcom was just a classic example. We had this huge run up, tons of capital. And then we had this bust, three years bear market. We can say today very clearly that that thesis was correct, the internet has become woven into businesses in a way today than it certainly wasn't 20 years ago. A lot of competition gets wiped away. A lot of silly money gets wiped away. And this creates a very fertile ground for them to grow their business. And that turned out to be the case.
The other thing that is interesting about Amazon is they've had these fits and starts. They go through investment spurts, which tends to press earnings, and then they scale back and they flourish a little bit. And the stock makes these little runs. We're now in the mother of these investment processes. Through COVID they invested just a staggering amount of money, both in CapEx and in terms of operating expenses. Whether the returns will be there or not, I think, remains to be seen. But we're probably in the phase now where it's digestion of investment that has been made. And if that is executed effectively, that should lead to improved profitability with less capital hence good cash flows and so on.
I don't want to come across as a hero on this because it's mostly because I'm lazy. When I buy something I very rarely sell. By the way, I bought things that have essentially gone to zero. I don't want to come across as some sort of a genius. But the original conviction came from talking to those people and thinking about the business that way and sort of just sticking with it.
Frederik: One quality that's important in investing is curiosity and ability to learn and improve and adapt over time. You wrote recently an interesting piece on feedback and how people and organizations can learn and improve. What was your key takeaway from that paper?
One of the things that I have always observed is that in most fields, timely and quality and accurate feedback tend to improve performance. If you're a tennis player or a musician, you're likely to have a coach, even if you're an elite participant, you're likely to have a coach to help you in that process. The investment management industry is an industry that draws a lot of really smart people. The remuneration is attractive and so forth. It's a very competitive, interesting field. It's remarkable in the sense that feedback is very difficult to attain. In the long run it's portfolio performance and so on. But in the short run it's very, very difficult to do.
The question is, are there any mechanisms to give ourselves quality feedback? That got me going back to the very top. If you study, for example, Phil Tetlock's work on Superforecasting. Tetlock, a psychologist at the University of Pennsylvania participated, this is probably a decade ago, in a forecasting tournament that was sponsored by the defense department. And they invited people to participate on their team and they found that 2% of them, one in fifty were so-called superforecasters, people making really good forecast that were way beyond what chance would dictate. And they decompose what those people were doing. But if you talk to Phil and you say, well, what is the key? He's like, well, you gotta get the right people. That's the key, that's the first starting point.
So I opened the piece by talking about what are the right qualities that we would look for as investors? We drew on that superforecasting literature. We also drew on this idea of rationality quotient by Keith Stanovich. I think that's very powerful work. Stanovich has made this really interesting, and I think provocative, claim that there's a distinction between IQ intelligence quotient and what he calls rationality quotient, which is the ability to make good decisions. Along with some of his colleagues he developed a specific test to measure rationality. And if you look at the subcomponents of that test, it seems really consistent with what we would care about as investors.
The next question to ask is what can we train for? I was inspired there by conversations with an executive at a professional sports team. It was American football and he was talking about, in each position we try to identify four to six sets of skills that we think are key to elite performance in the national football league. And as it turns out, some of those skills are things that they could teach, they're coachable and other things, height or speed, are very difficult to actually train for. That's another interesting thing, are there cognitive analogs to these physical things that these sports guys?
The other interesting question is, in every domain elite performers tend to practice. Every sports team practices, every musician practices, every comedian practices. What is practice in investment management? How much time should we be allocating to that? It's a fundamentally interesting question. What you're doing is taking yourself essentially offline in order to be more effective when you come back online. That's what I'm going to say is practice or training. And there are lots of interesting questions that come out of that, topics like skill transfer. If I teach you to be a great poker player or backgammon player or chess player, are those skills going to map over to you as you are in your investing seat?
The second big thing we studied was how people are embedded in organizations. It's lovely to think that you're doing all these things by yourself and you've got the right attributes and so forth. But the question is once you're in an organization, does the organization enhance your ability to make decisions or does it detract? The work on this is quite clear that when you're working in a team, you want to get different points of view. And the biggest problem in teams and organizations typically is that dissenting views tend to get squashed.
Then the last part is the feedback. To bring this back full circle, what we argue is when you have an investment thesis to buy or sell something, that means you believe you're going to generate an excess return, or there's a mispricing in the market. And you're going to have a thesis and that thesis should have sub-components to it that will allow us to create a scoring system. The most common of these or known of these is called a Brier Score. Brier himself was a meteorologist. So you can imagine this was developed first for meteorologists who obviously are predicting rain or sunshine with certain probabilities. And then they observed the outcomes very quickly, to see if they're right or wrong. So that helps them get better calibrated.
