RSBT – Return Stacked™ Bonds & Managed Futures ETF
In this episode, Corey Hoffstein, CIO of Newfound Research, Rodrigo Gordillo, President of ReSolve Global* and Adam Butler, CIO of ReSolve Global, delve into the concept of return stacking and introduce the innovative RSBT Return Stacked™ Bonds & Managed Futures ETF.
This podcast is essential for investors, financial advisors, and anyone interested in learning more about return stacking, the RSBT ETF, and the potential benefits of combining bonds and managed futures for portfolio diversification and risk management. Don’t miss out on this insightful conversation to deepen your understanding of these innovative investment strategies and their potential impact on today’s complex financial markets.
They cover a wide range of topics, including:
- The motivation behind the return stacking concept and its relevance in today’s market environment
- The history of institutional leverage and diversification in retail portfolios
- The advantages of using return stacked strategies for portfolio construction and risk management
- The role of bonds and managed futures in building a robust, diversified investment portfolio
- The importance of low correlation between asset classes for effective diversification
- The mechanics of combining bond exposure with a managed futures overlay in the RSBT ETF, including the use of cash collateral and Treasury Futures
- The benefits of using ETFs as capital-efficient building blocks for return stacking
- The potential for a family of return stacked ETF products to address various investor needs and preferences
- The significance of managed futures as a “third leg of the stool” for managing inflation and mitigating market risks
- The challenges and opportunities related to implementing managed futures strategies and managing leverage in retail portfolios
- The goal of matching the RSBT ETF’s bond strategy to core US fixed income, such as the Bloomberg US Core Aggregate Bond Index, and adjusting duration accordingly
So we put this podcast together in hopes that we can address most of the high level concerns and opportunities that people are trying to explore in under an hour. So, maybe let’s just get started with an understanding of what motivated you, maybe, Rodrigo, to start thinking about this return stacking concept.
What was missing from the market in your opinion, and how does return stacking address it?
[00:01:04] Rodrigo Gordillo: Well, yeah, look, return stacking was simply a rebranding of an old idea. When the idea is something that institutions have been using for decades is, it’s adding multiple diversified return streams, but really going beyond the hundred dollars mark, and adding strategies that were layered on top using derivatives and leverage.
That’s been available in institutions, but it wasn’t available, or at least it was thought not to be available in retail, in the retail space for years. So in fact, Corey had been doing this for years. We’d been doing it, but not really talking about it. We started digging into other funds and ETFs that were using hidden leverage and not talking about it.
And it became clear that there were ways of providing institutional leverage and institutional diversification to the retail space if we were thoughtful about introducing it with new language and new approaches. And the biggest issue was, it was 2021. You are trying to educate advisors and investors on how to, how beneficial it is to allocate to things at zig when everything else is zagging.
So, alternative strategies, but it required them to make room in their very successful portfolio in order to add these alternative sleeves, which at the time in the previous five years hadn’t done much. Right? So it was a MakeSpace fire, your good returning strategies and bonds and equities and add this very poor returning alternative to the portfolio.
With the ability to stack derivatives on top and strategies on top, we were now able to say yes and provide a diversifier on top of the hundred dollars that one would invest in a strategy that added an extra layer of return. And remember back in 2021, we were looking at yields close to zero.
We were looking on the bond side and we were looking at valuations and equities that were much worse than they are today. And so people were struggling to find any sort of return, and they were moving away from their bonds towards equities to try to find it, are private equity, private real estate, more of the same things, things that would suffer in a period of high inflation or would suffer in a period of bear markets.
So that was our attempt to kind of bring a new way of doing portfolio construction for a space that didn’t know existed. And, and yes, a lot of these return stacked solutions were around but not visibly clear. And I think we ended up writing a paper, the three of us, talking about how using products available in the last couple of years, you could create something that was, you know, a little bit of equity, a little bit of bonds, and a little bit of alternatives, and providing that diversity without sacrificing the return of your core holdings.
I don’t know if anybody…
[00:04:09] Adam Butler: I think we’re all caught up. I think we’re all caught by surprise at just how popular this concept would be. I mean, it really did catch fire with, you know, thousands of downloads and hundreds of inquiries and, so, you know, it’s one thing to propose a concept and write a white paper. It’s a whole other thing to come up with a product to satisfy demand.
Corey, what led you to conclude that there was an opportunity for a family of return stacked ETFs.
[00:04:40] Corey Hoffstein: I know, it’s funny, Rodrigo mentioned that this is something that both of our firms have been doing for a long time. I was actually quoted back in an article in Barons back in 2017 saying, what’s next for ETFs? And I said, I think what’s next for ETFs are these capital efficient building blocks, combining betas with other betas or betas with alternative betas in a way that allow investors to perform return stacking, without having to manage the derivatives or leverage themselves. Right. And I think that’s a real key aspect of this. Most financial advisors or individual investors don’t want to have to manage that or don’t necessarily know how to manage that thoughtfully by packaging them up within mutual funds or ETFs.
