Trusting the Process: Michael Mauboussin & Tom Digenan

Michael J. Mauboussin is Director of Research at BlueMountain Capital Management in New York. Prior to joining BlueMountain in July of 2017, he was a Managing Director and Head of Global Financial Strategies at Credit Suisse. Before rejoining Credit Suisse, he was Chief Investment Strategist at Legg Mason Capital Management from 2004–2012. Mr. Mauboussin joined Credit Suisse in 1992 as a packaged food industry analyst and was named Chief U.S. Investment Strategist in 1999.

Mr. Mauboussin is the author of three books, including The Success Equation: Untangling Skill and Luck in Business, Sports, and Investing and is also co-author, with Alfred Rappaport, of Expectations Investing: Reading Stock Prices for Better Returns. Mr. Mauboussin has been an adjunct professor of finance at Columbia Business School since 1993 and is on the faculty of the Heilbrunn Center for Graham and Dodd Investing. He earned an A.B. from Georgetown University.

Tom Digenan is the head of the US Intrinsic Value Equity team at UBS Asset Management. In this role, he is responsible for U.S. equities portfolio construction and research. Prior to this role, Tom had been a Strategist with the team since 2001, where he participated in the analysis and development of U.S. equities portfolios, focusing on alpha generation and ensuring client investment objectives were met. Prior to his role with the U.S. Intrinsic Value Equity team, Tom was president of the firm’s mutual funds and relationship funds organization. Prior to joining the UBS predecessor organization Brinson Partners in 1993, Tom was a senior manager in the tax department of KPMG Peat Marwick, where he worked exclusively in the investment services industry.

Tom is a member of the CFA Institute and the American Institute of Certified Public Accountants, and he is on the board of CFA Society Chicago. He is currently Vice Chairman of the CFA Society Chicago. Tom was an adjunct professor in the Marquette University Graduate School of Business from 2012–2016.

Graham & Doddsville (G&D): Can we get started with each of you discussing your background?

Michael Mauboussin (MM): I was a liberal arts major in college so I never studied business. It’s an interesting question whether that’s an asset or a liability. I came to the business world knowing close to nothing. My father made me take principles of accounting when I was a senior in college and I got a C+ in the class, and only out of the generosity of the professor’s heart.

I started at Drexel Burnham, which is now defunct but was an amazing place to learn about the business. I was in the training program and was confused for a very long time. I guess I still am confused to some degree, but the virtue of being a liberal arts major was that I was compelled to go back to first principles. I always want to understand how things work from the ground up. While the world was and still is replete with rules of thumb and old wives’ tales, we can decompose a lot of it.

For one of my first early projects, I remember thinking: what do the great investors do? I built files on Warren Buffett and Ben Graham and other great investors, just to study how these folks operate. There were some common threads. They seemed to be long-term oriented. They seemed to be focused on cash, not accounting numbers. They seemed to really value good businesses. Those are the sorts of things that stood out to me.

Then, in 1987, I had my professional epiphany. A guy in my training program handed me a copy of Al Rappaport’s book, Creating Shareholder Value. It was awesome. There were three things in that book that have remained the bedrock of everything I do, and are things Tom and I have talked a lot about over the years. The first was: value is not about accounting numbers, it’s about cash. This is a lesson that we relearn from time to time. The great analysts always focus on cash.

The second thing was that competitive strategy and valuation should be joined at the hip. It’s interesting, even in business school we teach strategy and finance separately. The strategy professors will say, “well, you want your strategy to create value” but they don’t really explain the financials. The finance guys say “well, it’s good to have a competitive advantage,” but don’t quantify it. As an investor, you’re operating at the intersection of those two fields. You can’t do an intelligent valuation without understanding strategy. And the litmus test for a strategy is whether it creates value. Even though the book was written for corporate executives, the relevance for investors was obvious.

The third lesson came from chapter seven of the book, Stock Market Signals to Managers. The argument was that your stock price reflects an expectation about how you’re going to perform as a company. You, as an executive, need to understand what the market expects, and exceeding those expectations will make your stock go up. The market may think you’re going to create a lot of value, but if you don’t create as much value as the market thinks, your stock is actually going to underperform. Again, executives were the audience but the implication for investors was also clear.

