Michael Mauboussin: Finding Easy Games
The author and financial expert discusses 'expectations investing,' the problem he sees with valuation multiples, the outlook for active investing, and more.
Our guest this week is Michael Mauboussin. Michael is the head of consilient research at Counterpoint Global. Before joining Counterpoint Global in January 2020, Michael was director of research at BlueMountain Capital Management and prior to that held research leadership roles at Credit Suisse and Legg Mason Capital Management. Michael is the author of three books including The Success Equation: Untangling Skill and Luck in Business, Sports, and Investing and is also coauthor with Alfred Rappaport of Expectations Investing: Reading Stock Prices for Better Returns. He has been an adjunct professor of finance at Columbia Business School since 1993 and is on the faculty of the Heilbrunn Center for Graham & Dodd Investing. Michael is also chairman emeritus of the board of trustees of the Santa Fe Institute. He received his bachelor's degree from Georgetown University.
The Success Equation: Untangling Skill and Luck in Business, Sports, and Investing, by Michael Mauboussin
Expectations Investing: Reading Stock Prices for Better Returns, by Michael Mauboussin and Alfred Rappaport
More Than You Know: Finding Financial Wisdom in Unconventional Places, by Michael Mauboussin
Consilience: The Unity of Knowledge, by Edward O. Wilson
“Charlie Munger’s System of Mental Models: How to Think Your Way to Success,” by Andrew McVagh, mymentalmodels.info.com, Aug. 7, 2018.
“Increasing Returns and the New World of Business,” by W. Brian Arthur, harvardbusinessreview.com, July-August 1996.
“Why Foxes Make Better Decisions Than Hedgehogs,” by Kevin Sookocheff, sookocheff.com, July 15, 2021.
Jonathan Baron, Professor, University of Pennsylvania
Active Fund Success
“Turn and Face the Strange: Overcoming Barriers to Change in Sports and Investing,” by Michael Mauboussin and Dan Callahan, morganstanley.com, Sept. 8, 2021.
“Dispersion and Alpha Conversion: How Dispersion Creates the Opportunity to Express Skill,” by Michael Mauboussin and Dan Callahan, morganstanley.com, April 14, 2020.
“The ‘Paradox of Skill’ Adds to Active Management Woes,” by Christine Idzelis, institutionalinvestor.com, Sept. 17, 2020.
Triumph and Tragedy in Mudville: A Lifelong Passion for Baseball, by Stephen Jay Gould
“Looking for Easy Games in Bonds,” by Michael Mauboussin, bluemountaincapital.com, April 16, 2019.
“Do Individual Day Traders Make Money? Evidence From Taiwan,” by Brad Barber, Yi-Tsung Lee, Yu-Jane Liu, and Terrance Odean, Berkeley.edu, May 2004.
Creating Shareholder Value: A Guide for Managers and Investors, by Alfred Rappaport
“Market-Expected Return on Investment: Bridging Accounting and Valuation,” by Michael Mauboussin and Dan Callahan, morganstanely.com, April 14, 2021.
Security Analysis course taught by Michael Mauboussin at Columbia Business School
“The Math of Value and Growth: Growth, Return on Capital, and the Discount Rate,” by Michael Mauboussin and Dan Callahan, morganstanely.com, June 9, 2020.
“Public to Private Equity in the United States: A Long-Term Look,” by Michael Mauboussin and Dan Callahan, morganstanley.com, Aug. 4, 2020.
“How the Parting of Two Market Forces Helped Spur the Equity Rally,” by Michael Mauboussin, ft.com, Feb. 8, 2021.
Business Quality and Capital Allocation
“Thoughts on Cost of Capital and Buffet’s $1 Test--Part 1,” by John Huber, sabercapitalmgt.com, Oct. 30, 2017.
“Return on Invested Capital (ROIC)--Michael Mauboussin on Investment Concepts,” anthenarium.com.
“Michael Mauboussin on Capital Allocation and Value Creation,” anthenarium.com, Nov. 29, 2019.
“Chancellor: Tech Growth Comes at Irrational Price,” by Edward Chancellor, reuters.com, Sept. 9, 2021.
“Categorizing for Clarity: Cash Flow Statement Adjustments to Improve Insight,” by Michael Mauboussin and Dan Callahan, morganstanley.com, Oct. 6, 2021.
Other and Recommended Reading
Aswath Damodaran, Professor of Finance, Stern School of Business
The Warren Buffett Way, by Robert Hagstrom
Warren Buffett: Inside the Ultimate Money Mind, by Robert Hagstrom
Jeff Ptak: Hi, and welcome to The Long View. I'm Jeff Ptak, chief ratings officer at Morningstar Research Services.
Christine Benz: And I'm Christine Benz, director of personal finance and retirement planning for Morningstar.
Ptak: Our guest this week is Michael Mauboussin. Michael is the head of consilient research at Counterpoint Global. Before joining Counterpoint Global in January 2020, Michael was director of research at BlueMountain Capital Management and prior to that held research leadership roles at Credit Suisse and Legg Mason Capital Management. Michael is the author of three books including The Success Equation: Untangling Skill and Luck in Business, Sports, and Investing and is also coauthor with Alfred Rappaport of Expectations Investing: Reading Stock Prices for Better Returns. He has been an adjunct professor of finance at Columbia Business School since 1993 and is on the faculty of the Heilbrunn Center for Graham & Dodd Investing. Michael is also chairman emeritus of the board of trustees of the Santa Fe Institute. He received his bachelor's degree from Georgetown University.
Michael, welcome to The Long View.
Michael Mauboussin: Jeff, great to be with you and Christine today.
Ptak: Well, we're thrilled to have you. Thanks again so much for joining us. We really appreciate it. I wanted to start with consilient research. You head up consilient research at Counterpoint Global. Can you talk about what consilience entails and how it can benefit investment decision-making in practical terms?