It allows investors to access this very thoughtful way of introducing diversification into their portfolio without them having to do all the legwork, allowing an institutional manager to do the legwork. Fast forward a couple years, I think it really was Rodrigo’s rebranding of the idea of capital efficiency and portable alpha into this word return stacking that really made the concept click for a lot more people.
Sometimes it’s just reframing with the language that allows the concept to be understood. And once the concept was understood, it was very obvious to me that this could be the birth of a whole suite of products, a suite of building blocks that would allow people to thoughtfully combine stock and bond beta with alternative beta like commodities or managed futures trading, or systematic macro, or gold, or what have you, in a way that they could meet their portfolio design and introduce this diversification, while thoughtfully introducing the leverage they needed to hit their return targets.
And so it was really exciting to see the concept start to take off, and I think it was very obvious that product should follow on after that, to allow people to continue to implement this concept, however they want to in their portfolios.
[00:06:39] Adam Butler: Yeah. So the building block concept was, was really critical to the vision of this whole family. Right? So, why do you think the combination of bonds and managed futures trend following made sense as the first product in this suite?
[00:06:57] Corey Hoffstein: So for us, again, there’s the idea, the core idea over the long run is these are building blocks. There’s nothing special about the combination of bonds and managed futures. It could have just as easily been equity and managed futures. But for us, what we were looking to bring out the door first was what we think solved the immediate problem the market was facing.
Rodrigo mentioned that we initially wrote the paper in 2021, launched at fall 2021. I think 2022 proved the idea out when we talked about needing a third leg of the stool in a portfolio that could help manage inflation and using things like managed futures or systematic macro strategies to do that. So we knew the first product we wanted to bring to market was something that could be that third leg of the stool, uh, hence the managed futures component.
And I think the bond component allowed us to address the big problem that a lot of people were facing, which was when they tended to include managed futures in their portfolio, they were very often having to sell fixed income. So they might have their 60/40 and they might sell some of the bonds to buy managed futures.
Ultimately, what we’re trying to do with Return Stacked Bonds and Managed Futures ETF is allow them to keep that bond exposure that they were selling and then add the managed futures on top. So it was recognizing the pattern we saw, and the way people were implementing managed futures, as well as recognizing that we think today the need for managed futures is much higher than it’s been, in sort of the previous decade.
[00:08:29] Rodrigo Gordillo: Yeah, so let me add…
[00:08:30] Adam Butler: Yeah. Okay.
[00:08:31] Rodrigo Gordillo: Let me kind of show more of the reasons why managed futures was useful in that time. And I mean, we wrote about this in 2021, and it was just kind of fortuitous for managed futures in the way that it performedas expected, right? So what is Managed Futures Trend?
It is a long/short strategy that can find trends in commodities, equities, bonds, and currencies. So, when you can go long and short these things and you have exposure to an inflation sensitive asset or a series of inflation sensitive assets like commodities, then you have the opportunity to, or you, that type of strategy has the opportunity to really zig when equities and bonds are zagging.
Right. So, if I can show my screen here. Okay. I am sharing, so this is in the presentation on the Return Stack ETFs website. This particular slide just clearly visually shows the three equity lines, the US stocks, US bonds, and CTA Trend. And for those listening and not watching, what the story that it tells, is basically that they’re very independent.
The moving equity lines, they’re very, very different from each other. And if we look at just the CTA Trend, correlation to stocks and to bonds, you see that from 2000 to,when is this, and here to the end of 2022., What you find is that the SocGen CTA Trend, sorry, the SocGen Trend Index has a negative 0.07 correlation to US stocks over that period and a 0.097 correlation to US bonds, right?
This is what we all learn in first, in the first week of finance that we want, right? We want to add as many return streams that have a positive expected rate of return that are as lowly correlated to each other as we possibly can. And when you look around the landscape of alternative solutions, I think one of the attractive features of trend following habits to be that it’s broadly the lowest, one of the lowest correlated to equities and bonds. And that’s kind of the magic ingredient, right? So that’s why I think trend following was an attractive first launch at a time where we felt maybe inflation and possibly bear markets might be on the horizon.
[00:11:12] Adam Butler: Yeah, great color. So Corey, let’s drill down a little bit. So we wanted to combine bonds, a broad bond index with a trend following overlay. How exactly did we put the building blocks together within R SBT to achieve that objective?
[00:11:32] Corey Hoffstein: Yeah, so the core idea here is that for every dollar an investor allocates to the fund, what we really want to do is provide $1 of core bond exposure and $1 of managed futures, $1 of exposure to a managed future strategy. And so we actually, our two firms represent the sub-advisors of both those strategies.
My firm, Newfound Research is the sub-advisor to the bond strategy. ReSolve Asset Management Global is the sub-advisor to the managed futures strategy, and what we effectively do is we take that dollar and we invest a component of it in either treasuries or bond ETFs or bond treasury futures to get the bond allocation, to get that dollar notional of bond exposure. And then we have some cash that we use as collateral in margin for the managed futures trading program. So ultimately, the goal right, is again, for every dollar you give us, we’re trying to maintain that dollar of core bond beta while simultaneously stacking on top a dollar of exposure to the managed futures strategy.