To have a Brier score you only need three things. You need an outcome that we can agree upon, within a time period that we are finite, with some probability. And if you have those three things, you're in business to calculate a Brier score. And so my argument is break down your thesis and put it into some Brier score ready predictions. Again they're embedded there. You just have to surface them and start to keep track. And this doesn't have to be on a public score board or anything like that, you can just do this for yourself. But what I find is the very discipline of writing those things down will force you or compel you to think more about them and to think more deeply about them. For example, if you're assigning probabilities, you're going to immediately start searching for base rates.
The evidence shows that when people get feedback that's timely and accurate, they get better. So they get better at these probabilistic forecasts. This requires a little bit of discipline. It's not costly in terms of extra stuff. You're just writing things down effectively, but it requires some discipline. I think it's something our industry could do more of.
The other thing I'll say, when you make an investment or a bet on something and it doesn't turn out well, we're very skilled at telling stories as to why it didn't work out. We're very skillful as storytellers. And I think people are saying these things quite earnestly, but the question is whether we can do better than that? Instead of patching over our mistakes by telling ourselves stories, can we actually learn from what we’ve done correctly and what we’ve done incorrectly?
And by the way, sometimes you make a perfectly proper decision and the outcome is not good. Well, that's fine. That's also a very important lesson, which is, don't deviate from what you've done if over the long haul you continue to believe that will serve you well.
Frederik: In the piece you mentioned the term of the elite team. Teamwork is both more important than ever, but there's a new challenge with everybody being distributed. And the benefit of having a team work really well is high. What is an elite team, why are they special? And did you learn anything about how to create one?
Michael: This is a great question. Tetlock and his colleagues, when they did the Good Judgment Project, this forecasting tournament, they did a lot of really interesting things. They would say, well, if we train people well, will it help them or not. If we put them in teams, will it help them or not. And they have controls for everything, so they can compare it to what the other outcome would've been. What they found, and this is in terms of forecasting accuracy, is if there was no training, those people tended to do the worst relative to randomness, versus just flipping coins.
If they're trained, they did somewhat better. By the way, most of the training that's most effective relates to base rates. Even that core concept carries a lot of freight in terms of getting you to a better spot. Then they found that people operating in teams did better than the people even with training. Teams added value relative to even those individuals who were trained. The apex was that elite teams did the very best. So elite teams are now markedly better than an individual with no training.
By the way, this has been a watershed change even within my career, portfolios used to be predominantly run by individuals. Let's call it called 75, 80%. And that ratio now is completely flipped. Something like 75 to 80% of portfolios are now team run, which is in and of itself very interesting.
Can you harness the benefits of that team, all the good things about it without the bad things about it? If you think about teams, there are really three components that are essential. And when I say elite teams, or when Tetlock talked about elite teams, this elite teams in superforecasting. So these are the best of the forecasters working together. There are three important things. How big should it be? There's a guy named Richard Hackman, but he was an organizational psychologist most recently at Harvard, who made it like basically a life's work of the study and found that the optimal team's size was four to six. He also found that if you were going to make a mistake, three would be preferable to seven. Four to six seems to be the sweet spot. Hackman didn't really study investment organizations. He studied all sorts of organizations. This is something that's important for us to think about because it tends to be human.
The second is how do we compose the team? And here we get into the discussions about diversity, and they're typically defined as three types of diversity. The first is social category diversity. Age, race, gender, ethnicity, and so forth. And usually when you hear about diversity programs, it's almost always referring to those social category dimensions of a diversity.
The second type of diversity is called cognitive diversity. This is ways of thinking about the world. It's training, it's experience, it's personality. It's just what is unique that you're bringing to the party. I would just say that when you study the decision-making literature, what you find is that people will suggest that it is cognitive diversity that is the key to solving problems. This is what we're really after. Now I think one can make the case very seriously and quite rigorously that social category diversity contributes to cognitive diversity, but it is cognitive diversity that we're after. The third type of diversity is values diversity. You might think about it as a sense of purpose, and on that you actually want to be low. We want a common mission, even if we are of very different background, we're pulling in the same direction.
So we have four to six people, we have cognitive diversity. The third and final piece is how you manage the group. And this is usually where the mistakes happen. In most organizations there are people thinking things that are different than what's going on around them. But they're not going to say it. Leaders of teams often stymie this process by indicating what they believe. Here is the leader, he or she leans into one sort of solution, one sort of decision, and everybody else falls into line in the investment or in business.
It's truly rare to have consensus. If you have consensus, you should be asking what the heck is going on. Because there are too many different ways to think about this. If ask a team of people, where do you think will prices or interest rates be? If everybody said, oh, we all agree. That would actually put up a bunch of red flags. You'd be like, what the heck is going on here? You want people to have different points of view. The idea there is to make sure you have mechanisms, to make sure that you're thinking about distributions and potential outcomes and that you're weighting these things. So when you come up with a decision, you have a richer way of thinking about that.