Mauboussin: Absolutely, Jeff. And I think it's actually quite timely, because the inspiration for the term “consilience” was a book by Ed Wilson, E. O. Wilson, who just passed away last December of 2021, so just very recently, in his early 90s. He was a very influential biologist and probably the world's foremost expert on ants. And in the late 1990s, he wrote this book called Consilience. And he argued that much of science had made huge progress through reductionism, breaking things down into their components. But he felt much of the future of science and scientific progress was going to be by taking different disciplines and bringing them together. And in fact, the most vexing problems we face in our world today are those that require interdisciplinary approaches.
So, consilience was something that struck a chord with me, and I think that it's also very consistent with what Charlie Munger, Warren Buffett's partner at Berkshire Hathaway, has talked about the mental models approach. And the way I like to think about this is building a mental toolbox. So, consilience is really about learning key ideas from various disciplines, so when you're faced with a particular problem, you can pull the right tool or sets of tools out to solve that problem most effectively.
I've been affiliated with the Santa Fe Institute for about a quarter century. And back in the mid-1990s, I learned from Brian Arthur, an economist there, about the concept of increasing returns. And this is an example of something that was not in the mainstream of economics. In fact, Brian was considered to be heretical for sort of fostering this belief. But he felt it was very important, especially as information goods or information businesses became more important, intangible businesses became more important. And I was able to learn about that fairly early and to understand where that type of increasing returns might be at play relative to decreasing returns, which were taught in microeconomics. So, there's an example of learning about someone from someone who's a little bit out of the mainstream to some degree and being able to see how to apply that to specific types of businesses. So, there's one example. But there are many, many more. And I think the idea is to have, again, a very full toolbox in order to think well about the world.
Benz: What does it look like when an organization really embraces consilience? And how might that be evident to outside investors?
Mauboussin: Christine, it's a great question. And I think you guys probably have a sense of this. Phil Tetlock, who's a psychologist at University of Pennsylvania, riffing off of Isaiah Berlin and others, talks about this distinction between hedgehogs and foxes. So, hedgehogs are those people who know one big idea, and you can throw anything at them and they're going to fit it into their worldview in some way, shape, or form. Foxes, by contrast, are people who know a little bit about a lot of different things, and they tend to be more flexible, more malleable. So, I think it's that fox mentality.
Typically, the way you'd see that is people who are really committed to learning all the time. And so, that often in our industry, of course, typically means reading, and not just the basic stuff we need in terms of business and finance and so forth, but also perhaps a little bit outside of the domain. So, reading different fields, whether it's psychology or parts of science or what have you, and literature, candidly, in order to make sure that they're thinking about the world in a very broad way. The phrase I really like to use the best is that organizations that are this kind of consilience are called actively open-minded. This is a term that was coined by Jonathan Baron, also at the University of Pennsylvania, about a really, I think, high-quality psychological characteristic. So, not only are you willing to entertain different points of view, but you actually seek them out. So, to me, that's the set of skills: It's this learning commitment; it's reading widely; creating an environment in the organization where people can disagree with one another where ideas get vetted versus more that hedgehog mentality--here's what we do, don't bother us with anything else.
Ptak: I wanted to turn to active investing. It's a topic that you've written at great length about and very insightfully at that. Many have attributed active stock funds' underperformance to closet indexing. Managers cling to their benchmarks to deny themselves the chance to meaningfully outperform. My question is, what role do you think incentives can play in inducing prudent risk-taking so as to avoid closet indexing?
Mauboussin: I think it's a big issue. And this is not just in the world of investing. If you look around the world, you see this same type of behavior. We recently wrote a piece in the fall of 2021 about professional sports and how many professional sports leagues and teams and coaches pursued historical conventions, even when certain analysis would say there are better ways to do this. So, I think that this is a big issue is that typically people are willing to give, forego some upside and potential performance in order to stay a hew to the benchmark. So, that is definitely a case.
Now, I will say that there are measures, and there are a lot of limitations to measures like this. But if you look at long-term trends in something like active share--which is a measure of how different portfolios are than their benchmarks--that had been drifting lower for some time, but in the last few years, it's stabilized and actually seems, in some cases, to be going back up a little bit for active managers. So, maybe some of this has been offset to some degree. But I think incentives are a big issue. And what you want to do, especially if you're looking at a manager, is to make sure that he or she has the incentives to go out and do something that's different in order to generate those excess returns.
Benz: You've written a lot about the role of skill in investing. But you authored a piece last year that highlighted the importance of dispersion to investment success. Can you talk about what you found and the implications for investors?
Mauboussin: I think we started that piece with the concept called the “fundamental law of active management,” which was developed by Richard Grinold and Ron Kahn many years ago. The fancy formula, which I'll just say, was information ratio = information coefficient x the square root of breadth. So, forget about all that for a second. And in English, what it says is, excess returns = skill x your opportunity set. So, saying this differently, you can be the most skillful person in the world, but the opportunity set is extremely limited; it's hard for you to express your skill. So, just imagine this as a crazy market, for example, where every single stock went up 10%. You could be the best investor in the world, and you just couldn't differentiate yourself from anyone else.
So, this idea of breadth, one of the simplest ways to think about that is the notion of dispersion. And dispersion is simply a way of thinking about how well the best stocks performed versus how poorly the poorest stocks performed. And what a lot of research demonstrates, and I think it's quite intuitive and obviously fits the fundamental law of active management, is that high dispersion allows skillful managers to express their skill and allowing them to generate better excess returns. And it's actually a fairly monotonic relationship, which is to say, low dispersion, hard to express; high dispersion expresses it pretty well.
So, when you review performance of managers, and you're trying to think about their skill contribution, it's really important to keep the backdrop of dispersion in mind. And again, typically, high-dispersion realms are where the best managers can express themselves. There are a couple noteworthy periods--actually, 2020 was a very high-dispersion year, and there was a fair bit of dispersion in performance of managers. And then, the last really big one was the late 1990s: 1999-2000. So, keep an eye out for dispersion, because again, it's hard to express your skill if you're constrained by a very limited opportunity set.
