Episode 56: Is the Stock Market Really as Predictable as You Think? Decoding the Cockroach Strategy (Part 1)

In this episode, Jason Buck (Mutiny CIO) and Taylor Pearson (Mutiny CEO) embark on the first of a series discussing the Cockroach Strategy. They are excited to share insights into the decade-long development of this strategy.

Jason and Taylor explore the probabilities of loss over extended time horizons, shedding light on often overlooked aspects of investment planning. They also discuss real returns and the influence of global economic trends on investment outcomes.

The discussion kicks off with an exploration of stocks, the cornerstone of the Cockroach Strategy, setting the stage for a deeper dive into its principles and construction.

Please see our Insights Page for blog posts featuring notes from the Cockroach Approach whitepaper. Additionally, you can access the Cockroach Approach summary and download your own copy of the whitepaper!

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Have comments about the show, or ideas for things you’d like Taylor and Jason to discuss in future episodes? We’d love to hear from you at info@mutinyfund.com.

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Transcript Episode 56:

Taylor Pearson:

Hello and welcome. This is the Mutiny Investing Podcast. This podcast features long-form conversations on topics relating to investing, markets, risk, volatility, and complex systems.

Disclaimer:

This podcast is provided for informational purposes only and should not be relied upon as legal, business, investment or tax advice. All opinions expressed by podcast participants are solely their own opinions and do not necessarily reflect opinions of Mutiny Fund, their affiliates, or companies featured. Due to industry regulations, participants of this podcast are instructed to not make specific trade recommendations nor reference past or potential profits.

Listeners are reminded that managed futures, commodity trading, Forex trading, and other alternative investments are complex and carry a risk of substantial losses. As such, they’re not suitable for all investors, and you should not rely on any of the information as a substitute for the exercise of your own skill and judgment in making a decision on the appropriateness of such investments. Visit mutinyfund.com/disclaimer for more information.

Taylor Pearson:

Welcome to the Mutiny Investing Podcast. I’m here with my partner, Jason Buck. We’re going to be doing the first of a series today talking about the Cockroach Portfolio and the thinking that has gone into it. And this is something we’re excited to start sharing and talking about. We’ve been working on it for the better part of a decade now, and I started to publish some notes on our website, which you can find at mutinyfund.com plus Insights, and are going to be talking through some of what we’ve written there, as well as going into a bit more detail on this podcast. So today, we’re going to start off with everyone’s favorite asset class, stocks.

Jason Buck:

Stonks.

Taylor Pearson:

Stonks. Talking about stocks for the long run, question mark, as opposed to stocks for the long run, declarative. So I’ll kick us off and we’ll go back and forth here. So, many people are probably familiar, there’s a very well-known book called Stocks for the Long Run by Jeremy Siegel. And I think broadly, when you look at how many portfolios are constructed today, Stocks for the Long Run is sort of the core there.

And I think there’s fairly straightforward logic, that if you look at most the large asset classes, let’s call it stocks, bonds, gold, historical data sets, particularly historical data sets based in the US, tend to show stocks as the highest performing long-term asset. And so the logic goes, you want to have a portfolio that’s mostly composed of stocks, especially if you’re relatively young or you have a long time in horizon, because of course, you want the highest returning thing investment over a long period. And I think that’s sort of the basis and where people get to, and we want to talk about maybe a little bit more nuance around some of the thinking there.

So a lot of this is based on, there was a great paper and written by Anna Kolova et al. in the Journal of Financial Economics. You can go to our website and we’ll link to that. Basically looking at developed market stock returns from 1841 to 2019. And what was interesting about this selection, this data set compared to what you typically hear, which is typically, I would say, in my experience, the most common thing is usually US stocks, usually 1920, 1929, something like that, to present, is typically sort of like the data set people quote from for stocks.

And so I think the sort of couple things that jump out about the broader data set, one, is the probability of loss over a 30-year horizon. So, Jason knows the answer, but Jason trivia, what is the… Well, hey, we could do a fun Mr. Market or a beauty pageant. What do you think, if I asked the average person the probability of a loss, losing money in absolute terms over a 30-year horizon with stocks, what do you think the average answer is? What does the median, reasonably intelligent investor that’s read some investing books think?

Jason Buck:

I honestly think if you’re going 30 year horizon, most people are going to think over a 30-year horizon, it’s just up and to the right. You may have gone through a drawdown or a losing period, but I think over a 30-year horizon, I don’t think anybody’s going to think they have losses.

