资本配置者播客访谈

Transcript: Michael Mauboussin – Who’s On the Other Side? EP.99)

Published Date: May 13, 2019

Length: 57 min

Web page: capitalallocatorspodcast.com/mauboussin2

Michael Mauboussin is the well-known investment strategist currently plying his wares at Blue Mountain Capital. He joined me for the second time to discuss his new research entitled “Who’s on the Other Side?”

Our conversation dives into the work, discussing how investors can focus on process over outcome, the four types of investment edges, behavioral traits of single and group portfolio managers, portfolio position weighting, informational edges available from paying attention and complexity, the principal-agent issues that create cycles and opportunities during dislocations, the growth of private markets, and implementing his research. We close with a discussion of data analytics in the game of lacrosse.

Edited by: Rev.com

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All opinions expressed by Ted and podcast guests are solely their own opinions and do not reflect the opinion of the firms they represent. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions.

Ted: 01:23 Ted: 01:58 Ted: 02:27 Hello. I'm Ted Seides, and this is Capital Allocators. This show is an open exploration of the people and process behind capital allocation. Through conversations with leaders in the money game, we learn how these holders of the keys to the kingdom allocate their time and their capital. You can keep up-to-date by visiting CapitalAllocatorsPodcast.com.

My guest on today's show is Michael Mauboussin, the well-known investment strategist currently plying his wares at BlueMountain Capital. Michael joined me for the second time to discuss a new piece he published entitled Who's On The Other Side. Our conversation dives into the work, discussing how investors can focus on process over outcome, the four types of investment edges, behavioral traits of individual and group portfolio managers, portfolio position weighting informational edges in paying attention and complexity, principal agent issue to create cycles and opportunities during dislocations, the growth of private markets, and implementing strategic frameworks day-to-day. We closed with the discussion of the data analytics in the game of lacrosse.

Today's sponsor hasn't mind a fascinating way of getting your attention on an investment opportunity. Manny Friedman and EJF Capital are so passionate about the future development of the US through qualified opportunity zones that he asked me to find a way to urge people with taxable capital gains to take a closer look at these investments. The government came out with the next round of regulatory clarifications on April 17th, and we now have answers to frequently asked questions that may have prevented investors from diving in previously.

EJF has a fund that's investing in a bunch of projects across the country, but Manny's sponsorship isn't about his fund specifically. It's more about getting the word out, so this innovative government program can be successful. The incentives for taxable investors in both real estate and new operating businesses in opportunity zones are massive, and if the program scales, it has the potential to transform economic development for the better in a way that may be bigger than any of us can envision.

So, that's it. Manny's trying to spread the word and get smart folks to pay attention and find investment in opportunity zones.

EJF's fund is one possibility, and there are plenty of others, too,

Ted: 03:28 Michael: 03:29 Ted: 03:30 Michael: 03:52 Michael: 04:16 Michael: 04:35 but please take a look if you haven't already. If you want to learn more, have a listen to my podcast with Manny about the opportunity zones. It's episode number 91.

One last note, you may remember my very different conversation with psychologist, Michael Mervosh about the Hero's Journey. I've attached a replay of that episode on the feed. Start listening right at the 20-minute mark for a discussion of the journey itself in the mountains of West Virginia. If you're intrigued by the Hero's Journey immersion experience, now is a great time to sign up for this year's men's or women's summer journey. You can find out more at herosjourneyfoundation.org.

Please enjoy my conversation with Michael Mauboussin.

Michael, great to see.

Great to see you, Ted.

I want to dive in to your recent paper. As a framing of that, one of the things that you've talked a lot about is this concept of process versus outcome. It's now known that people should think about process over outcome and, behaviorally, we all think of outcome anyway. You have this question of, how long should you suffer losses? It's such a problem for everyone.

It is a huge problem. I don't know that there's a good answer to that. Part of it is there are two components, maybe, I would think about. One is to think about the system itself or the activity itself on how much is skill and how much is luck.

Obviously, the more luck there is, essentially, the more patient you have to be to see if a good process is going to reveal a skill over time. So, it's this backwards thing like you need larger sample sizes when there's more luck.

The second thing is to constantly reevaluate whether the process is a sensible process, right? So, you give your money to a money manager, and the results have not been good. There are one or two possibilities. One, the skill just doesn't reveal itself, and you're seeing a stretch of bad luck or the second is they've lost their marbles, and they don't know how to manage it anymore, right?

So, part of it is to say, "Can we constantly reassess process?" Some of the things I would probably think about, "Is the

Michael: 05:16 Michael: 05:37 Michael: 06:00 Michael: 06:27 analytical backbone continue to be sound? Is that organization making sure they are managing and mitigating behavioral things?" The third is an organizational one, "Are they dealing with agency issues appropriately?"

So, it would be those two things is the time horizon probably is a function of the skill-luck combination. Second is you have to check in to say, "Is that process, does it continue to be robust?" but a hard one to answer.

You recently wrote a paper that really defines inefficiencies in this elusive term edge. I thought it would be really fun to walk through that paper.

Well, I think that this is something that, clearly, all investors think about or really, anybody that's dealing with things that are probabilistic. You say, "I'm doing a transaction. How do I know that I'm on the better side of things?" This is also something I've talked a lot about over the years, but really hadn't sat down and really formally codified this to some degree. So, I would characterize this as a work of synthesis.

We ended up using an acronym BAIT just because it's an easy way to remember things. So, we talked about four areas in this taxonomy. One is behavioral. By the way, to some degree, everything is behavioral, right? So, in some way, we could distill it all back to that, but behavioral is the first one. The second was analytical. So, you and I have the same information, but we analyze it differently and come to different conclusions.

The third is informational. You know something I don't know or I know something you don't know. So, there's some asymmetries, but there's a lot of interesting subthemes and information mostly related to attention. Then last is technical, right? People have to do things for reasons that are non-fundamental. Those can be interesting opportunities, and they are often things like liquidity become really important. You have to be a liquidity provider. Yeah. So, those are the four high level things.

The other thing I'll just say in doing this research, I probably underappreciated, which is that there's really a market for information, so figuring things out or what you want to do, but there's also a different market like an asset market for how to implement the ideas. Those are handy to keep at separate

Michael: 07:10 Michael: 07:33 Michael: 07:51 Michael: 08:21 different things. You might have what you think is edge, but it might be very difficult to monetize it or you might have just a tiny bit of edge, but you can really monetize it efficiently.

