Motley Fool Money - Expectations Investing with Michael Mauboussin

Episode Date: September 3, 2022

Michael Mauboussin is an adjunct professor of finance at the Columbia Business School and the Head of Consilient Research at Counterpoint Global, Morgan Stanley Investment Management. Bill Mann interviewed Mauboussin in front of a live audience about a range of investing topics, including: - The approach of "expectations investing" and how to apply it - Why a company's base case for growth is so important - Peloton’s faulty growth predictions - Businesses with real option value   Companies mentioned: SBUX, PTON, AMZN, GOOG, GOOGL, WMT, TGT   Host: Bill Mann Guest: Michael Mauboussin Producer: Ricky Mulvey Engineers: Tim Sparks Learn more about your ad choices. Visit megaphone.fm/adchoices

This episode is brought to you by KolaGard. Do you know what's really scary? Not screening for colon cancer when you turn 45. The KoloGard test is non-invasive, requires no special prep or time off work, and ships right to your door. In just three simple steps, KolaGar takes the scare out of colon cancer screening. If you're 45 or older and at average risk, ask your health care provider about the KolaGard test. KoloGuard is available by prescription only. Learn more or request a prescription today at kolaGar.com slash screen. There are certain businesses that have option value, right? Which is an option is the right but not the obligation to do that. And if there are market leaders in uncertain markets with smart management teams and access

to capital, they may be able to see opportunities as they present themselves and take advantage of them. So the put, you know, we wrote about it in 2001 and end up being lucky more than the impression, but Amazon.com was a great case in point. I'm Chris Hill and that's Michael Mobison. He's an author, a professor of finance at Columbia Business School, head of research at Counterpoint Global, a division of Morgan Stanley. But at The Motley Fool, we like to think of Mobison as the Investors investor.

There are other investors who are more famous. There are certainly other investors who spend more time on television. But if we could grab coffee with any investor, Mobison would be the first pick for a lot of us. At our Fool Fest Investing conference last week, Bill Mann interviewed Mobison in front of a live audience. They talked about the approach of expectations investing, why a company's base case for growth is so important and much more. One of your most famous pieces of work is expectations investing and it's a wonderful process.

And I think that one of the great things that you have brought to the table, and a lot of people call you the investor's investor, is the thought of having the market inform you what what it is thinking as it values companies. With every single company, the stock price is a piece of information. So for our foolish investors, maybe just give a little bit of, you know, thought of where you started from that and how you apply it. Yeah. So I actually went to college here at Georgetown.

I was a government major, had no business experience whatsoever when I went on to Wall Street. And so I'm still confused, but I was definitely very confused with that. You're confused in the right direction. In the right direction. And someone gave me a copy of a book called Creating Shareholder Value, which was written by Alpha Rappaple, who's my co-author. And I read that book, and that was the first thing that added some coherence into my thinking.

And there were three things he talked about. One was, it's not about, and this is all important for all of us, it's not about accounting numbers, it's about cash and economics. So go beyond the accounting to understand what's really going on. The second, which I think is also really important, is that he argued the competitive strategy analysis, so what is, why is this business distinct and unique and good, should be joint at the hip with valuation. And we tend to do those things separately, but they should go together.

And the last thing was, the original book was Chapter 7, was called Stock Market Signals for Manager. So the audience was executives, but clearly the relevance was for investors as well. So the idea here, expectations of investing, is to say, we have one thing we know for certain, and that is the stock price. And what we can then do is reverse engineer what has to happen for that stock price to make sense. Now, we think you should do that with a discounted cash flow model. That can get a little bit fancy, but it doesn't really matter.

The core concept is how high is the bar set and how high must my company jump to clear that bar? And so that idea of always understanding what has to happen for that stock to make sense, I think is the core idea. Now, we actually do want, we want you guys to use expectations investing to try to make it somewhat accessible. We have built a website called Expectationsinvesting.com that has downloadable tutorials, including Excel spreadsheets. So if you think the idea makes sense, you think it fits your philosophy and how you want to approach the world, and you want some tools at your fingertips to be able to do that, we try to provide those. So that's the basic setup. And by the way, it's true for almost everything in life, you know, what has to happen for this

to make sense? And I think, by the way, we're approaching football season. The way I like to think about it is the over-under for football games. You know, you're not betting on the actual score, which is itself very difficult, but you're saying, no, I think they're going to score more than this or less than this, and that I think is a cleaner type of bet to make. You know, it's a way that I think about investing

