Why Capital Efficiency Is the Next Edge in Investing ft. Charlie McGarraugh

[00:00:01] Charlie

And so the difference between somebody who can live with a 10 point drawdown versus somebody who can live with a 20 point drawdown is not like 10% more, it’s like way bigger than that depending on your time horizon. There are all these arbitrage alphas in the world and people get spent a lot of time thinking about predicting returns on the basis of those things. But the sizing is just such an important piece of the puzzle and thinking more about that, I think it’s just a place that we’re spending a lot of time thinking about and working on.

[00:00:30] Intro

Welcome to Top Traders Unplugged. In markets success doesn’t come from predicting what happens next, it comes from being prepared for what you can’t predict.

In each episode we go deep with some of the world’s most thoughtful minds in investing, economics, and beyond to understand how they think, how they prepare, and how they decide, and the experiences that shaped how they see the world. No noise, no short-cuts, just real conversations to help you think better and invest with confidence.

[00:01:03] Moritz

Hello and welcome to another episode of the Open Interest series on Top Traders Unplugged. This is episode number 23 and I’m your host, Moritz Seibert. I’m joined today by Charlie McGarraugh, the CEO of Altis Partners. Altis Partners was founded in 2000 as a trend following CTA business and has since evolved into a macro focused trading firm with a focus on combining factors such as trend carry and reversion all into a single portfolio. Additionally, Altis functions as the sub advisor to two US domiciled ETFs that are managed by Simplify and this is now by far the largest part of the business, at least in terms of AUM.

Charlie looks back on a long career at Goldman Sachs, including metals trading and then got involved in a sports betting business, which I personally find very interesting. We’ll get into that a little bit later, I guess. And that one got sold to blockchain.com. Following this, Charlie acquired Altis Partners.

So, Charlie, let me stop there because you can add much more detail and background and make it more interesting. Let me say welcome to Open Interest on Top Traders Unplugged. And I hope we’ll have a very interesting and cool conversation.

[00:02:09] Charlie

Awesome. Well, thanks Moritz.

[00:02:10] Moritz

Excellent look. I mean I gave a little bit of an intro. You have a… my understanding is you have a long career at Goldman. You were a partner at Goldman Sachs, working in the US, working in London. You are from the US but you moved over to London, then started trading metals. Give us a little bit of background on Charlie, yourself, and the sports betting piece and how you came to acquire Altis.

[00:02:38] Charlie

Sure. I’ll try to keep it pretty brief because the markets and the products and the strategies are the interesting part. And me, I’m boring. And boring is good in asset management. At least that’s what we hope.

So, I joined Goldman Sachs right out of undergrad. I majored in math and econ, did pretty well. I’ve worked on a number of different desks including emerging markets, and mortgage trading, and, ultimately, the commodity business. I started in New York and one day they said you’re moving to London. And I thought that would be pretty fun and interesting adventure. And it was.

We traded mortgages throughout the post-crisis world where there was a lot of distress in Europe. And eventually, again, as happens in these big firms, one day it was sort of made clear to me that management wanted me to move to the metals desk. This was 2014. And I did.

It took quite a while to adjust to a trading environment in listed futures where the product is relatively simple but the market structure is extraordinarily complex. Very different than asset backed securities and structured finance where it’s pretty easy to understand who’s buying and selling stuff. It’s a relatively specialized product but the products themselves are complicated. So, it’s a very different beast in the dynamic world of liquid macro. And that took a little bit of learning.

Now, I realized that this is now the mid-2010s, the markets already had significantly electronified, and that if I was going to be good at this new thing it wasn’t enough to understand sort of just valuation. I really had to have a better understanding of the dynamics of the market. And the old model where it was kind of voice trading, and a big salesforce making phone calls, was not enough really to understand, particularly in a market that had asymmetric information flows like physical commodities often do.

At that time China was dominating the base metal flow, and it was very difficult to get a sense, as a Westerner sitting in London, of what was really going on the ground there driving base metals. So, it took a little while to adjust. And I kind of arrived at the conclusion that I really wanted to have computers help me trade and that a data driven approach might be the better way to do it.