The onus here is on the leader. The leader of that group has to make sure that he or she is surfacing alternative points of view, making sure that their people are expressing those views in an independent fashion. That as a group, everybody thoughtfully weighs those things. Not all ideas are created equally. Then you come to a solution based on all of that. When I talk to investment organizations and I say, oh, have you ever been in a meeting where you have a thought that's different than what the leader believes? There's usually not a lot of incentive to chime in on that.
Frederik: The room gets quiet.
Michael: The room gets quiet and you're better off suppressing your own views. The best leaders are those who purposefully draw those out and consider them, again going back to this idea of being open-minded.
Frederik: You recently republished an updated edition of Expectations Investing. You emphasize how closely corporate strategy drives a lot of the factors. Your audience are primarily professional investors, but what do you think are the lessons for somebody who's in the operating seat, a founder or manager?
Michael: Great question, Frederik. And I think they're on opposite sides of the same coin. I learned about the link between strategy and valuation from Al Rappaport. Rappaport's book called Creating Shareholder Value came out in 1986 originally and the new version of his book in 1998. The target audience for that book were corporate executives. Chapter seven of the original book was called something like stock market signals for managers. That was the audience he was speaking to. So how do we make this link really explicit? Well, the litmus test of a quality strategy is that it creates value.
You're an executive and you're thinking about various strategies. You're thinking about how you're going to spend your marketing dollars. You're thinking about expanding to this geography, raising prices, lowering prices, whatever it is. The question is, does it create value? At the end of the day, there could be other objectives, but that's the primary objective we tend to focus on. The other thing is if you're valuing something you need to understand the competitive position of that company within its industry to have a sense of the stream of cash flows. For a corporate executive for example, that's enormously relevant, for example, in M&A.
M&A we're going to buy X, Y, Z. We may identify synergies. But at the end of the day, we need to know that this is going to be a business that will live up to what it's already priced in, if we're going to pay a premium for it. It's absolutely the opposite side of the same coin. Executives of public companies in particular should absolutely understand the expectations priced into their stock. The first reason is that if they believe something that the market doesn't seem to be pricing in, they have a communication opportunity.
The second is if the market doesn't seem to be giving you credit for what you think you can achieve in terms of financial performance, you have an opportunity either to buy back stock, or, if you think the market's overestimating it, to sell stock. As a consequence, you can create value for ongoing shareholders by doing that well. I'll just say that most chief executive officers are not at all versed in this. This is the core element of capital allocation. They're just not versed in this. In part because the skills that required them to get to their seat as CEO were not these skills. I think I got this from Warren Buffett and others. When you become the CEO, you become chief capital allocator. And very, very few executives have been taught and know how to allocate capital.
Very few executives really understand how capital markets work. When you get to that seat, all of a sudden you have responsibilities and skills that become important that you may not have ever dealt with before. Will Thorndike wrote a wonderful book called the Outsiders about these eight CEOs who did an exceptional job. He's obviously picked people who did well, but the title of the book gives it away: these people are kind of unusual, of unusual backgrounds. They were often not traditional. And as a consequence, this was something that they embraced or somehow did naturally, which is really interesting.
These things absolutely go together and probably the funnel it leads to is capital allocation. As investors what are we doing? We're allocating capital. You give me a hundred dollars and I try to put it to its best and highest use. And if you're an executive, you have a hundred dollars, you try to put it to its best and highest use. I mean everybody's doing sort of the same thing and we're using the same way to figure it out, excess returns versus an opportunity cost. That's basically what we're all doing. It is absolutely applicable and obviously Expectations Investing is essentially taking the same ideas from creating Shareholder Value and flipping them for the investor, but the core ideas and the core drivers are all similar.
Frederik: Are there any hurdles for this idea to proliferate? Why do you think people are hesitant to adopt it or why hasn't it caught on more? Is it too difficult to find and understand the expectations or is it too counterintuitive?
Michael: This is a fascinating question because I actually set out to try to answer this before we republished the new version of the book. I had the same exact thought. First of all, in many other domains you see people do this almost as a matter of course. I've mentioned Steven Crist who has written a lot about handicapping. He wrote this chapter called Crist on value. For those who have not gotten to it, you should read it. You'll see that he's explicitly talking about fundamentals versus expectations. Fundamentals being how fast the horse will run. Expectations being what's on the board. He makes the point, it's not about the fastest horse, it's about where there are mispricings. That's the first thing, this absolutely does exist in other domains.
