In this episode of The Acquirers Podcast Tobias chats with Jason Buck and Taylor Pearson of The Mutiny Fund. The Mutiny strategy is designed as a form of ‘antifragility’ or ‘crisis alpha’ intended to achieve large asymmetric gains in times of tail risk events. During the interview Jason and Taylor provided some great insights into:
- A Dynamic Way Of Trading Left And Right Tails
- Trading Around Earnings Announcements
- Parlay Bets
- Finding The ‘Moneyness’ In Active Managers
- An Ensemble Approach To Tail Risk Trading
- Trading Volatility In Wonky Environments
- Antifragility Investing
- Investing Like Rodman – The Worm With The Rebound
- How A Goat Farmer Built A Doomsday Machine That Just Booked A 4,144% Return
- CNN Fear & Greed Index
- An (Institutional) Investor’s Take on Cryptoassets
- Gresham’s Law: The Bad Drives Out the Good As Time Passes
- Follow Macro Like You Follow Sport For Entertainment
- The Lesson That Robinhood Investors Are Going To Learn
You can find out more about Tobias’ podcast here – The Acquirers Podcast. You can also listen to the podcast on your favorite podcast platforms here:
Tobias: Hi, I’m Tobias Carlisle. This is The Acquirers Podcast. My special guests today are Taylor Pearson and Jason Buck of the Mutiny Fund. It’s a great name, you have to find out. You have to listen all the way to the end of the podcast to figure out why it’s called Mutiny Fund because I’ve got to ask the question upfront. It’s long volatility and tail risk, particularly apt for this time of the market cycle. I’ll be talking to them right after this.[intro]
Tobias: How did you two guys meet?
Taylor: I wrote an article and Jason read it, and we started emailing.
Tobias: What was the article?
Jason: It comes out of crypto? Yeah.
Taylor: I’m trying to think when this would have been. It would have been early 2018 at some point, I wrote an article about Stablecoins. I just had this idea of Stablecoins. And then Jason was also [unintelligible [00:01:19] like, how could you construct a basket of assets that was stable over time. So, we started talking about that, and then got into– we had both read a bunch of the similar stuff around tail risk and traded options on and then went from there.
“Black Swan” Volatility
Tobias: So, the Mutiny Fund is, from what I can see, it’s a tail risk fund, is that a fair description of it?
Jason: We’d say tail risk and long– We always say– it’s a mouthful, but always, long volatility and tail risk. So, we have the tail risk in there. I’m sure we’ll get into this. But it’s built around also long volatility to maintain some of that bleed that you would get with just pure tail risk, like a Universa or something like that.
Tobias: How do you construct a long volatility component?
Jason: You use people like Chris Cole. [chuckles] So, the way we look at it is, long volatility is that dynamic way of trading tail risk, both left and right tails. And so, they’re using their own algos or market timing to either structure those trades. So, whether it’s Logica with Wayne that’s using straddles and gamma scalping the position to manage that data bleed, but either way, he’s long volatility and maybe that’s the best describer for long volatility, is your long volatility on both the left and the right tails. And that’s probably the simplest way.
We use firms like Logica that straddles and then firms like Artemis that strangles, and we also use some opportunistic traders like Headwaters volatility. But that combination gives a long volatility profile. We add back in those deterministic rolling puts that would be typical tail risk. And then around the periphery, we use volatility arbitrage and intraday futures traders to kind of manage that bleed or give some uncorrelated rebalancing premium that we can try to maintain that profile that are at risk on cycle.
Tobias: So, what’s the objective with the fund? Is it to provide blow-up protection? Or is it to, you can allocate however much of your portfolio to it, and then it’s both, it’s going to manage through the good times and through the bad?
Tail Hedging And Crisis Alpha
Jason: Yeah, the idea being that spoonful of sugar. For decades, Taleb and Spitz Nagel, and all these guys have been saying, “You should just eat the bleed of tail risk.” And we just felt behaviorally people aren’t willing to do that. We believe in ensemble approaches. So, we think through the ensemble approach, we can try to maintain a flat or slightly positive return during a risk on cycle, that will make sure people hold it on their books. It’s really just that spoonful of sugar help the medicine go down to make sure you maintain that tail risk protection for the blow-ups. We want to try to use an ensemble rebalancing premium approach to try to maintain a flat to slightly positive carry instead of that negative carry, and then your CalPERS and you get rid of it right before the blow-up.
Tobias: [laughs] They always seem– it’s funny, the two challenges that I can see with tail risk is, the bleed over a long period of time makes it hard for folks to hold. And then on top of that, really what they should be doing as the short volatility side of it, whoever that’s constructed as that’s going up, they really should be rebalancing away from that and increasing their allocation to long volatility. But that’s hard, because they’re looking at that side, losing all the time. That’s a sickening thought, particularly when we’ve been through these very long periods of volatility suppression.
Then, the other challenge is when you finally get the blow-up, it needs to go the other way. You need to be able to rebalance away from that side of the book that’s working so that you can now go and buy all of these undervalued assets on the other side. It’s just hard in a lot of funds to achieve that because the lock-up and so on.
Taylor: To going back to the goal thing at some point, I hate the way we generally talk about is. The goal is to help investors maximize their long-term compounded wealth. That’s the goal. And from our perspective, the reason we started this was– we felt like an essential piece of being able to do that and just was really hard for noninstitutional investors to get access to these sorts of strategies. So, yeah, I think you’re right. You want the end investor to look at the whole portfolio. It’s like this is improving the long-term compounded growth of your portfolio. Yeah, we’ve had to be conscious to some extent of– as people are going to look at as a line item, whether or not they should, and they probably should to some extent, but by having it, by trying to bundle it up, and look at this in the context of the broader portfolio, it’s a little more palatable.
Investing Like Rodman – The Worm With The Rebound
Tobias: Chris has got the great analogy of Dennis Rodman, the worm with the rebound. If you’ve got a really good offensive team and you’ve got one guy like the worm getting the ball back and feeding it back to the guys who are offensively strong. So, the worm’s your volatility, your long vol portion, and the rest of the team is your shortfall portion. So, he goes and gets the rebound, feeds back to the offensive team, and all of a sudden, you’re much more powerful than you’d be by yourself.