In the early 1990s, I was working for a senior analyst following consumer companies. One day, he said, “You work for me from 9 to 5, but if you want do more on the weekends, you can write about whatever company you want. But my name will be on the top.” The first company I wrote about was Ralston Purina. The CEO of Ralston at the time was Bill Stiritz. You may have read the book The Outsiders by Will Thorndike, which is awesome. There’s a whole section on Bill Stiritz. He was considered the smartest guy in the food industry, kind of like the Warren Buffett of the industry. So I write this report and my senior analyst’s reaction is tepid. But he figures, nobody cares, let’s just publish the piece anyway. The content was all Rappaport. It was all cash flow, why buybacks made sense in the context of what they were doing, and so forth. One of the first phone calls I got after the report came out was from Bill Stiritz’s office. They said, “Bill really liked your report. Can you to come out and talk to our senior executive team about how you think about valuation?” I’m a pretty young guy at the time, and so it was a very exciting imprimatur.

After that, I became a senior analyst at First Boston following the packaged food companies. I had other jobs there, which is now Credit Suisse, and is was around the time I joined First Boston that I started teaching at Columbia Business School. From there I went to Legg Mason Capital Management for nine years, implementing a lot of these same ideas on the buy-side. Then I went back to Credit Suisse for a short stint, and now I’m back on the buy- side. So I’ve been back and forth between sell-side and buy-side, but really thinking about the investment process the whole time.

Tom Digenan (TD): I didn’t go out into the world knowing I was going to be an investor. I worked at the Chicago Mercantile Exchange in college as a runner. That’s not investing. The one investment concept I got from that is that the futures business, unlike the equities business, is a zero-sum game, and it’s also mark-to- market. If you invest in cattle futures and they go up today, you can run up to the office and pull money out of your account. If they go down, you’ve got to run up to the office and put money into your account. You don’t think about yesterday. One thing that surprised me when I got into the investment business is how focused people are on what happened yesterday. I’d be driving in to work and somebody calls in these stock shows on the radio and they ask, “should I sell XYZ?” And the host asks, “well what did you buy it at?” And I’m almost going off the road saying, “it doesn’t matter what you bought it at!”

I was an accounting major in college because I wanted that stability and I liked having an answer. And I’ve got to tell you, this is a business where you don’t get an answer. In accounting, you get an answer. In the early 90s, I had an opportunity to join Brinson Partners and work with Gary Brinson and Jeff Diermeier. They were my two most significant mentors from an investment perspective. They followed a pure discounted cash flow approach. If you stick to it, it helps you avoid bubbles, but you must have faith in it, and your faith will get tested. For you young guys going into the business, I would say you will be wrong a lot — even when you follow your process — but be ready to be right and have the world temporarily think you’re wrong. In the end, you’re only wrong if you don’t stick to your process.

G&D: Michael, a lot of your research reports focus on broad investment themes, for example the “Base Rate Book.” How did you go from being a sell-side research analyst covering a single sector to the very broad, multi-disciplinary perspective you’re now known for?

MM: When I was an analyst, I was very influenced by Al Rappaport and his work on valuation. I was also very interested in value investing. When I was an analyst, it was increasingly the case that I would go out to talk to clients and they would ask me about specific stocks, but they’d also say, “tell us more about your valuation approach.” So I ended up spending a lot of time just talking about how to do valuation. It was a natural evolution because that’s what people were asking about. If I were to break down my approach, the first really important thing to think about is why stocks are mispriced. Every day, you have to ask the question, “what is the market not getting that I think I know?” That’s a nontrivial problem. The second component is valuation and how to do it properly.

What’s interesting about valuation is if you use heuristics like P/E or Enterprise Value to EBITDA, you don’t blow yourself up because the markets are smarter than you are, so your heuristics don’t really make that big a difference. You mentioned the “Base Rate Book.” If you asked me what I wish I knew when I was a 22-year-old analyst starting out, I would say without hesitation, it’s on the idea of base rates. Danny Kahneman, the renowned psychologist, calls this the inside versus outside view. The idea is to integrate historical corporate performance into my bottoms- up model.

We wrote about Tesla in 2015 when Elon Musk laid out the path for Tesla to get to a $700 billion market capitalization. That was Apple’s market cap at the time, so it was a very ambitious plan. He said, “we’re going to do six billion in revenues in 2015,” — which they didn’t do — but also added, “we’re going to grow 50% a year for ten years with an eventual net margin of 10% and a P/E multiple of 20x.” If you work out the math, it gets to $700 billion. By the way, if someone gave that problem to me, I would do what you guys would do. I would open an Excel spreadsheet, then figure out how big the auto market is, what percent would be electric, and what percent would be Tesla. And then I’d ask, “does this seem reasonable or not?” The outside view, the base rate, would say, “has any company with six billion in revenues ever grown 50% a year for 10 years?” The answer is that it’s never been done, not even close. Might it happen? Yeah, it might happen, but it certainly wouldn’t be your base case, and it’s certainly a very low probability. Something like that’s a sobriety check right away.

