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Episode #14: “It’s Not Greed and Fear that Drives the Investment World; It’s Envy”

 

Guest: Eric Crittenden. Eric is the Chief Investment Officer of Longboard Asset Management. He brings nearly two decades of experience in disciplined, rules-based investment strategies to his position. Eric drives Longboard’s focus on offering high-quality alternative mutual funds that seek to deliver long-term results. Numerous publications have cited his research on trend following investment strategies, including The Journal of Finance.

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Date: 8/9/16

Run-Time: 52:49

Topics: Episode 14 is easily one of our most interesting so far. While there’s great content about trend following, Eric and Meb also delve into the psychological side of investing. There’s a fascinating tension between what people say they want from investing, versus what they actually do. For instance, investors say that want diversification, but very few, in practice, are willing to implement a truly diversified portfolio. Why? The psychological trauma that people experience when they diversify (and watch parts of their portfolio draw down) is simply too painful. This leads into a discussion about one of Eric and Meb’s favorite ways to diversify a portfolio: managed futures. The numbers suggest managed futures are a fantastic addition to a portfolio. Eric ran an experiment with his clients involving portfolio construction. He presented clients the returns and volatility numbers of a handful of asset classes – without revealing what those asset classes were. 100% of the time, when presented blind, people chose managed futures as their core holding. Eric and Meb then move on to the returns of great fund managers like Buffett and Soros. Eric studied these managers with the thesis that they must have done something other investors are uncomfortable doing (which is the source of their long-term alpha). He concludes that this differentiator is actually “underperforming their benchmark.” Eric says Berkshire Hathaway is a “glaring” example. An investor in Berkshire would have underperformed the S&P more than half the time (over various time-periods), but would have made tremendously more money than investing in the S&P. This leads Eric and Meb back to the psychological side of investing, specifically, the pain of relative performance. Meb recalls the Buffett or Munger idea that it’s not greed and fear that drives the investment world; it’s envy. Meb then turns the focus toward playing defense, which leads Eric to tell us how few people realize the impact on their returns of avoiding drawdowns. Avoiding the big losers has more impact on your compounded returns than catching the big winners. In other words, defense is what wins championships. There’s far more: how 80% of all stocks effectively return 0%, while just 20% of stocks account for all market gains… a pointed warning from Meb to listeners about the fees associated with managed future “fund of funds”… and of course, plenty more on Eric’s trend following approach. All of this and more in Episode #14.

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Running Segment: “Things I find beautiful, useful or downright magical”:

Transcript of Episode 14:

Welcome Message: Welcome to the Meb Faber Show, where the focus is on helping you grow and preserve your wealth. Join us as we discuss the craft of investing and uncover new and profitable ideas all to help you grow wealthier and wiser. Better investing starts here.

Disclaimer: Meb Faber is the co-founder and chief investment officer at Cambria Investment Management. Due to industry regulations, he will not discuss any of Cambria’s funds on this podcast. All opinions expressed by podcast participants are solely their own opinions and do not reflect the opinion of Cambria Investment Management or its affiliates. For more information, visit cambriainvestments.com.

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Meb: Hey, everybody. We have a great podcast coming up with you with my buddy Eric Crittenden. And I wanted to do a quick intro. And one of the reasons is a lot of investing topics can be a bit jargony. So I wanted to just quickly overview, define two topics we’re gonna be talking a lot about today. The first is trend-following. We talked about this at [inaudible 00:01:47] on my blog and books and white papers. But in general, remember that trend-following is simply an investment approach that’s been around for 100 years. The goal of trend-following at its core is simply to invest in a market that’s going up and either be out, sell a market that’s going down, or be short. There’s a lot of indicators that can help you measure those exact trends. It could be something as simple as a long-term moving average, something like a channel breakout, or something as simple as this security hit the highest high of the past two years or you sell it when it’s hit the lowest low. Infinite ways to examine this but the goal…and this applies to any market. You could do trend-following on stocks, on foreign bonds, on Bitcoin, whatever.

And then we also talked about asset strategy where-trend-following is applied to as many assets classes as possible. And historically, that’s been known as managed futures. And this strategy has been around in its current form with commodity trading advisors, CTAs, commodity pool operators, CPOs, and now as mutual funds and hedge funds as well. And the goal of managed futures is to trade as many markets as possible. So Eric talks about trading over a hundred markets around the world and even 50 distinct markets all with the trend-following approach. So you may be long wheat, for example, and short the Japanese yen and long European stocks, so all of these markets. And this sort of ultra-diversification and different approach, meaning you’re both long and short, is one of the reasons managed futures is such a wonderful strategy historically to combine with a traditional portfolio. So just wanted to give that real quick overview and enjoy the show.

Good morning, friends, and welcome to the show. Today, we have an extra-special guest, a long time friend. Eric Crittenden, welcome to the show.

Eric: Thank you, Mebane.

Meb: So Eric and I go back about a decade. I knew Eric and his partner Cole when they were just a two-man shop. They’re now, I think, approaching 60 employees, Longboard Asset Management, Longboard Funds located in Arizona. Eric, if I remember you correctly, what time did you get up this morning?

Eric: About 5:45 a.m.

Meb: Oh, man, you’re sleeping in these days. You’re slacking. You got a bunch of employees. Eric used to get up around 4, and we used to chat, and I’d visit him in Arizona. And I have a very fond memory when he picked me up once. It’s probably 110 degrees outside, not joking. He picks me up, windows down, so no AC going on. And he just picked up a hot coffee. And I was like “My God, man, you are open to punishment.” And I was just wilting in the heat. Like many of our guests, Eric has somewhat of a winding road to get to Wall Street. Eric, why don’t you give us a super quick background to how you guys got Longboard started in your background? And then we’ll get into all the good trend-following stuff.