But when you turn to investing, I think that there's this sense of being in control. I went back and looked at this. John Burr Williams in the late 1930s wrote the first I would call it pretty foundational text on valuation. It was called The Theory of Investment Value, which is just such a wonderful sweeping title. And he laid out essentially the dividend discount model. There are lots of odds and ends that had not been figured out, but that core idea of Williams in 1938, that is still around today. Williams got some great quotes where he says, hey, you may want to use my model to figure out the value. But if you don't want to forecast, just take the current price and go backward and say what has to happen.
Keynes’s chapter 12 of General Theories is called The State of Long-Term Expectation. Keynes was on this. When you look at some of these great thinkers, they certainly were on it. But going back to today's investors, I think we all have the sense of being in control and being in control is me saying that this company is worth X and then finding gaps between X and where the stock price is today. And they're not mutually exclusive, but understanding what has to happen for today's price to make sense is just such a fundamentally attractive proposition. And then evaluating whether you think that those growth rates in sales and profit margins and capital intensity and return on capital that's implied, whether those things are plausible or not, it just makes enormous sense as an approach.
If you say this to people, everyone nods. It makes sense to everybody. But it requires a little bit of discipline and it's not how people were trained. It's not how they grew up. You go to an investment firm, they go okay, here's your industry, create a comp table, a comparative table. You're going to compare this company versus other ones, and you're going to compare it on price to earnings ratios, and price to book, and enterprise value to EBITDA, or whatever other metrics. That's how people are trained to do it. What looks cheap, what looks expensive. It tends not to be part of how people think about these things.
The last thing, there is technical stuff. We wrote a piece many years ago which we should probably do a reprise of. It was called common errors of DCF models (page 206 of Mauboussin’s work 2005-2011). If you just read most DCF sell side models, there just tend to be lots of flaws, both technical flaws and conceptual flaws. If you're a sell side analyst and you're publishing, you have the answer in your head and then you create a model that solves for your answer. You’re not really doing it the other way around. People are not doing these models with the complete integrity that they probably demand.
Frederik: You recently tweeted about Stanley Druckenmiller's chat at the Ira Sohn Conference. He's not your typical long-term fundamental investor. And yet you pointed out that there were quite a few things he does that tie in with the concepts that you use.
Michael: Thank you. And first thing I'll say is I want to communicate how much I appreciate all the work you do. It's been a great benefit for all of us in the investment community. What Stan Druckenmiller and George Soros have done over the years is very different than the kinds of things that I think about or the kinds of things that I've taught, for example. When you observe very successful people over very long periods of time in these probabilistic fields, they tend to have certain attributes that are worth all of us paying attention to.
One is this idea of base rates. Druckenmiller doesn't use the term, but he clearly understands the concept, which is saying, I'm looking at a particular situation, is there a reference class? Is there some sort of a past pattern of outcomes that will help inform me about the decision? There's another really important skill there, which is understanding when that reference class might have changed. And so he doesn't look at it as chiseled in stone. He looks at it as a flexible dynamic thing.
He had this one phrase where he says we have to operate with ruthless discipline and open-mindedness. Those are other qualities that I think are really important. It's very often the case that investors have very good investment processes, certainly on paper that look terrific. Where some of us struggle is execution. That's where that ruthless discipline component comes into play. And the one thing you find across almost every great investor is this idea of curiosity, which leads to this idea of open-mindedness.
Curiosity really is, I want to understand how this thing works and how I can make sense of it, and then hence potentially how can I profit from it? Whether that's Jim Simons at Renaissance Technologies or Warren Buffett at Berkshire Hathaway, those guys share that fundamental curiosity. Druckenmiller has all those things in droves.
He seemed to be very sensitive about what he thought he knew and what he thought he didn't know, which I thought was quite interesting. He was very comfortable creating a limit to his understanding. Those characteristics are common among everybody who's successful in probabilistic fields. It's not just investors, but if you look at, for example, successful poker players or handicappers, sports team managers, they share many of these same qualities. Whether or not you're doing that type of investing yourself or that fits your personality, there's still a great deal we can draw from it.
Frederik: You mentioned one more concept. Druckenmiller says, I have to know whether I'm hot or cold. You pointed out a related concept: “A better parallel is "bursts of high impact works occurring in sequence" in creative fields. That's a more accurate analogy, IMHO.”
Michael: There's been a decades-long debate in sports about this idea of the hot hand. If you're an athlete, or if you are a fan, it's something that you feel. As an athlete myself, I certainly had those sensations. The question is, is this a statistical property that's important? Amos Tversky wrote a very famous paper saying that there was no such thing as a hot hand. That was the received wisdom for many decades. More recently with much better data and better statistical techniques, others have demonstrated there in fact is a hot hand.