Ptak: One of the concepts you popularized is the paradox of skill, which holds that as a group becomes more skilled, then relative profit opportunities shrink, and the importance of luck grows. Do you think the rise of free trading platforms and the frenzy and things like meme stocks will alter the trend we've seen where skilled investors have been pitted against each other? Is that the sort of thing that could yield better results for active managers in the future?
Mauboussin: Jeff, it's a great question. And I think it's hard to get a good, great read on this early on. I'd love to get your take on this. But I think the answer may be potentially. So, let's just talk about the paradox of skill very quickly. The idea is that in activities where both skill and luck, contribute to outcomes, which is most things obviously, it can be the case that as a skill increases, luck becomes more important, which doesn't seem to make any sense on the surface. And so, the way to unpack that is to think about skill on two levels.
The first is absolute levels of skill. And I think when we look around the world, whether it's investing, of course, sports or business, I think we'd all agree that the absolute level of skill has never been higher. In other words, if I put you with the tools at your fingertips today as an investor back into the ‘70s or ‘60s, you could run circles around your competition. The second aspect of skill, those ones that are really pivotal for our discussion, which is relative skill. And what we've seen in all these same domains is relative skill has also narrowed. So, the difference between the very best and the average has shrunk over time. I, by the way, first learned about this from Stephen Jay Gould, an eminent biologist, actually a colleague of E. O. Wilson's at Harvard, where he talked about baseball of all things, and he talked about batting averages and the standard deviation of batting averages shrinking, again, not because players are not better today than they were a generation or two ago, but because they're more uniformly excellent.
So, taking this to an extreme, if everybody is completely perfectly skilled at the same level, then the outcomes are going to appear to be essentially random, a coin toss. So, that's the idea of the paradox of skill is to say that in areas that are very competitive, very skillful, and very uniform skill, the results are going to appear to be random, even though there's an enormous amount of skill going into things in the first place. So, how does that express? Usually, we look at the standard deviation of alpha, candidly, and that had been trending down really since the 1960s. There's been a little kick up recently, interestingly, in the last couple years.
I want to now refer to your second point, which is really what you want as an investor is to take one step back and say, in one sense, investing is a zero-sum game. Markets go up over time, so, everyone can participate in that. But if you're looking at performance, a performance is a zero-sum game, which is to say, if you're going to generate an excess return, I have to underperform in the equivalent amounts, because we know that excess returns net to zero, by definition. And so, what you're really looking for is what we always call the easy game, which is participating in such a way that you are competing against weaker players. There is a very rich literature demonstrating, and I think quite conclusively, that when institutions compete against individuals, institutions tend to generate the excess returns relative to those individuals. There's actually a beautiful paper by Brad Barber and Terry Odean about trading data in Taiwan. There's really nice literature on this in initial public offerings. So, this is a pretty well-known concept. And it just invokes a really important idea for any kind of manager, investment manager--we called our report “looking for easy games,” you want to look for an easy game.
I'll tell you one very quick story. I was preceded as chairman of the board at the Santa Fe Institute by a guy named Jim Rutt. And Jim, in his younger days, was a poker player--this was before the big poker boom--but he was a poker player, and he'd spend his days learning about the mathematics and poker tells and so forth. And by night, he would play, and as he got better, he played in more difficult and difficult games and typically higher stakes games. And he was doing OK on balance. But, of course, it got harder as he got to more advanced levels. And then, one day, his uncle pulled him aside, and he said, “Jim, I would stop focusing at getting better at poker and start focusing on finding easy games.” So, actually, playing where you're the most skillful player at the table is the best way to ultimately make money. So, I think that's a really important backdrop for thinking about investing is, can you sit down at the table and be the one who is the most skillful--and again, it's a probabilistic statement--but the most skillful and an opportunity to generate excess returns.
Benz: Well, speaking of that, and speaking of easy games, we've interviewed several portfolio managers who specialize in Chinese stocks, and they've highlighted the large role that retail investors still play in that market. That's created opportunities that managers have been able to exploit and that's led to very high success rates when compared to markets like the U.S. So, why don't more investors target deep pools of excess return like China's instead of trading in large but less-target-rich markets like the U.S.?
Mauboussin: It's a great question, Christine. By the way, I one time had a conversation with a quantitative manager, and they said that they had a systematic strategy but it traded in China and against Chinese individuals. And they said, it was like a little money faucet. Every day they would turn it on, every day, they would make money. Typically, the problem with these things is they are very difficult to scale. The pools are not big enough. And so, the stakes are usually smaller. And going back to my poker analogy, if you want to play for big stakes, you have to play at big-stakes tables, where the skill generally tends to be higher. And by contrast, if you're a great poker player, and you go play in the small-stakes tables, you're going to clean up, but the dollars that you make are not that great. So, I think, that's the trade-off challenge is usually where these easy games exist, tend not to be very large markets. And the larger markets where the big dollars can be made, tend to be more skillful. So, that's the tension that you always run into when you think about finding the easy games.
Ptak: And that's actually one, I would say, advantage that individual investors probably boast over institutions is that scale for them isn't quite the obstacle that would be for an institution that's trying to put to work vast sums of money. I wanted to build on that and ask you about individual investors. Apart from finding easy games, like you mentioned, what are some of the other key things that you think that they should focus on if they're committed to successful active investing? I would imagine one of those is going to be time horizon, perhaps another one would be consilience and being open to new ideas. What else would you cite from the work that you've done?
Mauboussin: I like that list, Jeff, a lot. And the first thing I should just say is, I think it's very important, especially given what we've seen in markets in the last, call it, 24 months, very important to underscore the difference between speculation and investing. So, speculation is buying something in the hope that it's going to go up. We've seen, by the way, even things like options markets, lots of activity. There's no moral judgment about that. But I just want to say if you're speculating, perfectly fine. By the way, it's got some even societal benefits. But you're not investing, just to be clear. And I think a lot of people--and certainly people who have come into the market--have been speculators versus investors. Investor is thinking about the world as if you're buying part of a business, a piece of a business, and typically tends to have a longer time horizon.