So, there's a whole, again, a little matrix you could create just on those two concepts that I think is also really important. So, it's not just having edge, it's a way to make that edge translate into excess returns.

Let's start on the behavioral side. What is it about behavior that drives someone's ability to have an edge?

Just to clarify a specific point, a lot of what we talk about in the behavioral stuff are things like the heuristics and biases. So, these are the mistakes you and I make as people. So, we're overconfident, we anchor, and how things are framed affect how we decide and so forth. The point I try to stress is that it's not clear to me that those little things actually manifest in markets because they can cancel out, essentially.

So, the market is really ... You're not competing. It's not me, Michael versus Ted. It's really Ted versus the market. That's a different dynamic. So, you're competing with this thing, a complex system called the market. So, as a consequence, really, the level you want to think about it is how do people behave in group, in group settings. How do they follow one another?

So, there are two or three things that I highlighted. The first is something that we see everywhere. There are probabilistic decisions being made, and that's over-extrapolation. So, people take the recent past, and they think the recent past will continue going forward. There's some very nice work on this. By the way, Andrei Shleifer has a new book out, where they talk about this. Basically, here's a simple example. If the markets have been doing well, people think the markets will continue to do well. If they've done poorly, they'll continue to do poorly. So, over-extrapolation is one we see very commonly.

This is another very common thing in sports, for instance. An athlete, a baseball player has a great season, and he comes up for free agency. Well, if he's come off a great season, he's more likely to get an attractive contract, and if he's come off a below average season. Again, luck could be the complete explainer of

Michael: 09:46 Ted: 10:00 Michael: 10:31 that most recent performance, but somehow gets extrapolated going forward.

The second area I think, and this goes back to really complex system stuff is have the interesting question of, how's the wisdom of crowds flip over to the madness of crowds? All right. So, the wisdom of crowds exist when you have heterogeneous agents, good aggregation mechanisms. So, in other words, the information is being brought together, and you have good incentives. By the way, that should be your default assumption is that markets are pretty smart, and probably smarter than you are.

We have centuries of data showing that from time-to-time markets go haywire. I think the best way to explain that is this notion of correlated beliefs, whereas our views may have been heterogeneous before, and we come to believe the same thing.

There, I like to invoke this really wonderful line from Seth Klarman at Baupost where he says, "Value investing in its core is the marriage between a contrarian streak and a calculator," which is to say you want to examine the other side of the topic when everyone seems to be either bullish or bearish, but the most important piece is a calculator, which means that is led to an inefficiency, a set of expectations for that asset price that are too high or too low which will allow you to take advantage of it.

So, just being aware of that framework, that framework as distinct from classic efficient market frameworks like rational agent market models or even arbitrage models. I think it's a really, really rich vein to think about the behavioral stuff.

When you put those two things together, you have over-extrapolation of trends, and then you have the wisdom of crowds turning into madness of crowds. It dovetails right into this other paper you wrote on cyclicality because you could see how those two sets of beliefs take a good idea to an extreme. How do you as an individual or an investment manager think about you're trying to modulate your own behavior as it relates to the market, and at the same time, you need to be aware that things happen in cycles because of group behavior?

You could think about this. Even corporate performance is quite pro-cyclical. Things like mergers and acquisitions, share buybacks, IPOs have historically been associated with high

Michael: 11:47 Michael: 12:07 Ted: 12:31 market levels, right? On some level, that makes sense because when do companies have money is when they've been doing well, right? So, in other words, there's some logic to that, and by contrast, M&A tends to dry up when you've had difficult times. IPOs dry up and buybacks dry up. Why? Because these companies are struggling or they don't feel as flushed as they

do. So, there's that component of it.

Right. Again, just like anything in life, investing is all about trying to find that middle ground, right? When everyone is getting really excited about something, you want to tone it back down.

You're regressing, right? You're trying to regress toward the mean. When people are really pessimistic, you want to bring it back up.

It's all very difficult. I mean, just to be super clear. It's very difficult behaviorally because you think about March of 2009, so 10 years ago. You mathematically, the S&P had touched 670, earnings power was probably 85 bucks. You had credit spreads of thousands. VIX is going through the roof. You say from a normalized point of view, this is incredible opportunity. You don't need to go four digits on your HP-12C to know that this is actually a pretty interesting time to invest.

The flip side of that is if you were involved in markets, you've just gone through a horrific period. It's conditional, right? So, you're saying, "Gee! I can't afford to lose another 50% from here. This could be a real problem." So, even though the math is straightforward, I think psychologically and behaviorally, it's extraordinarily difficult.

Again, when things are going really well, it's the same thing. The dot com thing, your neighbor across the street is making a killing in internet stocks, and you're feeling like a chomp. You're like, "Maybe I can get part of that." We saw that, by the way.

Bitcoin was a classic example. We saw that in late 2017. Same thing. People felt if they weren't involved, they are missing something monumental and, of course, they come in right at the last minute just to see the price swung.

Once you're able to define out as you have some of these behavioral characteristics of inefficiencies, what do you do to improve?

Michael: 13:34 Ted: 13:53 Michael: 14:05 Michael: 14:31 Well, I think you try to monitor all these things. That's why we just anchor back on that Klarman thing, which is to say every time everyone seems to be uniformly constructive or pessimistic about something, you first want to dispassionately examine the other side. The key thing is really going back to what is the asset price baking in.

I say this with more than a dash of hyperbole that the biggest mistake in the investment business is a failure to distinguish between fundamentals and expectations, which is to say when fundamentals are good, we all want to buy. Welcome to the human race, right? When fundamentals are bad, you want to sell. Really, the mindset you should have is that of a handicapper, horse race handicapper. The fundamentals are how fast the horse will run. The odds in the tote board are what is priced in. What you're really looking for is not winners of races, but rather mispricing in the odds. That's the key component to always introduce, to ground this in a quality decision making process.

So, whether you're totally managing all the behavioral things, I mean, it's hard not to be caught up in it to some degree, but that's one way to ground yourself to say, "I'm going to be determined to always think about fundamentals and expectations as two separate things. They'll inform one another, but they're separate things, and then make your decisions accordingly.

How different is it when you have, say, a fund where there's really a sole PM compared to there may be a PM, but they have more of a group process?