However, it's just not that big a factor. It's not insignificant, but it's not that big a factor. Druckenmiller described a situation where he said, Hey, sometimes I'm feeling it. I'm seeing the ball. I know what's going on. And I feel like I can press what I'm doing quite aggressively. And then other times I don't feel as much in sync. I thought that there's actually an interesting side literature on bursts of creativity in creative fields. Think of any kind of a creative field and many creative people tend to go in fits and starts.
I thought that what Druckenmiller was describing was a little bit more like that creative field, where things seem to line up for you. You seem to understand what's going on. You seem to be very productive. In other periods, things feel a little bit less in sync and you may be inputting, but nothing sort of clicks into place. And then you go back and forth.
Frederik: Are there any fundamental ideas that you've changed your mind on? Anything where you’ve discarded a model or an idea?
Michael: The one that comes to mind first is an understanding of markets and market efficiency. I lean toward the Chicago school. I like all that stuff, the market efficiency stuff. If you had asked me probably close 30 years ago, I very much aligned with that. It made a lot of sense and I understood that there were limitations to it. But that would be my default and then I'll look for exceptions. Then I was introduced to the idea of complex adaptive systems. My education mostly came through the Santa Fe Institute. And when you start to understand the fundamental components of complex adaptive systems, there's no way to look at the stock market the same way again, personally.
A book which I'd recommend everybody should read, it's been around for a while, is James Surowiecki’s book, The Wisdom of Crowds. The wisdom crowds captures the essential features that we care about. The wisdom of crowds would say, crowds are wise when there are a diversity of agents, there's a properly functioning aggregation mechanism. To tie this back to teams, when we say that people don't say what they think, what we're saying is information's not being aggregated. And then incentives, which is rewards for being right and penalties for being wrong. When those things are happening, you get wisdom crowds. We can demonstrate it in the classroom and elsewhere, that works really well.
And the new version of expectations investing, gave us an opportunity to reflect on the last 20 years. You mentioned the public to private, that was certainly a component of it. The other one that we've been spending a lot of time on these last few years is the rise of intangibles. When I grew up, certainly when I started in this business, investments were dominated by tangible investments, so physical assets. And intangibles were of course always on the scene but not quite as prominent. In the last couple decades we've seen a complete flip there. Intangibles now are the dominant form of investment. And that's important because the accounting is different. That's important because the characteristics of intangible assets are different. Economists have understood this for a long time, but they're now more important. That's a whole other area where, if you said to me a company's profitable or unprofitable, I would say that unprofitable is bad, almost uniformly. And now recognizing there's a lot more nuance in that. You can be unprofitable for the right reasons or unprofitable for the wrong reasons and making that distinction is actually really valuable.
Frederik: You've been teaching for a long time at Columbia, the Securities Analysis course. Is there anything that stands out to you in terms of being an effective teacher?
Michael: I don't know if I am an effective teacher, but the great teachers I have known are great students. Being a great student means you're constantly learning and you're excited about what you're doing. I've never lost enthusiasm for the topics we're talking about. I think this stuff is infinitely fascinating. The course is broken into modules on market and market efficiency, including an examination of the performance of professional investors. A lot on valuation, a lot of competitive strategy, which also incorporates things like capital allocation and finally decision making. These are all fields where we don't really have the answers to almost anything. We're still working on all these things.
The other thing I'll say, this is a communication thing. The key to me to be comfortable is to be really prepared. I spend a lot of time on preparation so that when I'm presenting ideas to the students, and I'm sure I get lots of things wrong, but I'm very prepared and excited about the topics. That enthusiasm and preparation I'm hopeful comes through.
I did a little tweet thing last couple weeks about how the course has changed over 30 years. It's interesting to reflect back on. Part of it has been revealed in research. Research on finance, economics, and strategy marches along. But also it is what was I not aware of that I should have been aware of that I've now integrated in what we're doing.
Now I'm at the point in the course where I'm trying to par it back because I want to strip it back down to the core elements, and leave other stuff to be ancillary because there's so much material to try to master in a short period of time. To be a great teacher, an effective teacher, it's about being a great student, be a great learner yourself. And I think that comes through I think if you're doing it well.
Frederik: If you consider yourself a great student, where are you going right now to learn? What are you interested in? And how do you filter, how do you decide what areas to focus on?
Michael: I didn't say I was a great learner. I aspire to be a great learner, but I'm not sure that I am. I wish I could say I'm more disciplined on this than I actually am. I just meander around a fair bit and you can actually follow the research we publish. You can see how I'm meandering about. From time to time, there are topics that either I have revisited or things I talk about or pontificate about, but really haven't done a lot of work on. For instance, capital allocation. For years and years I would tell my students, oh, capital allocation is the most important thing, and you should really pay attention to it. And then Will's book came out and for all the wonderful things about Will's book, it wasn't like a comprehensive discussion of capital allocation.