Jason: Exactly. Taylor and I are big fans of like deep value. We think this actually pairs phenomenally well with like deep value. Like you alluded to, it’s like when that sharp selloff happens and liquidity bank crashes and we provide almost like a convex cash position, now you have tons of [unintelligible [00:06:34] on your books to rebalance into value at even better prices. So, it pairs incredibly well over market cycles with deep value. The way we look at it too, is we don’t believe you should try to time that insurance but by having managers that are trying to time that insurance, but an ensemble of them, it allows you to just hold that on your books, which allows you to take more risk of that implicit short volatility. So, you can hold more deep value if you have us sitting on the books and you can sleep at night.
CNN Fear & Greed Index
Tobias: Just using something as simple as the CNN Fear & Greed Index. I don’t know if anybody else tracks that. I don’t know how intelligent that’s regarded in the vol community, but it’s just something for non-vol guys like me, I just sort of look at it. When I look at the performance of that thing, I go back, you get about two bites of the cherry every single year where you get CNN Fear & Greed goes below 20, which is very much the fear side, below the fear side. If you’ve got a long vol component, like you’re getting two opportunities a year to take away from the long vol component to jam it a little bit longer so you get that third pocket opening up with a little bit of extra cash in it, I think that that should be a very successful strategy.
Jason: Yeah, if we just can convince more people of it. That’s–[laughter]
Jason: -what we’re doing to do.
Tobias: It’s always going to be hard when it’s a market like this. Why would you hedge anything? The best performing asset in the world is the S&P 500, why hedge anything? It’s just going to keep going up in a 45-degree line run.
Taylor: This part is really interesting too because it’s going up at a 45-degree line, but six months ago, it went down at a 88-degree line.
Tobias: That was just a blip.[laughter]
Taylor: Yeah. Everyone’s like, on both sides where it’s going straight up, but it just went straight down, how is this going to play out?
Tobias: The market just completely forgot that that happened, I think. It’s as if you could just rub that off the chart and it just keeps on going straight through it as if it didn’t happen.
Jason: And to your point, that’s when that rebalancing is phenomenal, at the end of the March, we had allegedly been up like [redacted] 10 after like then you could rebalance back into all of your stock positions and then just crushed since then.
From Stablecoins To Volatility
Tobias: Right. So, you wrote the article on Stablecoins, how do you get from Stablecoins to volatility?
Taylor: At least philosophically for me, like, I think you could think about, bitcoin, if you’re going to you take Bitcoin specifically, it is a long volatility thing. The only way in which bitcoin could possibly make sense as an investment is if stuff gets weird. If the stock market just keeps going up 20% a month, inflation stays at 2%, nothing happens. In my mind, it’s a long volatility bet. Again, as Jason said, we’re big believers in this ensemble approach in general and in particular, ensemble approach to long volatilities. You find there’s a portion of that, you can look at commodity trend or gold or bitcoin as just other aspects of expressing that sort of long volatility piece of the portfolio.
Tobias: So, has bitcoin behaved like long volatility?
Taylor: No, I wouldn’t say it has. I would say I think it has the potential to do so in the future.
Tobias: If you get inflation or hyperinflation, that’s the kind of scenario where it works well.
Taylor: Yeah, it’s regarded as highly speculative and I think that’s the appropriate thing. You should know, people should position size as though that’s the case. It has interesting theoretical properties to me that it could behave, yeah, similar to a gold in an inflationary environment.
Tobias: What are the theoretical properties?
Taylor: What is it that makes gold particularly– why is gold considered a good– I wouldn’t say it’s a good inflationary hedge, but hyperinflationary hedge. The other primary thing is the stock to flow ratio that it has 100 years of history, in no year have you been able to mine, I can’t tell you off the top of my head, it’s like 2.5%. The total gold stock has never increased by 2.5% and that’s just like a function of geologically how gold is in the earth’s crust, and how expensive it is to mine it and all those sorts of things.
Bitcoin has the same property, but it’s not a function of geology. It’s a function of the way in which the consensus mechanism is established, and new bitcoins are created, that’s programmatically determined. The whole proof of work mining algorithm is basically a way that makes it prohibitively difficult to change that, or at least an economical change. I think part of the interesting thing about Bitcoin is it’s more profitable to play by the rules than cheat the rules.
There’s all these game theory scenarios, under what scenario is it profitable to undercut bitcoin? And it’s hard to find those scenarios. Chinese government decides it’s not in their national security interests, then you have a huge externality. But if you just look at it as sort of a microcosm, the security model is very interesting and the stock to flow model is very interesting. I think it has some properties that gold lacks. One, the stock to flow ratio is theoretically more predictable— it is more predictable.
You know we can say with a high degree of certainty how many bitcoins are going to be created over the next 12 months. Whereas like gold, you can put it within a band, but there’s some variance there. It’s easier to transport. I need a USB stick or I need 24 words in my head, and so you get people that make, they’re like– if you were a Jew living in Germany in the 1930s, it would have been useful to have a thing where you could remember 24 words and that would be your wealth, and you could get out of town. So, I just there’s interesting theoretical properties there.
I think another element of it that we really haven’t– are just starting to see a sort of this like programmability element. There’s this whole sort of one of the recent trends this year has been decentralized finance or defi and that you can do all these– you can program money now, that’s the interesting thing. To some extent, you can already do that. Some people can go to JP Morgan and write these big complex contracts for certain [unintelligible [00:13:23] wherever what happens when that’s more broadly available. It’s probably what happens initially, what’s happening now is a mix of a lot of fraud and people doing gambling and a bunch of stupid stuff. But in the long run, it seems very interesting to me.
An (Institutional) Investor’s Take on Cryptoassets
Tobias: Can I ask you a noob question? I understand the scarcity argument when it comes to bitcoin. But isn’t that thwarted a little bit by the fact that it’s so easy to create a competing currency?