Now, I had backed the sports betting business, there, a few years prior to my departure from Goldman, and this is now 2016. I decided to leave Goldman and work on that under the basic theory that sports are interesting and they lend themselves well to statistical analysis. This will be a good way to get an education in this new toolkit called machine learning and AI. Like many things in my life, early is the same thing as wrong. I was a little early on that one perhaps, but it was good to get the education. And the sports betting business was difficult business because the barrier to entry is very low and because of the seasonality of kind of the entropy in the business, the seasons start and then you learn more about the players. But it just didn’t really capture, I guess, my heart or my desire for scalability in the same way. Now I know there are people who do exceptionally well at it, but I decided by about 2018 it was time to pivot to crypto.

Crypto had been incredibly interesting. Crypto had this really interesting property that the deeper you looked at it, the more there was and yeah, so I sold the business to blockchain.com in 2018, and joined there, and started working on institutional trading with the team there.

[00:06:45] Moritz

Was it still a sports betting business that you sold to Blockchain or was it a crypto business?

[00:06:49] Charlie

No, I mean it was more of an aqua hire. It was sort of like we’re going to pivot it from sports betting to crypto. We had pretty good software engineering capability, a good concept of trading, and let’s just change it up to something that we think can scale and is maybe more dynamic. Now, I know people have done really well on sports betting, and now prediction markets are all the thing. So, I guess everything moves in cycles, but at the time it felt like the right move.

Yeah, so, I was watching Stephen Hedgecock, who is Altis’s CEO. I’m actually the CIO of Altis. Stephen Hedgecock had been a board member of the betting company. And he called me and let me know that his partner, who had founded Altis, had died in an avalanche while skiing in 2019. And Stephen was saying to me, we have a lot of IP in this business. It’s a pretty interesting business. Do you want to have a look? And so, I started looking at it in late 2019 and by 2020 I acquired a stake in it.

The theory at the time being that the math of how do you trade leverage stuff competently is directly applicable to crypto just as much as in futures, which I think it probably still is. So, we thought maybe we’d build an asset manager using Altis’s IP in a JD blockchain.

But in any case, I acquired the stake in Altis in March of 2020, right as COVID hit, and then started work with the team on a carve out of my time, working on the systems and then ultimately ended up moving to Altis full time in ‘22 as the crypto markets were pretty bumpy and I felt like a pivot to re-materialization, re-industrialization, and TradFi was going to be a thing, and that macro volatility was going to start to pick up again, which it clearly has. So, that’s the story of the long journey into Altis. But basically, I bought a stake in Altis. Altis had been founded in 2000 as a trend follower with some…

[00:09:03] Moritz

Yeah, tell us a bit about the history. You started, so more than a quarter of a century ago that was obviously not with you. You were maybe still in college, maybe. You were already at Goldman, but it wasn’t with you.

[00:09:17] Charlie

Yeah, Altis was founded the same year I joined Goldman, and Stephen Hedgecock, and Natasha Reeve Gray, and Alex Brunwin, and Zbish Hermaszewski were the four founding partners. Natasha moved on sometime later and then Zbish tragically died in 2019. But back in 2000, they… It was kind of the heyday of CTAs, and they built the business up over the course of that decade for 2000-2009, let’s say. And it was really focused on trend following with a couple of alternative indicators in there, but really a tape reader, basically, with some pretty good IP around portfolio construction that, to this day, I think is fit for purpose.

And then the business grew and grew over the 2000s. And then, as you will have undoubtedly discussed on previous episodes, trend following was terrible in the 2010s. The amount of liquidity provided to the government to the market via QE and the volatility suppression. You basically had a governmental complex globally saying here’s giant piles of low velocity free money and the job is to suppress volatility. And that was just kind of inimical to the returns of the trend factor. So, Altis had a tough run of performance in the 2010s. It took them a little while to kind of figure this out.

By the mid 2010s they were pretty aggressively refactoring the system and thinking through how to be a bit more multidimensional in terms of the risk premia that they were attempting to access, and more advances on risk management and portfolio construction, and then they did pretty well.