Eric: Okay. Well, my background is a little bit unusual. I started out as a medical student in the early 1990s. I didn’t know anything about capital markets, had no interest in stocks, bonds, derivatives, futures, none of that stuff. I had a thing for the natural sciences. My first love was meteorology. And also, I grew up surfing in Southern California. I really had a fascination with dynamic systems, systems that had non-linear elements, and basically phase state changes, so surfing, meteorology, storms, weather, things like that.

In my first attempt at college, I was pre-med for several years, so I took all the science classes and math and whatnot not from the view of a business student. And it wasn’t until later that I developed a fondness for economics, econometrics, investments. So I had to retake a lot of classes from the perspective of a business student. And I think that that gave me a unique perspective on the world, seeing things from different perspectives, having different priorities when you’re looking at data and a different level of respect for data.

So after spending nine years in college, I think I had five different majors, I eventually graduated with a degree in finance but had a heavy emphasis on computational finance derivatives, modern portfolio theory options, pricing and spent a lot of time studying computer science as well. So my first job out of college, I was a teacher, loved that job, but it didn’t pay very well, and ultimately ended up working for a big family office in Kansas for a number of years and learned quite a bit about the psychology of investing, how people mentally make decisions differently, depending upon whether they’re profitable or unprofitable or they’re feeling pressure.

Meb: Let me interrupt real quick. Two questions, one, where in Kansas was this? And two, wasn’t this where you started looking at managed futures strategies and trend-following strategies in general as well?

Eric: It was in Wichita, Kansas. This was the mid and late 1990s. And yes, I had a fondness for contrarian thinking and skepticism and a database and, you know, a computer science data aggregation background. So I spent a lot of time trying to figure out if there was value hidden in plain sight, and that led me to a lot of data analysis. When you’re looking at global financial data, you can basically distill it down to a handful of sustainable risk premiums. And there was one in particular that was not very crowded and not very well understood. And we called that the risk transfer premium. And that is what trend-following, commodity trading advisors source. Most of them don’t even realize that that’s what they’re sourcing. But that caught my attention when I was younger, because, you know, supply and demand, you wanna go after risk premiums that aren’t crowded so that your profit margins aren’t threatened over time.

Meb: Just to clarify real quick, when you say risk transfer, you’re meaning something like the hedging markets. So if you’re a cereal company, you may need to be buying wheat futures, or if you’re an airline company and wanna hedge oil prices. Is that what you were talking about, or are you talking about something else?

Eric: No, that is what I’m talking about. Whether you’re a corporate farmer and you’re trying to hedge, you know, your production costs or your output prices, there’s hedgers on both sides of all the different derivatives markets, even some of the counterintuitive markets, like short-term interest rates, equity indexes, and whatnot.

Meb: Really quick interesting aside. I wrote an article called “How to Hedge Your Business.” And we were thinking about the traditional asset management businesses that are equity long only, and you guys aren’t, and neither are we. And I always said, you know, assuming these guys treated their book of business like a commodity, it always was curious to me why they wouldn’t hedge some or all of that through straight-up options, derivatives-based hedging, or a trend-following approach. Because all of their business is related to management fees based on long-only equities, both the assets will come out, and the revenues will decline when their assets under management go down. Anyway, totally different aside. It’s a fun article I’ll put it up in the show notes. But all right, totally, totally different tangent. Let’s go back. So all right, so you were looking at a lot of these strategies, managed futures for this family office. Were they receptive to it? And then that also led you to, I think, then moving to Arizona to start your own company, right?

Eric: Correct. You know, in theory, people are receptive to the idea of bringing in uncorrelated risk premiums, uncorrelated to what they’re currently over-allocated to. In practice, it’s very interesting, the psychological trauma, for lack of a better term, that people experience when they diversify properly is one of the most fascinating observations I’ve ever made during my life. And I’ve been doing this for 20 years now, and nothing has changed. People want diversification. They want a higher quality of their portfolio. They want higher returns at lower risk. But in practice, very few people are actually willing to do the things necessary in order to achieve that. And the family office that I worked for in Kansas was no different.

Meb: And if you had just to give one reason, is it because people don’t wanna look too different? What is the overriding reason that people…because the example we always give, and I totally agree with you, in trend-following, in my mind, managed futures, we always called it desert island strategy, is the one big diversifier strategy that if you went to a CFA meeting and said, “All right, we’re gonna blend all these asset classes or strategies on paper, and you’re gonna have to select which is the best diversifier or return enhancer and everything,” you would end up with almost everyone in the room selecting managed futures and, not only that, selecting it for a very large part of their allocation. What do you think is the main reason that people…is it because they don’t wanna look too different? They’re unfamiliar with the strategy? What do you think it is?

Eric: That is a very interesting question. And in fact, what you just described is very similar to an experiment that I’ve done many times over the years. Or I’ve done exactly that. I have put in front of potential clients or existing clients a bunch of different return streams without identifying what those returns streams are. You know, it would be real estate, equities, bonds, managed futures, and maybe a hedge fund index. And I tell them you, know, “Build a portfolio. Start with your foundation asset class. And then start building a portfolio from there.” So what they’re looking at are the compounded annual returns, the annualized volatility, the maximum drawdown, and then the cross correlations from all the asset classes. And about 100% of the time, people will choose managed futures as their core foundational asset class. And after that, they’ll choose typically the hedge fund index and then real estate and then bonds and then stocks.