Back in March, there was a feature story in The Economist about Amazon. An analyst projected them growing 15% a year off a $100 billion revenue base. Has that ever been done before? No. Might Amazon be the first? Of course. Is it your base case? It would seem optimistic for that to be your base case. You might assign it some modest probability, but it’s certainly not the most likely outcome. The outside view is incredibly powerful, and gives you a practical way to integrate concepts such as regression toward the mean. Everyone knows that regression toward the mean is important, especially if you’re a value investor, and the “Base Rate Book” tells you how to operationalize it. It’s not just that you understand there’s this thing called regression toward the mean, you now know how to do it quantitatively, which is really helpful.

G&D: Speaking of base rates, Tom, do you and your team utilize these types of frameworks?

TD: Yes, quite often. Michael wrote a great piece called “Managing the Man Overboard Moment.” Last summer, Kroger took a rapid nosedive and I pulled out Michael’s analysis and used it to frame the situation. We ended up selling Kroger. It was a good sell. The reason I say it was a good sell is that this was a stock where we had two signposts relevant to our long position: one, we will see a return of food inflation in the U.S. which will improve margins in the grocery business, and two, Amazon will have less than 1% market share in groceries.

In a span of two days, both signposts were debunked. On a Thursday, they announced earnings and lowered guidance because they weren’t seeing any signs of food inflation. Then literally the following day, Amazon announced the Whole Foods acquisition. We had an analyst who is incredibly smart, very well-educated. The natural analyst bias is to maintain the position. Cognitive dissonance impairs our ability to immediately incorporate evidence refuting your current hypothesis. In addition, there is a value trap element in play where you can justify maintaining the position by saying, “but it’s really cheap now.”

It was the appropriate sale for the portfolio I manage and based on other opportunities available to me at the time.We own this stock in our Global Equity portfolio, managed by one of my colleagues. That team, after analyzing the situation, felt there was enough downside protection to maintain a position in the stock. My advantage and disadvantage as an investor is that I’m not an analyst. I don’t know more than the analysts do about these companies. I have faith in our process. I realize that if you don’t formalize the process, you won’t follow it, because when you get to that event, there will be some emotional reason to stray from your process. I think most managers stray from their process more often than they don’t. I’ll use a baseball analogy Moneyball by Michael Lewis came out in 2003. In 2005, if you asked general managers in Major League Baseball if they had read Moneyball, over half of them hadn’t read it. Can you imagine that? You’re one of 30 competitors in the world, and one of them is telling you exactly how he does things. These are the people you trade with. It’s ridiculous. People get set in their ways. I don’t think most organizations have an actual process that pushes you toward continuous improvement and it’s something that you’ve got to be adamant about because it’s not comfortable. I have one person at my firm who said, “but that would be overriding analyst judgment.” I said, “that’s exactly right.” There are times when you must override an analyst’s judgment because it’s the process, and you have to follow the process.

MM: I’d like to just talk a little bit about the story behind “managing the man overboard moment.” Decision making is difficult in all environments, but it’s particularly difficult at emotional extremes. For example, if you’re feeling really good or really bad, it’s very difficult to have a clear head about anything. Having been on the buy-side, there were these unfortunate incidents where we’d have a stock go down more than 10% versus the market. As an analyst, you’re disappointed, you’re frustrated, and maybe you’re even angry.

TD: You’re defensive.

MM: You’re defensive. No one’s happy. We created this analysis going back to 1990, just looking at thousands of instances of stocks going down 10% versus the S&P. Then we introduced factors including momentum, valuation, and quality. As you introduce the factors, you increase your specificity but you reduce your sample size. We then asked, “how did the stocks do in subsequent periods?”

That analysis does two things. First, it gives you a naïve default. If you know nothing about the situation and the stock has bad momentum, good valuation, and high quality, it will say: buy, sell, or hold. Now you have the default. It’s not an answer. It’s a part of a distribution, but at least something to hold onto. Second, I think because you have that naïve default in your back pocket, you can have a calmer conversation. You have this sort of backdrop behind it and you can say, “all right, let’s think about this properly.”

We wrote two pieces. The first was “Managing the Man Overboard Moment,” and the other was “Celebrating the Summit,” which dealt with situations in which stocks had outperformed. I don’t know if this is true, but apparently most mountaineering accidents happen on the descent, not on the ascent. Partly it’s because descents can be more technically difficult, but it’s also because people are more excited at the top of the mountain. They’re high-fiving, taking pictures, and they let their guard down. I don’t want to stretch the analogy too far, but in investing too, we were trying to say, “let’s address process at emotional extremes, when you’ve made a lot of money or you’ve lost a lot of money.”

G&D: Would you say in your opinion, an important difference between a good versus a great investor is that ability to manage the behavioral side?