But then Zbish died in 2019 while skiing and so that kind of put the kibosh on that part of the firm’s journey. And then I sort of showed up in the picture and bought the CIO stake.

[00:11:19] Moritz

So back then, I think you’ve just mentioned, it was focused on trend following with some advanced techniques around portfolio construction. And then, I think after you’ve joined, you introduced a new program, a new trading strategy, which I think is the enhanced macro programmer, if I’m not mistaken, that’s the name. So, is this still anchored in systematic time series momentum or trend following or is it now more of a combination…

[00:11:48] Charlie

It absolutely is.

[00:11:49] Moritz

Of all sorts of different things like a multi strat quant type of program?

[00:11:54] Charlie

It’s a bit of both. I’d say it’s an evolution of the long-standing trend program that had existed at Altis called Global Futures Portfolio. So, it was an addition of additional factor return prediction systems inside the context of a similar portfolio construction IP layer.

So yes, it is very much a sister or sibling product to the product that has always been Altis, which is fundamentally a trend CTA, but it attempts to address that problem, which I think is familiar to any kind of CTA and systematic trader which is trend following is great. It’s got scale, it’s got anti correlation to global growth beta, typically, in crisis alpha, but it’s also episodic in its returns and it’s a bit difficult to stick with. It’s kind of like eating your vegetables. Like, you know it’s good for you, but it doesn’t always taste great.

And so, like many people in this space, we’re sort of thinking about like, do we want to break out of that kind of intellectual rut of pure trend plus nothing else kind of thing and start thinking about blending other types of risk premia into the system? The IP is quite fungible. If you’ve got decent predictors for the variants that you might see in the market then you might try to access them in some way.

So, I kind of look at it, it’s like a game. It’s like every day there’s this massive cross section of movement that happens across all these things that you could trade and mostly the market is noise. So, it’s sort of well documented that momentum maybe has some (you should pardon the pun) persistent ability to explain some of that cross section of that noise, or that movement which is mostly noise. But could there be other sort of known things in there? So, that was one thing.

And if you got decent predictions, then it’s easy enough to start thinking about risk managing around them and sizing them up and blending them into the optimizer. And so that’s really kind of the approach we’ve taken, which is like, hey, there’s nothing really new under the sun. It’s sort of like positioning momentum and value. And we want to start to do more than just deliver the unadulterated momentum because we think ultimately what clients want is returns, and anti-correlation, and capital efficiency. So, I’m just trying to get in there and predict more, basically, without overfitting.

[00:14:47] Moritz

How many markets do you guys trade in that program?

[00:14:52] Charlie

Yeah, we’re trading something like 150 ish markets across many, many regulated exchanges all over the world.

[00:15:01] Moritz

And that includes, and maybe there’s this, I was asking this maybe out of schedule because it will lead to a question that I will later have related to the ETFs that you’re sub advising on. So, in that futures portfolio you’re trading, all the markets, equities, FX, bonds, commodities, everything across the board.

[00:15:19] Charlie

Equity index, fixed income, STIR, FX, commodities, yeah, independent bet count like so many others in the space.

[00:15:30] Moritz

Yes. Okay, got it. So, this is then probably a differentiator to the performance in one of the ETFs or in both of the ETFs that you sub advise on. Because these ETFs are not allocating their risk across all of these markets that you’ve just mentioned, but only to a subsection of them.

[00:15:51] Charlie

But yeah, I would say without getting too deep into any specific product. The investable universe that one selects can vary across products for sure.

[00:16:02] Moritz

Yes, yes. Before we go into this more from a holistic perspective, when you look at our industry, the CTA trend following hedge fund industry, if you will, what would you say are the most important themes these days? What is changing? What is strategically important? What’s happening right now that kind of like gets your attention?

[00:16:27] Charlie

It’s a great question and there’s a lot happening in the market. Right? And I think the structure of the business and the curation of the product set is as interesting as I guess, the underlying trading systems themselves. So, if you think of kind of like a design space of what kinds of investment strategies could a person build or invest in, it’s like the thing I like to think about the most is reactiveness to new information.