[00:12:36] Rodrigo Gordillo: And what’s the goal for, in terms of when you, we talk about helping advisors swap their portfolios, in the bond side. What is the average duration that we’re aiming for here, given what the market currently uses?
[00:12:51] Corey Hoffstein: Yeah, so really what we’re trying to do on the bond strategy side is match core US fixed income as closely as we can. There’s gonna be some wiggle room there that’s necessary based on us keeping some cash collateral available for the managed futures program. But ultimately what we’re trying to do is get a return stream that looks similar to, say the Bloomberg US Core Aggregate Bond Index.
We’re not trying to do anything active around that within the bond strategy. It is really meant to be that core passive beta as much as we can get it to be, which means that the duration for us will actually move with that index. So right now, it’s a little bit north of a duration of six, that can go up and down.
We are not targeting a specific duration other than trying to have a return profile and a duration profile that is very similar, uh, to that core US fixed income benchmark.
[00:13:49] Adam Butler: So what actually goes into that core bond portfolio within RSBT?
[00:13:54] Corey Hoffstein: Yeah, so today if you were to allocate a dollar, what you would see in the holdings is, there’s about 50 cents of that goes into an ETF that captures core US fixed income. It is the iShares AGG ETF that we currently use, and then some of the cash that we, is held in T-bills and money market funds as collateral, is used as collateral to buy a ladder of Treasury Futures 2, 5, 10, and long bond treasury futures to fill out the rest of that notional exposure.
The reason we can’t allocate, say, a full dollar to bonds is because, again, we need that cash there to act as collateral and margin for the managed futures program. So when we sort of disintermediate all the positions from one another, what you would see on the bond side today is about 50 cents of a dollar in the AGG ETF and about 50 cents notional in the Treasury futures ladder to fill out the rest of that bond exposure.
[00:14:54] Adam Butler: Yeah, so you’ve got kind of half of the credit exposure that you would get from a broad exposure just to the AGG ETF, but you’ve got a very close replication of the treasury duration exposure that you would get within the AGG ETF.
[00:15:12] Corey Hoffstein: That’s correct. Yep.
[00:15:14] Adam Butler: The idea is to just track that benchmark as closely as possible.
[00:15:19] Corey Hoffstein: That is correct. Yeah. Again, the idea here is, there’s nothing meant to be particularly active on the bond side. We’re not trying to time duration, we’re not trying to pick individual securities. We’re simply trying to provide as close as we can that core bond beta while maintaining, the cash we need to make sure we can implement the futures program.
[00:15:43] Adam Butler: Yeah, which is a good segue to a discussion of the managed futures overlay, which of course, because we’re trading bonds and stocks and currencies and commodities, both long and short, the trend, the act of trend overlay may have an opportunity to adjust the duration or exposure to bonds alongside all of the other assets in the portfolio as a function of its normal course of trading.
So, Rodrigo, why don’t we transition to, dig into the objectives of the managed futures strategy and maybe the character that we were going for.
[00:16:19] Rodrigo Gordillo: Well, yeah, I think the, when we think about managed futures, this has been a pet peeve mine, right? Talking about language, how important it is. Managed futures can mean a lot of things. You’re managing futures. We decided to focus on Managed Futures Trend, specifically for the reasons that I addressed earlier, right?
It happens to be non-correlated. It has a, the idea being that if something has recently gone up, it’s likely to continue to go up for a short period of time. Something’s recently gone down, it’s likely to continue to go down for a short period of time. And we could source many academic papers on the behavioral side, explaining to us why trend and herding behavior exist.
Cascade effects, you know, anchoring and adjusting. All these are behavioral reasons why trend following is likely a real phenomenon that is going to continue to provide unique return streams that has positive expectancy, right? But as it does that, it’ll be structurally non-correlated by design.
Just from, just from the basics, if we were to articulate what it’s trying to do, you got a long bond portfolio in the ETF, or an advisor has a long equity portfolio, that’s all they can do is just be long. Those things, when things start going poorly and duration, for example, in bonds is a bad thing and you want to minimize your duration, this automatically is designed to take the other side. If there’s a negative trend in duration, then we’re gonna see the trend strategy go short trend, as described on the Coca-Cola ingredients. Right? Very, very simple. And if, if it’s time to actually double up on duration in, on the bond side, it’ll be able to double up on duration.
And that just, that applies to absolutely everything. Bear markets. If there’s a prolonged sustainable negative trend in equities, the trend of, approach is a very simple way to take the opposite side of that and protect. So structurally, we know that it is likely to continue to be structurally and non-correlated over long periods of time.
And, and this is conditional correlation over long periods of time. When it’s appropriate to be long with equities, it’ll be correlated to equities when it’s appropriate to be the opposite of that, it’ll be ne negatively correlated to equities. All in all, we get that average result that I showed earlier in the presentation.