So, there's interesting research on this. I think this is relatively a new finding last two or three years. What was found was that the funds that delivered the most alpha were actually funds with three portfolio managers, and better than single managers, and by the way, better than two and four. So, what's interesting about three is odd number, right? So, you don't need to have a consensus. You can have two versus one and make decisions.

So, that's an interesting question is whether ... I mean, the whole purpose of things like committees or groups is to try to find that center ground and avoid extremes that an individual may be more subject to. I think the challenge in any team

Michael: 15:23 Ted: 15:45 Michael: 16:01 Michael: 16:21 Michael: 16:34 setting or committee setting is that you really have to be extremely mindful about the process in that case.

So, the first thing is to have a team of people. If you're going to say, let's say, do three, four portfolio managers that you really want to make sure you have cognitive diversity. So, people that really do think about the world, maybe different sets of skills, maybe different personalities.

Then the second thing is you really want to manage the process effectively, which is the key to why you have group decision makings. It allows you to surface alternatives, vet them appropriately, and then decide. So, the point of a committee or a team is to allow you to do that as efficiently as possible.

So, I think whereas money management, the industry has evolved. By the way, in my career, it used to be almost all single manager PM funds. It was more than three quarters of them.

Now, that's less than a quarter. So, we've really seen a watershed change in the last quarter century, but I still think that people are not fully aware of how to think about the process of doing that the most effective way.

It's funny. As you're saying that, I put on my allocator hat, I'm thinking, so on the one hand, you could probably ask a set of questions. Let's say there's three PMs to try to figure out if there's cognitive diversity. If you've realized that there is, that can cause all kinds of issues, whether these people can get along.

That's right. That's a dual edge of diversity because you often hear ... Also, organizations will talk about how great diversity is. I think it is done appropriately. The downside is if people are too different from one another, they don't interact. If they're too similar, of course, then there's a group thing, right? So, there's this Goldilocks between these two extremes.

If you survey the diversity literature, it's pretty ambiguous about whether it's a net benefit or a net drag, but I will say that I think that if it's done properly, it should be a net positive.

I also mentioned just talking about this for a moment that when we talk about diversity, we specifically said cognitive diversity, but most organizations do on social category diversity. So, that will be age, gender, ethnicity, and so forth.

Ted: 17:36 Michael: 17:47 Michael: 18:02 Michael: 18:35 Cognitive diversity, as we've been describing, would be things like personality or training or experience, dispositions in some way, shape or form. There's only one paper that I've ever seen that attempted to tackle whether it was cognitive diversity or social category diversity that added value. What that paper found, and it was a couple of thousand mutual funds. It's hard to tag these things really super effectively, but what that paper found was that social category diversity was a neutral. It wasn't an additive or super negative, but the cognitive diversity, indeed, add value.

So, I would call that a nascent framework. For us, that's an area for additional work on that, but I think the key there is to say teams, committees, multiple portfolio managers can be really good, but you have to be very, very thoughtful about the people and the process in order to make that work for you.

If you're sitting across the table from a team, I mean, you sit in this interesting seat where you're at a fund, but you also talk a lot to fund managers, how do you think you tease that out in a series of questions?

Part of it is interesting even on this cognitive diversity, it might be, I mean, I guess you can talk to people, but it might be literally just looking at their own backgrounds and what kinds of things did you study in school, what are your interests away from the office or what have you. So, that might be as simple as something like that.

In terms of the process, I really would want to know that people are versed in the key components of it, right? I will usually say it's the composition of the team both in size and who's part of it, the process, and that's probably the knots and bolts of it. You said to me where most processes break down I think it's actually that. It's often because there's a leader, he or she has a senior person, typically, and they either wittingly or unwittingly undermine the process of surfacing different alternatives. Then the third is how you decide, which is voting strategies.

Once again, for example, a simple rule, if you're ever voting on something, it always should be independent ballots. What is not uncommon is for people just to go around the room and say, "Hey, Ted. So, what do you think?" Ted, you're a really important, smart guy, so what you say will deeply influence

Michael: 19:22

Michael: 20:03 Michael: 20:14 what I think or how I answer. I'll say, A, "I'd rather align myself with Ted the smart guy," and B, "It may be politically thoughtful to do that as well."

So, some might be just examination from arm's length, but some might be, really, to query people as to whether they really understand how to go through those processes as explicitly as possible. Again, I think it's rare that you'll hear people really be able to explain what they're doing. You may even guide them a little bit on that, but that to me would be how I might approach that.

All right. Let's turn to the next acronym, A for analytical.

There were a couple of buckets. This is actually a very rich area. One is just that there's differential skill. The example given to piece is there's been a really good word by Brad Barber and Terry Odean on this, and that's just institutions versus individuals. There's a really nice vein of work showing that when institutions compete with individuals, institutions tend to do much better. One example, the Barber and Odean papers on trading in Taiwan. Taiwan was a particularly nice dataset because they could really identify the characters behind all these different trades, and they found that institutions delivered excess returns, individuals lost money. You can see other examples of that like participation, IPOs, and other things.

Now, the challenge is often that individuals are becoming directly less involved with markets. They're now working more through intermediaries, so that, well, that's really interesting, maybe less relevant.

The second thing is this idea of weighting information. I got on this idea that I heard this story, and I think that it's maybe partially apocryphal, but it's interesting. So, Bill Gates, when he was CEO of Microsoft, used to carry around a list of priorities for the organization. So, it was called the top 10 things we're interested in. This is now the early 1990s, and a few of his senior engineers go off to a conference and it was about this called the internet. They come back and they say, "Bill, this thing called the internet, it seemed like it's going to be a really big deal."

Michael: 20:57 Michael: 21:23 Michael: 21:44 Michael: 22:06 Michael: 22:17 Bill goes, "Hey, look. It's on my list. It's number six. See? I got a card."

They're like, "No, Bill. You don't seem to understand. This should be number one with a huge gap, and then everything else follows."

I think that that's when Microsoft made a big pivot toward understanding the importance of the internet. So, there's an example where it wasn't that he didn't have it on his list, he did, but he had it in the wrong spot. This is very much akin to position-sizing your portfolio, right? You and I can have the exact same 25 stocks, but what we know is how we size our positions will have a huge impact on how our portfolio performs over time.