There’s an entire school of thought out there, passive acolytes who are like, hey, anything you learn, the market’s so smart that anything you learn has no value. You should not attempt to react to information because if you do, you’ll only hurt yourself. Right? And so like, that would be like one extreme view, which is like the change in my behavior relative to a change in new information is zero. And that’s basically like dollar cost averaging passive. And amazingly, something like 60% of the market is on that theory of the case.

At the other end of the design spectrum is sort of how much will I react to information? I’ll react a lot. Every time anything changes, I’ll just redo my whole book. And we know that if you’re that reactive, you’re probably going to bleed out on transaction costs, and pay too many commissions, and slippage. You’re also probably going to overreact and, if you’re using computers to do it, overfit. Right? So, I guess my view is like, there’s probably a happy middle.

And interestingly enough, there’s not that many people in that happy middle. So, CTA and futures trading are really interesting because futures are great for reacting to changing information because they’re really efficient way to move a lot of risk around. And they’re not just efficient from a sort of transaction cost and transparency perspective, but they’re also efficient from a capital efficiency and leverage perspective.

It’s kind of like the only way that normal people can get access to borrowing as cheap as like a bank can, just synthetically, by virtue of the way the futures are set up, you’re basically getting access to institutional funding, market funding.

And that’s like, that’s pretty great. Most normal retail people, even trading a merger account, it’s like pretty expensive to get access to leverage. So, I think that historically, maybe the CTA industry hasn’t called out the value of that dynamic leverage enough or the value of that capital efficiency enough.

You’re starting to see a focus on things like return stacking and portable alpha. But the direction of travel for me, that I think is most interesting is this question of capital efficiency. It’s like capital efficiency combined with dynamism and reactivity. It seems pretty dumb to just be like, my view will never change no matter what information I’m learning, yet that’s 60% of the flows in the market. It’s like passive financial assets. And under that theory you’d be buying bonds with a negative yield. Right?

Also, it’s like obviously terrible to just trade way too much and die of transaction cost and overfit. Right? So, that middle case of sort of what’s the optimal amount of reaction to changing information? It seems like it should be related to whatever the cost of changing your mind actually is.

And so, from that perspective, I think there’s a story to tell about how much adaptiveness is the right amount of adaptiveness and how much should I be willing to pay transaction costs for the ability to adapt? And what I would kind of offer out there for people is this world seems like it’s changing a lot faster than it did during the QE era.

So, wherever you were in that design spectrum before between, I never changed my mind at all, and I changed my mind too much. You’re moving more, now, over the last five years, in the direction of, I want to adapt more and be more adaptive because the amount of fundamental volatility in the world is just picking up.

You’ve got geopolitical stuff, crucially, versus pre COVID and really, before the election of Trump one and Brexit, the government was in the business of volatility suppression, just globally. And now the government’s in the business of volatility inducement. Right? Starting wars, trade policy, tariff, you name it. They’re in there and they’re stirring the pot. And that means you need to change your mind because the fundamental conditions that you’re operating under are meaningfully changing.

And so, my view is adaptive, is interesting. And there’s no place more efficient to be adaptive in all kinds of things that matter than the futures markets. And for that reason there’s this sort of latent demand, that people don’t even know they have yet, for adaptive investment product because the world’s moving faster than ever before.

And yeah, and so, when I think about the structure of the market, it’s like how can that value prop be delivered to which segments of the potential total addressable market? And it’s not just high net worth individuals or family offices or institutions who buy high fee hedge fund product, although that is an important part of the business. There’s also opportunity in other distribution channels for various flavors of adaptive and efficient, basically.

[00:21:49] Moritz

Gotcha. What I’d like to understand a little bit better is how it came about or how it happened. What triggered your involvement as a sub advisor to the ETF space because you started in 2000, or Altis started in 2000 as a CTA, like many others, offering their products I guess to private investors, high net worth individuals, and so on, and so forth, in a private fund or in SMAs segregated managed accounts. And now most of your AUM are in ETFs you’re sub advising on with Simplify in the US.