and in thinking about the stock price, expectations investing, and that is your returns will be what the stock price was when you bought divided by what actually happened. Like everything in investing from the moment that you buy, I mean, there's asset values, and you've written a lot about intangible markets, but essentially everything is based on the discounted cash flow

when it comes to investing. Right, and I mean, the way I would think about it is your return, and I'll just replay it what you said, your return is the expectations of point A and the expectations at point B. And the question is, what will the world think in the future? so six or 12 months from now. And by the way, it's super relevant in this environment

where now would allow all this uncertainty. So the question is, what will the world understand? And so obviously what happens in terms of financial performance between A and B is going to inform B, but really what you want to do is put yourself into the mindset is what will the world believe and why at some point in the future? So it's really revisions and expectations. And in a sense, it's a trivial statement,

but in other way, it's actually very important. It's profound, right? So are you familiar with the book of lists? Do you remember this from 1980? was Irving Wallace and David Wallachinsky and Amy Wallace. They put together this list of, it was a bunch of lists, and it was like, famous people who died in the bathtub and people whose brains weighed more than nine pounds.

Do you remember? Not really. Yeah, or the people's all mad. So anyway, all right, great story so far. They put out a second book, and this is one of my favorite books in the world, not because it's a good book, because it is a terrible book.

It's called The Book of Predictions, and this is for you. Thank you. Yeah, oh, really, enjoy. And here's the thing about this book that I absolutely love. Look at this. We should have put your book on the other side, just keep stacking them up.

Here's what I love about this book. They went around to a bunch of futurists in every area and said, okay, tell us what is going to happen in this area, in this area, in this area, 10, 20, 30 years from now. And there are some things that are in here that are prescient. Like there was a technologist who said, in the year 2010, there will be plenty of jobs servicing electric cars. This is 1982, so they're out there a little bit.

You know what only gets mentioned once in this book? A priest, a Roman Catholic priest from Phoenix, Arizona said, by the end of this decade, the Soviet Union will not exist. It's the only one. The rest of them, every single one, was, well, the Soviet Union is going to do this, they're going to do that. Some said they're going to take over that we have no chance of winning. So why did a priest?

Yeah. I wonder if the priest was exactly. That's right. The priest may have been talking his book a little bit. I think he may have been wondering why it was that he was being asked. But everybody else at that time in 1982 did not see 70 years. that the Soviet Union would cease to exist. So when we're talking about investing

and when we're talking about expectations, the future is really, really hard to predict. What are some of the ways that you, in your process, that you get out even two, three years and make adequate or roughly accurate predictions about the future? Yeah, the first thing, just to reinforce what you said, and for those that are not familiar with it, familiar with it, you should definitely check out the work of Phil Tetlock at the University of

Pennsylvania. Phil's done a lot on expert forecasting. His original book was called, well, he wrote a book about probably 15 years ago about, it's called expert political judgment, where they actually took hundreds of experts and asked them to make predictions. These are not Roman Catholic priests. These were people actually purported experts. I mean, the thing is, everybody else had to be laughing at him. Yeah, no, exactly. That's the, you know, he said something And then Tedlock did something that was unusual, which is actually kept track. And it turns out that they're actually quite poor forecasting. And by the way, they're like the rest of us.

They have a whole litmus, a list of excuses as to why they almost got it right. It was just a timing thing. One of my favorites was my forecast was so significant. It changed the course of world events. The forecast stuff. I like to play that card. The world made sure I was incorrect. I like to play that card every now then.

But, you know, so Telak went on to do, which is now famous for, participating in a forecasting tournament, his team, and they found that of the thousands of forecasters they had, there were a handful of people, so-called super forecasters that did very well. I would just say if, and by the way, if you said one mental model that anybody could give, if I wish I had when I was 20 years old, it would be the concept of base rates. And a base rate basically says, you know, usually, let me just take one step back, when we have a a problem, and it could be forecasting a company's performance or whatever it is, the classic way to do it and see if it makes sense to you, right, is you gather a bunch of information,

you combine it with your own experience and your own inputs, and then you forecast into the future, right? So whether it's, you know, how long it will take you remodel your kitchen, what will it cost, you know, how... The answer is longer. Right. The answer is always longer and more cost than you think, right? The base rate, by contrast, a very different way of thinking about the world. and says, I'm going to think about my problem as an instance of a larger reference class. So in other words, I'm going to ask what happened when other people were in this situation before.