And so once you have, with this type of alternative, and if we’re introducing a new concept to a return stacking into an audience that is fairly new to it, it seemed appropriate to offer the, kind of the easiest step forward. You know, people can understand something that goes up is likely to go up, something that goes down as likely to go down.
We can articulate easily why things are happening in the background. And for a product like an ETF that I think is gonna be likely to have a mass adoption, this is a, this is a type of stuff that can help advisors, really well implemented quickly, get clients educated on it, and really benefit from its diversification and return benefits.
Right? So that’s, I think, why it made sense, and why managed futures trend as the first foray.But again, let’s just bring it back to managed future’s trend. Let’s, I’m gonna throw it back to you, Adam and Corey. There’s many ways of implementing it. We could have decided to run a trend strategy based on what we think the ideal specifications of when to go long and short all these contracts.
Why, why did it make sense for this product to do a trend replication strategy? I don’t know, who wants to take that one?
[00:20:07] Adam Butler: Maybe Corey, you can, you can speak to what the vision was for the product and then, then I can maybe speak to how, how we went about, um, attempting to track the managed futures index that we targeted.
[00:20:21] Corey Hoffstein: You know, as we surveyed the landscape of our clients and other advisors who had implemented managed futures, one of the core frustrations we heard time and time again was that often they felt like they were correct in choosing managed futures as a category, but that decision was often based upon the long-term track record of a blended index of managers.
So they might look at the Barclay’s Top, what is it, the Bar Top 50 or the SocGen CTA Index. And those indices are actually a blended combination of managers. But what they would do is then choose a specific manager. And if you look at the year to year returns within the managed future space, there is massive dispersion.
Because as you mentioned, Rodrigo, that flexibility that managed futures managers have in actually running the portfolio, the ability to go long and short a variety of different global asset classes and futures markets, means that the actual construction they can end up with, while ostensibly in the same category, can lead to very different performance than their peers.
You can have funds that you would think, 2022 should have been a standout year for managed futures funds. There were funds that posted negative returns last year, and there were funds that posted some of the best returns they’ve had in a decade. And so one of the frustrations we heard from a lot of allocators was they felt like they made the right category allocation and the wrong manager selection decision.
And if they could, they would just allocate across a number of managers to diversify that selection risk. But then they end up with a whole bunch of small line items in their portfolio, and they don’t want to do that. So for us, and I think a perennial attribute of both of our firms has been embracing diversification in all its forms.
You guys have long written about the idea of process diversification. If you don’t have a particular view as to how to implement something, you should perhaps implement it multiple ways and blend those together. I think that concept is something we really embraced and then realizing, well, we could either, again, come up with our own implementation, where we’re trying to create almost a virtual fund of funds and implement this all these different ways.
But if allocators are really just looking to get the benchmark, why not consider a replication based approach where we simply try to provide the benchmark returns over the long run, because that’s what the allocators are looking at anyway. And so that’s ultimately where we came together and said we think sort of the blend of core bond beta, plus trying to replicate the SocGen Trend Index made the most sense. And then obviously the devil’s in the details, Adam, in terms of how you went about trying to do that, cuz that’s not necessarily an easy task. And so I, I’d love to turn it over to you to talk a little bit about the ways in which you had to think about trying to actually replicate that index.
[00:23:18] Adam Butler: Yeah, I mean the good news is we didn’t have to reinvent the wheel. There’s some really good academic precedent, for replication, going all the way back to Fama and French with the returns based style analysis. There’s a really great paper by AQR called, Buffet’s Alpha, where they illustrate how you can replicate the outperformance of Warren Buffet relative to the US Cap Weighted Equity Indices, by allocating to a combination of equities with certain types of characteristics, quality for example, and then adding some inexpensive leverage on top.
So we just sort of stood on the shoulders of giants there and attempted to track the SocGen Trend Index, using both a top down approach, which is kind of analogous to that return based style analysis, and a bottom up approach, which is more analogous to the method that AQR used in their Buffett’s Alpha paper.
So just starting with the top down approach, the idea was, can we assemble a portfolio of assets that are likely to be held or to be a representative sample of the markets that are held within the funds that are included in the SocGen Trend Index and assemble that portfolio at each point in time so that, that portfolio would have best tracked the actual return trajectory of the index over, say the past 10, 20, 30, 40 days. And in fact, we can do that. And the advantage to replicating the benchmark in this way is that we are able to take advantage of any potential changes or innovation in the underlying process that the managers within the index are changing over time as they’re innovating and making improve improvements to their own strategies.
The downside is that, because we need to sort of look back 20 to 40 days to be able to model a portfolio that best tracks the returns of the benchmark, sometimes, when the underlying funds are trading rapidly in or out of positions, there’s a lag in the underlying ability to track that portfolio.