So, how did this happen? Was this an intentional change to say okay, we’re going to go down the ETF route because this is where the money’s going to be, this is the fastest growing part of the market, or was it more like happenstance, you ran into the right people at the right point in time and it happened that way?

[00:22:43] Charlie

Yeah, I mean it’s kind of a little both. So, they say luck is a combination of sort of preparation and I guess something else, I don’t even know what they say, but basically there was an element of luck to it. I ran into Mike Green at a macro conference at Bretton Woods in summer of ‘21 and Mike had been a client of mine at Goldman long ago and a good friend as a fellow student in the market.

And we got to talking and he was like oh, I’ve joined this new active ETF firm and I’d really like to build a bunch of cool things and one of the things I’d like to build is a managed futures ETF. And I was like, well, funnily enough, Mike, I just bought like a futures platform kind of like serendipitously and I think it’s got pretty good IP in it, so maybe we should collaborate.

And we did and then six months later we were launching product on the stock exchange, so that said I was pretty open minded about it, and that was the preparation side which is, I had worked in fintech with direct-to-consumer stuff in crypto. I think I understood pretty well at that point (after having been in the tech industry for a good, I don’t know what is it, six years after leaving Goldman) about how platforms can scale and what the unit economics can look like when you’re building a scalable direct distribution business that is powered by the leverage of software.

And I felt like I was not as precious about only having a single distribution channel. I just sort of felt like the firm has just one product which is trading IP, and there are lots of different means of packaging that IP, and not all packagings are created equal. Like some packagings lend themselves better to scale but are a little bit lower resolution. And then other packagings can get to a much more granular trading approach and are more suitable for complexity. And broadly defined, I’d say that it would be like mass market listed product versus hedge funds. Like there are just things you can do inside a hedge fund or an SMA that you just can’t do inside an ETF.

But ETFs have this incredibly low client acquisition friction and they scale.
And so, if it’s a scalable risk premia that you think can add value to the client base and it’s comprehensible, then I think an ETF is a great package for it.

[00:25:27] Moritz

So, in 2021, when you ran into Mike at Bretton Woods and you started to think about collaborating on an ETF project, how did you go about designing that ETF?

[00:25:43] Charlie

Right. So here I’m going to…

[00:25:44] Moritz

Because at the time is you already had replicating ETFs out there. And so, that would have been an option, but I think you decided against that.

[00:25:53] Charlie

Yeah, it’s a great question. I think this is like where the experience on the tech side really is relevant. In the financial industry we sort of talk about the word PM, and it means something very specific. It means portfolio manager. But all these crazy tech people running around, they also use the word PM, and it means product manager.

Being a product manager I think is equally or even more important than being, I mean… The asset side is always important. It’s a returns-based business. Being a portfolio manager is always important, and managing risk is always important. Right? Obviously, no doubt.

But the liability side of the business, which is how do we build a product that potentially services a need in a particular segment of the total addressable market? I think is also a really interesting question. And so, without getting too heavy into the specifics of any one ticker, again, there’s a spectrum of design choices that you can kind of think about.

One of them that I think is really important is if you’re going to build a liquid alternative product, is it designed to be an uncorrelated absolute return stream or is it designed to be a statistical hedge of some kind or even a contractual hedge? So defined outcome, versus statistical outcome, versus and hedge versus just uncorrelated returns. Those are all different choices that you can make on the menu and turn the knobs in terms of product design accordingly.

And one of the things that tech people will say is like, you’re always trying to think of like jobs to be done, like what is the job that needs to be fulfilled by a particular product? And then, so, it’s sort of like you have the technology at the center, then you have the product that you’ve built to hopefully solve an actual problem from the client’s perspective. Then you have a go-to-market strategy, and then you have a business built around the go-to-market strategy.

And so, for us it was a case of like, if we’re going to try to build things that are number one, capital efficient, and number two, really pull out the diversification side of the puzzle, obviously you want more return, more diversification and more hedge like properties. Those are all good things. But everything comes in a package of tradeoffs. And it’s like, how do you think through that?