Taylor: Yeah, there’s a guy named John Pfeffer. I think he’s at a P/E firm. He wrote an interesting paper. This was in 2016-2017. I haven’t really read anyone that’s written a good rebuttal to it. It’s an institutional investor’s take on crypto assets. But basically, the thrust of his thesis is, let’s just say there’s two cryptocurrencies. Everything else being equal, you’re going to hold the one that is more secure and a better supply schedule. For example, you have a new cryptocurrency that supplants bitcoin as just a store of wealth. You have to basically convince the market that that’s going to be a better store of wealth in some capacity. I just think that’s very hard. I think with the security stuff, especially with like bitcoin or the way the mining industry is structured, there’s just like a lot of– it’s totally doable in the same way like you could start another search engine that is better than Google, but there’s a lot of network effects that make that hard. Yeah. I’m not explaining this super well.
Tobias: No, I understand. There’s some competing, like Ethereum– another noob question. But Ethereum supposedly got some properties that makes it more useful than bitcoin?
Jason: But they’re totally different.
Taylor: Yeah. We’ll see how that shapes up. I think Ethereum only works, and this was the paper I mentioned, this was specifically one of the things he talked about is, let’s just say it’s just bitcoin and Ethereum. The bet Ethereum is making is, Ethereum also wants to be a form of money, but it thinks if we have all these applications, which have all this utility because it’s easier to program on Ethereum than it is on bitcoin– actually, it’s sort of at a high level the way I think about the tradeoff at least is. Bitcoin is more secure, but less adaptable or less flexible, and the programming language Ethereum uses is Turing complete, which gives a lot more flexibility, but also increases the attack surface. Whereas Bitcoin uses a much lower-level programming language, which makes it more secure, but also makes it much harder to write applications in bitcoin. Some applications that you can write in Ethereum, you can’t write in bitcoin at all, and others might take 50 times longer just because of the level of the programming language.
But let’s just say you have those two things. And so, effectively, Ethereum is like you’re working capital. I’m going to use this thing to execute these smart contracts that are going to be able to do all– whatever these different terms of programmable money thing, yield farming, all this stuff. But if you know it has a higher inflationary schedule, you’re not going to store– you’re going minimize the amount of working capital, you can hold on that thing. And then you get into the velocity problem. Money only has value if people want to hold it. As soon as you have something with a very high velocity of money, the value goes down. Whatever crypto wins is, it has to minimize that philosophy, in some capacity. So, bitcoin seems much more focused on that than Ethereum.
Gresham’s Law: The Bad Drives Out the Good As Time Passes
Tobias: I’m going to flub the name of the law, but isn’t that the good money drives out bad? Isn’t that the [crosstalk] theory–
Taylor: Yeah, Gresham’s law.
Tobias: Gresham’s law, yeah.
Taylor: I think it’s called the theory of exchange. It’s been a while since I’ve read up on the stuff. MV equals PQ is what it is, and I’m not going to remember what all the variables mean. But it’s like the quantity of the money times the price of the money is equal to the velocity times the– I’m forgetting what M is. But basically, the way it nets out is if the velocity is high, the price is low.
If the velocity is low, the price is high, sort of all other things being equal. And so the challenge, I think, with a lot of these, like Ethereum, in particular, but these more smart contract, we’re going to be utility as they have like– it could be Ethereum is wildly successful in terms of people build applications on it, it becomes highly utilized, but also accrues no value.
Because the logical thing to do is to store all your– keep as much as your money possible in the thing that is more likely to retain value, and then just use whatever the minimal amount of working capital you need is, the thing to Ethereum or whatever the smart contracting token is, to execute the things. And then you get into security issues. If it doesn’t add value, and the mining or the consensus mechanism is based on it having value, does it become less secure, and you get into some sort of death spiral, and what does that look like?
Follow Macro Like You Follow Sport For Entertainment
Tobias: To what extent do you guys have macro views that you employ in the management of the fund?
Jason: We don’t. The way we look at it is you don’t want to time your insurance. So that’s why we tried to build the product the way we did, that you can just hold it indefinitely. And we actually come from the background of– Chris Cole’s Dragon portfolio comes out of the intellectual path work of Harry Browne’s permanent portfolio, which then Ray Dalio piggybacked on for risk parity, which then Chris Cole’s Dragon portfolio’s a modern interpretation of that. But the way we try to look at it generally is that nobody can predict the future. If they can, none of us would be talking to them. They’d own New Zealand at this point.
Jason: So, it’s an entertaining game to predict globally macro picture and what’s coming in the future, and I think all of us get caught up, our egos get caught up in that game. But we try to build a portfolio of this ensemble approach to long volatility tail risk so that way you can hold it indefinitely and it makes you sleep at night while holding these implicit short volatility long GDP assets. We try not to predict futures at all and then we rebalance frequently to also harvest a little bit of rebalancing premium off of the dispersion of our managers’ returns.
Tobias: Yeah, that’s refreshing to hear. I like following macro the way I like following sport, but I wouldn’t ever use any of it in anything that I do.
Jason: I feel the same way. It’s entertainment. I love watching entertainment. But the hardest part is you can’t let your ego get caught up in it because it’s so sexy for your ego. You’re like, “I agree with my green here. I disagree. I agree with you.” You just get into these loops and you’re like, “I can predict the future. I’m all-knowing. I’m omnipotent.” It’s so sexy to get caught up in. But I was watching– Dan McMurtrie was on Real Vision yesterday. And then I was just looking through all the comments, I was so confused because everybody’s like, “I disagree. He’s an idiot. He doesn’t know this, this and this.” You know instead of typing that up, there’s a market where you can go and take the other side of this trade. Why are we pontificating? Show me your book, put your money where your mouth is, there’s no reason to talk about any of this.
And then, what I always find fascinating by global macro that drives me nuts is you can have guys that completely disagree with each other. So, let’s just say Mike Green and Ben Melkman completely disagree, but the way they construct their portfolios is what matters. But everybody’s worried about this narrative. But it’s like as long as they construct their portfolios with a ton of asymmetric bets, they can both be right and wrong on simultaneous things and still end up out ahead on their P&L. Nobody sees that. Everybody gets caught up in these beautiful narratives. And I understand, it’s a beautiful framework they build but literally, nobody can predict the future. So, I don’t know, it’s perverse.