So, Jeff, I would echo many of the things you just said. I think, it's typically helpful to invest in a business that you understand, or you could articulate what they do, the most core aspects. The second is to identify businesses with good returns on capital. So, that may take a little bit of calculation, although a lot of services will do those calculations for you and provide guidance in that regard. I do think thinking about things in the long term is very helpful, so not thinking about short-term noise, and in fact, almost using the short-term to your benefit. In other words, if you find a business you really like, you think the prospects are attractive, and it is underperforming for some short period of time for some sort of near-term set of concerns, that may be the ideal time to buy it. So, I think it's those kinds of things that I would point to. There's no easy one on this one. I think it's just the basic stuff.
Benz: You recently revised and updated Expectations Investing, which is the excellent book that you cowrote with Al Rappaport back in 2001. For those unfamiliar, can you give a brief summary of what expectations investing is and how it might differ from traditional investing approaches?
Mauboussin: By the way, Christine, Al Rappaport is a Chicago guy. He was taught at Kellogg School of Management for many years. And the start of this is, he wrote a book in 1986 called Creating Shareholder Value, and I read that book in the late 1980s. Chapter 7 of that book was called “Stock Market Signals for Managers.” So, the original target audience was executives, actually, and asking them to understand that value creation or building stock price performance over time had to do with meeting and exceeding expectations for financial performance. So, as I read that, obviously, it had a big impact on me, but it had clear implications for investors as well. So, essentially, the opposite side of the same coin. So, Al and I collaborated on writing the investor version of essentially Chapter 7.
Let me just first say that most investors when they think about whether a stock is attractive, the typical way to do this is to say, “Here's what I think it's worth.” So, determining value in some way, shape, or form, and then comparing that value to the price. And that's the very typical thing. Expectations investing, as the name suggests, actually does this backward. Step one is starting with the only thing we know for sure, which is the current stock price. And step one is saying, what expectations in terms of value drivers--so typically sales and margins and capital intensity and so forth--do we need to achieve to justify today's stock price? That's step one. Step two then is introducing both historical analysis but also strategic and financial analysis to determine or judge whether that set of expectations is too optimistic, too pessimistic, or about right--which, by the way, in most cases, is probably the right default answer. And then step three, following from step one and two, would be to buy, sell, or hold based on what you found.
Now, coming out of step two, we really try to think about things probabilistically. Step two, really, as part of that is we try to develop scenarios for how the world might unfold, which allows us to come up with an expected value, and it's that expected value that we compare to the current stock price. So, it's basically the same mechanical process in terms of cash flow models and so forth but going backward from the price to value versus the value to the price.
Ptak: We're going to talk in more depth about some of the concepts that underpin expectations investing, which you just referenced. But before we do that, let's run through why you updated the book. You cited four factors: the shift from active to passive, the rise of intangibles, the blurring of public and private firms, and changes in accounting rules. Can you talk about why those trends warranted an update?
Mauboussin: The first thing I'll say, Jeff, is that the timing of the initial version was horrible. We actually signed the contract to write the book in the late 1990s when markets were roaring, and investors were keen on investing concepts and so forth. And the book came out Sept. 10th, 2001, so the day before a national tragedy and in the midst of a three-year bear market. So, it was a good idea at the time, and then, of course, the timing of it was poor.
The second thing is exactly what you said. I think we felt that there were enough things that had come along that we should refresh, certainly just the case studies. For instance, our original core case study was on Gateway, which was a computer company that no longer exists, and certainly young people probably never even heard of it. So, having fresher, more contemporary names. And then, many of the things you just ticked off, I think the most significant of those, at least from my point of view, is the shift from tangible to intangibles, and what that means for accounting and cash flows and how we think about value.
And the last thing I’ll say, is that Al was retired as a teacher. But the last couple years, I've continued to teach essentially these concepts at Columbia Business School. And as I've taught them, I think I've learned a little bit about how to communicate it more effectively, what points to emphasize and so forth. So, it was sort of a combination of those things. And then, the last thing I'll just say is that Al is now in his late 80s, he's phenomenal. He's an incredible partner, a great guy to talk to, so thoughtful, and knowledgeable, and critical. And so, for me, personally--I can't speak for him--but for me having an opportunity to work with him, again, on a big project like this was a real thrill. So, it was a combination of all those things brought together, mixed in with a little COVID staying at home, and that was the magic formula.
Benz: One of the things that's interesting about expectations investing is the way it nods to efficient markets. It treats the securities' price like that's a keystone piece of information. That seems justified, but how do you implement expectations investing in a way that isn't too deferential to price, especially at times when the markets seem frothy?
Mauboussin: That's a great question. And you do want to balance these things. I think one of the analogies for a metaphor--for expectations investing is the racetrack, which is parimutuel betting, and there are odds on the board which give you some sense of the horses' probability of success, and then how fast the horse is going to actually run in the race. And what we know, stepping back, is that by and large, these are fairly efficient markets. Horse race markets are pretty efficient. But we also know from time to time there are market mispricings. So, I think we try to strike this balance with an appropriate amount of humility that markets are pretty smart and typically smarter than we are. But with the appropriate sets of tools, we can start to determine or assess, at least probabilistically, whether expectations are blowing too hot or too cold.
Now, we could have a whole separate conversation, I think, about subsegments of the market where there seem to be excesses. The main area I would point to is probably the meme stocks, which, by the way, in historical context is nothing new. We've seen episodes of this kind of thing many, many times over time. But again, where expectations themselves appear to have gotten overly optimistic. There are some self-reinforcing things that make things interesting--the idea, for example, reflexivity. But I think you're saying it's deferential to efficient markets. I think that's not a bad way to say it. I think it was just some sort of sense of humility in going into these things.
Ptak: A cornerstone of expectations investing is to try to exploit opportunities where expectations priced into a stock are thought to be likely to change in the future as you've described. People tend to evaluate expectations using two main pieces of information: short-term earnings and profit multiples. You think that's the wrong way to go about it. Can you talk about why you think that is?