So, there was a long conversation between my team and Mike’s team around some of the choices that we could make. And that involved curating the investable universe and thinking about the different types of alphas and risk management methodologies that could be on offer there.

So, that’s kind of one thing. And then I think you asked something about replication versus our internal stuff.

[00:28:41] Moritz

Yeah. Because you run your own system, your own signals.

[00:28:47] Charlie

Yeah. I mean look, the cool thing about software is it scales. Right? Once you build it, its marginal cost of deployment is relatively low, its opportunity cost, if it’s a capacity constraint strategy, its opportunity cost of deployment may be very high. But if it’s a scalable thing that can be delivered with software, I guess my view was eventually somebody else will deliver it if they’re any good, so we might as well. Right?

Again, the firm has one product that’s trading IP and our goal is to try to put as much value down every distribution pipe as the pipe can handle. Right? From the packaging of those, sort of daily rebalance ETF only allows for certain types of things, but again maximum value for the package and then just try to create value for clients.

And so, I wasn’t very precious about it. And maybe also my background as sort of an outsider to the system. I’ve trained, I’d grown up on the sell side. I’d grown up cat hole structure and derivatives valuation stuff, not really time series optimization stuff. I think it just made me a little bit more of an outsider. And it was like, oh well, we have this IP, we might as well deploy it in new and interesting ways. And so, we did.

[00:30:01] Moritz

Give us a little bit more background. I mean the first ETF you started incorporation with, Simplify. I think you’re only referencing the commodity markets and the fixed income markets if I’m not mistaken. So, you’re missing currencies and you’re missing equities. What were the driving factors for that decision? Because these are important markets, they are liquid markets, they scale they have momentum. But you razed them from the portfolio.

[00:30:30] Charlie

Yeah, I mean again it’s a tradeoff between correlation to global beta and returns. It starts with a perspective of where can I add value incrementally to the client? Right? If the client is an advisor who’s already got clients on their side who are chock-to-the-gills full of financial assets, then just stacking more equity beta in there, even if it has a positive return associated with it, may not be the way to really give them a distilled value proposition versus other stuff. You want to differentiate and basically be like, here we are. And so, for some of the products it’s like basically capital efficient diversification is sort of what you’re calling out.

Now, I think it’s a challenge in the market, and this is true actually on the institutional side too, not just in the sort of mass market channel, which is that no matter how much people talk about the value of alpha, and the value of anti-correlation, and the value of non-recourse leverage, at the end of the day they also want to see absolute returns. It just makes every conversation less complicated.

And even if you’re working with an incredibly sophisticated advisor or capital allocator as your client, they will invariably have some committee or third parties that they have to explain the complexity to. And so, everything is just defricationalized to the extent it’s got a nice return on it. And that’s why I think a lot of kind of bundled products that just have a lot of equity beta in them tend to be attractive for business builders in the liquid space. Because it’s just like, okay, well, you’re kind of playing the game on easy mode in terms of putting up returns.

And that said, my view is that, in the future, more and more of the portfolio construction process is going to be carried out by machines that are looking for mean variance, optimization of variance flavors. And trustworthy brands will matter and headline returns will matter, but also the covariance properties of your product will matter a lot. And probably, increasingly on the margin.

And what’s really cool about this sort of active strategy space is that unlike passive ETFs, which are just a race to the bottom on fees and just a pure economy of scale game, you can actually differentiate a lot as an active manager as a small guy. Right? Because there’s a huge amount of choices to make in the design space of types of stuff to build and what its value prop might be.

My theory is recommendation engines and recommendation systems are likely to become more important. Agentic allocation is likely to become more important. And in that world the numbers will speak. And people care about the numbers that will matter which are liquidity, length of track, correlation to other assets in the portfolio, and the higher moments of the covariance properties just sort of generally out there, and liquidity. And so, yeah, we’re just trying to build for that.

And you can do that in different ways. You can do it by curating the investable universe, you can do it by curating the signals, and you can do it by curating the portfolio construction methodologies. I’m sure there’s other ways too.