And there’s also extra noise for statistical reasons in trying to track that portfolio through time. So, you know, pro again, the pros are that we’re able to actually x-ray into the underlying portfolios of the fund managers and try and see what they’re actually holding from day to day and week to week. The drawback is that there’s sometimes a lag on the flip side. Another way to think about replicating…
[00:26:25] Corey Hoffstein: I’ll interrupt really quickly? So, would it be, going back to your Warren Buffet analogy, would it be sort of equivalent to saying, if I wanted to replicate Berkshire Hathaway, I’m gonna look at say, the last 30 days of Berkshire’s performance and then try to figure out the portfolio of stocks that best replicated that performance, like maybe it’s a bunch of Coca-Cola and Geico and I come up with the weights and it looks really close. And so my presumption is, I think Warren Buffet probably isn’t selling out of a hundred percent of a position tomorrow. This is the portfolio that I think he’s holding and I’m gonna hold it for the next day and then we’ll redo the analysis the next day.
And so the, the sort of pro is you don’t care how he’s picking stocks, as long as you get stocks that get the, you don’t care what his process is. And his process could change over time. But the con is, well, maybe he does decide to sell out of Coca-Cola entirely in a day. And your ability to pick that up is gonna be on a bit of a lag.
Is that, is that sort of analogous to what you’re saying with the top down?
[00:27:25] Adam Butler: Yeah, I think that’s a great analog. There are elements of tracking managed futures that make a little, make it a little bit easier than it would be to track Buffet’s portfolio on a day-to-day basis. I mean, the underlying constituents of a managed futures fund tend to be a lot more diverse.
So for some statistical reasons it’s a little bit easier. On the other hand, Buffet doesn’t turn over the portfolio very often, so you probably, for the most part wouldn’t have the same kind of lag, whereas managed futures trend following tends to on occasion, exhibit very large shifts in the portfolio, sometimes almost overnight, right?
So yeah, the, the analog is strong, and it also is a nice segue into the other way of thinking about it, which is, well, what if we sort of understood Buffet’s process? We know that Buffet likes to buy companies with strong balance sheets and strong strategic moats, right? High margins that have been high for a long time.
And where the company is not really directly under threat because they have, for example, a strong brand or strong intellectual property rights that make them sort of a fortress. They can’t be easily overcome by competition. Well, in the same way, managed futures, there’s a huge amount of literature, many books have been published on this strategy because it has been so successful, for so many decades.
And so there’s actually a decent general understanding of the processes that most trend following managed futures managers use in their funds in order to decide whether to be long a market, short a market or flat a market, right? So we can actually apply these relatively well known processes to all of the different individual markets that form a representative universe of what these funds might trade, and then use a regression analysis or some sort of model to determine what specific processes the funds in the SocGen Trend Index are using in order to decide from day-to-day whether they want to be long, short or flat the individual markets, right? So it turns out that the benchmark is very readily modelable by a fairly parsimonious suite of relatively simple methods of identifying trends.
And that when you implement the weights to each of those methods that are suggested by the modeling process, what comes out is a return profile that tracks the Trend Index very, very closely. The benefit of this is that, first of all, the turnover is a lot more close to what you might experience within the underlying managed futures funds.
Especially after accounting for the fact that each of the individual funds employs their own unique process. But when you blend all of the funds together into the Index, if you were to able to sort of look through those funds, own all of the individual positions within those funds, well, because some funds might be buying, while other funds are selling, you actually get some trade netting.
So there’s actually more stability in the holdings of the replication strategy, uh, than we would expect there to be within each of the individual funds that are the constituents of the index. So you have sort of lower turnover, which means lower transaction costs and you’re also able to respond more quickly in the way that the actual underlying funds would to major overnight or very short term shifts in trend profiles, across the different markets that are traded in a way that you can’t do, using the the top down approach, because of the lag that we’ve already mentioned. Right? So the great thing is that each of these different approaches, the top down and the bottom up has advantages and disadvantages, but they compliment one another. One of them’s disadvantage is the other’s advantage and vice versa, and they’re not perfectly correlated.
And when you put them together in a portfolio, they both track the benchmark relatively closely, surprisingly closely, actually, and deliver performance that you might expect to get from a combination of all the underlying funds if you didn’t have to also pay the two and 20 fees that typically accompany an allocation to managed futures managers.
So there’s an opportunity to accrue some fee alpha by just not having to pay those steeper fees.
[00:32:29] Corey Hoffstein: Adam, we’ve mentioned a few times futures markets, but we haven’t really specifically said what markets are being traded by the ETF, and that’s another one of the decision vectors that can lead to wildly, wild dispersion among managers. There are managers out there who might trade just a handful of markets, a dozen or so.
They might exclude certain markets. They might choose to not trade equities or not trade rates for whatever reason. They might be commodity heavy. There’s other managers who trade literally hundreds of markets, some of which are not exchange traded futures. They might trade true unique OTC-type derivatives.
How did you end up choosing the investment universe you did and what do you think the implications of that choice are?