MM: That’s why I evolved that part of my course because knowing the mechanics of valuation, or knowing how to do the strategy analysis is almost the ante to the game. If you can’t do that, you’re not even in the game. Everyone has to be able to do that. If you distinguish the great investors from the average investors, it’s not because their cost of capital calculation is more accurate. It almost always has to do with the fact that they’re able to make good decisions and be correctly contrarian in adversity. Seth Klarman’s got this line that I love: “value investing is, at its core, the marriage of a contrarian streak and a calculator.” The contrarian streak means if everyone thinks one thing, I’m going to at least examine the other side. But the consensus is often right. Being a contrarian for the sake of being a contrarian is a bad idea.

The second part, the calculator, is really crucial. It’s really the combination of being willing to take the other side when expectations are mispriced. There’s another interesting question, which is, how much of this is just your natural personality? How many value investors are born that way, and how many can be trained? I think a lot of this is based on people’s natural proclivities, and we can add on some tools to help people get better at it, but guys like Warren Buffett, Charlie Munger, and Gary Brinson seem to be that way naturally.

TD: Yeah, I think that’s true. Both a good investor and a great investor will be wrong 45% of the time. But a great investor will admit when he’s wrong. I think that’s the hardest part of the business. If you can be right 55% of the time, you’ll be good. If you can admit when you’re wrong, then you will be great.

MM: There’s a famous quote from John Maynard Keynes, “worldly wisdom teaches that it is better for reputation to fail conventionally than to succeed unconventionally.” If I’m short retail, and everybody else is short retail and it goes up, yeah, it’s too bad, but everybody else had the same view. We’re all together, right? That’s where it becomes really difficult. A lot of the great investors I’ve been around, somehow they don’t care much about what other people think. It’s actually a phenomenally good trait as an investor and a phenomenally not good trait as a human being.

G&D: Can you each talk about your specific strategies and process?

TD: My flagship strategy is a core U.S. equity fund. It has about 70 names. There are periods when we have pretty high tracking error, and periods when it’s not as high. I tend not to be sensitive to sector allocations. I think there’s some opportunities out there right now. We find both semiconductors and financials really attractive, which is great because they are low correlation, kind of like energy and airlines. My newest strategy is a U.S. sustainable portfolio. That one’s going to be really interesting. It’s about two years old. It’s a concentrated strategy. I think investors more and more want concentrated strategies, which I think is a secular shift and not a trend. There is also growing sensitivity to sustainability, like Environmental, Social, and Governance, or ESG. What we’ve been trying to do is incorporate some ESG metrics into our valuation methodology. If you’re a pure investor trying to figure out the cash flows that are going to accrue to the owner of a business, you should always have been incorporating that, right? You’ve always cared about governance. You always care about environmental impact. You produce something that has a need for water and you’re not near a water supply, things like that. But right now, we’re starting to see a lot of interest from clients in some of the ESG stuff.

G&D: Can you talk a bit about GEVS, and why you guys have set the system up that way?

TD: So Gary Brinson, Jeff Diermeier, and Bob Moore built this thing in 1980. Back then we called it EVS, Equity Valuation System. They threw a ‘G’ on there at some point, for Global. I’m surprised Gary did, because when I started with the firm, our 401(k) had four options: equity, fixed- income, balanced and cash. Those were the names. They were all global. Gary didn’t even put global because he said, “how else would you invest?” The valuation system for us is basically a means of incorporating all of the analyst’s ideas and insights into something where I can use the calculated part for my contrarian analysis and compare price to pure value. Then we get a ranking of stocks. I can print out a histogram. I can rank it by analyst, by sector, and by country. The other thing that’s nice is that we don’t have just all of our outputs, but we have all of our inputs. We have all of our inputs for the last 35 years for every company that we’ve been covering. The nice thing is, if you come in and say, “IBM looks cheap,” I can see if it looks look cheap relative to our history. How have we modeled this historically? Have we tended to be right on IBM? No, we’ve been wrong. Since I have all of the inputs, I can basically look at it and say, “well, if our analysis is correct now, what are our assumptions?” Where it helps me the most is when you go through that period when you underperform. We measure the standard deviation of the alphas, because the alpha from our valuation system is expected excess return, and if the alphas are really tight, that means the market’s pretty efficient. When the standard deviation of the alphas widens, and I can tell you that when the distribution goes from narrow to wide, we will underperform in that area, during that period. It means the expensive stocks are getting more expensive and the cheaper stocks are getting cheaper. We’ll underperform when this widening occurs because we tend to own more of the cheaper stocks that are getting cheaper.