Taylor Pearson:

Yeah, I think it’s zero or 1%. I think it’s incredibly low. So on US return data, that’s actually pretty close to correct. The number is 1.2%. And that’s real return, so loss in buying power over a 30-year horizon. Across developed markets, 1841 to 2019, the number is a much higher 12.1%. So, call it roughly a one in eight chance of a loss, a decline in real terms of a stock-only portfolio, which I think… I did a Twitter poll to this effect, and yes, the results were very different. That’s not what most people would expect at that level.

Jason Buck:

Yeah, it reminds me like Meb’s Twitter polls. That’s what I was just thinking, I should text Meb and have him do a Twitter poll to see, he would love one like that, but I feel like he’s probably done one similarly. But also, with some of Meb’s great papers, as you know, he is using global financial data and I think he has some pretty good heuristics in there.

But maybe I should start with, in your paper and stuff, we’re talking about real returns and what are real returns? That’s your nominal return minus inflation. And so that’s what I think people really care about your real returns because you need… What can you eat after inflation? And I think rarely do even people look at real returns. So, throughout this, we’re talking about real returns.

But I think Meb always has good heuristics, too, of the simplest way to think about it is, I think, 6, 5, 4, 2, 1, is basically over the last 100 years, the US stock market has produced 6% real return. So once again, returns after inflation.

The global stock markets have returned 5% real return after inflation, just shows you that American exceptionalism over the last 100 years. And once again, that’s rearview mirror that we’ll get to as well.

Commodity trend following produced about 4% real returns. And similarly, with bonds is 2% real returns, and then T-bills is 1% real returns. There’s a little fudge factor. I think T-bills is actually 0.78, but you get the general idea, it’s 6, 5, 4, 2, 1. So you get an idea of the different asset classes and what they produce in real returns.

But that’s why it’s important, like we said, US is six, but global stock markets, if we look globally, which you’re writing about in this essay, it’s a very different scenario. And one of the luckiest things, if we’re talking about our Peter Zeihan, I guess, thinking about we have these great oceans on either side of us and all this great growing crop land where we can feed ourselves.

But especially if we look at Europe going through the world wars, they’ve had some dramatic drawdowns. And I don’t know about you, I knew we all hear about Weimar going to zero, Russia going to zero, those sorts of things. But I don’t know if Italy jumped out at you, man, they’ve been through hell and back. It looks like [inaudible 00:07:29]-

Taylor Pearson:

Yeah, -87% drawdown, 1928 to 1948, -84% drawdown, 1907 to 1927, -72% drawdown, 1960 to 1980. Yeah, that’s brutal. Argentina, we looked at some of the worst scenarios across countries. Argentina didn’t make that. I guess they’re probably maybe not in the developed thing, but they also jumped out in real terms. I can’t imagine they must’ve had some, I would expect they’d had some sort of similar periods. But yeah, some brutal Italian periods in there.

Jason Buck:

And I think you bring up in the essay, yeah, talking about Germany, Europe, and even Japan, and we’ll come back to Japan. But you’re saying in 1900, a priority looking forward. And everybody, if they were picking the best economies in the 1900s that they thought were going to out compete everybody. I think you put in their Germany and UK were like number one, number two.

And even in the Western hemisphere, as we know, everybody’s betting on Argentina, they would’ve picked Argentina over the US. And like you said, they got wiped off the map multiple times with their stock market and currency. So, it gives you an idea of at least trying to place ourselves in that timeframe looking forward, instead of placing ourselves currently and looking backwards with that benefit of hindsight.

But one of the other things I love that you did, is one of my favorite phrases always, is everybody has all these great economic theories and how global macro works. And then you go, “Well, now do Japan.” And Japan usually throws them all out the window. So talk a little bit about Japan a little bit too over the last few decades.

Taylor Pearson:

Yeah, Japan, it is sort the poster child case study for country that… I think it’s interesting about Japan, Japan is really nice. I haven’t spent a ton of time in Japan, but it’s not like it’s a dump. It’s a really nice… The food’s great, everyone’s… It’s a very high-functioning, the day-to-day experience, it’s very high-functioning there, from all the times I spent there. It’s great. I love it. I’ve actually wanted to go back.