So, there's one interesting thing and this goes back to the stuff on overconfidence, which is you can think about two dimensions. One is the strength of a signal. So, for example, if you flip a coin 10 times and it comes up tails seven times, that's a strong signal, right? Then the other is validity, which is based on, basically, sample size, right? So, when you say 10 flips, that's probably not telling me all that much.

So, there's an example if you have strong strength and low validity like small sample size, people tend to be overconfident.

You flip that thing 10 times, they go, "It's a tails-biased coin," right? The opposite side would be like, "If you flip the coin 10,000 times and it comes up tails 5100 times," that's 51/49, you go, "Oh, it doesn't seem that big of difference," but it's 10,000 flips, right? That's statistic is extremely unlikely, right?

So, in the former case, it's much more likely to be a fair coin than the latter case, but most cases, we tend to be underconfident, right? So, it's this idea of how we weight the information I think is super interesting.

The other really, really big one, and I think this is ... If you said to me, "What are the biggest behavioral issues that we tend to deal with?" one would be overconfidence. The main concept there is overprecision. We tend to think we understand the future better than we do, but the second is really confirmation bias, which is you struggled to come up with a decision. You've really worked hard on stock X or whatever it is.

Ted: 23:19 Ted: 23:37 Michael: 24:07 Confirmation bias basically says you're going to dismiss, discount, disaffirm information against your thesis. If there's information that's ambiguous, it's a jump ball, it's always going to go your direction, right? I think that's something we all tend to do because we really prefer not to continue to think about the problem. So, that's an interesting question, especially in markets where a lot of the feedback is noisy based on asset prices.

How do you create structures in such a way that you become an effective updater of new information? It's super hard. You need to be super disciplined, but that to me is a big analytical one, right? So, you're updating your views based on new information.

I break down that analytical piece. I think I'm hearing two different things. The first is how much raw horsepower does someone have, and you could apply that to individual ideas like how good are they at taking a whole bunch of information about a company, and deciding whether that's a short or long or whatever it is.

The other is, really, portfolio construction, just this math and probability weighting exercise. In some sense, if you're sitting across the table from someone or lots and lots of people to take the 10,000 coin flip, after a while, you might think, "Ah! They seem like they have a lot more horsepower than the next guy." It feels like it would be tougher to tease out if someone good at weighting their ideas. How would you try to address that in the context of, say, trying to evaluate someone as a portfolio manager?

Yeah. I mean, I think that might be just having conversations. I think the weighting thing is really important, but also, the updating thing is important. Those are the things that I'd really would want to tease out. So, one of the things that's interesting I've always found and on this information weighting thing, and this comes up with my course at Columbia Business School, so the very end of the semester, the students pitch stocks to real portfolio managers, and they're doing buys and sells. It's a great exercise for them because they're getting a realtime feedback from a real professional.

Michael: 25:08 Ted: 25:41 Michael: 26:07 Michael: 26:30 One of the things I always stress to them is for most stocks, there tend to be two or three key issues. You might call them linchpin issues perhaps, and the ability to find those things and dwell on them as soon as possible tends to be very helpful, and that really might be this idea of information weighting.

So, you might have two investors, one who goes through this long laundry list of things around the company of which eight of the 10 items are not that relevant for value and two are really essential. Whereas, the other person will dwell on the thing that's most important.

So, again, how can you tease that out? I think it might be tricky, but it's almost always the PM that can understand the pivotal issues for a particular company. By the way, that's often the complaint I hear with PMs, portfolio managers and analysts. The analysts tend to value the breadth. They know everything and all these different details. The PM will say, "I don't really care about 90% of what you're talking about. Let's focus on these two or three key issues, these linchpin issues." So, that might be one way I'll try to understand what is the headline issues, and does it seem like they've got those things lined up correctly.

That dichotomy of the analyst and the PM, and if you marry that with the confirmation bias issue, is there any research that talks about the way that someone thinks about it? So, if somebody thinks about an idea as just, "These are the key linchpin issues," does it become easier for them to move on because they haven't done all this work to understand all 80 issues. They just really understand the three things, and it's easier to understand the three things at 10 different companies than the 80 things at 80 different companies.

Super interesting. Yeah. I think, well, there's a thread of research, and I'm sure you've seen this, but it's really interesting, and it also goes to our analyst-portfolio manager differences. The research shows that as you give people additional pieces of information about something, the accuracy of their forecast don't improve at all or their bets don't improve at all, but their confidence tends to soar.

Part of that is, the original study was done back in the 1970s, and it was with handicappers. So, if you're only allowed to get, whatever, five or 10 bits of information about a horse, you're

Michael: 27:20 Ted: 27:38 Michael: 27:46

Michael: 28:16 Michael: 28:33 going to probably pick the stuff that's most important first, right? I think in a handicap, that might be relatively self-evident.

So, I think the key task here is to figure out what matters first. I think that's for PMs. So, they're dwelling on that left-hand side of that graph, which is not that much information as accurate as a lot more information, and then not so confident, which means that the view is lightly held, and more malleable when confronted with new evidence. So, I think that is probably the sweet spot in this thing.

I think as an analyst, as you gather all these more information, you tend to think you know more than ... You would become more confident in your scenario, and that may be a mechanism that locks you in more than you want to be locked in. So, that might be one way to think about that.

Now, it probably does take a little bit of experience and savvy, and you have to understand competitive strategy and economics, and so forth, to be able to isolate, identify those linchpin issues. I mean, that in and of itself is an extraordinary skill, but that might be one way we could pars that a little bit.

This flows nicely into the next inefficiency or edge, which is this informational piece. Have you thought about the importance of information as competitive advantage?

There are a couple of components to this. The first is really this idea, can you find something out before other people can?

Every regulation out there is meant to make information dissemination uniform and relatively low cost, but to state the obvious, every idea starts somewhere. So, someone's got to know it before other people do. There's obviously a big arm's war, for example with data and unstructured data, to try to glean some of that information. So, there's a lot going on with that. That hasn't gone away.

By the way, one of the things I really like, there's a really nice natural experiment with this. So, when Reg FD went in to place, I think it was 2000, Ref FD was meant again to have uniform dissemination and low cost dissemination of information, so that individuals and institutions could be on the same footing.

One group that was exempt from that was actually credit analysts. So, equity analysts were getting the same information.