Think back to the end of 1999 when the market was exploding. That’s the tricky part of this business, and when your clients become really important. When the standard deviation of the alphas widens, that means two things. One, you will have just underperformed by a lot, and two, you will also have the greatest opportunity. That’s when you want to sit in front of your clients and say, “this is what we’ve been waiting for. This is probably the only thing you’ll purchase in your life that you don’t get excited about when it goes on sale.” If you wanted some new Nike shoes, and you see they’re on sale, you get all excited. When the stock goes on sale, you say, “uh, I’m not sure.” I know so many people — I call them the dry-powder brigade — who have lived their whole life with dry powder. Most of them were not investing in March 2009. These investors need some kind of “true North” that will tell them when the opportunity set is wide and when the world is expensive or cheap. At the moment, it’s not that exciting. The spread’s about average, which is okay. You can make money during average periods. Also, I don’t think the world is as expensive as most people think it is.

G&D: Michael, do you feel comfortable talking about the strategy?

MM: Well, BlueMountain has multiple strategies. We do a lot: anywhere from credit to systematic and discretionary equity, to distressed, to volatility trading. As a consequence, the processes range from quantitative and systematic strategies to fundamental analysis, credit, and parts of discretionary equity. It runs the gamut. The unifying theme is ultimately decision making, which is thinking about probabilistic bets. What’s interesting is that there’s an opportunity in a firm like this to really collaborate across asset classes. As an equity analyst, is it helpful to talk to a credit analyst, or even someone who trades volatility? My job as Director of Research is basically to work on all aspects of the investment process.

G&D: What are the biggest challenges you face as a Director of Research, overseeing that many different types of strategies and so many different types of people?

MM: There’s a great essay that I learned about from Atul Gawande, who wrote The Checklist Manifesto. It was an essay written back in the 1970s by, of all things, two philosophers about medicine. The question was, “why do doctors fail?” They said it basically comes down to two things. The first is ignorance, meaning you just don’t know what you’re doing. You don’t know how to do this particular operation or whatever it is. The second way doctors fail is execution. People just don’t do what they know they should be doing. When you read The Checklist Manifesto, it’s much more about the latter than the former.

TD: They weren’t washing their hands.

MM: He’s getting people to wash their hands. Now, by the way, I wouldn’t want to be too critical, because if I’m a physician, and I’m trying to treat a patient, I’m interested in the patient’s well-being. That becomes the most important thing. These other things become, I don’t want to say that they’re sidebars but they don’t seem to be the most pressing things at the moment.When I think about investing, it’s really trying to bring both of those things to bear. Are there tools that we can provide people with to make them even more effective at what they do? The second part is we make sure people are very methodical in their decision- making. Every time we make a decision, are we thinking about things properly and considering all the different alternatives? Why do investment committees exist? Why are there committees at all? Why do people work in teams? The answer is that a team, if done properly, surfaces and considers more alternatives than you might consider by yourself. It offsets some of the biases that we all bring to the job every day. To me, those are the two big areas: just getting better and executing effectively day in and day out. I think Gawande’s major contribution to the world is really recognizing that there’s huge upside to just executing what we already know how to do. It’s remarkable how often people deviate from their process.

TD: On our team, adding a name to the portfolio requires two out of three votes. So, if I vote yes and the other two vote no, it’s not going in the portfolio, even though I’m the head of our team. I know a boss who wasn’t happy with this structure. He said, “you’re the decision maker. You should have the final say.” I replied with, “no, I want the process to be the final decision maker.” If us getting it right depends on me being smarter than the next guy, we’re not going to win. Once you have a well- developed process, it’s easier when you bring people in. And it’s easier with the current team, if they understand and appreciate it. It’s like parenting, in that you need to be consistent. If you start deviating, then there are no rules. In the investment process it’s important that you have tight guidelines and rules.

MM: I want to say a couple more things about investment process. One is to have a clearly stated thesis and some sort of identifiable edge when entering into a position. The phrase I really like is “linchpin issues.” What are the key things that this story’s going to pivot on? Usually as an analyst, you’re looking at a lot of information, but for the most part you’re looking at two or three key things. Tom mentioned with Kroger the food inflation and Amazon participation, but it could be whatever is relevant in that particular case. The second thing that is extremely relevant is “sign- posts,” which is, if my thesis unfolds as I anticipate it is going to unfold, here’s what we should see happen. If it doesn’t, this gets to one of the most difficult things we have to do as investors, which is to update your view. The fancy term is Bayesian reasoning. Every day, we all wake up with prior views of how the world works. Then we walk into the world and things confirm or disconfirm what we believe. The question becomes, how good are you at updating your views when new information comes in? That’s incredibly difficult, and part of it is overconfidence. Another huge component is confirmation bias. Even if you struggle to invest in something you’ve done a lot of work on, once you’ve made the decision and it’s in the portfolio, your reputation is on the line. You will tend to seek information that confirms your view. You’re going to dismiss information that disconfirms your view. It’s incredibly difficult to overcome.