[00:33:12] Adam Butler: In aggregate, the managed futures industry can only hold markets in proportion to the total open interest of each of the different futures markets. In other words, the total liquidity or number of contracts that are open in aggregate across each of the different markets. Right? Well, it turns out that, call it 80 to 90% of the total open interest within futures markets is captured by between 25 and 30 of the major futures markets, right? We’re talking about the major equity indices, the S&P futures, the DAX futures, the FTSE futures in the UK, that sort of thing. Some of the major bond benchmarks, like obviously the treasury complex, the bond, the OAT, the Gilts in the UK, that sort of thing.
And then, you know, a smattering of different energy markets, which tend to be very highly liquid and have a lot of open interest, and some other, for example, some of the metals, that sort of thing. And if you allocate to a representative basket of kind of 25 to 30 of these markets, you actually cover the vast majority of the major directions of risk that are taken within the, underlying managed futures funds. Right? So, and the other benefit of allocating to this representative universe of very highly liquid markets is that the, the product can scale to hundreds of millions and billions of dollars in allocation without expecting a major increase in market impact or slippage or transaction costs.
Or potentially running into regulatory limits that you might otherwise run into if you trade less liquid markets, where the CFTC says, we don’t want any single manager controlling beyond a certain fraction of the total amount of contracts outstanding because they can monopolize that market and corner that market and there, you know, there may be some other adverse effects there.
So it was really striking a balance between spanning all of the relevant major bets or directions of risk or markets that the underlying CTAs are probably trading but doing so with a maximum amount of liquidity.
[00:35:40] Corey Hoffstein: I’d love to go.
[00:35:42] Rodrigo Gordillo: I
[00:35:42] Corey Hoffstein: Go ahead, Rodrigo.
[00:35:43] Rodrigo Gordillo: The slide here. So here’s, we trade in, the ETF itself is trading currently with 27 highly liquid exchange trade of futures contracts, around seven global equity contracts, six bond contracts, five currency contracts against the dollar and nine different commodity contracts.
And that broadly kind of spans the liquidities available in this space. And then, like Adam said, 80 to 90% of what we need to replicate that index.
[00:36:15] Corey Hoffstein: Adam, I’d love to go back to the replication approaches. We recently saw one of the largest routs in US treasuries in decades and it was a time in which most CTAs seemed to be positioned largely short bonds. And so what we saw, and I think looking through and x-raying was a very different response in the two approaches to a very violent and sudden shift in treasury returns.
I was hoping maybe you could talk about the nature of what happened in the market and then how we saw these different two replication approaches adapt.
[00:36:57] Adam Butler: Yeah, it’s a great case study. Recall that coming into the week of March 6th, 7th, Jerome Powell was testifying before Congress about the reasons for their current policy stance and trying to provide some guidance on the potential policy trajectory for interest rates and quantitative tightening. And when he spoke, he reinforced a message that he has been very consistent about over the last 12 to 15 months, and that is inflation has been higher than expected. It has sustained a higher rate for longer than both the Fed expected and the market expected. The Fed reconfirmed their commitment to bring inflation down to their target of 2%, and stated that they’re willing to move to a higher terminal interest rate and keep rates higher for longer if necessary in order to achieve that target.
Now, keep in mind that they have been communicating this exact message for 12 to 15 months and the markets have, for the most part, especially the bond and rates markets, have been taken very seriously. So there had been a very strong and persistent negative trend in rate futures, a strong and negative trend in bond futures.
There was also very strong negative carry and there were other reasons why CTA managers might want to be short, very aggressively, both the bonds and the rate complex, and that had been a very profitable trade. You know, being short bonds and short rates were two of the largest contributors to trend CTA performance in 2022.
And they’d also been a positive contributor to CTA performance in 2023. On March 9th and 10th, obviously there was rumors of a major bank run. I think it was the 18th largest bank in the US, which prompted the market to anticipate a major run into other cash instruments, and also anticipate a shift in the Fed’s reaction function that might result in them pivoting to a more dovish orientation to cut interest rates in subsequent meetings in the very near future.
And the market went from pricing in an increased likelihood of a higher rate trajectory to pretty well overnight pricing in a major shift, lower in the rate trajectory. And what that did is it caused a major rally in bonds and an even more substantial rally in rate instruments that resulted in, in some cases, a 10 or 12 standard deviation move in, especially some of the major rates.
What was interesting to observe was how the different trend replication methods responded to this major shift in trend in rates and bonds. The top down approach for reasons that we’ve already discussed, requires us to look back at the implied positions of the trend following managed futures managers over the past 20 to 40 days.
This is the kind of move that happened almost overnight, in a span of two or three days. So it took the top down method many days in order to lower its short allocation to rates and bonds at the same time. The bottom up methodology, because it understands the underlying mechanics of the process that the managers are using in order to decide whether they want to be long or short every single day, actually managed to flip to a very neutral position in rates and bonds. Well, this product trades primarily bonds, but flipped to a, primarily a neutral position in bonds over the span of a day or so. And so it was very neat to see how those different methodologies adapted and was probably a reason why the ETF delivered a slight out performance versus some competitors over that acute, intimate timeframe.