Mauboussin: So, let's take a look at each of those pieces, Jeff, and the first piece is on earnings. And I think the first thing to say is that--well, two things to say about earnings. One is that earnings growth in and of itself doesn't really tell you about value creation. So, saying this differently: for a company that's earning its cost of capital, growth does not create value. And so, all earnings growth rates are not created equally. And that's a very important point to understand.
The second thing is, I think, earnings have been increasingly distorted by the shift from tangible to intangible investments. At the very highest level, historically, most investments were tangible, so physical things, so think factories, or machines, or trucks, or whatever it is. And those were reflected on the balance sheet and then depreciated on the income statement. So, they showed up in the income statement, but relatively modestly. By contrast, what's happened now is intangible investments have become more important. And intangible investments are nonphysical by definition, and more importantly--so you think about software code, or branding, or training your employees--and more importantly, those are expensed on the income statement. So, the hit is all upfront. And I think that creates a distorting effect.
Now, to give some sort of context, tangible investments were about double intangible investments for companies in the late 1970s. And today, intangibles are double those of tangible. So, we've had a complete flip in, let's call it, a couple of generations. I think earnings themselves are misleading because of the value creation and then just the way we account for things.
Multiples are another issue where we are packing a lot of information in a multiple that we really need to disentangle. So, as I mentioned before, a multiple at the end of the day is attempting to reflect growth prospects, return on capital, sustainable advantage, all those kinds of things are melded into this one number. What we argue is, it is much more effective to unpack those things, make the assumptions bear, and then debate them rather than simplistically applying a multiple to earnings. So, you're now looking at a hard-to-understand number called the multiple applied to a nonreliable number called earnings and attempting to define value. So, we're just saying, let's break it down to its core components, try to understand the pieces much better, debate them, debate where they're going to go expectationally, and that hopefully will give us a lot of insight as to how the business works and where the expectations might go in the future.
Benz: Expectations investing seems somewhat contrary to traditional value investing in that there are perhaps better opportunities to exploit expectations, revisions in businesses with higher growth potential where the cash flows are more distant, where the underlying assets are likelier to be intangible than tangible, and where they're earning more than the cost of capital. Do you agree? And, if so, do you think traditional definitions of value and growth have become outmoded?
Mauboussin: I think the last statement you said is what I agree with emphatically--well, I'm not sure that they're outmoded. I'm sure they should have ever been introduced in the first place, candidly. And just to be clear, I teach at Columbia Business School on a part of the Heilbrunn Center for Graham & Dodd Investing. And the course I teach is Security Analysis, which is sort of a spin-off course of the same one that Ben Graham started teaching in the 1920s. So, where I teach at least is very much steeped in the Graham tradition. And I think that at the end of day value investing is buying something for less than what it's worth, full stop. Now, typically, low expectations are better than high expectations. I think we'd all agree on that. But I think, Christine, you made the point, which is exactly right, which is where are expectations most likely to be revised up. And the bar may be set a little bit higher for certain types of high-quality, high-growth, very profitable businesses, but if they can meet or exceed that bar, that is a very attractive investment and certainly a value investment. And by the way, I've seen Warren Buffett has talked about this. The concepts of value and growth are joined at the hip.
So, I think that whole value-versus-growth discussion is just basically a waste of time, and you should think about where there are opportunities to buy something for less than what it's worth, and that should be the focal point for everybody at all times. And the same thing, by the way, also statistically cheap stocks, so low price/book, low price/earnings, low enterprise value/EBITDA multiples, what have you. Often those are justified because those businesses don't have great prospects or great value creation.
So, I think you said it perfectly, and I would just echo it that I think this distinction has never made sense. And it makes less sense today as intangibles have taken center stage, and we just need to update how we think about things. Obviously, Warren Buffett has evolved a lot over the years, and I'm quite convinced if Ben Graham were active today, that he'd be very much on the same wavelength.
Ptak: We talked about value versus growth. What about public versus private? Obviously, in public investing, we've got a fresh price that we can work from. And I would imagine it makes it a whole lot easier practically speaking to implement a framework like expectations investing-- different story for private firms. So, how would one take expectations investing and apply it to privately held firms?
Mauboussin: I think it is the same concept. And I think that venture capitalists, or even like late-stage growth investors, they're all doing the same thing, which is, they're saying, “If I put $1 into this business, is it likely to create value?” One of the challenges with private markets is the notion of price discovery. So, price discovery is this fancy way of saying, can we figure out how to get to the correct price? And typically, you do that by having on one side potential buyers and on the other side, potential sellers, and you line the buyers and sellers up and find out where there's some sort of meeting of the two minds. In private markets, you don't really have that. You have sellers in the sense that company itself is maybe issuing equity or something. But for the most part, it's just that they're mostly just buyers. And so, it often goes to the highest bidder. I think it's fair to say there's probably less price discovery in private markets than there are in public markets.
Obviously, these two things, to some degree, work off of one another. They probably don't get too far out of sync. But the core ideas are the same. And I think if you talk to seasoned venture capitalists, they may have to have a little bit more vision, thinking about potential for total addressable market and understanding how the economics of the business may unfold and so forth. But they're looking at the exact same things. They understand that ultimately delivering the expectations for financial performance have to improve over time for the value of the business to justifiably go up.
Benz: If we decompose stock market returns, I think that we'd find that indeed a good chunk of the returns do come from cash flow growth, but a fair bit do come from multiple expansion. You lay out a lot of useful frameworks in the book for estimating the fundamental expectations that are being priced into a stock but not multiples, per se. So, in a scenario where I conclude that the market is pricing in fundamental expectations that are too low, how should I think about the ultimate payoff, knowing that some of that payoff is going to relate to how the multiple changes?