[00:34:02] Moritz

Or all three of them at the same time.

[00:34:04] Charlie

Yeah, or other stuff we haven’t even thought of. Right? But there’s always more to do.

But anyway, that’s how I think about it. And I think, when you think, just again, to make a kind of a comment about the business on the distribution side, when you think about like those advisors, I would recommend anybody who’s kind of interested in this scalable distribution stuff, go spend some time with some advisors on either side of the pond because what you’ll hear, when you actually start talking about what’s valuable for them and what’s valuable to their clients, it’s like half the job of the advisor is psychotherapist because no matter how well off you are, money makes you anxious because the cost of screwing up is really high.

And so, a big piece of what the advisor does is this relationship management which is designed to assuage anxiety and that’s really good thing because people need it. But another piece of the job, I’d say probably 30%, is tax and estate planning. It’s just being efficient, making sure you’ve done things the right way and have thought about stuff. Everybody’s situation is unique. It’s complicated. Right?

And then there’s 20% which is actual like investment selection and portfolio construction and allocation. And that last 20% is getting more and more mediated by software. So, it’s kind of like SEO. It’s like you want to build products that can get picked up by whatever those software systems are if you want to scale, at least in that distribution channel. And so, that’s kind of how we think about it.

[00:35:38] Moritz

Oh, and you did scale with that ETF, I think it’s fair to say. More recently, I think Charlie, it was earlier this year, you started self-advising on another, I think the second ETF together with Simplify that has a specific focus on Chinese onshore commodities. Speak a little about that, like what makes these markets interesting? That would be my first question.

And the second question I would have is, why a pure Chinese commodities focus? Why not, again, a more diverse mix that includes maybe other commodities or then currencies or then equities in addition to these, presumed, very diversifying Chinese onshore commodities. Why this pure play? Because to me it sounds like a little bit limiting, but I might be wrong. So, I’d like to hear your opinion on this.

[00:36:34] Charlie

Yeah, so I think I’ll start with, again, without going too deep on any one product, I’ll speak in generalities first about Chinese commodity derivatives.

So, the Chinese futures markets are, they’re very large. They trade a lot of volume. The contract sizes are small, but a lot of volume goes through. And that’s interesting. And China is something… Yeah, these numbers change through time. But let’s say it’s order of magnitude a third to half of the just overall molecular and energetic flows of the human economy on planet Earth. It’s not small and it is interesting and it’s also heavily policy driven.

And because the systems between the West and the East are financially not that interlinked, although physically highly interlinked, there’s a chance for some segmentation in the market to create some independent bet to make. And that’s interesting. I think there’s a strong argument to be made that there’s real diversification benefit in some of this stuff.

The second thing is, I think historically, the market structure in China was just completely different than the market structure in the West. And as a result different types of risk premia pertain, like in particular short-term momentum seem to work better in China than it did in Western markets. People love short-term momentum when it works because it’s like a high book turnover, the number of bets is high, which directly translates, if you have a positive edge, to a decent ROE that’s not very capital intensive. And of course, longer wavelength risk premia require longer commitment to capital, and therefore are more capital intensive. So that’s desirable.

Now, some of our research suggests that the Chinese commodity markets momentum factor is extending in its duration and that might be a function of both the markets becoming more sophisticated and maybe incrementally a little bit more interlinked with the West. Although that second thing I think they’re likely to maintain sophistication and get more sophisticated. But their degree of interlinkage with the Western system I think could easily go backward, not just forward, as we’ve seen with some of the trade policy stuff in the last couple years.

And that’s another reason I think to possibly be in there, which is like if you get this rip deglobalization impulse in the system, you might see pretty heavy divergence between onshore and offshore markets and, again, get some independent bets to make which is never a bad thing in the context of an active trading book.

So that’s the first, I guess the first question which is they’re interesting, they’re different and they’re active in their scale there. Now, why do it as a single isolated product? That is more about a client side perspective of user choice. It’s like here it is. Right? It’s not the easiest thing to have on. It’s expensive to access it. Generally speaking there’s some structure in the market. In order to navigate the complexity of cross border financial arrangements you typically have to trade these things via swaps with other dealers and stuff. And none of that is frictionless.