Meb: We got to pause on that too, because Eric and I have been collaborating on research for almost a decade now. One example, I mean the hedge fund index, that already is the one that…there’s a couple of major versions of those, but almost the one that’s, you know, usually widely cited is not investable right? The investable version of that, the returns are about four percentage points less than the non-investable version. So on paper right there, yes, they may select it. But it’s, in reality, a much tougher asset clause to allocate to.

Eric: It’s a good point. So in this context, I was using investable, realistic hedge fund indexes.

Meb: They still took it, all right.

Eric: Yeah, they still took it. But you’re right, absolutely. There’s so much survivorship bias baked into most of the hedge fund indexes that they paint a very unrealistic picture. But in this particular experiment, I’m using all things that are investable.

Meb: Okay, so quick question for you, Longboard manages almost a billion dollars across their two main funds, I’m rounding up, but $600, $700 million dollars. You guys, I assume, talk to a lot of institutions. I’ve always been curious. You don’t have to say their name. But have you talked to institutions or even a family office? What is the highest percent you’ve ever seen in a managed futures strategy as a percentage of the overall allocation?

Eric: Well, we actually try to avoid institutions. You know, our focus is retail financial advisors. You know, our whole goal is to bring institutional quality portfolios over into the retail space. We’ve not seen a lot of people do that successfully over the years. But that is our goal. That doesn’t mean we haven’t talked to institutions. We have, especially back in the Blackstar days prior to Longboard. And I would say that, well, the maximum allocation I’ve ever seen is probably been about 30%. That’s very rare. Typically, you’re gonna see somewhere between 2% and 5% allocated to managed futures or global macro.

Meb: Well, the funny thing about that is, and you and I both know, for an allocation to really make a difference, and David Swensen at Yale talks a lot about this, you really need a 5% allocation, if not more, for a not to make a rounding error kind of adjustment. So we actually just wrote a paper called “The Trinity Portfolio” that talks about a lot of the themes you’re talking about with managed futures or with trend-following approach. And in this paper, we show that…and it’s kind of like what you’re talking about with the example you would show advisors, where we said, “Look, despite the fact that we’re comparing a buy and hold global portfolio to a global trend-following portfolio and the global trend and momentum portfolio had better returns, better risk adjusted returns etc., but we said maybe an optimum portfolio for most people is actually just a 50/50 mix of the two, you don’t look too different. But you have a large allocation to trend.” But for many people, a 2% allocation, it may get you in the door, but it’s not gonna end up driving a lot of the other returns. And you give one more example. There’s a bunch of papers that Longboard has written. And like Eric mentioned, they used to be called Blackstar. Did the name change what? About three years ago?

Eric: Five years ago.

Meb: Five years ago, okay. And so we’ll link to these in the show notes. But one was talking about these strategies in general, and so managed futures, one of the challenges…and we’ve probably waited too long to discuss this for the newbies on the podcast. With managed futures strategy that has a very long-term trend-following applied… Trend-following has been around for over 100 years, if not more. But it applies long-term trend-following across many, many markets and takes a long and short approach. How many markets do you guys track in your funds?

Eric: Right now, we’re looking at 145 different global futures market.

Meb: And how many of those would you consider distinct? So if you’re not counting, say, you know, gold trading in the U.S. and London, but maybe like kind of distinct actual markets, is it still above 100?

Eric: No. You know, if you did principal component analysis or correlation analysis, I think you’ve got somewhere between five and eight distinct risk premiums around the globe. And that seems like a low number, but that’s actually about the best you can do in the world. You’ve got metals. You’ve got grains. You’ve got equities, bonds. And then you’ve got dollar-denominated currencies and then regular old cross rates.

Meb: If I remember correctly, and I could be wrong, I remember looking at your fact sheets over the years, there’s at least one market that I’ve seen you all trade that no one else I’ve ever seen trade. You know what I’m talking about?

Eric: Would that be the carbon emission credits?

Meb: Yeah, you guys are still trading that?

Eric: Yeah, it’s a very big, deep liquid market. It trends beautifully, a lot of commercial hedging pressure. And for some reason, most CTAs just ignore it.

Meb: I love it. When are you guys gonna start trading Bitcoin?

Eric: We’re looking at Bitcoin. When we look at markets, we want to be able to understand that they’re a free and fair market that actually facilitates risk for transfer between speculators and commercial hedgers. And Bitcoin’s not quite there yet. But it’s on the shelf. We’re looking at it.

Meb: Yeah, the challenge with Bitcoin, [inaudible 00:17:17] lot of these vaults. There was another break hack the other week that they stole, I think, 70 million out of it. Anyway, yeah, I would love to see some digital currencies get a little tailwinds but haven’t seen it yet, could be at some point. All right, let’s get back to the topic. All right, so you guys have done a number of articles, and we’ll touch on a few of them here, and then we’ll possibly get into equities a little bit as well. One of the most linked and liked articles, there’s been two we cited back in the day, and then we’ll talk about that in a minute. But looking at the spread in front of me, I got one called “Discipline Trumps IQ.” And similar to your presentation to managers, and this I think goes back to why a lot of people struggle with managed futures, you have an example where you say, “I got two investments for you. Investment A outperforms the S&P by 10 times. Investment B underperforms the S&P half the time. Which would you rather choose?” Do you wanna talk about that example real quick?

Eric: Sure. So one of the theories that developed out of our debates internally here at Longboard is that the best performing managers over the long term must have been doing something that other people could not do. And at first glance, you’d think that they’re simply more skilled. They’ve got insider information or better information. Or they’re better at discounting data than the market itself. But we like to invert things. We like to respect the fact that we don’t know what we don’t know. And I think that you can learn a lot by simply inverting things and working backwards in addition to working forwards. So that’s how we stumbled upon the concepts of survivorship bias and postdictive error and whatnot.