Michael: 29:53 Michael: 30:18 Michael: 30:48 Credit analysts were able to get inside baseball. It turns out the importance of credit rating changes went way up after Reg FD, which is super cool. So, that was an example of asymmetric information. Market recognized that that was important.

Why it's an interesting actual experiment is that Dodd-Frank in 2010 repealed that access. So, the credit guys went right back to everybody else, and immediately, the impact of credit upgrades and downgrades actually went away. So, it's a really nice example where that information truly was important. The market recognized it, and then when it was taken away, it went away.

I think for informational, the thing that is by far the most interesting to me, at least, is this notion of attention. By the way, this is way beyond just markets. This is just in our day-today lives, which is all this information is out there, but you either can choose to or going to pay attention to only a little part of it. I'll just mention one thing I thought was a fun thing. Everyone else probably seen the very famous Simons and Chabris gorilla video. So, you're showing these two teams passing around a basketball, light shirt, dark shirt, and you're asked to count the passes.

The key there is that your attention is being focused on this particular task and then, of course, this gorilla comes in the middle and beats her chest, and then walks off toward the end.

Many people did not see it. So, what's also interesting is I was just looking at this over the weekend. I'm reading this book by Eric Topol about healthcare, and I'm reminded of this that there was a study with radiologists.

So, they show these radiologists these long X-rays or scans, I guess, and they actually super imposed a gorilla in the corner of

it. It turns out that 83% of the radiologists failed to see the gorilla. Now, what's also cool is they have eye tracking software and they note that about half the radiologist who missed it looked right at the gorilla, and they didn't see it. Now, again, they're not looking for gorillas. They're looking for cancer, right? So, the attention issue.

So, the point is that what will you pay attention to is super, super important. By the way, there's a really interesting line of research on how attention can really affect your happiness.

Ted: 31:49 Michael: 32:13 Michael: 32:37 Michael: 32:48 What you pay attention to can affect how happy you are as a person. So, attention, I think, is a big deal. I think that's something that remains certainly wide open.

The last area that I think, and it's related to this, but there's certainly also a research showing that very complex situations tend to be difficult for people to sort out. So, for example, there's research showing, for example, if you think about a value chain for an industry, so companies and suppliers, and so forth, that if one part of the value chain, so for example, if a customer does poorly in an earnings report, for instance, it likely indicates that the supplier is going to do poorly because they're obviously interconnected, and the market can be slightly slow on the uptake on that.

Now, again, these are areas that people identified, and I'm sure it's gotten more efficient, but still, there's some evidence that complexity tends to create opportunities for those that can be coded more effectively and trade on effectively.

How much as more and more active managers use data analysis, artificial intelligence, whatever the buzz word is for using computers to take what they know to be fact patterns in their brains and making them faster? Can you think about something like paying attention? How much does that advantage go away as the attention of computers becomes longer duration than just say high frequent training?

Yeah. So, I would just say this that, and this actually reaches back a little bit on one of the points we try to make an analytic involvement. I think a lot of it has to do with time horizon. So, my sense is that a lot of where ... and natural language processing and computers, and so forth, will allow some parts of the market to be very efficient in the short run. You can make shorter term predictions. That will probably make that aspect of the market more efficient.

By the way, as a discretionary manager, I'd be very low to try to compete with those kinds of folks. I don't want to compete with the renaissance technologies or Two Sigma. Certainly on their playing field, they're really, really good at it.

The flip side is if you said time horizon, if I'm looking out three to five years, a much longer time horizon, it's not inconceivable.

Ted: 33:41 Michael: 33:54

Michael: 34:37 Ted, you and I get together in a few years, and we would say the future is going to be electric autonomous vehicles. I make this up, right? That's not implausible at some point in the future.

Well, what would the world look like? What are the primary, secondary and tertiary effects of that happening?

There is no program that can help you, a computer that help you do that because this is not in the data, right? Defining the bands of where you as a person are likely to be able to add value versus where you can. So, I think it's in the shorter term stuff. It's extremely difficult to beat these things.

Now, whether, for example, a natural language processing would reveal, for example, this cantor drug and the beneficiaries of it. I don't know if there's specific people working on that, but again, I would just assume that things that are shorter term now are probably more efficient.

So, the behavioral analytical information, a lot of it, that's behavioral, is tied to that notion of companies? It's what I think about companies. Let's shift over to technical, which gets more back to sound of the market.

Yeah. It goes back to the market. I think that maybe the overarching theme in technical is really this notion of principal agent issue, and are people doing things that are not related to fundamentals? So, we talk about a few things. The first is this notion of just basically forced buyers and sellers. One of the models I like a lot with your Yale connection is John Geanakoplos' model on the leverage cycle. The story is pretty straightforward. It's this optimistic people. For whatever reason, they're optimistic, and they have access to leverage. So, they buy a particular asset, they drive it up, they use leverage to do that, and then John in John's story, there's some bad news, some shock, which forces the asset price to go down.

So, now, all of a sudden, we get this positive feedback on the way up. It becomes positive feedback on the way down is those people have to sell some of that asset when it goes down, and then they get margin calls. So, when they get margin calls, it forces them to sell more to get their margin back, the equity back in line.

Michael: 35:32 Michael: 35:56 Michael: 36:15 Michael: 36:38 Then there's another factor, and this is what John really emphasizes is the terms of the margin become more onerous, right? We saw this even in housing market, but in other words, I would lend you 80 cents, you put up 20 cents of equity. Now I say, "No, I'm going to lend you 50 cents," and you have to put

50. So, in other words, you have to sell even more to meet our new stringent margin requirements and that compels the asset price to go down.

So, that positive feedback on the way up and positive feedback on the way down is a great example. Now, these don't happen everyday, but some of the greatest biggest we've ever seen are related to the leverage cycle. I think that's a central actor on what we had in the financial crisis.

The other example I've always been fascinated with is arbitrage. By the way, you go back to how do we get to market efficiency. There's three classic way to do that. One is mean variance. So, we have rational agents that go around and understand their preferences and buy and sell accordingly. I don't think anybody really believes that cartoon version, but it's really nice benchmark from which we can depart to understand how markets work.

The second argument, I think, is where most finance professors would be, and this is the absence of arbitrage. There are no $20 bills lying on the street. So, if there are aberrant price gaps between price and value that there is arbitrageur who cruise markets, who buy what's cheap and sell what's dear, and bring prices back in line, and collect a little toll on the way.