So, we wanted to basically pull that out and basically be like if you want a concentrated ability to kind of dial your own exposure in it, then here it is.

And, again, it’s like what does software do? Software unbundles and rebundles, and in this instance, because it’s sufficiently out there offering for Western allocators of any flavor to decide to allocate to, we wanted to pull it out as a sort of standalone, as a standalone thing to give people that choice of unbundling it from a product perspective.

[00:40:26] Moritz

Is this one a pure time series momentum trend following model or does it also have other factors and flavors on top of classic systematic trends?

[00:40:41] Charlie

It has some relative value stuff on top of the trend factor.

[00:40:48] Moritz

Cool, Charlie, well, before we close it down, anything new, any new initiatives, new ideas, stuff that you’re working on, maybe you cannot share it, but things that keep you excited at the moment?

[00:41:00] Charlie

Yeah, I am, again, just obsessed with this concept of capital efficiency and leverage. I think the market just does… The average advisor and the average retail person in the market generally thinks of leverage as like the 3X Levered MicroStrategy or Tesla. It’s like gambling product that is sentenced to death by volatility drag, basically.

But capital efficiency is something that everybody likes and I’m really interested in sort of packaging that capital efficiency and getting more focused on CAGR for people and sort of like, where’s that efficient frontier sort of prudent leverage management? I think most systematic traders, when they’re packaging up client strategies for clients, at least sort of fungibly leverageable strategies like you can in futures by changing the margin equity dynamics, they are sort of saying like, hey, what margin equity should I run this thing at? It’s a question of my own risk appetite. And that’s fine. And that makes sense. Totally makes sense.

But I think an interesting and related but different question is, how far could I push the envelope prudently in search of compounded returns? We all know that you can’t bet a hundred percent of Kelly because Kelly’s brittle. And if you have estimation error, you will hurt yourself. So, greater than Kelly for sure is bad. And then even at Kelly, full Kelly, it’s like, you better be really confident in your estimations of distributions.

[00:42:37] Moritz

Yeah. So just stepping in there… So, what you’re talking about is fractional Kelly bet sizing, and like the Kelly criterion, just for listeners who haven’t heard that term.

Yeah, go on. I mean, so you probably… But the issue in our business is we do not have defined odds. So, even coming up with a fractional Kelly is kind of like yeah, well, it’s not a precise exercise.

[00:43:03] Charlie

Not at all. And so it gets pretty philosophical pretty fast. But if the question you’re asking yourself is, for some pool of capital, how do I compound returns as solidly as I can while being indifferent to the risk? All I’m trying to do is prudently maximize my expected return, then how far can I push the envelope? And if you knew what the odds were, the optimal leverage, you have to be smaller than that.

But picking that fraction is really a game of estimation error and thinking about, how do we know what we know and how can we be humble about it while at the same time doing the fundamentally unhumble thing of really leaning into it? And I guess the observation I would put out there, which I think is really interesting, is that the incremental returns for being able to stomach a little bit more drawdown, when you start talking about compounding through time, is really, really big. And so, the difference between somebody who can live with a 10 point drawdown versus somebody who can live with a 20 point drawdown is not like 10% more. It’s way bigger than that, depending on your time horizon.

There are all these arbitrage alphas in the world and people spend a lot of time thinking about predicting returns on the basis of those things. But the sizing is just such an important piece of the puzzle and thinking more about that, I think it’s just the place that we’re spending a lot of time thinking about and working on.

[00:44:32] Moritz

That is an excellent wrap. Thank you. Charlie, thanks for joining me on the podcast today. It’s been great and I hope our listeners will find it interesting and informative as well.

A quick note to everyone. As usual, I’ll put the most important takeaways of my chat with Charlie into our show notes, and please remember that you’re always welcome to submit questions to us in case you have any. Our email address is info@toptradersunplugged.com. So, thanks for listening and until next time on Top Traders Unplugged.

[00:45:02] Ending

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