So one of the things I wanted to look at was let’s look at the best performing managers over a long period of time, Berkshire Hathaway, George Soros, Bridgewater, and whatnot. The theory is that they must have done something that other people aren’t comfortable doing. And one of the things that people are very uncomfortable doing is underperforming their benchmark either frequently or for an extended period of time. And what we found was very interesting. When I looked at some of the best track records out there, they underperformed the S&P 500 or 60/40 portfolio most of the time. And Berkshire Hathaway is a glaring example. If you look at Berkshire Hathaway on a daily, weekly, monthly, quarterly, or six-month basis over its entire history, an investor in Berkshire Hathaway would have underperformed the S&P 500 more than half the time. But despite that, an investor in Berkshire Hathaway would have made tremendously more money than an investor in the S&P 500.

Meb: You know, we actually talked about this a little bit recently where, you know, we do a lot of tracking through SEC 13F filings, public disclosures for hedge funds, and the Buffett clone, which is buying the top ten Buffett holdings, has outperformed the market by about 5 or 6 percentage points per year to 2,000 despite underperforming…I think it’s six of the last seven or seven of the last nine years. And this is a great example. So he would have beaten 98% of all mutual funds over that period. But despite that, you know, how many advisors or investors would be able to sit through underperforming…I mean, God forbid, seven out of nine, but even two out of three years.

And there was an institutional study, which I don’t know if you saw, that Financial Times just did recently and then asked institutions. So this isn’t retail investors. This is institutions. And they managed something in the trillions, I forget what it was. It was 400 of them. They said, “How many years would you tolerate the manager underperforming?” And 99% said, “One or two years.”

Eric: That’s exactly the point that I like to make. When you first started doing the clone work several years ago, I was skeptical, because I thought, well, it can’t be that easy. You can’t just watch what other people are doing, copy the top 10, and outperform. Everyone will do it, and it’ll get [inaudible 00:21:26 away. And then after thinking about it for a while, I realized that it is sustainable, and it probably will work, because it will force you to do the things that those elite managers are doing. And there’s a reason that that produces sustainable alpha over time. The fact that it’s public knowledge isn’t gonna make a difference. People will not be able to stick with it in real time because they’re effectively hedging a different kind of pain. And you just talked about it. It’s the relative performance envy pain, which is what guides most of the alpha in the world.

Meb: There’s a great Buffett quote, or Munger quote, that says, “I can’t tell how many times I’ve heard Warren say, ‘It’s not greed and fear necessarily that drives the investment world. It’s envy.'” And that’s a good example of, you know, how many people they just…we just gave them an investment strategy. How long has everyone known that Buffett has been a great manager, that it will outperform by five percentage points a year? How many of our listeners here are gonna go implement it? Well, probably zero. But how many are gonna go home and turn on CNBC here or chat with their neighbor and say, “Oh, man, I got a new biotech stock for you or whatever”? That’s much more exciting, much more interesting than a strategy that takes 10 minutes.

And one of the biggest reasons we say that a lot of these strategies work is that sort of internal pain, that gut of having to sit through a managed futures 2009 or even a few years after of underperformance when the S&P is going straight up. And it applies to everything. It applies also to asset allocation, you know, looking at emerging markets and commodities, have been down for how many ever years in a row going into this year. But eventually, the internal pain subsides. But, yeah, I think that’s a great point.

But you guys also talk a little bit about offense and defense. And so thinking about, you know, investments, and you talk a lot about statistics, and there was one recently called “Bump the Bell Curve,” I think it was by Cole, about a few months ago. And he starts, and he says, “In any competitive environment, whether it’s baseball or financial markets, our first instinct is to identify the few top performers. However, Longboard’s research shows that for investments to win over the long term, it’s more efficient to strategically avoid the many underperformers.”

Eric: What we found is that, again, inverting, working backwards, eliminating losses, and reducing volatility does more for your compounded return than identifying the big winners. It’s the physics of finance or the physics of compounding. It’s very counterintuitive. People do not realize the impact that avoiding draw-downs has on your overall compounded rate of return and risk-adjusted returns over time. So when you study financial markets and you have a representative sample that includes, you know, the bad data points as well as the good data points, paints a very different picture. It’s not very exciting. You know, risk management is not exciting. Most people that get into this business, they do so for the wrong reasons, the excitement, the hero complex, winning achievement-oriented people. And it’s not until they go through several market cycles that, if ever, they realize that defense is what wins championships. It’s avoiding losses, avoiding catastrophe. And, yes, you have to catch the winners as well. But avoiding the big losers has more of an impact on your compounded return than catching the big winners.

Meb: That even applies with something like stock investing and value investing. A good example we always give is a global investor. You know, it’s great to buy the value stocks, to buy the cheap stuff or buy the momentum. That’s great. Those factors all work. But it’s also equally as important to avoid the bad side of that. So in any broad index, so if you’re gonna own the world, you would have owned Japan when it went through the biggest bubble ever in the ’80s. You would have owned the U.S. in the late ’90s when it went through this huge bubble. And the same thing today or same thing with any index, you’re gonna end up holding the crap, which is very expensive. Just buying the cheap stuff is good because you’re buying cheap stuff but you’re also avoiding the really expensive. And this goes back to a really old paper these guys did back when they were Blackstar called “The Capitalism Distribution.” And this was a study of stock returns and the distribution of stock returns. I’m gonna try to recite this from memory, because I’d mentioned it so many times. And their study basically looked at all Russell stocks back to, I think, the ’80s. Is that right?