G&D: What are the pros and cons of working in investment teams?

MM: We’ve also done a lot of work on teams in general, and I have some thoughts on that. The first thing I’ll say is that the investment industry has changed radically in the past 30 years. It used to be the case that almost all portfolios were run by individual PMs, and a very small minority was run by teams, but now it’s the opposite. Something like three- quarters of all mutual funds in the United States are run in teams, which is an interesting thing.

For teams to be successful, there are sort of three key elements to get right. The first is the size of the team. Tom mentioned this, but the empirical research shows that the ideal team size, the team size that creates the most excess return relative to an individual management portfolio, is three. The second best is five. Why three and five? The answer is odd numbers. To reinforce what Tom just said, you can get situations where it’s two-to-one and you can proceed, which is really interesting. People talk about decision making like it’s all about consensus. This is not an industry where there’s going to be consensus because there’s just too much stuff going on.

The second component is team composition. The ideal here is to have what social scientists call cognitive diversity, people with different training, experience, personality, and background, and who are willing and able to surface different points of view. Every analyst who walks in has their own distribution of potential outcomes. Cognitive diversity makes sure that we’re thinking about things that we may not have thought about otherwise, or we’re placing greater weight on it than we otherwise would have. So cognitive diversity is important. If everyone’s thinking the same way, it does you no good.

The third component is how you manage the team. If you’re the head PM, the key is to methodically draw out different points of view. If you walk into the meeting and you’re the head guy and you sort of indicate that you like it or don’t like it, people will tend to fall in line for social reasons, whereas if you truly are managing the process correctly, you’re soliciting views openly, getting them on the table, and properly vetting them. You’re even conducting your voting with secret ballots. By the way, when I talk to investors about this, they always nod knowingly because opinions are often suppressed in real meetings because of seniority or whatever it is.

G&D: Tom, you mentioned the importance of admitting when you’re wrong, and Michael you mentioned sign- posts. How do you marry the two of those? If you see a stock go down, do you have a mechanical process that says get out or do you allow yourself to re-evaluate?

TD: There are three things that could put the stock on our radar screen. One is that man overboard moment when the stock’s down 10% and we run Michael’s screen. The second is if a stock has underperformed its sector by 25% since the date we initiated our last review, we do what we call a “stop look.” The analyst comes back in to pitch the stock. The third scenario we look at is if a stock that we’ve held for two years has underperformed its sector. We identified that holding onto old losers was hurting our performance.

When you think about it, if our thesis hasn’t played out in two years, maybe we were just wrong in the first place. We owned Teva a couple years back and our linchpin was that they’re not going to lose the Copaxone patent. Well, they didn’t, and it was still a horrible stock. This was in our old losers’ bucket and this is one where I went to the analysts and said, “You know what, unless this is the most compelling idea we have, we’re getting this out of the portfolio.”

G&D: Do you want to talk about your relationship, how it started, and how it’s evolved?

MM: It goes back to Brinson, just the discipline of the Brinson approach. That’s something I’ve always admired about Tom is his disciplined process. We’ve also done some interesting things in implementation, like Brier scores (which measure the accuracy of probabilistic predictions). We put these ideas out there, and very few people follow up, but Tom is one of them.

TD: Do you keep Brier scores here?

MM: We’re working on it. When you go through memos, it’s obvious that most people are not used to thinking about things like Brier scores. They’re much more comfortable with vague language.

TD: My guess is they don’t like it.

MM: Yeah, well, the key is to not frame it as a scoreboard or as a way to embarrass people. It can be personalized; I just give it to you one-on-one and it’s here to make you better. We know that everywhere that Brier scores have been kept and the feedback’s been shared on a timely basis, people get better at making probabilistic forecasts.

Another thing we’ve been doing a lot of work on lately is portfolio construction. It’s a thing that seems to be remarkably underdiscussed. When you read books about blackjack like Beat the Dealer, there are only two things that are really important. One is gaining an edge, and the second is how much you bet, given the edge you have. We spend a ton of time thinking about this. Many people spend almost no time thinking about this. I’ve talked to a lot of portfolio managers and a lot of different organizations that are very heuristic-based in their portfolio construction.

G&D: On the topic of value versus growth, do you think there’s room for actually having a preference, in the same way that someone might prefer chocolate to vanilla, other than simply recognizing that historically, value has quantitatively outperformed?