As a first order consideration, that's absolutely right. I mean, there are arbitrageurs and they do this everyday, and the interesting thing is that it is often the case when some of the arbitrage opportunities are among the most attractive, the arbitrageurs don't show up. The main reason they don't show up is because they don't have access to capital. It goes back to this principal agent examples.

So, we talked a bit about this, and probably I think one of the best documented examples was longterm capital management.

A lot of longterm capital management book was classic arbitrage trades. Many of those things were as plain vanilla, the on-the-run, off-the-run 30-year treasury bond. That's a straight

Michael: 38:07 Michael: 38:21 Ted: 38:33 Michael: 38:35 up textbook example of arbitrage. What you do basically in that case is, typically, the 30-year trade is a little bit, a little slightly lower yield than the 29.5 year even though mathematically it's exactly the same security.

So, you go long the 29.5 and you short the 30, and you just wait for the spread to contract again. Well, the spread widened, again, classic arbitrage, and the arbitrageurs didn't show up, and the spread just kept getting wider and wider. Of course, this is a very levered position, so longterm capital management end up being in a lot of trouble. I think we probably will have well-documented from the financial crisis of other examples of these arbitrage opportunities. So, that's a really interesting one, too. Again, it's very episodic, but these arbitrageurs don't show up.

The last thing I'll say that I've always found interesting, I think some of this has been diminished in recent years because of technology and trading, and so forth, but this idea of demand shocks. We teach in finance that demand curves are largely horizontal, right? That's because you can create supply. What we also know is demand curves are downward sloping. The original literature on that really came out of things going in and out of indexes, where there is nothing different about the company or its prospects from day one to day two beside the fact that it was now in an index and that created the demand.

So, there have been some really interesting papers about who has the money, what do they want to buy, and what does that mean for these downward sloping demand curves, and there's good evidence that you create these excess returns as a consequence simply of these demand shocks.

So, there are these little technical things that, again, they have nothing to do with the fundamentals of the businesses per se, but there are these features of the market that if you're well-positioned, you can probably take advantage of.

What does it take to be well-positioned to take advantage of?

I think the big thing is just having access to capital, and that's something that runs through all these themes because you mentioned briefly this stuff on pro-cyclicality is, again, when things are going well, people feel good about the world, and they want to do more of what made them feel good, and when

Michael: 39:42 Michael: 40:05 Michael: 40:49 markets had done poorly, they want to do less of what feels

bad. So, yeah, it's access to capital.

The question is, how do you as, if you're an investor, how do you make sure that you always have access to capital? Now, you work for a very famous endowment, and I think some of these endowments certainly should be in a position to do that. You think about guys like Warren Buffett. One of the advantages is he constantly has flowed. He always has money coming in the door. That really helps for you to be able to behave in a way that counters this pro-cyclicality.

If you take outside of Baupost, which is a notorious example of Seth and the team have run for a long time with a big healthy cash balance and from the returns of earned the right and trust of their investors to do that, if you're trying to, say, allocate capital to managers who I think have an opportunity to go the other way, what are you looking for?

What comes to mind is Rick Bookstaber a couple of years ago wrote an interesting book called The End of Theory. The End of Theory, basically, argues that in finance and economics, we don't have very good theories of crisis. It's like when the mail is being delivered on time, and the trains are running, we have pretty good stuff that helps us understand that, but crises, we're not very good at.

So, he advocates for an agent-based model that allows you to simulate the world many times and see these difficult situations, right? He had a really interesting little discussion toward the end where he said, "It's almost like Ulysses Contract," which is to say you go to a sovereign wealth fund or whatever, some organization that has capital and you say to them, "Listen, here are certain either priced levels or spreads for credit or whatever it is where if this happens, we want you to give us money. We, in fact, want to do Ulysses Contract with

you. We want to say if credit spreads get to 1,000 bases points or whatever the number is, we're going to come and ask you for X dollars, and we want you to write the check."

By the way, you're not going to want to write the check because you're going to be freaked out. So, some mechanism like that, the question is whether you could create these pre-commitment contracts that would allow you to act in these

Michael: 41:56 Ted: 42:06 Michael: 42:19 Ted: 42:40 Michael: 42:53 situations. By the way, I'm reminded, I mean, this helps me think about this great work by Atul Gawande on checklist, right? That's a great book, The Checklist Manifesto.

If you read the book, I mean, there's two different kinds of checklist. One is called the do confirm, right? So, you got to go about your job, da-da-da, and then every now and then, you stop and pause, and say, "Can I confirm that I had done all the stuff I was supposed to do?"

The second checklist is called redo. The redo says something bad happened. You're freaked out. The left engine on your airplane is dead. You go to the checklist and it says, "Read." Left engine dies. Here's what you do in this order. The reason a redo checklist is really helpful is it takes the emotion out and gives you an action plan. I think we need something akin to that in the world of investing, which is take the emotion out, have an action plan, and allow people to act on these things.

Now, look. Maybe someday the world will end, but so far, the world hasn't ended. So, I think more times than not, these kinds of pre-commitment contracts could be really helpful for people.

How do you handle? There's this dichotomy of the pre-conditioned contracts to handle a crisis, but then on a day-today basis, when we're not in crisis, you still have some of these more micro technical opportunities.

Yeah. Those tend to be not as large or not as difficult to deal with, right? Look, we, like many other investment organizations, have people to do this all day. So, they're in and out all day trying to think about these kinds of things. I guess we're talking about, at least for me, where the principal agent issues become the most pronounced is when you have these really major dislocations, and it happens.

We've seen if you go across markets, there are certain assets like distressed at where people have raised commitment funds.

Private equity is probably the greatest example if you have multiples. Have you thought about any ways to execute on that in the public market?

No. I don't know a way to do that. I've been thinking a lot about this topic of public versus private markets. There are certain ... Both of those markets have their pros and cons, but that may

Michael: 43:33 Michael: 44:02 Michael: 44:20 Michael: 44:43 be something that may be a check in the benefit for private markets. It allows you to have these mechanisms in place.

Now, I guess you could do something similar just to say in public marketing, we're invested in some public vehicle. If we have, again, preordained, whether it's some magnitude of some drawdown or some evaluation levels or some combination of these things that we go back to our pre-commitment contracts, but I'm not aware of anything. Like you said, you do see it much more in private stuff than you do.