So rather than me thinking about, I had this conversation with my contractor and he told me this, that, and the other, you say, okay, of all the people of remodeled kitchens, what happened? And so it's a very different way of thinking about the world and a very informative way of thinking about world. So the answer is appeal to the base rates.

And by the way, Jason's Wyde, the wonderful journalist at the Wall Street Journal, once interviewed Danny and said, what's the most important advice you to give to an investor? And he said, what is the base rate? So it turns out that for corporate performance, we have very rich repositories of base rate data. And the big ones, not surprisingly, for companies,

are sales growth rates and basically margins, right? Those are the two big drivers, essentially. And sales itself, the most distinct key thing. And so what you can then say is, I'm going to look at a company, and I'm going to say, the market thinks it's going to grow X percent, I'm going to say, I'm going to look at the base rates of companies

of this size or in this industry, and actually look historically at what the distribution of growth rates has been. One example I often like to give on this is actually Peloton interactive. And it's been through, it's been a rocky road for Peloton. But in the fall of 2020, right, so roll back basically two years ago, the pandemic was just getting going, and of course, people were now working at home. And so the demand for Peloton boomed. And they had a fabulous fiscal deal.

2020 and they had really excellent prospects. And there was an analyst who said, we believe that they can grow 30% compounded annually revenues for the next 10 years. And he had a very, a really good model. It was bottom up, very well thought through and so forth, right? And so the question you would ask, and so you might say, okay, that's persuasive. The question you would ask is how many companies of that size have ever grown 30% compound annual for 10 years? And the answer was about 1%. So then you say to yourself, oh, well, we've just been through an incredible exogenous shock called a pandemic. Yeah, I heard of that. And 1% of companies have ever done this in history. What's the likelihood, you know, maybe you give some a probability to it, but it's not going to

be your base case, right? So I think to me, the answer, long-witted answer that is to think about, is to think about what are the base rates. Now, the application of base rates is all over the map. Some things it's relatively straightforward to do, because we have a lot of data and the, and the distributions are well-behaved. Other situations are unusual, and the distributions look really kind of funky, and so the application. But I would just say, broadly speaking,

it's a vastly underutilized framework versus a misused framework. How do you go about determining the difference between a 1% type company and a company whose valuation is completely off the rails? So like, for example, if I were to come into your Columbia class, as a first-year business student, and I were to present to you a discounted cash flow for Starbucks

and say it's growing at 21% per year for 25 years, you'd kick me out, but that is precisely what happened. So when you were talking about edge case companies, or what are some of the ways that you separate fact or potential from fusion? I think there are two big things to think about, and I'm sure this is everything you guys are thinking about when you're looking at businesses as well.

The first is what I would call the basic unit of economics, which is try to get down to the basic unit of how that company makes money. For Peloton, for example, it would be subscribers. So a connected fitness subscriber costs how much to acquire that person, how long do they stick around, what do they pay, what are the costs against them? For Starbucks, it might be a store, you know, store economics, for wall economics. So that's the first thing is to understand that, really understand that intimately.

Now, what we know is as companies invest more, it's often difficult to sustain a store attractive return. So that's, you know, you want to understand that there might be, as you move geographies, whatever, some sort of faith. But that would be the first thing. So I really want to get my arms wrapped around on that. And the second is, how big is, you know, the fancy term is total addressable market, how big is the potential market for this? And just to take a step back and say, and again, do this, you know, with a sober, through a sober lens, is how big could this potential market be? And trying to understand that intelligently. We wrote a piece about And we argued for, you know, first a bottom-up analysis.

We also looked at historical diffusion models to see how, and then using base rates. So you can triangulate these different techniques to get a sense of it. Now, so that would give you the opportunity, that might give you the pond in which to fish for the future rapid growth, high return businesses. But there's no, it's hard to know.

And then the other thing I'll just add in there is that we have a chapter about this in expectation investing. There are certain businesses that have option value, right? Which is an option is the right but not the obligation to do that. And if there are market leaders in uncertain markets with smart management teams and access to capital, they may be able to see opportunities as they present themselves and take advantage of them. So we wrote about it in 2001 and end up being lucky, more than impression, but Amazon.com was a great case in point. So at that point, AWS was, I doubt was even a glimmer in

Jeff Bezos' eye, but at AWS, of course. Yeah, no one would have built that in as a... Right, and so what we did say, we did say this is a company that is positioned to have options, and ideally, by the way, from an investor's point of view, you want to have that potential for option value without paying for it. So we see it in retrospect, but it's hard now.

