More Mauboussin

I enjoyed, as I always do, an interview with Professor Michael Mauboussin. For those, with a trading slant, he is the academic that best bridges mainstream investing concepts (like stock-picking) with the decision and game theory concepts that derivatives firms focus on. It’s value investing concepts married to the pari-mutuel discourse traders are used to.

Reflections on the Investing Process with Michael Mauboussin (47 min read)
Interview by Frederik Gieschen via theManual by Compound

My excerpts and notes:

  1. Most investors act as if their task is to figure out a stock’s value and then to compare that value to the price. Our approach reverses this mindset. We start with the only thing we know for sure — the price — and then assess what has to happen to realize an attractive return…The most important question in investing is what is discounted, or put slightly differently, what are the expectations embedded in the valuation?
  2. Question: Unlike other competitive fields like sports, feedback and coaching is more challenging in investing. The rudiments that lead to success seem more poorly defined and the field has more randomness (esp if investment horizons for individual investments span significant portions of an individual career).

    One quality that’s important in investing is curiosity and ability to learn and improve and adapt over time. You wrote recently an interesting piece on feedback and how people and organizations can learn and improve. What was your key takeaway from that paper?

    One of the things that I have always observed is that in most fields, timely and quality and accurate feedback tend to improve performance. If you’re a tennis player or a musician, you’re likely to have a coach, even if you’re an elite participant, you’re likely to have a coach to help you in that process. The investment management industry is an industry that draws a lot of really smart people. The remuneration is attractive and so forth. It’s a very competitive, interesting field. It’s remarkable in the sense that feedback is very difficult to attain. In the long run it’s portfolio performance and so on. But in the short run it’s very, very difficult to do.

    The question is, are there any mechanisms to give ourselves quality feedback? That got me going back to the very top. If you study, for example, Phil Tetlock’s work on Superforecasting. Tetlock, a psychologist at the University of Pennsylvania participated, this is probably a decade ago, in a forecasting tournament that was sponsored by the defense department. And they invited people to participate on their team and they found that 2% of them, one in fifty were so-called superforecasters, people making really good forecast that were way beyond what chance would dictate. And they decompose what those people were doing. But if you talk to Phil and you say, well, what is the key? He’s like, well, you gotta get the right people. That’s the key, that’s the first starting point.

    So I opened the piece by talking about what are the right qualities that we would look for as investors? We drew on that superforecasting literature. We also drew on this idea of rationality quotient by Keith Stanovich. I think that’s very powerful work. Stanovich has made this really interesting, and I think provocative, claim that there’s a distinction between IQ intelligence quotient and what he calls rationality quotient, which is the ability to make good decisionsAlong with some of his colleagues he developed a specific test to measure rationality. And if you look at the subcomponents of that test, it seems really consistent with what we would care about as investors.

  3. Question: What is practice in investment management? The other interesting question is, in every domain elite performers tend to practice. Every sports team practices, every musician practices, every comedian practices. What is practice in investment management? How much time should we be allocating to that?

    The individual

    It’s a fundamentally interesting question. What you’re doing is taking yourself essentially offline in order to be more effective when you come back online. That’s what I’m going to say is practice or training. And there are lots of interesting questions that come out of that, topics like skill transfer. If I teach you to be a great poker player or backgammon player or chess player, are those skills going to map over to you as you are in your investing seat?

    The organization

    The second big thing we studied was how people are embedded in organizations. It’s lovely to think that you’re doing all these things by yourself and you’ve got the right attributes and so forth. But the question is once you’re in an organization, does the organization enhance your ability to make decisions or does it detract? The work on this is quite clear that when you’re working in a team, you want to get different points of view. And the biggest problem in teams and organizations typically is that dissenting views tend to get squashed


    Then the last part is the feedback. To bring this back full circle, what we argue is when you have an investment thesis to buy or sell something, that means you believe you’re going to generate an excess return, or there’s a mispricing in the market. And you’re going to have a thesis and that thesis should have sub-components to it that will allow us to create a scoring system. The most common of these or known of these is called a Brier Score. Brier himself was a meteorologist. So you can imagine this was developed first for meteorologists who obviously are predicting rain or sunshine with certain probabilities. And then they observed the outcomes very quickly, to see if they’re right or wrong. So that helps them get better calibrated.

    To have a Brier score you only need three things. You need an outcome that we can agree upon, within a time period that we are finite, with some probability. And if you have those three things, you’re in business to calculate a Brier score. And so my argument is break down your thesis and put it into some Brier score ready predictions. Again they’re embedded there. You just have to surface them and start to keep track. And this doesn’t have to be on a public score board or anything like that, you can just do this for yourself. But what I find is the very discipline of writing those things down will force you or compel you to think more about them and to think more deeply about them. For example, if you’re assigning probabilities, you’re going to immediately start searching for base rates.