Mauboussin: It's a great question, Christine, and you think about a discounted cash flow model, again, let's unpack that a little bit. There are three--and I think these are kind of common sense--there are three elements to it, and they interconnect. The first is just the cash flows. Please think about a mom-and-pop store. You run a corner dry cleaner or a gas station, or whatever it is. It's the cash flows. The money that comes in, minus the money that goes out, cash flows. That's the first component. The second component is a discount rate. So, we're going to get some of those cash flows in the future, those cash flows are worth less than the cash flows today. So, we have to discount them in an appropriate rate of return. And then, the third is going to be some sort of time horizon. So, for how long can we find investment opportunities that generate returns in excess of the cost of capital?
At Morningstar, you guys do a lot of work on things like moats. This is going to be this idea of durable competitive advantage. So, you might say it a different way. Again, if I were asking you to buy your local dry cleaners, what kinds of questions would you ask? You'd say, “What are the cash flows; when am I getting them and how certain are they?” So, essentially, we're recasting these.
I want to laser-focus a little bit on your point about multiples, because probably the biggest driver of the multiples, all things being equal, is going to be the discount rate. So, what we've experienced in the last 40 years, since the early 1980s, is a pretty steadfast decline in bond yields. If you take the 10-year Treasury note yield, as an instance, it's down from the mid-teens down to whatever we are today, at 1.75%. And so, as a consequence, that's lowered required and expected rates of return, and a lower rate of return imputes a higher multiple. So, the higher multiple has been, I think, sort of a consequence of what we've seen against that backdrop.
And if people want a really simple little heuristic for thinking about this, the answer is, you just take one over the discount rate as the appropriate multiples. I'll try not to hurt myself doing this. But $1 divided by 10%, so if your discount is 10%, that's worth $10 or 10 times P/E. $1 divided by an 8% discount rate would be 12.5%, so a 12.5 times P/E. And $1 divided by a 5% discount rate would be 20 times P/E. So, that's the PE, assuming no other growth, nothing else, just so that you can earn that dollar into perpetuity. So, you can see, Christine, just by that little illustration, if you say, “We've gone from roughly 10-ish, to roughly 5-ish on our cost of equity assumptions, you can see how the multiple effectively doubles--again, leaving aside cash flows and everything else--just as a consequence of the lower expected return.”
Ptak: I wanted to jump to talk about business quality, which is another dimension and something that you talk about in the book. It seems like business quality can be a decent guide to the types of value triggers one would focus on in evaluating the potential for future expectations revisions. For instance, I think you'd written that revisions to future sales expectations at firms that earn more than their cost of capital matter quite a bit more than revised sales expectations at lower-quality firms that struggle to earn their cost of capital. Can you talk about how business quality can influence which expectations an analyst should focus on?
Mauboussin: It's a great question. And again, let's just play the intuition of this, which is, if you're a value-neutral business--in other words, expected return is 10%, I give you $100, you earn $10 on it, so you're earning exactly what the expected return are. You're essentially on a treadmill. If I give you another $100, you earn another 10%. You're not going anywhere; you're not adding any value whatsoever. By contrast, if the cost of capital is still 10%, and I give you money, and you're earning 20% on it, so for every $100, you earn $20, you're creating a lot of value. And by the third scenario, of course, if you're earning $5, that's a problem. Because now you're in the hole. Every dollar you invest is worth less in the marketplace. By the way, Warren Buffett has famously called this the $1 bill test. So, if you're earning above your cost of capital, $1 bill going into business is worth more than $1; if you're earning exactly your cost of capital, $1 going in is worth $1; and if you're earning below, it's worth less than $1.
So, this is the key concept. And we have a technical way, which I won't go into, we call it threshold margin. But there are ways to think about specifically this notion of value creation. And once you have that in your mind, and you zoomed in on that, then Jeff, your point is exactly right, which is to say, when you have high return-on-capital businesses, value-creating businesses, they're going to be highly sensitive to growth. The faster you grow, the more wealth they're going to create. And the expectations for rapid growth, even small declines in those expected growth rates can have a very material mathematical impact on the value of the business. By contrast, if it's a value-neutral business, you can grow to your heart's delight. You just don't get any multiple; you don't get any improvement in the value of the business as a consequence of that. So, for those kinds of companies, their first order of business should be to improve the economic returns of their business. And by the way, you could do that by restructuring, by selling the nonprofitable businesses, whatever it is. And then, value-destroying businesses, as Warren Buffett says, “The first thing to do when you find yourself in a hole, stop digging.” Value-destroying businesses got to stop digging, and figuring out ways to get to value neutrality. And certainly, growth for those kinds of businesses tend to be very bad.
Now, one thing you might say is, well, companies have seen the name I’m sure and they get this and so forth. But it's an interesting case in point is actually mergers and acquisitions, which is, we know that historically a majority of deals have not created value for the acquirer. And these are cases where, obviously, the company is fat, bigger, so they have grown, but in many cases, they have not created value. So, there's a there's a perfect case in point: the number one source of capital allocation over many decades is M&A, and by and large, it has not been a value-creating activity for acquirers. It creates value in the aggregate but not for the acquirers. And here we are, it's exactly to your point, growth doesn't add value.
Benz: In the book, you mention a few types of very powerful business models: aggregators and platforms. Some of these firms like Alphabet and Facebook have entered lines of business that weren't part of their original blueprint. Is it correct to say that they've been in fact fantastic investments partly because the expectations that were originally priced into their shares changed so radically over time? And does that suggest a key to finding super compounders like these is being able to camp out in the shares of dominant firms that throw off so much cash that they can afford to experiment and enter whole new categories?
Mauboussin: I love that question, Christine. I think the answer is yes. And we actually have a chapter dedicated to this, Chapter 8, where we say sometimes expectations feel a little bit rich, and you don't want to throw out the situation right away, and you want to contemplate what we call real options. And so, not to get too fancy, but most people know about financial options. It's the right but not the obligation to do something, and in this case, buy or sell a stock. And what we're doing is just taking the mathematics of those options theory and applying it to real investments in the real world and extended lines of businesses, new distribution centers, whatever it is.