TD: Think about it as though you’re fishing on a big lake, and you’re going to go in one segment of the lake. Well, sometimes the fish aren’t there. Sometimes they’re at the other side of the lake. If you’re a quality guy, you’re basically limiting yourself to this segment of the lake. Maybe you’re a good stock picker, but your opportunities have been minimized just by putting yourself in that box.

MM: To me, I would translate value investing into an expectations model, so that what you’re trying to do is buy low expectations and sell high expectations. Everything else follows from that. Value investing to me is just buying low expectations. In the Fama- French model, value is statistically cheap stuff, which is a proxy for low expectations, but sometimes it’s just bad stuff. That said you might ask, “what does quality mean?” Let’s decompose that. You might come up with a little checklist. You might say well, quality means high return on capital, which is often associated with low leverage because you can finance your growth internally and reasonably readily.

High quality might be “sustainable competitive advantage,” so some kind of moat. We have to figure out what that moat is and whether it’s going to stick around. High quality might imply management that’s really judicious with capital allocation. So this all becomes part of the analysis of fundamentals versus expectations. I say this all the time, but I’ll say it again right now: I think one of the biggest mistakes you see in the investment business is people fail to distinguish between what’s priced in and what’s going to happen fundamentally. These are two different mindsets. It’s the difference between the odds at the horse race and how fast you expect the horse to run. Those are fundamentally different things. An interesting experiment would be to break your research department into two groups. One group looks at just expectations. If Cisco’s at $45 a share, what has to happen for that price to make sense? Then the second group looks just at fundamentals. They’re basically consultants. They just look at businesses and profit paths and so on. Then, bring them together at the very last second. This is the starkest way how to combine the two parts of the analysis and have a truthful discussion.

Everybody has the same person doing both of those things, but they’re very different. The great investors always separate those in their head. Just because things are going well doesn’t mean the stock is good. Just because things are going badly doesn’t mean the stock is not attractive. The quality thing is only an input to a broader construct.

TD: People like to say, “it’s different this time,” but that’s the one thing that can never be different. “It’s different this time” implies finding a new way to value companies because it’s the only way to make them look attractive. That’s when you should run.

G&D: Is the future of investing going to consist solely of algorithms and artificial intelligence or will humans have a role?

MM: This is an interesting question. I think Ben Graham talked about this. What is consistent in the last 500 years of markets? The answer is human behavior. Humans oscillate between periods of euphoria and periods of despondence. Can that ultimately get arbitraged out by a machine? I think that’s an open question. Bitcoin is evidence that’s not the case. An idea that’s important in the finance literature is limits to arbitrage. Even if there are amazing arbitrage opportunities, if you can’t execute, it doesn’t make any difference. I think bitcoin is a big limit to arbitrage. I think tons of people would love to go short, but it’s just not really viable to go short. These are just markets. There are many other aspects of interaction where I’m sure human emotions will continue to play a big role. These are interesting questions, even for you guys who are thinking about going into the investment world. How do I think about where my opportunities are?

G&D: The last few years have been tough on the long/short space with many high-profile funds reducing AUM or shuttering altogether. How do you see the long-short space evolving over the next five, or 10 years? Do you think recent trends are cyclical or secular?

MM: One of the most interesting departure points for thinking about that problem is a paper Sandy Grossman and Joe Stiglitz wrote in 1980 called On the Impossibility of Informationally Efficient Markets. Now, if you’re a bit of a historian, you know that the 1970s were probably the peak of enthusiasm for the efficient market hypothesis. In 1978, Michael Jensen, a prominent finance professor, proclaimed, “I believe there is no other proposition in economics which has more solid empirical evidence supporting it than the Efficient Market Hypothesis.” The argument in Grossman- Stiglitz is pretty straightforward They say that if there is a cost to gathering information that determines asset prices, there should be a requisite benefit in the form of excess returns. Lasse Pederson has this catchy phrase, “markets have to be efficiently inefficient.” Enough inefficiency to get you to do it, but not so much inefficiency that you avoid markets altogether.

So, if the amount of available alpha has been coming down, the amount you should be wanting to pay to capture the alpha should also be coming down. I think that’s a rough cartoon version of what we’ve actually seen: people flipping from active to passive in order to reduce their fees. If you look at the standard deviation of excess returns from mutual funds on an alpha basis, you see that alpha used to have a big, fat distribution. There was lots of positive alpha and lots of negative alpha. Smart guys win, dumb guys lose. Today, that distribution has shrunk.Very little positive alpha, very little negative alpha. That partly relates to the lack of volatility in the market. It’s very difficult to distinguish yourself when realized volatility is around 6–7%. Is this volatility decline secular or cyclical? I don’t know the answer. Having been around for a long time, I don’t know what the mechanism is to make volatility go up, but I’d be willing to bet that the current low volatility environment is not going to stay here forever. We’ll see a reintroduction of volatility at some point. That’s going to freak out a lot of people, I think, when that occurs.