Eric: Yeah, 1989.

Meb: 1989, and found that, and you can correct me, I’ll see if I can get it right, out of all the stocks in their history, two thirds of all stocks underperformed the index. Forty percent had a negative rate of return over their lifetime. And I think maybe 19% or 20% essentially lost all of their…gains were like -75% or more. And so the takeaway I always have from this is, one, if you throw a dart against the wall, chances are you’re gonna underperform the index. So 50/50, dart against a wall, you pick a stock. Chances are you’re gonna underperform the index because the index owns the very biggest gainers. And so you guys talk a lot about this 80/20 rule and how this applies to stocks. So maybe you wanna talk a little bit about that original study as well as follow-up studies you guys have done like, you know, “The D Wins Championships” and everything after.

Eric: Sure. It was absolutely fascinating. I’ll go back to my junior year in college when I was in a portfolio management class. One of the assignments was to build a mechanical trading system, just completely rules-based. And at the time, I designed a system doing what everyone does, you know, wanted to buy low and sell high.

Meb: That’s an amazing class as an undergrad, especially that long ago. Did you have a particularly interesting professor? Or was this trying to prove the mechanical strategies don’t work?

Eric: I don’t think they had an agenda at the time. But I went to Wichita State University in Kansas and had two professors that were from the University of Chicago. So they had a pretty extensive training in modern portfolio theory and whatnot. I don’t recall if the professor in this class had an agenda. But the assignment was to build a mechanical trading system and then run it for the entire semester.

Meb: Cool.

Eric: So I did that. Well, I was looking at some charts. And I thought, “Well, this is gonna be so easy, just buy down here and you sell up there, and it’s a license to print money.” So I designed a system that bought 52-week lows, went long, and went short 52-week highs. And I back-tested it on all the constituents of, I believe it was the Russell 1000 at the time. It might have been the Russell 3000. The back test was beautiful. I mean, to tell you, it was making 40% annualized returns with 20% volatility. And I thought, “Wow, I’m gonna have my own private island some day. This is so profitable.”

Something interesting happened that when you run it in real life… I don’t know. We set up a paper trading account. All the students did. And we had to apply our mechanical trading systems on a go forward basis. And an interesting thing happened. In real life, I started losing money. But if you ran the back test, it said you were making money. And I ran this for a couple of months. And because I had a database background, it really intrigued me. I wanted to go in and find out why my simulation was saying one thing, but my real-life results were saying something else. Now, they were highly correlated. But one was making money, one was losing money.

To make a long story short, essentially, what was happening is the stocks that were getting delisted for two different reasons. First reason they, were going bankrupt. This was in 1997 and 1998. It was over two semesters. There were stocks that were going bankrupt, and they were being expunged from the database and not showing up in the back test after they were expunged. On the other hand, there were stocks that were getting bought out of the premium. Those were also being delisted. So they were being expunged from the database.

So at any given point in time, if you took a look at the database, it only included the surviving stocks. It omitted the stocks that got bought out of the premium and the stocks that were bankrupt. That explained the 99.7% of the performance difference. And it was enough to turn what looked like a winning strategy into a losing strategy.

Meb: And then this is hugely important. I can’t tell you how many times in the past 15 years I’ve used a software program or have people email me about a software program, and some very famous publicly available ones that charge in the thousands of dollars, and will find out that the software program either, like you said, has survivor bias, so they exclude delisted stocks, or it will have…you know, they’ll exclude dividends or something other crazy. So it’s massively important to be able to find a stock database that is free of all these.

And we used one at one point ,Norgate, which I think is Australian, that isn’t that expensive. But there’s other ones like FactSet. So if you’re a student or an individual listening to this and you wanna go play around with a very expensive database, I think FactSet’s like 80 grand, go find a local business school, make friends with a professor or student. And you can find probably some access there. But otherwise, you’re kind of playing with a database that’s just gonna lead you to false conclusions.

And so, wait, it turned out the actual 52-week highs is actually probably a pretty good strategy, right?

Eric: Well, that was my next move. I just inverted everything, you know. I’ll use that word invert a lot. I inverted everything. And all the sudden, it started making money. That’s what motivated me to do research and do trend-following, because those are the prerequisites for a sustainable rate of return. It needs to be something that is unpopular. It’s too hard for most people to do. It doesn’t get traction. Therefore, there won’t be a lot of competition for those profit margins. And to this day, like you, I’m still flabbergasted at how even very sophisticated people will build investment methodologies without factoring in the dividends, without factoring in survivorship bias, and without realizing that a lot of these fundamental databases have restatements that are back-propagated, which results in postdictive error.

Meb: It’s a minefield. Our industry is a minefield. One of my most popular tweets of all time was a chart from one of you all’s research reports. And it was looking at the total lifetime returns of individual U.S. stocks. So this is thinking about one of the reasons that this 52-week highs study may work. You guys looked at again the distribution of stocks. And I’m gonna name a few statistics. And it says, “Looking at total returns of individual stocks, about 8% of all active stocks outperform the S&P index by at least 500% during their lifetime. Likewise, about 7% of all active stocks lagged the S&P 500 by at least 500%. The remaining 12,000 stocks performed above or below the same level as the S&P.”

But if you kind of look at this also, look at the attribution of collective returns since the 80s, the worst performing, which is 11,513 or 80% of all stocks, collectively had a total return of zero. And the best performing, let’s call it 3,000 stocks, which is only 20% percent of them, accounted for 100% of the gains. And so, readers…let that soak in for a second, the old 80/20 rule. Eight percent of all stocks, had you just missed the top 20%, you would have had a 0% return. Eric, can you comment on that at all or have any other thoughts? To me, it’s such a profound study and maybe why it was so popular and re-tweeted. But kind of what led you all to this research report? Any other thoughts you may have on it?