What are your thoughts on private markets, since you've mentioned it?

We wrote a piece a couple of years ago about the decline in public companies, and a lot of it is smaller companies moving out, but one of the points I thought was interesting is just taking a step back and saying, "You're the CIO of Yale let's say in 1975 and you want to expose your two US equities." Basically, you'd buy the Wilshire 5000, which only has 3700 companies by now.

You are at the Wilshire 5000, right? Maybe you get in some early stage venture, but basically, your base would be covered right there.

Now, if you're doing the same thing, you'd have early stage venture, you'd have late stage venture, you'd have private equity, which has gotten significant, and then you'd have public markets. Part of it is you and I as regular guys don't have access to all that stuff, whereas a sophisticated endowment might have access to that.

So, I've been fascinated by these ecosystems, especially, for example, these unicorns. Now, it's interesting, of course, this 2019 appears to be a year where a lot of these things are coming public, and we'll see how this goes. It's a fascinating development. The notion that you could be a multi-billion dollar valuation company raise hundreds of millions of dollars in late stage venture.

By the way, even to the degree which you can cash out employees so they can monetize, I mean, all the mechanisms that used to be crucially done by public markets, now, many of these things can be done privately. I think that's really interesting. Now, that said, I mean, you go through different

Michael: 45:58 Michael: 46:21 Michael: 46:38 asset classes. I mean, I think private equity, these multiples are going up. These guys are paying to acquire businesses, and there may be some justification for that, but these are the interesting dynamics is to say it's been a great asset class. It is a party that has been going too long kind of thing.

When we last recorded a podcast, you had pretty much just arrived here at BlueMountain. There's a lot of really interesting structural things we've talked about. What's it been like on that side of your day job taking these frameworks and seeing how they apply inside this organization?

Yeah. I think a lot of it for most investment organizations, we've been talking about I hope should be mostly mom and apple pie for people, right? In other words, there's nothing here that should be shocking. The challenge, I think, everyday is two dimensions. One is having some flexibility to think about these things in the first place, right. So, most investment professionals are really busy making money, and don't allocate a ton of time to think about these.

Then the second is, really, what are the processes you can put in place to make sure you're trying to do these things effectively as possible? We talked a few minutes ago about what do you want to call a team or a committee and those dynamics. The challenge is to put in to place the things that we know allow those things to work well, and decide stuff or avoid the things that don't allow those to work well.

Who's on the other side? The name is report. It does sound like a very basic question, but it's a really interesting question is every time you do something, ask that question, right? You should, hopefully, have a satisfactory answer for it. Again, that's just a discipline thing versus anything else.

So, the other about our industry in general is that, and this actually goes back to principal agent issues, is that sometimes people feel like they have to do things, and having to do things can be good and can be not as good. In one of our pieces, we wrote about it. We call it instead of principal agent problem, we call it principal agent agent-agent problem, right? Again, you're the CIO of an endowment, you might have a committee, which hires a consultant, which hires an asset manager, and then alarm bells if there's poor performance, alarm bells coming up

Michael: 47:47 Michael: 48:09 Ted: 48:33 Michael: 48:59 and down the chain. The committee doesn't say, "Let's do nothing." They always say, "We should do something," right?

So, this notion, and by the way, I think it's a Western thing, maybe an American thing, too, this notion toward action or activity versus doing nothing. So, sometimes just sitting on your hands is the best to do, and it's very difficult when you have a number of folks, which may not be completely aligned in terms of the end objective. Those are the interesting things.

So, in your day-to-day now as Andrew brings you in and you have a fantastic organization, there's a lot of ideas coming in, do you get brought into meetings to evaluate? How have you integrated into the process?

It's really two parts. One would be just to make sure that a lot of is just make sure the process is to begin. Analytical processes are good, right? So, if you're having an investment idea, like we talked about before, other proper ideas being prioritized, is the presentation clear and so forth. Then a lot of it is, yeah, it's process stuff on how group decision making would work.

Then there are lots of little sub-projects. You want to make sure that, for example, your analytical processes are uniform across different teams. So, these are mundane things, but do we calculate return on investment capital calculate the same way.

Do we calculate cost to capital the same way? Just to make sure that everyone's communicating using similar language in such a way that allows us to make comparisons and choices from one thing to another in an effective fashion.

Well, we can't sit down without talking somebody about sports.

So, I thought ... A couple of weeks ago, I interviewed Paul Rabil.

I know you're a lacrosse player in college. So, I, actually, relative to other sports, I'm not very good at lacrosse. So, if someone is going to tune in in June, in July, whatever it is this year and watch the PLL on television, what are the key ... So, if you're doing data analytics on lacrosse, what matters to first success?

So, lacrosse is actually not dissimilar conceptually I think to basketball. It's more complex because there are more players, but it's conceptually very similar to basketball. There are a couple of interesting differences, but it boils down to possession and possession efficiency. So, how many possessions?

Michael: 49:35 Michael: 49:54 Michael: 50:15 Michael: 50:35 Michael: 50:57 Ted: 51:03 Now, the reason it's different than basketball is after scoring a goal, you have a contested possession in the form of a face-off. Hockey face-offs, lacrosse, it's a real specialization there. Guys just take face-offs. So, if you have an amazing face-off guy, you essentially make and take it, right? You score goal and then you can get the ball back and just do it over and over.

What does it take to be an amazing face-off guy?

Yeah. So, I mean, these guys are ... By the way, there are people who are really ... It's gone very specialized. Yeah, I don't know, quick hands, good center balance. I don't know what those guys do exactly, but it's possession, possession efficiency, and then if you breakdown possessions at least on the offensive side, it would be typically what we look at is shots per possession.

There's two other weird things about lacrosse. One is you can run behind the goals. Unlike basketball, you can run around.

The reason that's interesting is because it changes the defensive dynamics. In basketball, the basket is always to your back if you're facing your offensive player and you're playing defense.

In lacrosse, the ball could be behind you. It could be behind the goal. So, you have to swivel your head back and forth, which is interesting.

The other thing in lacrosse, which is weird, is if you shoot wide and it goes out of bounds, the closest person to the ball gets the ball back. So, it's essentially a free offensive rebound, right? You get the possession back. So, how many shots per possession, and then shooting efficiency is probably the single biggest thing, and it's like basketball, how efficient are you in shooting.