Tobias: I couldn’t agree more. That’s almost always my first question. When someone has one of these very elegant theories, how do you execute it? What are you going to do?
Tobias: What’s the construction?
Jason: Exactly. Tell me your position sizing, tell me the other positions, show me the asymmetry of the trade. That’s all that matters. I tried to do that with Hugh Hendry because in the past, he talked about being a centipede. If he’s got 100 positions on, he doesn’t mind chopping off a few arms, so that’s what matters. Not what he thinks about, are we going to negative rates or not? It doesn’t matter. Show me your book of construction of the trades.
Tobias: Hugh, in particular, I love Hugh, I’m not trying to be critical of Hugh. But when he lays out his theory, it seems to me that it’s got this– this is going to happen and this is going to be the impact of this, then this is going to happen. By the time you’re like the third or fourth derivative, I’m like, well, what’s your confidence around each of those? What’s the probability that each of those occurs? And then, multiply any set of probabilities, even reasonably high probabilities in a sequence, the chance that they all happen in series or in sequence, you get a very low number at the end.
Jason: Exactly. And that’s why you need to construct these hugely asymmetric trades. And so, you only need a few of them to hit out of 30. Like you just alluded to, you’re adding such a specific path dependency, but they do that also to get such cheap convexity. So, it’s this tradeoff between nailing the path dependency versus the convexity of the position. So, if it was a very vanilla trade, you might only get three to five to one payout. But if it’s crazy path dependency, you may get 20 to 51 payout. So, then you’re trying to layer in path dependencies hoping you hit a few of them.
Tobias: It’s the parlay bet. It’s heading to the racetrack and trying to get a number in a row.
Jason: Man, I swear you’re inside my computer, Toby, because I just interviewed Diego Perea and that’s what I talked about was, I used the analogy of parlay bets. And as all of us know what a parlay, you get two of them. You’re like, “Oh, shit, oh, shit.” And the [crosstalk] you’re back to zero, every time.
Tobias: I’m retired. [laughs]
Jason: Essentially, if you have exotic correlation trades, that’s exactly what you’re doing. It’s a parlay bet. If you’ve been a sports bettor, you understand the excitement, but you also understand the probabilities are incredibly low.
Tobias: Yeah, you bought a lottery ticket. It’s fun, but it’s going to pay off like a lottery. I read in your bio, Jason, that you come from property development, real estate, is that–? So, how do you get from real estate in 2008 to volatility in 2020?
Jason: Sure. They bookend each other incredibly well. So, basically, from my side, this has been a 12-year project to bring Mutiny Fund to fruition. In 2008, as a commercial real estate developer, I owned several restaurants as a part of a restaurant group, even owned a wireless internet service provider. So, I owned all these businesses, but primarily commercial real estate development. When you have that liquidity dry up, like we saw in ’07, ’08, ’09, and see how that just cascades through the entire system, that pain was so profound for me that I figured there had to be a solution. As entrepreneurs, Taylor and I are just problem solvers. I was like, “There’s got to be a way to hedge some of this macro liquidity risk.” Because as an entrepreneurial, idiosyncratically, I can really believe in myself and I can really work hard on my projects. But if the global macro liquidity dries up, I’m screwed along with everybody else.
And then, especially if you’re looking at it from the commercial real estate development space, is you have to predict like five years out, if you start a project, and you have to hope that everything ceteris paribus is going to be low vol from now to those five-year path dependency for you to pay out your pro forma idea of what this project is going to payout. And so, if you have to take such long time horizons, there’s got to be a way to hedge your macro risk. And so, for the last two decades, I’ve been trading my own book ever since I was even a teenager, but really got into trading options and trading the VIX around 2010-2011 and was really working through a lot of these ideas. Through losing money doing these trades is the best tuition in the world, that pain makes you dive more into it and learn more and more and more. It’s why I don’t get upset about Robinhood, like these other old guys do is. You forget when you were young, we were all doing really stupid things, we lost money. And that was the pain and the tuition that made us learn more. So, it’s no big deal.
So, throughout that process of trading options and VIX and everything, I started tracking a lot of the other managers in the space, reading Chris Cole’s work, etc., and just over time, just felt there’s so many path dependencies to risk off that you need to cover a lot of path dependencies for it to work. And this is where Taylor and I really came together was, we’re looking at placing our own money with, say, an individual manager, but there’s a lot of idiosyncratic risk there. So, we both believe in taking this ensemble approach to really reduce that idiosyncratic risk and cover as many path dependencies as possible, knowing none of us know a priori, once again, what the future is going to look like.
And so to do that, we figured– this was a multi-year project, to work with the lawyers and everything and figure out all the workarounds and everything to actually offer a product that retail our family and friends could use, but also we could use. And so, part of that to get to that ensemble approach is you had to be able to aggregate a bunch of retail investors to a QEP minimum fund. And that’s how we could actually place our own money with this ensemble of managers. So, we actually built it for ourselves and our family, knowing that it would also be helpful for other people.
Tobias: Yeah, because I met Chris in about 2010, the beginning of my education and volatility started around about then, took about two years, about a bottle of wine a night for about two years with Chris, explaining it over and over and over to me until I finally– I did finally get it in about 2012. And then, hasn’t really worked that well since 2012. Although it did work earlier this year, so how did you guys fare through the big drawdown?
Jason: I’ll maybe let Taylor talk about the timing of when we launched. [crosstalk] [laughs]
Taylor: Actually, we went live in mid-April. As I’m sure you’re aware, we started working on it in earnest beginning of 2019. We’re like, “Oh, we’ll just get the large drop, the docs and raise the money and it’ll be no problem.” It took basically a year. I think we finally got all the docs and legal stuff done just before the holidays of 2019. We started basically fundraising in mid-February. And March, it’s a very interesting conversation. Literally, we’re on the call with someone and the markets down 4% since we started the call.
Tobias: Compelling pitch.
Taylor: [crosstalk] Yeah. We then got really lucky with the timing. Obviously, it was on everyone’s mind, or really unlucky with the timing. So, yeah, ideally February 15th would have been a nice time to have launched.