Eric: It is fascinating. It’s even more fascinating when you consider the fact that we replicated that study on Canadian stocks and UK stocks and got virtually identical results. I’ve also done a similar study on sports statistics. Whether it’s pitching in baseball, hitting in baseball, rebounding in basketball, the 80/20 rule just jumps right out of you. If you get the real data and you’re intellectually honest about it, the 80/20 rule applies to virtually all competitive systems. So it’s just the way the world really works. And trying to be in harmony with that, rather than fighting it, is our goal.

Meb: And the cool thing about this is so, this one, it explains why market cap indexes work. And we’ve said many times on this podcast that, look, market cap weighting index, which just means investing in the biggest stocks and biggest by size, that’s it. Price times shares outstanding, the only metric, is actually a trend-following strategy, because you end up owning more of stocks that are going up and less of stocks that are going down. But that ends up as an okay first, naive sort of market strategy, because you’re guaranteed to own the really big gainers, and you’re gonna own less and less of the big losers. So market cap weighting, a lot of people don’t know this, the S&P is a system of owning these long-term trend-following type of strategies.

By the way, you guys wrote a report on this 80/20 called “Building a Better Bracket” where it talked about the same thing. It talks about college teams, you know, the very minority of all the college teams in the NCAA tournament. Twenty-five percent of the teams made 95% of all semi-final appearances. I tried to use this to build my bracket this year, lost again. I’m always been terrible with brackets, but mainly because I picked UVA to win all of the brackets I was in.

We’re talking a little bit about equities. We’re gonna transition a little bit, because everyone can at least grasp managed futures, [inaudible 00:35:19] futures markets. People have a little harder time believing that trend-following works on stocks. And this was actually one of you all’s original research reports. We’ve talked about it over the years. And now actually just launched, I think in the last year or two, a stock-based trend-following fund despite having…I know you all had a private one for many years. Talk a little bit about trend-following on stocks, because I think a lot of people think that that’s an area that they think it just doesn’t work.

Eric: Well, it’s such an interesting concept to me. You know, Cole and I were both equity traders during the ’90s and then discovered managed futures in the year 2000 and started allocating our firm’s capital out to CTAs, and we learned a lot from having managed accounts and, you know, transparency into what they were doing.

Meb: Let me stop you real quick. And I apologize for interrupting. It’s my least favorite thing I hear on podcast, “The host is interrupting.” But before we go into equities, will you comment, because a lot of people don’t know this, on the managed futures, the public [inaudible 00:36:19] managed futures space, because you guys, I know you looked into it before you started launching funds. There’s kind of a big disparity between the types of funds and there are some funds…can you talk a little bit about that real quick, apologies for the interruption, and then continue on in your thought?

Eric: Sure. Well, so managed futures means different things to different people. It’s a big space. There’s a lot of money there and there’s different approaches. I would say that 80% of the returns from the “managed futures” category comes from long-term trend-following and medium-term trend-following. The rest you could attribute to short-term trading, relative value arbitrage, spread trading, and whatnot. But when you think of managed futures, think trend-following, because that’s where most of the returns come from.

Meb: Yeah. But where I was kind of going at was a lot of the mutual funds, there’s only a few, and I think it’s you all, AQR, maybe [inaudible 00:37:12] that actually are managing the strategy. Almost most of the managed futures mutual funds are actually fund of funds or outsourcing it, right?

Eric: That’s true. And so there’s probably 50 managed futures mutual funds, and, you know, 44 or 45 of them are effectively just fund of funds, which means they raise money from clients and they charge a management fee. But then they outsource that money through an offshore structure to CTAs that charge their own management fees, their own performance incentive fees. And then typically, they have swap fees involved. So the downside to that is you have three or four layers of fees that really eat into the returns. But there are a few managed futures mutual funds that are what we call direct managers, meaning they’re a CTA that’s simply offering the program directly through their own mutual fund.

Meb: And just for context, can you comment on just how large those fees add up on some of the fund of funds.

Eric: Well, there’s a lot of dispersion there. But 5 to 10%, I think, is a realistic range. I’ve seen it as high as 14. Depending upon market conditions, that performance incentive fee can really start to add up after a while. But generally, the fund of funds I’ve looked at, you’re gonna have to expect, I’ll say, 5% to 9% in total fees, but you won’t be able to see most of them.

Meb: All right, so, listeners, rewind, listen to this part again, play it three or four times. The fees on a lot of these fund of funds can add up to enormous amounts. So you gotta ask yourself how much alpha is this manager really gonna generate to be able to deserve a 5 to 10 percentage point fee per year on this allocation? It can be hugely expensive. So be very, very careful when you’re allocating any of these fund of funds. All right, sorry about that little interruption. We’re going back to the equities part. Do you even remember where you were?

Eric: Refresh my memory.

Meb: Okay, so we were talking about, you know, how a lot of people don’t think that trend-following can work on stocks. And so you guys had looked into…you know, you started managing. You met Cole in the late ’90s and then I’ll let you run from there.

Eric: Cole and I were both primarily equity traders. And we learned about managed futures in the very early 2000s. And during that process, we attempted to apply the managed futures style to equities, and we were confused as to why none of these CTAs had trend-following programs applied to stocks, because we saw enormous trends every year, different sectors, individual stocks. And we thought, “Wow! Why are no firms attempting to apply these robust trend-following approaches to this opportunity set?” And we asked a lot of people why they weren’t doing it, and we got strange answers. Some people said that it doesn’t work. Some people said that the data is too difficult to deal with. You’ve got dividends and delistings and thousands and thousands of stocks. And it’s just easier for them to keep track of 50 futures markets.

