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Commentary

Tired of Playing Games?

Michael Mauboussin dives into expectations investing and how you can game the market.

Michael Mauboussin, the head of consilient research at Counterpoint Global, joined Morningstar's The Long View podcast discuss active investing, the paradox of skill, and updates to his book, Expectations Investing.

Here are a few excerpts from Mauboussin's conversation with Morningstar's Christine Benz and Jeff Ptak:

The Paradox of Skill

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 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, 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 level of skill. And I think when we look around the world, whether it's investing, 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, 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, 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. 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 of 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 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.

Chinese Stocks and Retail Investors 

Benz: Well, 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, 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. That's the tension that you always run into when you think about finding the easy games.

Expectations Investing

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. 10, 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, 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 [co-author Alfred Rappaport] was retired as a teacher. But the last couple of 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 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.

How To Implement Expectations Investing

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: You do want to balance these things. I think one of the analogies for expectations investing is the racetrack, 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.

Short-Term Earnings and Profit Multiples

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: Let's take a look at each of those pieces, Jeff, and the first piece is on 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 up front. 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 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.

This article was adapted from an interview that aired on Morningstar's The Long View podcast. Listen to the full episode.