Tobias: I think Chris got a little bit lucky with his timing. I think he might have launched either January or February 2012 when there was a big vol spike and then not much in the intervening period from that time until basically until this year, to that big drawdown.
Jason: Yeah. I think you’re exactly correct on that. And part of it is– this is why we use that ensemble approach is you can get pops in volatility in different parts of the space, whether it’s in VIX, futures, or in options. And so, we try to use those ensemble of managers to capture some of those pops, and then redistribute it across the portfolio to help the P&L while we’re waiting for that big risk-off event. So, that’s another way to try to cover how do you carry this position during a risk-on environment. And then, as you know too what’s nice too, is as we get closer and closer to that risk-off event, those options and volatility become suppressed and those options become cheaper. So, you’re actually loading up on inventory serendipitously right before the crash happens.
Tobias: It’s one of the nicest things about it. You’re sizing into it right at the right time.
Jason: Except for the hard with– the flip side of that though is that can go on for years. You’re like, “This is great, my position, so it should be coming.” And then it’s ’17, ’18, ’19, ’20, you’re like, “When is this going to happen?”
Tobias: I read Taleb’s more readable book, not Black Swan. The one–
Taylor: Fooled by Randomness.
Tobias: Fooled by Randomness. Thank you, yeah.
Taylor: I agree that this is his most readable book. That’s the one– [crosstalk]
Tobias: Honestly, I couldn’t get through the other ones, I’m sorry.
Taylor: That one was successful and so then he could just tell the editors to fuck off and do whatever he wanted. Fooled by Randomness, he wasn’t that big and so he had to do what the editors told him to do, so that got streamlined, but then after that, he was like, yeah.
Tobias: “I’m the bloke who sold 3 million books. So, I’m going to give you the manuscript and you’re going to publish it.”
Tobias: Yeah, that first book was spectacular. When I talked to Chris, I was like, “Oh, here we go. This is how you actually implement this strategy.” And this makes total sense to me. Everybody underweights the tails because they happen so infrequently. Everybody’s clustered around the mean, buy the tail, sell the mean, this game is really easy. And then, the thing that Gladwell points out, Gladwell wrote an article about him, I think it’s called the Blow Up or something like that. And he said, the only thing basically that can happen to you is you can just bleed out. And I was like, “Yeah, but these things happen so frequently.
The thousand-year storm rolls around every seven years. You’re not going to bleed out.” Of course, here we go into one of the longest periods of volatility suppression. I see it happen to get value guys wind up their funds. It’s one of those things– I find value so compelling from a theoretical logical standpoint, how could you ever not do value? And then, you realize that there are these very, very long periods of time where it doesn’t work. And the reason that value starts working again is all the other value funds just get wound up, they just disappear.
Jason: [laughs] Exactly. Yeah, you know that pain of looking back over long time periods. But part of it though, where we take a bit of umbrage with that people don’t consistently look at is the holistic effects of your portfolio. And I think Mark Spitznagel at Universa, which is Taleb’s partner, Mark actually runs Universa, is that the way he explains it so well, is it’s a combination. So, if you use Universa, let’s say it’s a negative 3% bleed, just to throw out some numbers. But they’re allowing you then to carry 97% exposure to the S&P, and let’s say they’re truncating your left tail at negative 15 to negative 20% moves, and you’re blocked off from that down. And so, the combination of that rebalancing over multiple business cycles, actually, you end up ahead.
So, it’s a weird thing. It’s more about actually being able to hold more implicit short volatility assets, long GDP assets, and comfortably hold those and rebalance and compound wealth better over time. But everybody only looks at that line item. So, a lot of the arguments this year from like AQR, etc., were just talking about the line item and not talking about the holistic portfolio construction, and what that allows you to do to compound your personal wealth and savings over time. For example, I think that Universa is likely cherry-picking the timeframes as we all do, but that combination compounded at 11% or 60/40 was compounding at like 6% to 7% over the similar timeframes.
How A Goat Farmer Built A Doomsday Machine That Just Booked A 4,144% Return
Tobias: Yeah, there was a great article just after Spitznagel had the big win where it was goat farmer makes 4500%, something like that.
Taylor: [crosstalk] Forbes.
Taylor: [crosstalk] to Forbes headlines.
Jason: Yeah, that was weeks of me in Twitter DMs and everything breaking down what that actually means. It’s incredibly frustrating to have to deal with sensational journalism.
Tobias: Well, I think Chris is in the same boat. He’s got all of these people who’ve invested with him, saying, “Why didn’t I go with this other bloke who’s returned 4500%?” He’s just a goat farmer.” Here are you, you’re doing this stuff all the time.[laughter]
Tobias: So, let’s calculate it the way that they do.
Jason: Well, there’s two pieces and I’ll break down quickly. One, by the way. His goat cheese is incredible. I grew up in Michigan, and he has this beautiful farm in Northern Michigan, but he smartly bought that farm after ’08, ’09. He made such great returns in ’08, ’09, he invested in a goat cheese farm. It’s actually arguably the best goat cheese in America. So, I’ll set that aside. It’s amazing. [crosstalk]
Tobias: My wife will be excited to hear that. I think goat cheese tastes like it comes from a male goat, but my wife loves it.[laughter]
Jason: Actually, it makes me think that there’s a– I don’t know how true it is, but there’s a thesis that if you have goats that eat poison ivy, that gives you immunity to poison ivy by drinking their milk or eating their cheese.
Taylor: I smell DTC brand, some– [crosstalk] [laughter]
Taylor: There’s a supplement company in there for sure.
Jason: But then the 4,000% return, the easiest way to break it down to say it simply, that allocation to Universa was up, let’s say 12.8% total in March of this year, and the S&P was down 12.4%. So, net-net, you’re up 40 basis points. You’re up 0.4%, so they did their job. They covered that tail risk. They covered the downside risk. Fantastic, good on them. But it’s not a 4000% return. But let’s just be clear about that, once again, looking at the holistic portfolio construction.