It was a celebration effectively of people who had done it really well. So I'm like, you know what, maybe I should actually do serious work on this. That led to our big piece on capital allocation. And we hope to have something else on that at some point in the not too distant future. The other example was total addressable market. Everyone was like, TAM is this, TAM is that. And I'm like, where do these numbers come from? Is there a way to do this effectively? So we sat down. If we're really to do this seriously, how do we do this? And we appeal to things like base rates. And we used diffusion models and we trained and emulate a few different techniques to try to come up with what we thought would be an effective way to think about and measure TAM.
A lot of it is just nuance. We're working on a piece now. If you think about competitive strategy, obviously we're looking for businesses that are unique and will have competitive advantage over some period of time. But the reason you do that is because it ends up having an outcome. And the outcome is typically that the customers are loyal and they're happy and market shares are attractive and your profitability is good and so on. The question is, can you go to any of those outcomes? For example, we focus in on market share and say, if I just examined the market share, I'm going to show you nothing but the market share distribution in this particular industry, would you be able to say anything about the competitive positioning of the companies or the industry itself?
Not just a snapshot of today's market share. You have to look at the market shares over time, how they evolved. Are they more or less stable? So I think we're always going to have a list of things. Our list of things to work on never seems exhausted. There's always something else to work on. We're going to have something more on capital allocation. We'll probably come back to the DCF thing. It's never ending. In our industry this is the nature of what we do. It's just inherently fascinating. Because it's the intersection of business and people and psychology and sociology and numbers. There's a lot of macro factors. There's a lot of stuff that always makes sure you never have the game beat, never.
Bonus section: Deep dive into the investment process
On sizing investments:
Michael: There's one other thing [Druckenmiller] talked about and it was about position sizing. Broadly speaking when you're trying to maximize your returns, you need two things. One is you need some sort of an edge. Edge means you have a belief or a mathematical advantage that's not reflected in the current odds or in the market price. The second thing is how much you can bet on that when you have that advantage. And the intuition is quite straightforward. If you had perfect information, you knew your bet was going to make you money. You would bet everything you could, right?
And then there are degrees of certainty about that. So there's this relationship between edge and betting size, and that leads to your total ability to generate excess returns. He has this sort of zinger, where he says, people said, what did you learn from Soros? And he said, the main thing that he learned from Soros was that position sizing was 70 to 80% of the game. The reason that struck me is because, first of all, purportedly George Soros made money on fewer than 30% of his trades. And that alone is worth letting settle in a bit. And he's one of the great investors of our time. So what does that mean?
It means that he made a lot of investments that lost money. They probably did not lose much money. And when he did make money, he made a lot of money, both by betting a lot of money and by letting it run simultaneously. That I thought was a really interesting lesson.
Speaking with a lot of my friends in the industry that work, for example, at these multi-strategy firms, these big overarching wrapper hedge funds. They have many little investment pods within them. They can observe effectively dozens, in some cases, hundreds of little investment teams operating simultaneously under their roof, and they can examine their performance of course and how they got there.
These guys will go through quantitatively, a decomposition of the returns. By the way, they do generate, pre-fees for sure, alpha on average, which is a measure of excess returns. But what they found was that essentially all return came from security selection and specifically stock picking and very little came from sizing, portfolio construction. They said, basically 1 out of 10 portfolio managers add value through that. I think that's a really interesting observation that here we have George Soros and Stanley Druckenmiller, two legendary investors who say that this is the main thing that drives their returns and results over a long period of time.
Whereas we look at the real world, we find that most people don't create a lot of value from sizing and it's all security selection. The question is can we bring those things together to some degree? Can for instance a regular discretionary portfolio manager improve by thinking about and being more systematic about position sizing? I just throw that one out there as an open question, but that is an interesting and stark dichotomy between how he got to where he is and how most portfolio managers get to where they are.
Frederik: A lot of analysts ultimately want to be portfolio managers, but whereas there is a lot of training for how to be an analyst, there's much less for how to be a portfolio manager. For example, Druckenmiller learned it from a mentor, but you're not guaranteed to have a mentor who's either good or willing and able to teach you. You've seen a number of different investment organizations from the inside. You interact with a lot of professional investors. What have you learned about the relationship between analysts and portfolio managers and that transition?
Michael: It's a fabulous question. You're right, most analysts aspire to someday be a portfolio manager. And as you point out correctly, the sets of skills are somewhat different. And so some organizations by the way do a great job of grooming and teaching analysts to be great portfolio managers, other organizations do less of it. There are a couple things to point out. One is that when you're an analyst, you're more focused on what I would call depth versus breadth. You're going to go deep into a particular industry or sector. You're going to be the resident expert. Many funds would want their analyst following a company or industry to be the most thoughtful and detailed and most knowledgeable about that particular sector.