[00:41:33] Rodrigo Gordillo: So, I’ll just add the fact that Adam recently wrote a paper called Peering Around the Corners, How to Replicate Trend Following Managed Futures. And I think the idea of peering around the corners to differentiate one of the other is interesting, right? The top down replication. What you’re doing is you’re, you’re peering into the room and trying to figure out, hey, what are you, what are you holding on average over the last 20 to 40 days?
And you’re doing that every day and you’re kind of getting a lag response. Whereas the bottom up is us having peered into the machinery pre that they use on average. And so the peering happened once. And now we’ve built the machinery to execute on demand at the right time. And I think that’s the benefit of the bottom up, is the fact that the machinery was in place to be able to trigger those moves immediately while we had the other, bottom up be lagging a little bit because we have to peer into it once in a while,
[00:42:34] Corey Hoffstein: Yeah, put it, put another way, Rod. I mean, the bottom up is in and of itself a diversified trend following strategy. Right? I mean, it’s objective is to track the SocGen Trend Index, but even if it fails to meet that objective, it is implementing a diversified trend falling strategy. And so, as trends in bonds quickly reversed, it makes sense that the bottom up methodology would’ve reacted very quickly.
Whereas the top down again is trying to do this replication by looking at the prior returns. And that’s inherently a lagging approach. It’s ultimately going to do very well when transitions are slow and smooth, it’s gonna do very poorly or not track as closely, right poorly, and the objective here is to track closely.
It shouldn’t track closely when the changes are very rapid.
[00:43:20] Rodrigo Gordillo: Exactly.
[00:43:20] Adam Butler: Yeah. So now that we’ve sort of, um, drilled into what makes the, the different moving, uh, parts of the future strategy, maybe let’s shift gears a little bit. Um, Rodrigo, how do you anticipate investors are gonna put this product to use in portfolios?
[00:43:43] Rodrigo Gordillo: Well, look, I think initially the spirit of this whole return stacking concept was about, yes. And traditional portfolios, right? It’s, about not trying to turn the tables over and provide broadly different ways of portfolio construction that I know, you know, we’re all kind of interested in and would hope that more advisors tune into things like, you know, tail protection and risk parity and all that.
But really it’s about you know, we are stuck in a paradigm of 60/40. We understand why there’s a level of comfort. There’s been decades of relationships being created, uh, and understanding of what people own in terms of equities and bonds. You know, how could we add a diversifier without sacrificing or putting in jeopardy a relationship that has been built on that foundation?
And I think the immediate use case is, as Corey alluded to earlier, is a swapping a portion of your bond allocation for RSTB, where you’re just simply getting the same bond exposure, but now you’re stacking a diversifier on top. Okay? So I’ll, in the presentation that’s on the website, I’m kind of just give a brief example, which I will put up right now.
And basically, what if you look at, if you envision a bar chart which has 60 and 40 in it, and that bar chart ends at the a hundred percent mark, you can now swap, let’s say, in this second example on this slide, you can swap, you can sell 20% of your bond exposure and replace that with 20% of RSBT, and your client will see three line items.
Let’s say they’ll see, 60% in in equity and in equity ETF, 20% in a bond ETF, and 20% in RSBT. That’s what they will see, a total of a hundred percent exposure. But if we put our x-ray goggles on, what we’re actually providing the investor is a 60% allocation to equities, 40% to bonds, and 20% exposure to managed futures trend, right?
So at the end of the year, whatever 60/40 is going to do, that the client is gonna get that, and whatever the managed futures trend return is going to provide, they’re also going to get that right. And because managed futures trend is designed to, or at least, it aims to provide positive returns.
Most years we find that, you know, most of the time, it’ll be accretive, or it has historically been accretive and provided a return above and beyond the 60/40. It is because of its non-correlation, it also tends to not add, not stack. You can stack returns, but you’re not necessarily stacking volatility.
So the client experience seems to remain relatively normal over a full year cycle. And so you just get investors, advisors can use this as a way to add that much needed offset to inflation regimes and bear market regimes, without the risk or feeling that there might be a risk that we go through another boom period in their 60/40 portfolio, where they’re missing out because they’re in the wrong allocation.
They had to make room for trend, right? That’s an example. The third example we give here is if you were to replace 40% of your bonds and swap in RBST, then you would be getting 60, 40 and 40, right? And again, this is not designed to be investment advice, and how we think it’s optimal to allocate, it is just an example of the things that you can do.
And I think that would be the initial use case. And later on, you know, we’re gonna start publishing other ideas of more unique and thoughtful ways of allocating across alternative bonds and equities that will provide different types of return streams for people that are less susceptible to tracking error to the 60/40 portfolio.
But I think initially, to answer your question, Adam, this seems to be the best step forward. Uh, I don’t know if you would add anything.