Tobias: It does make sense if you can think about– if they can truncate the left tail so that you drawdown, say half as much as the market, you’re already 100% ahead when the market recovers. So then, if you’re giving away a little bit every year, a few percent, that’s quite a few years before that unhedged portfolio catches up with you. And then, likely, you get another big drawdown somewhere through that and that’s all you have to do. You just have to keep on sort of staying– As long as you’re not drawing down as much, it’s a much more attractive return profile anyway.
Jason: Yeah, it’s a more attractive return profile but I also want to highlight again that, with that profile, you’re able to hold 97% S&P exposure, where in 60/40, you only have 60%. So, you’re actually also outpacing when you’re waiting for it to happen minus your bleed. So, it’s that tradeoff of 97% exposure minus a small bleed, how does that compare to 60/40 during risk-on, and then obviously, the compounding is just exceptional when you have these risk-off events when you’re able to rebalance into that lower nab point.
Volatility In Wonky Environments
Tobias: When you have an environment like this, which is not unusual. In the late 1990s, in the dotcom boom, there was this– and Chris alerted me to this a little while ago and I’ve always wondered if we’d see it again where the markets going up and you had upside volatility. So, the volatility is going up as the markets going up. And ordinarily, it’s the other way around. As the market goes down, volatility goes up. As the market goes up, volatility goes down. And here we are in this environment, again, likely driven by maybe Robinhood option positions. How do you guys fare in a market like this? And what are the causes? Why are we in this unusual environment?
Jason: All right. So, there’s multiple ways to look at this. So, the way to look at volatility in general is people in risk-on times, unfortunately start to see S&P and VIX as negatively correlated because they are. The way VIX is not only downside volatility on S&P, it’s just outsized volatility. And unfortunately, the truism of the market takes the stairs up and the elevator down, is why we usually see that negative correlation and see VIX up when S&P is down because of the violence of those moves are outside of what the standard deviation is expecting that return to be. But if you have a melt-up scenario and the S&P or individual stocks are ripping up to the upside, but those returns are outside of that standard deviation for that day of what VIX is expecting, you’re going to have VIX up, S&P up.
So, these things happen. Like you said, ’99 is a great example. Abenomics in Japan’s another great example. But they happen infrequently, but they do happen. And so, you have to be aware of those different times when you have VIX up and then spot up which S&P up. But also part of that too is, you have to always worry about the term structure of the VIX trade. So, it’s not always so simple. But going back to what you said about the environment we’re in right now is, you have not only retail traders, Robinhooders buying options and how much that affects the — the dealer gamma hedging of those positions, is you always can have these wonky environments for volatility in equities.
There’s no free lunch. If VIX and S&P were perfectly negatively correlated all the time, it’d be such an easy trade and we’d all make money. It’s these times when you have these three- to six-week periods, where VIX and S&P are kind of all over the place. They’re getting a little wonky– as you’ve been in the markets long enough, there’s a lot of things we can’t explain that we just call wonkiness. It’s like saying like, “There’s dark matter in space.” It’s just a fancy way of saying, “I don’t know.” This is what happens. So, what you have in hindsight, is everybody’s going, it’s the Robinhood traders, it’s the Softbank’s, long gamma position. I’m sorry, the long Vega positions, but those are farther out, but they’re also hedged for equity. So, everybody, in hindsight is trying to be a detective and get their Sherlock Holmes hat on. But even they can’t all correlate around an actual explanation.
So, like you were talking about earlier, it’s not so hard to predict the future. In hindsight, it’s hard to predict the straw that broke the camel’s back. But part of it is, it’s just that S&P and VIX can get wonky, especially when you have an environment where– VIX tends to have like a bimodal distribution, and what that means is simply during a risk-on cycle when volatility suppressed, you have low VIX and the average VIX tends to be like 12. Then you have a risk-off event, a violent phase shift happen, and VIX has a separate distribution based on a higher volatility environment where average is around 20 to 22. So, you have these two different environments. And when you’re in that higher vol environment with a higher average vol, you can have more of this wonkiness between VIX and S&P, so you can actually have days when VIX is coming down and S&P is also drifting down, but the drift down in S&P is less than the average estimated standard deviation movement that single day.
So, that’s how you can have these environments when you’re coming from high vol and it’s drifting back down, where you have volatility down and S&P down in the same day, because they’re small drift moves that aren’t spiking volatility back up. Now, eventually they’ll drift back down where then any movement, S&P will spike volatility because it’s a mathematical relationship. But this is what we see over the last few weeks. And then, everybody tries to decipher what, why, where, when, how. Like I said, dark matter or wonkiness.
Tobias: Yeah. I guess the challenge for implementing one of these sort of strategies is, you can’t trade the VIX directly, you’re trading options or futures on the VIX and so there’s lots of smart– you’ve got Ben Eifert out there, you’ve got Chris Cole, you’ve got Himelsein, you’ve got all these guys out there who are– there are expectations built into the pricing that you’re getting at any point in the VIX. So, in an environment like this, is this a good environment for vol guys? Is this a tough environment for vol guys? Am I asking you a question like, is this a good market for equities? Is this a bad market of equities? [crosstalk] –depends?
Jason: It depends but I’ll break down the buckets on how we view it and that might that might be helpful. If you’re talking about somebody that was just purely buying options, as VIX is coming down, you’re still paying up for the implied volatility. So, you don’t quite have the convexity when you’re buying both puts and calls. And so, it makes it a little bit more difficult environment for buying options because you don’t have that. So, you could still be directionally right. But if implied volatility came down, you lost on the Vega side of that trade, and you’re combining that with the theta bleed.
The Lesson That Robinhood Investors Are Going To Learn
So, this is what the Robinhood traders are going to learn a lot, is you can be directionally right, but it’s about the price you paid for that option and the path dependency it took to get there. And so, you can be directionally right and lose money trading options. So, that makes it difficult for options traders in general, I’m not going to speak for any of our individual managers, they know this. They’ve been in the game for decades. So, they try to maneuver around this.