When you're a portfolio manager you don't have time to allocate to doing that. You have to rely on others. You're more about breadth. You have to understand how to construct a portfolio, being able to understand how to look across different industries in order to put something together. Breadth versus depth is really important. One of the big outcomes of that, and this is something I stress a lot with my own students at Columbia business school, is that usually a very good portfolio manager will be able to focus on the two or three issues that matter most for a particular company. And they're very good at identifying those and honing in on those. And as a consequence, they leave aside a lot of extraneous information and details and focus on what really matters. That's a key skill. I don’t know if you can teach that, but that's a big one.
The second thing is what we just talked about. Even if you think you can identify securities that are attractive, you have to put them together in a portfolio that's good. That has to do with portfolio construction and sizing, and how you think about issues like diversification. There are lots of discussions about concentration versus more diversified portfolios, but you have to have a point of view and a way to think about all those things that are really useful.
The last thing I'll mention, which I find interesting. This is academic research that mostly comes out of the mutual fund complex. Let me just underscore that. The reason it's mutual funds is because we have a lot of data. It's been around for a long time. It's relatively big. And so this may not apply broadly speaking, but it does apply for mutual funds. And what they found was older portfolio managers tended to do slightly worse than newer ones in part, because they stopped listening to their analysts.
Turns out analysts do add a lot of value or can add a lot of value in an organization, but PM sort of figured that they're a little more seasoned and they sort of figured it out. And the argument is that listening to the analysts would have benefited their performance overall. That's another thing, to stay in tune as a portfolio manager. You may think that you're sort of sitting on top of the heap, but just to recognize that depth does have value in some ways, and just continuing to integrate that breadth and depth as skillfully as possible is really important. It's a very different set of skills for sure. And I think many of them are teachable, but it's not for everybody.
Frederik: Are there any common themes where analysts get off track or common mistakes? What do all analysts have to pay attention to?
Michael: You want any investment organization to have a reasonably well articulated approach to how they think they're going to generate excess returns. There are myriad ways to do that. From Jim Simons at Renaissance Technology, which is employing scores of PhDs, highly mathematical and lots of trading, to Berkshire Hathaway. These guys sitting around and reading all day and making relatively few but very substantial decisions. And there's everything in between those two things.
The first thing is to think about why you think inefficiencies are going to arise, how you as an organization will take advantage of those things, how you're structured to do so. That's the first big thing. Once you've laid that out, you want to align the activities that you're pursuing as an organization, the term I use is congruent, to be congruent with that. So they're consistent and they're supporting it. I think the problem is often that people stray from that. They don't do what they say they're supposed to do. And it's easy to get drawn away from that and think about stuff that's extraneous to your process.
There was a letter from Seth Klarman at Baupost to his shareholders. He said, we aspire to the idea that if you lifted the roof off our organization and peered in and saw our investors operating, that they would be doing precisely what you thought they would be doing, given what we've said, we're going to do. It's this idea of congruence. It's very easy for people to stray. That goes back to our ruthless discipline. Making sure you're focusing on what you're supposed to be doing
There are technical things you need to be able to do to be an effective analyst. You need to make certain calculations the right way. You need to think about things clearly. I you're going to talk about return on invested capital, you should calculate that correctly. If you're going to talk about free cash flow, you should calculate that correctly. Those things should be done uniformly and correctly across organizations. That's often not the case. You're the portfolio manager and analyst A comes in and says, this company's got an 18% ROIC and analyst B comes in and says, this one's got a 32% ROIC and they're calculating them in totally different ways. That's not going to be very helpful.
When I've interviewed analysts or portfolio manager for that matter, I would often just ask them lots of questions about how they approach things like valuation, how they select the multiples they use, or how they do their calculations in order to understand that they've just got their technical skills down appropriately. And it's remarkable how many people don't do that.
Frederik: I love this idea of being able to pull up the roof and see what's actually happening, versus sitting in a meeting and it's either a sales pitch or they believe it, but it may or may not be happening. What would your advice be to people who have to select managers and are confronted with this conundrum that it’s almost as hard to pick a manager as it is for the manager to make investments?
I would first want to understand a process and how it rolls up into what we deem to be excess returns. And so you can be pretty straightforward about going through the details of this. One way to think about this is called the fundamental law of active management. The fancy formula is “information ratio equals the information coefficient times the square root of breath.”
In plain words, it says excess returns are a function of skill times opportunity set. If an investor hopes to generate some sort of an excess return, you might use that as a guideline to break down the fundamental law of active management and ask if they've got the components in place.