TD: Especially if the things that lead to mispricing or dramatic movements are human beings. Humans haven’t evolved that much in the last 50 years.

MM: The 2008 financial crisis, which started in housing before spilling over into other sectors, was more leverage related. Today, the concern isn’t leverage. I think the banks and regulators are taking care of that, for the most part. I think the concern is more liquidity. Envision this scenario. Pick an ETF with a bad liquidity profile — high yield is probably the best example. You trade your high yield ETF all day, but the underlying liquidity is not as good as you’d expect. Today, the authorized participants are okay, but if there was a wave of sellers, there isn’t the underlying liquidity, so they might have some problems.

TD: They’ll have a run on the bank.

MM: They’ll have a bit of a run on the bank, and then what will happen is, all the newspapers will write, “ETFs are bad.” Mom and pop will see that, and they won’t distinguish between high yield ETFs and everything else, and the thing just cascades. You might initially say, “I own SPDRs,” or “I own the financials ETF. I’m cool.” The problem is, if it cascades, you’re not going to be cool. That to me would be the way the disaster scenario might propagate. I’m not predicting it, but I’m saying that’s not an implausible scenario to consider. I think very few people are really totally prepared.

TD: That would create a great opportunity because none of that impacts value.

MM: Right. When you sell the ETF, you’re selling stuff in proportion without regard for value, so everything goes up or everything goes down. It reintroduces the question: we’re humans, will things change? It’s very important to understand that the ecosystems are very different today. It will be a different path.

TD: The growth of passive has been very tough on active management. It has really changed the business. The investment opportunity would be if Michael and I were the only two investors in the world and we’re both trying to make money. I’m trying to beat the market and he’s trying to beat the market. Then, one day, you enter and say, “Yeah, I’m going to do this too, but I’m just going to buy and sell based on market cap.” The two of us would look at each other and say, “Finally!” It’s like you’re playing poker. You want something you can make money at, right? You don’t want to sit down with world-class poker players.

MM: I think the weak players at the poker table used to play and lose. Now, they’re indexed. They show up at your house Friday night and they drink your beer, but they don’t play poker. I think it’s actually gotten harder to generate alpha, even though intuitively you might think fewer participants should make the game easier.

G&D: We talked a lot about changes in the industry. Do you have any advice for students interested in investment management on how they should be spending their time?

TD: Michael talked earlier about the man versus the machine. You need to know how to use the machine. Be familiar with the machine. I can stick my head in the sand and say, “Oh, it’s not going to make any difference,” but it is real, and understanding the ability to code, things like that, I think are important. The other thing is to not assume life is a straight line. I’m tapping into hindsight bias here, but I actually think it’s good, whether it’s in your life or your career, for your path to be jagged. Sometimes you’re on the elevator and sometimes you’ve got to take the stairs.

Earlier, Michael and I were talking about the value of mentors. I feel very lucky in my career because you don’t always get to pick who your mentor is or who you work with. If you get the wrong one, move. The move might not be upward, it might be lateral, but you want to make sure you’re at a company with the right culture. It’s really important.

MM: I think it’s important for people who want to go into the investment management industry to do it for the right reasons. A lot of it is about passion for what you’re doing. I’m not sure everyone who goes into it is passionate about it, but it’s important that you really love it. It can be really challenging, it can be really humbling, but it’s an amazing field for learning with amazing people.

Opportunities are a big deal. Think about stepping back and saying, “If I want to generate excess returns, where is that likely to happen?” Being the 500th large-cap US manager is probably a tough way to distinguish yourself. However, there might be other markets where that could be the case. The last thing I’ll say is this is a fabulous business for constant learning. You can never rest. You have to learn every day, knowing you’re never going to whip this game. I think it’s a huge commitment. The best investors I know are really big readers. They are very thoughtful and they’re deeply committed. That’s not for everybody.

G&D: Do you have a favorite non-investment book that’s shaped the way you view the markets?

MM: I usually recommend three books: Consilience by E.O. Wilson, How the Mind Works by Steven Pinker, and Complexity by Mitchell Waldrop.

TD: My three to bring on an island would be: Atlas Shrugged by Ayn Rand, The Baseball Abstract by Bill James (historical or early 80s annual edition) and one I am reading right now, Thinking in Bets by Annie Duke. A great read and also a great way of improving your decision-making ability when dealing with uncertainty, which is what we do every day.

G&D: Thank you so much for your time.