The other way the bucket we look at it with futures is, we have managers that could trade intraday futures and they can go short those markets. So, now they’re not paying for that implied volatility, they’re not worried about the implied volatility at all, then it’s just about continuation of the trend intraday in market indices around the world. This could be potentially a target-rich environment or you never know a priori, it’s just like all trend-following. You put on the trade. You hope for the best. You have a short tight top loss. You get whipsawed a lot, but eventually make a bunch of money. So, that’s the way to look at the futures bucket.
The VIX arbitrage bucket though is– I don’t want to speak to what Ben Eifert does, but the VIX arbitrage is like a relative value trade. So, it’s relative value either on VIX versus S&P, which is the intramarket spread or on a calendar spread on VIX. So, those gives you more of a mean-averting pairs trade. Any environment can be good depending on your positioning and your ratioing of those VIX to S&P positions or the VIX calendar positions. It’s like how many units are you short versus how many units are you long, depending on what the markets giving you in the VIX that specific day or week. So, it’s hard to say a priori if those are good or bad environments for the VIX arb, it depends on where their algorithms are positioning them, if that makes sense.
Trading Around Earnings Announcements
Tobias: So, the vol surface, the VIX term structure is a little bit like, each month going out from here until the election say, we know that there’s an expectation of– there’s always shenanigans around the election. We don’t know what’s going to happen, there might be some volatility and so the market is expecting volatility. I’m not sure if it’s the October or November, but there’s a definite hump around there and there has been for a little while, which means that trade is expected to be some vol around the election. There may be an arbitrage there where you may be short that volatility and long some of the more front-month stuff. So, if you get a volatility event before then, you catch the front-month volatility and maybe you’re paying for it by being short that November volatility. Maybe it’s going to be a non-event. I’m not necessarily suggesting anybody put that trade on, by the way, I’m just using that as an example.
Jason: Well, I’ll counterpoint you and that will hopefully keep somebody from putting that trade on. So, there’s never any free trades. And so, part of that hump in the VIX term structure is because VIX is a variant swap on 30-day forward variants, so that’s why that October contract even though expires in October, is looking out into the November election. But then, you look at the November election and you’re in backwardation. So, what that says is if you’re a long front month, the term structure roll yield is going to kill you being long front month. And then if you went short back month, the backwardation is going to kill you. What I’m saying is the term structure is screwing you to make sure there’s no easy trades because there’s no easy trades. So, that’s a way to look at it.
The other way we think about it sometimes internally is that– I used to trade option straddles going into earnings on tech companies and trade the IV ramp going in pre-earnings and then close out before the earnings. And what you would find a lot of times is, if the last earnings announcement was pretty benign, it would be very low vol heading into this one, if the last earnings announcement beat expectations either way, I’ll send you to have high vol going into this one. So, it was a form of recency bias.
And so, we think about the last election, most people didn’t predict the volatility of the last election. Now, all these smart traders are so doom and gloom and predicting, “Oh, Trump’s not going to accept the election,” or, “Biden won’t accept it.” It’s because they got caught with their pants down on the last one and they have recency bias. And these things only happen once every four years, we have so few data points. At least that’s what internally I can’t help but see in that connection of correlation with– and I’m not saying this one’s not going to be contentious or any of those things. But that’s just why going into the last election, you would have the vol term surface would have been much lower and this one’s much higher, and to me, it’s more of a recency bias.
Tobias: I think there was a hump going into the last one, I think I remember Chris pointing it out to me, which is why I might have been looking for it this time around, what does that mean? It might have been– there was a lot of suppressed volatility around anyway, so I think it might have been a much lower market. Going into the earnings, if it’s high vol, you just try to find a way to short the vol if it’s the other way. If it’s low vol, you’re trying to get longer vol. How are you thinking about that as a trade?
Jason: Previously, when I say this, and by the way, it’s a great trade, it’s just a highly capacity constrained trade. So, somebody can make a decent living trading this, but the idea is generally that anywhere from 30 down to 7 down to 3 days prior to an earnings announcement, what’s going to happen is more traders start to want to trade around earnings. They’re going to get more into the markets and then the dealers are going to raise that implied volatility at that position. So, what you’re hoping for, I say you’re riding the IV ramp. If you put on a straddle where you don’t care if it’s going to be up or down, you’re playing your implied volatility and then the gamma that position as we get closer to the announcement. But what you’re looking for is basically the implied volatility to rise faster than the theta bleed on being the long options.
Then you want to actually– the way this trade works is you closed prior to the earnings announcement. A lot of times they’re after hours, so you’d close that position the day out. For example, what’s interesting is, and I haven’t seen great data on this, it’s hard to get it. But if you open days, a straddle trade, and that morning, the IV ramp till the close that day is going to rise enough to offset the theta for that bleed. If it doesn’t, you’re going to lose a little bit, but you’re still long astraddle. So, let’s also say during that seven days prior to that, also, an exogenous event happens like 9/11, your long astraddle. So, it’s actually kind of a great trade, but [crosstalk] maybe one week a quarter. But that’s the idea behind it, is it’s just that pricing of that IV ramp you’re hoping it’s going to expand, and that expansion of IV is going to offset the theta bleed in. And so that way, you can pick up a few pennies here and there every earning cycle.
Finding The ‘Moneyness’ In Active Managers
Tobias: You’re not implementing these strategies yourself. You’re doing this through managers. Mutiny Fund is a fund of funds. Is that fair description?
Taylor: Yeah. I think that’s accurate.
Tobias: How do you validate the managers? How do you make sure that the portfolio as you think about it is properly diversified across strategies? What’s the process there?
Jason: We think about it in multiple ways. The way we wanted to build this portfolio– because like we said, it was Taylor and I scratching our own itch and so it was our own money going into this. So, we had to figure out what we wanted. Part of that is the path dependencies. But at the end of the day, we wanted to have a portfolio that was buying as many options as possible. As Nancy Davis calls it, “It’s debit card investing.” You know what your downside risk is, you don’t have a blow-up risk, you can bleed to death from thousand paper cuts, but you know that what exactly what’s there. You don’t know what your upside potential is with buying options and that’s difficult for most people. But we structured the portfolio primarily just around buying options, because we knew exactly what that P&L would look like.