Information coefficient is a measure of skill. If you project something, does it come true? It's a measure of calibration in your skill, but you can also break that down in terms of batting average and slugging. This goes back to our conversation about Druckenmiller. Batting average is a measure for every 100 investments you make, what percent go up, literally just go up versus what go down. So we're measuring that. And then slugging is how much money you make when you make money versus how much money you lose when you lose money. And of course you can have a low batting average if you have a very high slugging rate. If you have a low slugging rate, then you need a high batting average. I'd want to understand exactly how they're thinking about that and that ratio.
Breadth is the other one. One of the ways we measure breadth practically is through the concept of dispersion. How much variation is there in stock price returns. You want to know the dispersion of the asset class in which that investor is participating, and to see if the dispersion is sufficiently large for them to express their skill, and whether that dispersion is widening or narrowing. So that's one way to have a systematic way to break down what a particular investment process looks like. And then you're going to focus on the people. Do they have the intellectual curiosity, the humility, are they hardworking?
For example, if you have a low batting average, just slightly over 50, and you have very low slugging, you need a lot of opportunities. As a consequence, those are organizations where people have to be constantly churning for new ideas. By contrast, if you have an organization that says, we're going to be relatively concentrated, we want a high batting average, and we want an even higher slugging average. They're going to have to find gems of ideas, but they're not going to find a ton of them. Then just making sure that everything seems to be aligned. Then the last thing, I think everybody in the world knows that performance is only one indicator of skill.
I think we all have a tendency when a manager is underperforming to think he or she doesn't know what they're doing. And when they're outperforming, we think that they’re geniuses. And of course, there’s so much noise, especially in the short term that tends to be very misleading. So trying to keep your head above all that fray to understand and think about longer-term processes, I think is a really big deal. And you can do this through simulation or whatever, but it should be very clear that even skillful managers will definitely underperform for stretches and even unskillful managers will do very well for stretches and sticking to the program is really important.
Frederik: There's a secular theme that you've written about in depth, the shift from public to private markets. How you think about your tool belt of concepts and ideas and how it applies to people active in private markets, where the rules are a little bit different, the feedback loops are fairly long. You can't just select any security, you have to get into a deal.
Michael: We wrote a report called Everything Is A DCF Model. I was arguing that these different asset classes and perhaps different heuristics notwithstanding, we need to recognize at the end of the day, an investment is an outlay today in return for more cash in the future. And, after adjusting for inflation, hopefully you earn some appropriate rate of return for the risk you're assuming. I never want to stray too far from those fundamentals. I believe that it applies across the spectrum of asset classes you just described. Second thing, we've had a 40 year secular bull market in bonds. Rates have come down and, it's not quite as simple as this, but basically expected returns for a lot of different asset classes have drifted lower.
At the same time, liabilities have typically not drifted lower. If you have to put a kid through college or save for your own retirement, or if you're an endowment, you're seeking to fund scholarships or the operations of the institution, your liabilities have not gone down. As a consequence, a lot of these pension funds and endowments, and even in our own personal accounts, have to pursue a little bit riskier strategies. Buyouts and venture help achieve that by pushing you out on the risk spectrum. Buyouts predominantly through leverage financial leverage. The premise is you buy this business, you can improve the operations, but there's a kicker from financial leverage. Ventures simply by getting in at earlier stages. And earlier stages come with the higher risk, of course.
Now, the other thing to think about is when you think about venture and buyouts versus public markets, is the trade-off between control and liquidity. In public markets, we have the benefit of liquidity, which is if we screw it up, we can reverse our decisions quite readily. It's not costless, but it's not that costly to do that. By contrast, if you're a buyout firm or venture firm and you make an investment, it is often very difficult to reverse that.
The last thing that's gotten a lot of attention recently, I think folks like Cliff Asness has correctly talked about this, which is, there seems to be this psychological component to private markets in general, which is their marks are not based on markets. Their marks are based on what the general partner says they are. They're obviously using some sort of benchmarks and have to justify what they're doing, but there tends to be inherently less volatility in those marks than there would be in public markets. And on one hand that's not realistic because if they had to liquidate those investments, for example, they would not be able to do it at the price at which they've marked it. But the flip side is it actually creates some sense that the returns are pretty good for the risk people are assuming, and it keeps the limited partners in their seats. The very fact that they're locked up and see less volatility, even though they are by definition in riskier assets, it keeps them from making suboptimal decisions.
This mirage of lower volatility creates essentially what ends up being an effective psychological technique to keep people in their seats. So we talk about the illiquidity premium. The illiquidity premium says that assets that are illiquid should earn a higher return, so they should get a lower multiple to compensate for that lack of liquidity. Now it seems like this illiquidity premium is flipping around, that people are not looking for a higher return.
Thank you very much, Michael!