But none of those answers resonated with us. So we embarked on a experiment, on a research project to figure out if we can apply these strategies to common stocks. And that’s where I learned, or that’s where, I would say, mastered the art of dealing with corporate actions and dealing with survivorship bias in the context of a complete product. The results were good. We thought that it was a viable product, that trend-following applied to Russell 3000 stocks, produced quite a bit of alpha. It had reasonable risk-adjusted returns. And it was a sustainable way to offer a return stream that is not redundant with what everyone else was getting in the equity markets. So we launched that product in 2005 in a private placement form. And I run it every morning. It exists still today. It’s done everything that it was designed to do. And you mentioned earlier, we launched the same product in a mutual fund format about 15 months ago.

Meb: And the kind of the basics of the strategy without giving away all the holy grail is that you’re essentially buying stocks that are going up or hitting new highs. And Longboard is a shop that traditionally…when you say trend-following, they focus on the very long term. And so that helps to reduce turnover a bit. But you’re also exiting stocks as they decline, I assume. And we didn’t talk about it a lot today, but the risk management and the money management sort of algorithms, you know…and it may have been, Eric, that we chat about it once and said, “Look, it doesn’t even matter as much the entry signal but also having a lot of really wonderful exit strategies can help a lot.” So you guys are buying stocks that are going up. You’re exiting them as they go down. And then you’re also hedging by shorting…is these individual stocks or futures or ETFs or what?

Eric: On the short side, we wanted to keep it simple and scalable. So we short index futures. We short the S&P 500, the S&P 400 midcap, and the Russell 2000 small cap. And then you’re correct. We go out and we buy the individual stocks as they’re breaking out to new three-year highs on a total return basis. But really, Mebane, it boils down to this. The indexes own the big winners. Catching those big winners just helps you keep up with the indexes. There’s not a lot of alpha on the stock selection side. It’s very minimal. It’s maybe 1% a year. The alpha comes from two sources. One, it’s deselecting those stocks that are gonna go to zero. It’s the stop loss. The stop loss is much more important than the entry signal. Avoiding those catastrophic losses…and they come in every market cycle 2002, 2008, and whenever it happens again in the future. Avoiding those losses is responsible for three quarters of the alpha that the program has generated over the years.

The other source is in the volatility weighting of individual positions. So unlike a market cap weighted index, we’re not gonna have a massive allocation to Apple and GE and Exxon Mobil. Instead, what we do is we weight each individual position according to its volatility. That way, we have a balanced portfolio. So we’re essentially rotating into sectors that are trending higher, rotating out of sectors that have a lot of stocks that are doing the Enron shuffle, are going down quite a bit, and then volatility weighting all the positions in the portfolio and controlling the amount of total risk across the whole portfolio. Those things aggregate up into a sustainable program that has a reasonable compounded rate return over time.

Meb: You guys used to have a research piece, and I can’t remember what it was called. Maybe it wasn’t even public. But it showed…talking about the Enron shuffle, it showed…it’s kind of a who’s who of famous bankruptcies and huge companies that went out of business and showed an example of how it was just a very simple exit algorithm or stop loss or whatever it maybe would’ve prevented you from losing all of your money. You would still lose some after they came off their highs. But you’d’ve prevented from losing all your money. And we talked a lot about this, because whether it’s the Batista, you know, the Brazilian guy who had 35 billion in assets and is now bankrupt or so many people that concentrate their stock positions, or even Bitcoin. You know, we say, “Look, you know, having a stop loss, one, will prevent you from losing all of your assets. But, two, it will prevent you from losing your sanity. because so many people, the emotions of watching an investment go all the way to zero can really be devastating not just to the pocketbook but also to your mental wellbeing as well.” And many people, when they lose that, they have that type of environment where they lose 100% in a position or all of their portfolio, you know, it can be like the death of a loved one. It’s very hard to explain to people the pain of loss if they haven’t been through it.

All right, we’re gonna start winding down here in a minute. What else are you guys working on these days? Any research? I know you’re consistently…there’s always about 15 ideas in your head. And every time I talk to you, you have about five different things you’re working on. You got these current funds out there. Any other research ideas you guys are thinking of? Any other non-correlated markets or systems or things you all got going on in the skunkworks over there?

Eric: Well, we’re always thinking about sustainable risk premiums that are scalable, but like I mentioned earlier in this podcast, there’s only a few of them in the world, and constantly looking for a new one. Opportunity cost of that is pretty high. So we spend a lot of time trying to make things more efficient. You know, we concern ourselves with things like counterparty risk. You know, it’s a new world that we’re in. There’s all kinds of regulatory risks and counterparty risks out there. So we spend our time trying to make our infrastructure as high quality as possible. Not a lot of new products on the horizon, trying to make our existing products bigger and more scalable and just stay disciplined and do the right thing.

That being said, you know, research is in our DNA. So we’re always looking. We’re never satisfied that we have all the answers. We really respect the fact that we don’t know what we don’t know. You know, we’ll know more in 10 years from now than we do now. So we’re constantly doing research. But I won’t say that the research is leading us to new risk premiums, at least not recently.

Meb: All right, good. Well, maybe when you find a way to systematically find Pokémon GO rare characters and we can sell them on eBay, that would be a good strategy. All right, look, so before we finish, I forgot one thing, useful, beautiful, or downright magical that most people wouldn’t have heard of. You got anything for us today?