    [The analogy to my post on post-mortems is obvious: Being A Pro And Permission To Be Serious]

  4. The importance of a team in calibrating

    [I’m always emphasizing that trading is a team sport contrary to the perception that it’s some genius alone in a basement who plays the drums to rest his mind.]

    Question: What is an elite team, why are they special? And did you learn anything about how to create one?

    Tetlock and his colleagues, when they did the Good Judgment Project, this forecasting tournament, they did a lot of really interesting things. They would say, well, if we train people well, will it help them or not. If we put them in teams, will it help them or not. And they have controls for everything, so they can compare it to what the other outcome would’ve been.

    Discoveries included:

    • training esp if you focus on base rates works
    • Teams added value relative to even those individuals who were trained.

    3 important features for effective teams:


    There’s a guy named Richard Hackman, but he was an organizational psychologist most recently at Harvard, who made it like basically a life’s work of the study and found that the optimal team’s size was four to six. He also found that if you were going to make a mistake, three would be preferable to seven. Four to six seems to be the sweet spot. Hackman didn’t really study investment organizations. He studied all sorts of organizations. This is something that’s important for us to think about because it tends to be human.


    Types of diversity

    Social: Age, race, gender, ethnicity, etc

    Cognitive: what makes an individual unique (training, experience, personality) Now I think one can make the case very seriously and quite rigorously that social category diversity contributes to cognitive diversity, but it is cognitive diversity that we’re after.

    Values: The third type of diversity is values diversity. You might think about it as a sense of purpose, and on that you actually want to be low. We want a common mission, even if we are of very different background, we’re pulling in the same direction

    Managing the team

    In most organizations, there are people thinking things that are different than what’s going on around them. But they’re not going to say it. Leaders of teams often stymie this process by indicating what they believe. Here is the leader, he or she leans into one sort of solution, one sort of decision, and everybody else falls into line in the investment or in business.

    It’s truly rare to have consensus. If you have consensus, you should be asking what the heck is going on…The onus here is on the leader. The leader of that group has to make sure that he or she is surfacing alternative points of view, making sure that their people are expressing those views in an independent fashion.

    [This section pairs well with Notes From Todd Simkin On The Knowledge Project specifically the section about a culture of “truth-finding”.]

  5. Implication of fundamental law of active management

    The fancy formula is “information ratio equals the information coefficient times the square root of breadth.” In plain words, it says excess returns are a function of skill times opportunity set. If an investor hopes to generate some sort of an excess return, you might use that as a guideline to break down the fundamental law of active management and ask if they’ve got the components in place.


    • Information coefficient is a measure of skill. If you project something, does it come true? It’s a measure of calibration in your skill, but you can also break that down in terms of batting average and slugging.

      This goes back to our conversation about Druckenmiller. Batting average is a measure for every 100 investments you make, what percent go up, literally just go up versus what go down. So we’re measuring that. And then slugging is how much money you make when you make money versus how much money you lose when you lose money. And of course you can have a low batting average if you have a very high slugging rate. If you have a low slugging rate, then you need a high batting average. I’d want to understand exactly how they’re thinking about that and that ratio.

      For example, if you have a low batting average, just slightly over 50, and you have very low slugging, you need a lot of opportunities. As a consequence, those are organizations where people have to be constantly churning for new ideas. By contrast, if you have an organization that says, we’re going to be relatively concentrated, we want a high batting average, and we want an even higher slugging average. They’re going to have to find gems of ideas, but they’re not going to find a ton of them. Then just making sure that everything seems to be aligned.

    • Breadth is the other one. One of the ways we measure breadth practically is through the concept of dispersion. How much variation is there in stock price returns. You want to know the dispersion of the asset class in which that investor is participating, and to see if the dispersion is sufficiently large for them to express their skill, and whether that dispersion is widening or narrowing. So that’s one way to have a systematic way to break down what a particular investment process looks like. And then you’re going to focus on the people.

      [Mauboussin has written extensively on when active management makes the most sense: when the dispersion of returns provides an opportunity for skill to reimburse its costs.


      Looking for Easy Games How Passive Investing Shapes Active Management (CSFB Research)

      Understanding Skill A Paradox Plus Qualitative and Quantitative Approaches (CSFB Research)

      You can find a repository of Mauboussin’s papers here. ]

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