But that was an example. If you said, gee, feels a little bit expensive, a little bit rich, the option value would have been one way to think about how that, to bridge those two points. So your first job in the industry was a food analyst

at credit squeeze? That's not really true. No? No. My first job was to be a training program to be a financial advisor, and this is important to say. I was a miserable failure at that job.

And I was fired. I was basically fired. I feel you on a molecular level right now. I was fired. People like look at my career, go, yeah, yeah, yeah. I'm like, no, no, you don't understand. My first job, I was an abject failure. Okay, yeah.

Now, that did lead. She got it out of the way. Exactly, I got out of the way. But the training, here's as important, the training program, actually, the virtue of it, was we went through 20 different departments at the firm, Drexiburnum. And so it's called skill matching. I was able to figure out what I felt I could do reasonably well. And one was equity research is one that.

So I ended up being a food analyst because of my experience there, but after being a failure. Great. Go ahead. All right. I hate being wrong. I'm still on that failure. How? What was your process, what access to information did you have at that time?

Like, I always think it's interesting to go back and think that when I first started investing, it involved a phone call to the company, to their IR to have, you know, send information. What was your process like in that for me? I mean, this is, obviously, this is pre-internet and all that. So, so, by the way, if I wanted 10K or 10Q, I'd had to request it from the corporate library. Yeah. Like our firm's library, and then they was sent it down an in-office memo or whatever. So, no, but I did the standard stuff.

Now, this is also pre-Sarbanes-Oxley. So you could have conversations with companies were a little bit more open than they are. Sarbanes-Oxley, for people who don't know, was a law that was passed that caused companies to have information go to everyone at the same time. Uniform disclosure, so that's 20 years ago, so that's been for a long time.

So now, it wasn't like I was doing anything nefarious with that, but that was helpful. So, yeah, no, I built, but I built models ground up, from basic financials, did talk to management. And I applied a lot of stuff we talked about. I did think about competitive strategy. I applied competitive strategy frameworks.

I did a lot of work on returns, did a lot of work on cash flows. So it was pretty standard. I mean, it's just stuff I teach my course to some degree. Yeah. I have 10 times the amount of information that you had at the time. Way more than 10 times. Way more than 10 times.

Why does it seem that outcomes and decision has not improved across the board with access to information that when you started, you would have said, that's the next best thing to perfect information. I'm not sure it hasn't actually on some level. So if you think about, I mean, it needs to be questions about market efficiency and stuff like that, and have markets become more efficient.

Now, you have these pockets of sort of like zany stuff happening with meme stocks or whatever it is, but for the most part, markets are really hard to beat, right? It's hard for you to sit there and say, you know, you know, I'm smarter than the market, I know something. Now, again, it's easy to say, actually. Yeah. It's just hard to actually.

And that's, I mean, it's an overt thing with expectation investing. But with expectation investing, what we're saying is you buy something when you, when the expected value is higher than the current price. And, you know, you're saying there's scenarios under what you're wrong, right? So it's acknowledging that it's still a probabilistic situation. But, but, you know, so I don't know if, I don't know that market isn't smarter and better than what it used to be. Now, that said, it's like we're subject to the same vagaries.

You know, you think about even if we had met here five years ago, and I told you there's going to be a global pandemic, there's going to be, you know, all these things with the Fed policy and all the, you know, I mean, inflation is going to rear its head in a way we haven't seen for 40 or 50 years. I mean, it would have been difficult to, you know, how do you factor all that stuff in? So these are the, there are things under your control and then things out of your control, and those out of your control things don't change,

and people tend to be bad at understanding that. You had mentioned last year that you felt that the market was dominated by speculators, that speculation was rampant, that investors were really in the minority in the market at that time. I'm reminded there was an article that came out in the Wall Street Journal last year, and it had a graph of five electric vehicle companies that come public through SPACs, So they didn't have to do an S-1, they did an S-4, and all of them had projected that they would have $10 billion in revenue within five years.