Eric: Well, my answer is probably gonna be different than answers you’ve gotten from other people. I’ve had to undergo a big change in my life recently. You know how I used to be. I was a researcher doing a lot of programming, spending a lot of quality time with myself and my small research team back in the Blackstar days. And now, we have a firm that has over 60 employees. So trying to scale our way of thinking, our critical thinking skills, is interesting. So I would say that the most beautiful thing that I’ve seen recently is when you can get smart people to work together as a team and build their own decision-making process, like scaling what we have at Longboard across other people, the return on investment is so high and the compounding is so great. And when you can help people to get past their own biases and learn how to be good critical thinkers and teach other people, it’s very powerful when they work together as a team and can solve problems.

So I’ve committed time and effort into training people. And it’s actually pretty easy. I just explain to them why I have confidence in our own products. It really is that simple. I show them how I made decisions, how we inverted logic. I give them examples like…you know, you probably heard this example about the World War II bombers and survivorship bias where, you know, the allied forces were studying bombers that were turned from campaigns over Germany. And, you know, they lost a lot of bombers in the early stages of World War II. And they were trying to figure out ways to reinforce these aircraft such that, you know, they would have higher survival rates. So they hired all of these statisticians to evaluate the data. And an interesting thing happened. They noticed the very clear patterns in where these bombers would take fire and sustain damage. And they were very clear and obvious. And their first instinct was to reinforce those sections of the plane that took the most damage.

But there was one statistician in particular, and I don’t remember his name, but I’ll send you the article if you haven’t seen it. And he said, “No, you’re thinking about this the wrong way. You need to invert everything that you think and work backwards.” It’s the information you don’t have that’s valuable. It’s what you don’t know that has the hidden value. The bombers that didn’t come back must have been getting hit in the other areas. So you need to invert the pattern, take the negative of it, and reinforce those sections of the planes. You’re setting the survivors, and there’s valuable information there, but you’re misinterpreting. Does that make sense?

Meb: I love that. That’s a great piece of philosophy. It’s kind of like you coming full circle. You’re now gonna be back, be a professor at Arizona or ASU and start teaching mechanical systems design.

Eric: Oh, I’m a professor at Longboard. And teaching people these things…and we use other examples here, like the Monty Hall problem with the three doors and people not switching doors, to demonstrate cognitive biases. And, you know, the tendency that we all have, you know, our mammal brains suffer from the same delusions. But getting people to learn on their own rather than preaching to them, walking him through examples and showing them the results and letting them feel it and experience it and then to learn on their own and then go out and teach other people and then having that cascade throughout the organization to the human resources department, the recruiting department, the trading operations department, and then you see them actually learn those lessons and then use those valuable insights in a totally different context, well, that’s a beautiful thing to me.

Meb: You know, it’s funny, because I started out as a biotech student as well. And eventually, similar to you, kind of slowly, the path moved away towards investing and systems as well. And one of my biggest interests has always been, you know, psychology, evolutionary biology. And so we’ll probably have to have you on again in six months, and we’ll do a pure psych episode. But you know, it’s one of my beautiful useful things…and I was gonna say Dyson fans, and I don’t mean Dyson fans like the one you see at the airport, which I actually think are kind of gross. But the ones, they have these fans you can get for a home and then the most beautiful fans are expensive 200, 300 bucks. But they also have ones now that will blow hot air, cold air. And for someone who doesn’t have any AC at my house, they’re a lifesaver. But I’m not gonna say that.

I’m gonna give you a book rec now because of your mention of evolutionary kind of psychology ideas or just psych in general. It was written by British professor Olivia Judson called “Dr. Tatiana’s Sex Advice to All Creation.” And it has nothing to do, really, with sex, but it has everything to do with animals and species around the world and how they’ve evolved against each other. And it’s such a wonderful book. There’s so many books that’d cause you to take a step back and think about the world in a different way. And your inversion comment, I think, is so useful to go look at all your ideas and process and say, “All right, let’s flip this and kind of understand what’s going on.” And this book in a similar way has you thinking about a lot of things in a different way.

All right, so we’re winding down. We got about a full hour already. Eric, where can more people find you if they want more information about your firm, research, products, etc.?

Eric: Our website’s a good start. We’re actually retooling the website, and we’re gonna come up with a microsite here pretty soon that’s gonna contain all of our historical research in a intuitive sequence. So simply Googling Longboard Asset Management will get you to one of those two sites pretty quickly.

Meb: All right, and you guys don’t really participate on the Twitter, do you?

Eric: No. You know, regulatory constraints on social media are a moving target. So we’re reviewing that. But right now, we don’t do a lot on Twitter.

Meb: You guys got 60 employees. You can just have one of them review your, really, stat-heavy tweets. We’ll get a cartoon version of you maybe online. All right, well, everyone look, Eric, thank you so much for joining the podcast today. It’s been really wonderful to watch the evolution of a firm, you know, in particular, two really good guys that have grown a business with some unique and interesting and different ideas. And looking forward to you all continuing to put out some research that continues to get appropriated by the investment banks that will give you no credit. I’m not gonna say who, but it rhymes with schmaybe Morgan. But anyway, thanks for tuning in today, everyone.

Look, you can always find archived versions of the podcast at mebfaber.com/podcast. If you really like it, you can always leave a review. We’d really appreciate the feedback. You can shoot us an e-mail [email protected] If you have any questions or comments, please send them in, and we’ll do some Q&A episodes and/or if you have any for Eric or the folks at Longboard, send them in, and we’ll do another episode. Thanks for listening, everyone, and good investing.

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