There's some interesting stuff. I mostly work on college lacrosse. There's a really fascinating arbitrage, which is Canadian players who generally learned to play in box, which is a different game. It's in the hockey rank, much closer quarters, much more contact, and the goal is smaller. When they come on to the field, they're vastly more efficient shooters.

So, to give you some sense, the average American shoots, like in division one, 28%. The average Canadian-

20% goals or 20% on that?

Ted: 52:05 Michael: 52:16 Ted: 52:24 Michael: 52:26 28% goals. So, for every 100 shots, 28% are goals. The average Canadian shoots about 34%-35%. So, it's a 700 or 800 bases point arbitrage in the shooting percent, which is interesting, right? Yeah. So, I think it's very much like basketball. Where I try to think about lacrosse analytics more rigorously, the book that I actually turn to is Dean Oliver's book called Basketball on Paper. Oliver is a basketball analytics guy. It was one of the first books that I had ever seen where it actually mapped all the possessions to understand exactly this notion of how many possessions they have, and what the efficiency is, and how to measure that efficiency. So, that to me would be my high level answer on lacrosse.

There's a lot to be done, things like shooting efficiency. I don't know exactly this new league whether they're going to have a two-point shot. They have a major league lacrosse. Anyway, there are things like at what point ... Like NBA, at what point does it make sense to take a two-point shot versus a one-point shot? Where on the field, there are people who are effective.

So, those heat maps on shooting, stuff like that. So, there's a lot to be done that's really cool.

All right. We'll be watching. All right. I did look in our last question, and fortunately, there's still a list of closing questions I hadn't asked you the first time. So, we'll go with those. What's your favorite hobby or activity outside of work and family?

I like to read a lot. So, I know that quasi work. I probably read, I don't know, 40 to 50 books a year. So, I try to do about a little less than one a week, and that's fine.

How do you decide when you're going to read through the whole book?

Yeah. I almost always read the whole book for better or for worse. I have a large ... For every book I read, I buy many more books. So, I have a huge library of things I've not read. I will typically flip through them and try to familiarize myself at least with that. So, reading, but I would say probably, actually, sports. So, I'm a big sports fan. I love watching almost any sport on TV, and I still have got a bad knee, but the one thing I'm allowed to do is play ice hockey. So, I still play ice hockey at a winter club. So, that's good fun.

Michael: 53:30 Ted: 53:52 Michael: 53:53 Michael: 54:13 Ted: 54:35 Michael: 54:39 The other thing I'll say about that besides it's good exercise, and it's a great sport, there's a lot for the camaraderie in these locker rooms because hockey happens to be a weird sport where you spend 20 minutes before you play and 20 minutes after changing and unchanging. There's also a lot of folks that play that are not in the world of finance or business, which is great. So, it's like getting access to different walks of life. So, yeah, I would probably say reading and sport. I love travel and all that kind of stuff, but those are probably be the big ones.

So, I think ... I play in beer league hockey, too. I have not succeeded in getting any of my teams to not pull the goalie after reading Cliff Asness' paper.

Exactly. Exactly, but it is funny because I'm a nerd on this. I almost always know my plus minus, even though at pickup game, I keep tracking my plus minus. I'm like, "I don't know if we could start doing coursey calculations for the different players," but I think about these things analytically. It's like, "Okay. Probably you should not worry about this Cliff Asness' analysis."

What's your biggest pet peeve?

Well, I'm sure my wife would say it's how people load the dishwasher in our house. That's probably not what you care about. I think in our business, I think the one thing that it's very easy to be superficial about lots of topics. Usually, when you dig in to something, there's a lot more subtlety and nuance than people perceive. So, plus, you and I are reading things.

It's funny, even when I do a lot of ... A lot of the research I do or what I write about is often synthesis. We do some stuff that's new, but a lot of it is synthesis. It's funny. I'll read a book and I'll say, "Oh, that's awesome," and then I'll go back to it. When you start to push on the details of it, you're like, "I don't know. It's not really that ..." It's either not that deep or not that tight. So, that would be ... I don't know if it's a pet peeve, but that's something that I would say is suboptimal.

In all the reading you do, is there any reading that you almost never miss?

Haha. So, probably, I was thinking about this one, too. There are probably two authors who I never miss, and one is Matt Levine

Michael: 55:30 Michael: 55:59 Michael: 56:23 Ted: 56:47 Michael: 56:49 at Bloomberg. That guy is an absolute genius. Look, he takes topics that are ... Certainly, they're obviously topical things, but breaks them down in a way that's very intelligent, I think, and often very entertaining. So, he's clearly super smart, and his writing is really fun.

The other one is Micheal Lewis, who I think probably not all of his work is of the exact same quality, but the guy is just an amazing, amazing storyteller, and he's got an amazing nose for interesting topics. So, I'd marvel at both of those guys how talented they are and what they do everyday. So, those would be two guys I would point to.

What is your favorite motto that teaches a life lesson?

So, this is going to be very nerdy. So, I went to high school that was run by Benedictine monks, and all of us had to take Latin, which I was not good at. There is a quote that was some of the monks are talking about and it's called ... The quote is, "Age quod agis." It's Latin. "Age quod agis" means do what you're doing, literally, but it's more like in the football they say, "Do your job," it basically means do your job.

This is something just a sense of responsibility that whether you're a teammate or part of an organization is just to show up, be in the moment, be present, and get after it. You went in school. You complained about how many things or work, right?

You complain about how many things you have to do and all these things that are going on. "Age quod agis" would say something like, "Just put your nose down and get after it," right?

So, this is for our kids. We have five kids. They have a little area where they would do their work. So, it's up on their chalkboard.

I think my wife did this, but one Christmas had T-shirts made for everyone in the family with this motto on it. So, the kids have gotten this beat into their minds. So, don't complain. Don't belly ache, just get after it. Do your job. I think that's a great lesson for people at any point, at any age.

Great. Well, Michael, thanks so much. It's always fun.

My pleasure, Ted. Thanks.

Ted: 56:51 Thanks for listening to this episode. I hope you found a nugget or two to take away and apply in your investing and your life. If you'd like what you heard, please tell a friend, and maybe even write a review on iTunes. You'll help others discover the show, and I thank you for it. Have a good one, and see you next time.