Now, part of that what we referenced earlier is, you can have bleed in a risk-on cycle. You don’t know how much or where it’s necessarily going to come from, but you want to limit that bleed as much as possible. We use very active managers, whether it’s Logica or Artemis or Headwaters that are trying to almost time that market position or load up or delever on inventory or gamma scalp if it’s Logica.
But basically, if we can create an ensemble of active managers in the buying options positions, we look for primarily moneyness. So, when we’re looking across those, we look at like– Logica is at the money straddles, so that covers at the money position. Primarily, they’re going to do great maybe on a negative 5% to negative 20% move because they have to pay for the offsetting position premia, so you’re not going to get it right at the money, but it starts to cover those smaller or closer to the money moves. We start to get out of the money, we’re looking at like an Artemis strangle that’s out of the money.
You’re going to get more exclusivity, but you have to have– that path dependencies needs to tick down far enough for that to really kick in. Headwaters, Matt Rowe does much more opportunistic trading kind of around positions where he’s looking for cheap convexity. But we’re trying to primarily create the options but get around the moneyness of the managers. So that’s how we look at those manager positions and position sizing, is the probability of that path dependency, combined with the moneyness of that path dependency, and we try to overlay those or overlap those so we capture as much of the meat of the move as possible during a risk-off.
Tobias: I was just going to say that makes total sense.
Jason: Okay, well, good. That sounds– [crosstalk]
Tobias: Smaller move is going to be Logica. A bigger move is going to be Cole. They’re less likely to happen, so Cole is going to be sized slightly smaller than Logica. And then, you’ve got the bread and butter, day to day is Headwaters. Is that fair?
Jason: Yeah. Another way to look at it– and then we also look at adding managers that may take some basis risk after a selloff like Diego Perea Quadriga that’s maybe trading correlation trades or FX. We look at those two, and we track those and we may be adding those in the near future. But the other way to look at it, too, is if you’re critical of Artemis, and you’re maybe in the market only 40%, 70% of time trying to limit that bleed, Taylor and I worry about what happens if you have an exogenous event on a Saturday or Sunday and our managers aren’t fully positioned. Logica will still be in there, but they may have a little less inventory of puts than they normally have. But we really worry about that sleep at night of our portfolio.
So, we added back in those deterministic rolling puts, and we use Hare Krishna on to manage those. And so that way, if there was some sort of exogenous event when markets aren’t open, we always have those puts on. And so, part of always having those puts on, that’s why I say deterministic because we know exactly what the bleed is going to be from those puts.
But we view through taking this ensemble approach to long volatility and tail risk, we can cover that bleed, so we’re happy to have it and be safe at night. So, the way we look at covering the bleed of buying options, is we added these periphery buckets with VIX arbitrage and short-term futures. And by having these three different market structures of VIX, options, and futures, and then an ensemble of managers inside of each of those buckets, there’s a lot of dispersion of their returns that we can harvest a rebalancing premium between them and we try to use that overarching ensemble or mosaic approach to try to have a flat, slightly positive carry over entire risk-on cycle, while we’re waiting for that risk-off event to happen. But we’re sitting on a massive inventory of options when that risk-off happens, so we have that huge convexity to the down move.
Taylor: I think at a high level, the way we typically talk about is like, carry certainty and convexity, that’s the tradeoff space that we’re dealing with it. The idea also of long volatility, tail risk hedge, you want to have high certainty, you’re capturing it. You want to have flat to slightly positive carry would be ideal, and you want to have a lot of convexity in the case that risk-off event. So, as Jason was saying, that ensemble approach helps us on all those layers.
You have the individual managers that are trying to trade off that carry convexity. You’re just rolling puts. You know you’re going to have convexity, but it’s going to really hurt your carry. So, having lots of different managers that are doing some form of market timing, and then combining them all together, we get the same benefits of that carry convexity that they’re doing, but then also adding that certainty back in possibly to just having the rolling puts but then by having nine different managers, if two miss it, that’s fine. We’re able to increase our certainty there.
Tobias: Yeah, that makes an abundance of sense to me. If folks want to get in touch with you or follow along with what you’re doing, how do they go about doing that?
Taylor: So, mutinyfund.com is the website. We have a newsletter that we send out a couple times a month, just with updates. And then, Twitter is probably the best place Jason and I are both active. So, Jason is– his handle’s @JasonMutiny. And mine is @TaylorPearsonMe. That’s probably the best way.
Tobias: I should have asked earlier, but why Mutiny Fund? Why Mutiny? It’s a great name. I love it.
Jason: I was going to say, as you know, Toby, part of the function is, every name is taken. As you know, you try a couple of business names, you’re like “This is a great one.” Then, you google search it and everything’s taken. But it was a combination of factors. One, we had all these highfaluting names like Ataraxia, which was Greek for unperturbed by external events. And luckily, Taylor’s wife and my girlfriend were like, “No.”
Tobias: Too hot. Yeah.
Jason: Yeah, exactly, all that stuff. So, I always had this idea of Mutiny in the back of our heads, because from multiple perspectives– It comes actually– one of them’s from Hugh Hendry. He was always talking about Crispin Odey of the 70s and 80s swashbuckling CTAs that were running like 40 vol, and it’s like, “Where have all those pirates gone?” So, we were thinking about that the back of our minds. But also, there was a Mutiny Club in the 70s in Miami in Coconut Grove. It was like this meeting place for eccentrics. So, you’d have spies from Europe, South American industrialist, and then like the whole Cocaine Cowboys trade. Not only it was a nightclub and hotel, and it was like every room was different. It was just this amazing place. And so, outside the drug part is like, we look at it like a meeting of the minds of eccentrics and trying to bring together all these different worlds. And then, we just love the idea of, from a marketing perspective, what mutiny gives us. We know we’re different. We’re outsiders anyway. So, instead of pretending like we’re not outsiders, we just play into it, I guess, a little more than other people would.
Tobias: Yeah, that’s great. I’m really envious. That’s a great name.[laughter]
Tobias: Thanks very much, gents. That’s all I have time for.
Taylor: Cheers, Toby.
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