But they had this 30 year period, sort of 1989 to 2019 with negative 21% real returns. I think what’s interesting about that is, “Oh wow, that’s so sort of uncommon.” And so that’s in the 9th percentile of distribution. So that’s a 1 out of 10 outcome, slightly worse, whatever, 1 out of 11 outcome. That’s not insanely, you know what I mean, rolling two dice or something. This isn’t some crazy one out of 1,000 sort of outcome. That’s in the 9th percentile distribution.

So I think that’s sort of one important point I wanted to stretch here, is just looking at global equity markets broadly, historically, and again, we can say going forward. But the sort of general confidence people have, that over even a very long time period, 30 years, that stocks are very likely to deliver a positive return. They’re certainly likely to deliver a positive return, and that’s what circa data would suggest. Maybe not as likely as people are generally expecting.

And I think the other thing I wanted to talk about here that I think we’ve talked about a bunch and is really interesting, is okay, we could take these really extreme scenarios. Again, Japan’s not that extreme of a scenario per se, but you could take these 1st percentile scenarios of really unlikely things. But just looking at, I think I was Googling around and that you often see like, oh, you Google what’s the average turn of stocks or something like that.

And typically, the number I see getting thrown around in the media is 7%-ish. That’s typically what gets quoted. And according to the data from this paper, it’s actually pretty close. That is pretty close to accurate. I think it was 7.12 or something. 7% was a reasonable estimate. But I think the interesting thing is, when you talk about average versus median or average versus typical.

So, I’ll bring up my favorite ergodicity topic here, but the fun ergodicity example is if you’re playing a game of Russian roulette and you have six people play one time or one person play six times, the sixth shooter will play one time, five win and one loses. If one person to play six times, is guaranteed to lose eventually. Eventually they pull the trigger and the bullet’s in the chamber.

So, as a one individual living one life through time, you do not get the average returns of the markets. You get what you get. You get whatever happened on that sort of path you are on so that the median, that 50th percentile return, it’s substantially lower. It’s a little less than 5%, 4.91%. Which is not, I think you said, yeah, Meb’s number was 6% US, and the US has sort of outperformed. So globally, it’s going to be a little bit lower. That’s not crazy.

But then I think what’s really interesting is the 25th percentile, is a CAGR of 2.02%. So a compound growth rate of 2.02%, which over a 30-year time horizon is an 82% return. So let’s say you’re 35 years old, you’re 40 years old, you’re retiring at 70, take whatever… If you have a sort of stocks line, the 25th percentile outcome is an 82% increase in real terms. And I think that’s the one, that I think if you surveyed people, would be really surprising.

Jason Buck:

It was surprising to me, we worked on this for 10 years and even when I was reading it, I was like, “Jesus, a 75th percent.” That’s crazy.

Taylor Pearson:

A 25th percentile. Yeah, I think it is surprising to people. And again, I’ll read some of the stats out here, the 75th percentile is an 800% return. Amazing over 30 years. And that’s actually pretty close to the average, the 75th percentile that says 7.6% CAGR. And I think I said the average or something, I think it’s something like 7.2%.

But again, you don’t necessarily get the average. You get what you get over the trajectory of where you live on. So I think one implication, people talk about this, [inaudible 00:13:42], so the country is a sort of global equity diversification. And I think that that is a strong argument for that sort of approach.

But I think it also raises this question of, if you’re setting reasonable expectations, I think planning for a 25th percentile scenario is not disaster planning. We’re not talking about some highly unlikely wild scenario. We’re talking about flipping a coin and getting heads twice in a row. That’s the probability of this outcome.

Jason Buck:

And there’s other things in there. I think that, like you said, if you run surveys, people say a 7, 8% return. What I actually think is more interesting, that is if you actually, a lot of the other surveys, people just talk about the actual just arithmetic return, just what the annual return is. They expect 10 to 12%. Usually you hear 10 a lot. I think people maybe just get fixated on round numbers like 10.

But it was either Meb or Jared Dillian or somebody, they ran a survey that among hundreds of people, and it was up to 12% was the expected return. But like you said, I think people a lot of times are just thinking about what the annual return is and they’re not thinking about the compounded return.

And when we get into this ergodicity, the simplest way to think about it is, it’s not addition, it’s multiplication. You have to multiply your returns. And that’s how that volatility drag, which we’ll always get into, is it’s reducing that compounding. So if people are even saying 10 to 12% nominal return, you’re saying, but on the compounding, that’s more like 7, 8% after inflation. You’re talking 5, 6%, depending on what the inflation environment is over those decades that you’re using.