And so, typically, those kinds of franchises you described are those that are laden with real options. And usually, we talk about four things that are important for real options to be potentially important. The first is uncertainty in the sector. So, the degree to which you're in a new industry, burgeoning industry, we don't really know how things are going to unfold. That uncertainty actually adds option value, because it's a right but not the obligation to do something. By the way, typically, uncertainty is bad for discount rates, and that means higher discount rates and lower value. So, if it's an option, it actually is additive; if it's the cost of capital, it's actually destructive. The second is a smart management team. So, these are management teams that know how to cultivate and ultimately, exercise options appropriately. Third is market leaders. You pointed that out as well. So, typically, it's the market leaders that get the first call and the most opportunities. And then, the fourth and final one is access to capital.
So, in our original version of the book, our case study for this was actually Amazon.com, probably in the same group of companies you just described. And Amazon, by the way, at the time, was predominantly a bookseller, they did a couple of other things as well. And we said, Amazon is pretty well situated for real options. In other words, their platform can be used for other things. And that was probably more lucky than anything else. But now, we look back 20 years later, and of course, AWS and other things they've done have been huge drivers of value; there wasn't even a twinkle in Jeff Bezos' eye back in 2001 when we wrote the original book. So, I think the answer is yes. Now, ideally, as an investor, what you'd like is a company that has lots of real option potential, and you don't want to pay a lot for it. Now, we do share a methodology to try to anticipate or value real options. But the idea is, let's find companies that have those potential real options, and we're not paying a ton for them today.
Ptak: I wanted to talk a little bit about management capital allocation. It seems like corporate managers would be in the best position, in a sense, to infer what expectations the market is pricing into their shares and whether those expectations are well founded or not. Does the data on corporate share issuance and repurchases bear this out? For instance, do you find that corporations are in statistically significant excess returns by repurchasing low and issuing high?
Mauboussin: Jeff, I think this is just a huge issue. We've written a lot about capital allocation. I hope we'll write about it again in the not too distant future. And you're exactly right. Obviously, judicious capital allocation is extraordinarily important for how the company performs. And obviously, that'd be vis-à-vis what is priced in. On buybacks, these people often make fun of companies and they say they buy high, and they don't buy when it's low, and after the pandemic happened, for example, companies sort of froze up. But if you take the aggregate evidence on this, there's pretty strong evidence that companies are pretty good about issuing equity when it's expensive and buying it back when it's inexpensive.
So, the answer is, companies are pretty good at this in general. And this, by the way, is a complete side note, but it's an interesting thing. I mentioned a few moments ago that investing was a zero-sum game, which was, if you're going to generate a profit, or you or Christine are going to generate profits, excess returns, it's got to come at my expense, for instance, or some other investor's expense, and then we net out to zero. But that's actually not strictly true, because that's true in a closed system. But it's not a closed system, it's an open system. And the other participants in the open system would include, to a lesser degree, governments, although that's important for some markets, but corporations. So, the degree to which companies are buying and selling stock, and if they're doing it in a way that they're generating "the excess returns," that can be really meaningful.
So, I love this question. And it circles back to our very beginning discussion about expectations investing in Chapter 7 of Rappaport's book Creating Shareholder Value, where Al was basically speaking to these corporate executives saying, “Hey, understand what your stock price reflects in terms of expectations.” By the way, most of the executives have a sense of this, but they don't really understand it. The people become CEOs are not people who are versed in this kind of thinking or this kind of methodology. So, they all think their stock is undervalued even though they've not done the work to substantiate that. But the key is finding great capital allocators. And it's not just buying back or issuing equity, although that can be a big part of it, but it's right down the list. It's mergers and acquisitions, which we just talked about; it's research and development; it's just all intangible investments; it's divestitures; it's things like buyback and dividend policy. We can go down the list of things that are really important in terms of capital allocation. And again, the judicious capital allocators are likely those companies that are going to exceed expectations in the long haul, and there are certain companies that are very poor capital allocators, and they get put into the penalty box.
An example probably is General Electric, which, I think, Jeff Immelt was handed the keys in September 2001 after a period of very high performance and very high expectations. And a combination of deflating of those expectations, plus, I think some capital allocation miscues, led to the company's underperformance over that period of time that he was CEO. So, I think it's an incredibly important component of this whole thing. And, Jeff, you asked the question at the outset about incentives--this is also important for executives. What are their incentives? Are there incentives to grow the business? Are there incentives to create per-share value? And those things can come into conflict for a lot of executives.
Benz: You've written a lot about sources of edge and how that's eroded over time due to technological innovation and other factors. How do you think about edge in an expectations investing context? Are there potentially new sources of edge that investors could leverage? Or do you think that expectations investing is a way in which investors can better adapt to the new competitive realities where it's maybe harder to generate alpha?
Mauboussin: I think, again, it's just a tool to try to do that. And I'll just start with a line that I've always loved from Seth Klarman, who is the founder of Baupost hedge fund up in Boston, and Klarman has got this great line where he says, “Value investing is at its core the marriage of a contrarian streak and a calculator.” And I just love that, and I'll try to explain how I think the expectations fits into this.
So, the contrarian streak just basically says, “When everybody leans one direction, I want to examine the other side of the case.” Right now, being a contrarian for the sake of contrarian is not a good idea, because often the consensus is right. So, it's not just about being a contrarian. And that's where the second piece comes into play, that is the calculator. And I think, to me, the calculator is fundamentally about expectations. So, when everybody believes one thing or another--everyone is bullish, or everyone is bearish, and that drives expectations to be too high or expectations to be too low, that presents an investment opportunity. So, I'll just start with that Klarman line: “Value investing is at its core the marriage of contrarian streak and a calculator.” I think is just fantastic.