And to me, okay, yeah, yeah, we can skip to the end part, but also to me, it seems like the information would have come back rather quickly and have been consumed, that there's only been one company ever that has generated $10 billion in revenue in its first five years.

that's Google. So to have five EV companies, it was something that I don't know if the level of information that's out there is crowding out those base rates. Yeah, that's an interesting. So, I mean, the way I would think about that is to say that this is the wisdom of crowds, right? So the market tends to be efficient when you have diverse agents, diverse investors, so the different points of view, you aggregate it effectively and there are proper incentives. when you have those things, and when we can do this in the classroom, it's easy to show that markets shouldn't be smart.

By the way, even with people have pieces of information. Markets tend to go haywire when you lose that diversity. So people, instead of being heterogeneous, become homogenous in their views. By the way, since the beginning of markets, people talk about Reddit boards and so on. Like, since the beginning of markets, this has been the case. Right, under the buttonwood tree, there's same.

So this is not, there's nothing new, the tools may be different. And by the way, taking away, friction and trading costs. There are tools that have changed it, but that have had an effect on it. And so I think that when you talked about the EV thing, when you talk about meme stocks or whatever, I think these would be examples of, these are pockets of these market inefficiencies that, and by the way, the other thing is important to understand about markets and market efficiency is, you know, the fancy term for its arbitrage costs.

But the answer is how do you, if something gets out of whack, how do you correct it? And if there's a large cost to correcting it, it may not be worth correcting it. As a consequence, this weird stuff can go on for a while. So if the cost to borrow stock makes it prohibitive to short it, then even the sophisticated people might say it's not worth my time and you sort of get these sort of unusual, these unusual outcomes for some period of time. So yeah, I mean, I think that, you know, that is something I will say with high degree of confidence.

I'll make a prediction with a high degree of confidence that we will continue to have those episodes of sort of craziness happening in different markets at different times in different corners. that's sort of part and parcel. Yeah, I love the fact that you frame it up as homogeneity versus diversity because my own impression as a practitioner for several decades is that during periods of extreme greed

and extreme fear, you get homogeneity amongst, even if you've got the same number of participants. So where do you feel like we are now after 18 months of, okay, let's back out, 36 months of a pretty wild market straight up and then really has been bruising over the last period. Look, I think that the fact is it's been extremely difficult, both for executives and for investors. And executives, I mean, people didn't, you know, you think about companies like Walmart and Target.

These are world-class companies, extremely smart management teams that have really struggled. And you say it doesn't get much better than that. And so I think COVID has been a very, very big managerial challenge. And as a consequence, it's been difficult. If companies don't know what they're doing or what they're seeing, then it's hard for investors to get a sense of what's going on. And then for investors, of course, I think people got overly enthusiastic about the stay-at-home, you know, COVID-related stuff, and then the pendulum swings back and forth.

And you see this, you know, things like travel stocks and so on and so forth. And then, of course, allow all this, even things like supply chain and monetary policy allowed reintroduced inflation, which we hadn't seen, so now that has to get tamped down. So, I mean, there are all sorts of very difficult moving pieces and all the stuff. So I'm not sure the market's been, you know, whether, again, like, in retrospect, it's easy to say these moves seem to be extreme in both directions. Yeah. But at any particular time, it's hard to know.

I certainly wouldn't have been pressure on about what was going to happen. So I think maybe my final question is, you know, in a group of, you know, in a group of, you know, of individual investors, what is one key piece of advice that you can give so that people, as they're looking at the stocks and they're looking at the markets and looking for opportunities, what's a way for people to remain as realistic as possible

in terms of what companies can do or what the market may do? Yeah, I think it does go back to, I mean, there are two things. One is it goes back to expectations and say, like, what do I have to believe for this stock to make sense? And then use the building blocks of sales and profits and basic unit of analysis. And the second thing, which I'm sure everybody knows, but it's so important to keep your eye on the horizon

and maintain a long-term point of view. It's just, it becomes very difficult in the short run, especially if you've enjoyed lots of gains or losses. You start to move, you know, your emotional seesaw starts to tilt one direction or another, and you have to really force yourself to keep yourself on balance. So whether it's been good or recent experience is good or bad, is just try to make sure that you kind of sort of keep it at level

terms of your decision. Wonderful. As always, people on the program may have interest in the stocks they talk about, and the Motley Fool may have formal recommendations for or against. So, don't buy or sell stocks based solely on what you hear. I'm Chris Hill. Thanks for listening. We'll see you tomorrow.