And then the other thing I want to be clear about, is we’re not anti-patriotic in any way. We hope America shoots the lights out for the next 100 years. It’s just looking at a historical representation, you can’t be so certain of that a priori.

And one of the ones I always think is interesting that we like to bring up, is people show 100 year back test of US stocks and it’s that up and to the right. And once again, they’re not looking at those individual decades or their life cycle.

But it’s also, I like to bring up, since the advent of the Industrial Revolution, let’s say the mid-to-late-1800s to now, we went from one billion people in the workforce to roughly six billion people in the workforce. That’s really unprecedented in world history.

And depending on which statistics you look at, we’re supposed to have peak population of nine billion. So the idea that you’re going to have a five, six-fold increase in the working population is unlikely. And how much that affects GDP and then America’s ability to hoover up global GDP is kind of unprecedented as well.

So it’s an interesting way of looking at it. Does that mean we’re calling for the demise of America or the American stock market? Absolutely not. It’s just this is the way we try to think about things, these things with the perspective.

What I thought was interesting recently, is they’re putting out, RIP, Charlie Munger, they’re putting out the newest version of Charlie Munger’s Almanack, a revised version. Stripe Press is putting that out. And on Invest Like the Best, they had John Collison doing an interview with Charlie, I think it was just a few weeks before he passed.

And what was interesting is Buffett’s known for recommending, just indexing, but Munger brought up exactly what we’re talking about. He’s like, “This last 100 years of American exceptionalism is pretty unprecedented. And if you’re betting on just a broad index of stocks for the next 100 years,” he’s like, he didn’t think that was a very good idea. And so it’s just another representation of that.

But as we look at these 30 year periods, and okay, what’s the grand takeaway? What was the lessons learned? Kind of like the end of the essay, what were you thinking about using these 160 years of developed world example in these 30 year cohorts? Maybe a 2% chance of losing money. What does that work out to? What’s the real takeaway?

Taylor Pearson:

So I think a couple of things. One, also, there’s a section in the essay that people can go read. It also sure looks at, if you started the time sample at different, I think we did four different periods, and you get roughly similar results. So it seems fairly robust.

And then yeah, as you said, I think one thing, it feels very obvious to people or somewhat intuitive to people that deal with markets a lot or interact with markets a lot, is it’s sort of like what’s priced in or whatever.

So this is a tangent, but I’m reading Making of the Atomic Bomb by Richard Rhodes right now, which is great. I would recommend a history of the atomic bomb and history of physics. But America was, I don’t know, my reading, it’s like a bit of a backwater in 1900. I think we take for granted America the superpower or whatever, but…

My guess is I don’t have anything to substantiate this, but if you did the equivalent of a Twitter poll in 1900 of which country’s going to be the most successful over the next century, I don’t think America does great. It doesn’t do terrible in that poll, but I don’t think it’s number one. And I think that’s perhaps part of why it did well. It was underpriced in a certain sense, that it outperformed, and so it makes sense that the returns were better.

But I think in terms of takeaways, I think the biggest thing is just, I think looking at this distribution here, I think the 25th percentile one is really the most interesting one for people to think about. That’s just historically, and you can make an argument that whatever the world is different and technology changed everything, blah, blah, blah, but you have to, sort of looking at this data set, say that’s historically what it’s based on. And so if you’re making retirement plans, whatever it is, and you’re doing an all-stock portfolio, that’s sort of the basis on which you’re planning.

And then I think that gets, as we’ll get into future episodes, the next question is, instead of taking an all-stock portfolio or taking that approach, what are some ways we could diversify that and add some other assets in? And what would that look like to try and reduce that 25th percentile outcome, effectively, to create something more robust over time? So we can leave that as the teaser for the next episode.

Thanks for listening. If you enjoyed today’s show, we’d appreciate if you would share this show with friends and leave us a review on iTunes, as it helps more listeners find the show and join our amazing community. To those of you who already shared or left a review, thank you very sincerely, it does mean a lot to us. If you’d like more information about Mutiny Fund, you can go to mutinyfund.com.

For any thoughts on how we can improve this show or questions about anything we’ve talked about here on the podcast today, drop us a message via email. I’m taylor@mutinyfund.com, and Jason is jason@mutinyfund.com. Or you can reach us on Twitter. I’m @TaylorPearsonMe, and Jason is @JasonMutiny. To hear about new episodes or get our monthly newsletter with reading recommendations, sign up at mutinyfund.com/newsletter.

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