Now, when we think about sources of edge--and I'll put this in the context of the Klarman quote--there are a few things. One is behavioral, and that is, again, collective behaviors, people tend to get optimistic and pessimistic. Clearly, the expectations approach would be helpful in trying to sort that out. Again, consensus may be right, but have expectations gotten too excessive on the positive or negative side? Informational advantage is very difficult, and I don't think we have much to say about that. They can come along. And so, you might get information that will lead you to believe that expectations are mispriced, but tricky to do, obviously. Analytical advantages, I think we might have something to say here.
I think one of the underappreciated chapters in the book is actually Chapter 3. And the core of that's this idea called the expectations infrastructure. And really, what that is, is a sensitivity analysis to understand how different changes of what we call value triggers, predominantly sales costs and investments, how those ultimately trickle over to cash flows. And this allows you to capture things like pricing flexibility, operating leverage, economies of scale, and so forth. And I think a really thoughtful application of that can lead to some analytical advantages that you may not have otherwise had. And then, the fourth and final one is just technical, which is, sometimes people have to buy or sell for reasons that have nothing to do with fundamentals, and as a consequence, if you stand on the other side of that and understand that people are doing this for reasons they don't really want to do it, there can be an opportunity there and a source of edge as well. So, I think it augments this, Christine, I think it's a tool that adds to all these things. It's not in and of itself going to solve the problem, though.
Ptak: At least some of our listeners aren't going to be conducting analysis of individual securities like stocks, but rather trying to forecast market returns to facilitate things like financial planning. How can a framework like expectations investing be applied for that purpose?
Mauboussin: It's great question, Jeff. I think the way I would think about this is referring to my friend Aswath Damodaran, who is probably the leading expert in valuation in the world, Professor of Finance at New York University. And Aswath every month publishes his estimate of the market risk premium. So, just to be clear what that is, a typical way in asset pricing that we build up the potential expected returns, what you're talking about, is we start with a risk-free rate. And typically, for equities, we use the 10-year Treasury note yield, which today is about 1.75%. But let's use the year-end number, so about 1.5% was where it was at the beginning of 2022. And then, to that we had a market risk premium. And by Aswath's reckoning, it's about 4.25. So, if I'm getting my math right, you get a 5.75% expected return for the equity market.
So, you say, “Why is that expectation?” So, the way Aswath does it, he essentially says, “I know the price.” He takes long-term forecasts for earnings and cash flows. And then, he solves for the discount rate that equates the two things. So, in a sense, he is doing an expectations analysis but solving for the discount rate. So, the expected return as of the beginning of 2022, and I'm going to call this long-term expectation, was 5.75%. Now, the question you might ask immediately is, how good is that forecast. And so, what we did recently actually is we tested this. Aswath has been publishing versions of this in his model back to 1961. So, we have now 60 years of data effectively. And we correlated--so, on the X axis, we put his estimate, and on the Y axis, we put the actual 10-year total shareholder returns for the S&P 500, and the correlation is about 0.7. So, it's not perfect, but it's pretty good.
That said, what that 5.75%, what does that mean? Historically U.S. equity markets have returned something like 6% to 7% real, so that's after inflation. Inflation expectations for today--if you take the 10-year Treasury note expected strip is about 2.5%. So, if you take 5.75%, and you take away 2.5%, you're talking about 3% to 4% real returns for equity markets, which is vastly lower than what we've historically enjoyed. Now, that said, you can then look at things like credit markets and credit spreads, and you see a very similar type of pattern. So, I think all of this together would suggest that expected returns for equity markets and credit markets are relatively muted vis-à-vis history. Now, again, there are always things that go up and down and so on and so forth. So, there are always ways to generate good returns. But I think that's how I would think about it, and I think the expectations today are pretty modest if Aswath's approach makes sense, and I think it does.
Benz: You write a lot, and it's very accessible. But it seems mostly directly relevant to professional analysts and investors. We have a lot of individual investors and financial advisors who listen to this podcast. What's something in your library besides expectations investing that you'd encourage them to read, because it's very pertinent to the decisions that they might make?
Mauboussin: So, Christine, I'd mention a couple of books, a few books, actually, that I've read recently. And all these things are to take people's appetite. I will just go back to the first comment about consilience and that is I would really encourage people to read, read widely, of course, so not just the stuff. The one I would just start is Morgan Housel's book, The Psychology of Money. Morgan is just an incredibly talented writer, really great thinker. So, that's a really fun book. It's very accessible. And again, it meets a standard that I think for people that do this for a living has something to say to them. And for even people who are newer to the industry or less initiated, has a lot to say to them as well. So, it really appeals to a broad audience.
A book that came out last year--within the last year--it was Robert Hagstrom's new book called Warren Buffett: Inside the Ultimate Money Mind. Robert wrote The Warren Buffett Way many years ago, obviously a smash bestseller, and he has had a number of Buffett books along the way. I found this book to be really interesting. And by the way, he sprinkles in lots of consilient-type of stuff in there as well. So, it's a lot of homespun, good thinking about markets through this concept that he calls the ultimate money mind and again, diverse, different points of view.
The third book I would mention is William Green's book called Richer, Wiser, Happier. This actually profiles a number of very successful investment managers. I'll just say that's for fun--it's hard to pattern yourself necessarily after these folks, but you can see the sort of the kinds of things that they do as investors and how they've distinguished themselves. Now, whenever you read a book about successful anything, whether it is successful investors or successful companies, you always have to be very, very attuned to survivorship bias. But that said, I always find myself very much enjoying these, enjoying the perspectives of people who have succeeded. So, those are the three books that I would recommend I think are accessible, they're interesting, and they're illuminating.
Ptak: Well, this conversation has been very, very illuminating in its own right. Michael, thank you so much for sharing your time and insights with us. We've really enjoyed it.
Mauboussin: Jeff, Christine, it's been my pleasure. Thank you very much.
Benz: Thank you so much, Michael.
Ptak: Thanks for joining us on The Long View. If you could, please take a minute to subscribe to and rate the podcast on Apple, Spotify, or wherever you get your podcasts.
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Benz: And @Christine_Benz.
Ptak: George Castady is our engineer for the podcast and Kari Greczek produces the show notes each week.
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