[00:48:05] Corey Hoffstein: Yeah. Interestingly enough, a lot of my conversations this year have actually been with allocators who have introduced managed futures already. So maybe they, instead of a 60/40, had 60% stocks, 20% bonds, 20% managed futures, and they’re trying to figure out a way to get the duration back in their portfolio.
They made the fortuitous decision pre 2022 to sell some of their bonds. Buy managed futures. Well, compared to that benchmark, they are inherently underweight bonds and overweight alternatives. They want to reintroduce that core bond beta, but they’re concerned about eliminating the managed futures, right?
If they sell the managed futures to buy back the bonds, it’s really a big step up, potentially, uh, back in, in terms of inflation risk that they’re taking in their portfolio. So the discussion has been, while replacing existing managed futures exposures with a product like RSBT, allows them to keep the managed futures exposure, but reintroduce the bond duration that they had gotten rid of, that is now potentially from a rate perspective, an interesting source of return for clients.
And so, interestingly enough, I expected the initial discussions to be around replacing bonds with something to get the managed futures on top. I’ve had more discussions with people who are already holding managed futures, trying to figure out how to get the duration back in.
[00:49:23] Rodrigo Gordillo: Interesting. Yeah. And look, and there’s a subset of advisors that have gone down the rabbit hole of the Dragon Portfolio or the Cockroach Portfolio or, you know, permanent portfolio plus alternatives and risk parity plus, that are using these types of exposures in order to create something that they wouldn’t otherwise be able to do.
Right? Because the moment you start adding too many diversifiers, the big issue is that you end up increasing return per unit of risk if you do it the right way, but not necessarily the absolute return money in pocket to the investor, because volatility has gone down so much, right? And so the ability to then rescale up the full portfolio pro-rata and get, and be able to, what we call eating your Sharpe ratio, right?
Being able to actually get that excess returns for the same amount of risk that you would, if you could have in infinite access to leverage. Now you can start playing around with that and provide absolute returns that make sense while providing maximum diversification. Right? So, there’s just a lot to do in this, in this playground, and we’re just really excited cuz this is the first of hopefully, many that we launched to help people create portfolios that make sense for themselves and for their clients.
[00:50:49] Adam Butler: Yeah. So I think we also wanted to address a few common questions that you’ve been getting in conversations with advisors. Um, who wants, do you have a list of those or what, what’s one of those questions you.
[00:51:04] Rodrigo Gordillo: First question is, how frequently is the portfolio rebalanced? Well, to do a lot of the replication stuff that we do, it made sense for us to do it on the daily. That’s that example that Adam gave earlier. About what had happened in the top down replication, you know, that was achievable because we’re observing and trading every day.
So that’s one thing. The other thing I don’t think you addressed, Adam, is, we talked about top down, bottom up, what proportion of each are we using and why?
[00:51:38] Adam Butler: Yeah, right. So we’re using about 70% of the bottom up and 30% of the top down, and it really just came down to the relative advantages of the two different approaches and how well the bottom up actually replicates the SG Trend Index and how stable the understanding of the underlying machinery within the SG Trend Index has been in its operation over time.
There, there just doesn’t seem to be much change in aggregate in the mechanical signals that the trend managers are using to inform portfolios. So it made sense from a turnover standpoint on a return relative to transaction costs on a replication standpoint. But the 30% allocation to the top down acknowledges that there are ongoing innovations within the managed futures space.
It’s a lot of really smart, creative, well, well-resourced, people working at these firms who are constantly trying to improve their competitive positioning and deliver better performance. And so the top down is an acknowledgement of that and, and an attempt at peering through into what they hold, which obviously is gonna be a reflection of all of the different innovations that they’ve introduced over time. So we thought that was the right balance.
[00:53:02] Rodrigo Gordillo: Excellent. Then the other question is, you know, when you look, go to the website and we talk about what we’re doing. It’s a very simple headline, right? $1 of exposure to bonds and then $1 of explosion to futures. And as people go to the website, we’ve gotten feedback that it’s a bit kind of tough to figure out what it is that we’re holding.
So I’m going to share my screen. I’m gonna try to describe what I’m showing as well. Just gimme one second.
[00:53:35] Corey Hoffstein: Yeah, just to, just to clarify what you mean, Rodrigo, right? People expect to see a dollar of bonds and then they expect to see a dollar of exposure to this managed future strategy. It’s a little confusing for two reasons. One, because there isn’t a dollar of bonds explicitly, right? Being held in in the holdings and then managed futures.
When you talk about a dollar to a managed future strategy, well, that can be a little confusing because. The notional exposure doesn’t necessarily add up to a dollar. What does a dollar of a managed futures strategy mean? Right? And so I think it makes sense to spend a minute here and disintermediate how the holdings look, for people and how to interpret them.
[00:54:12] Rodrigo Gordillo: Yeah. So if you go to Returnstackedetfs.com and go to the RSBTT landing page, you can scroll down to the bottom and you’ll find the top 10 holdings. And right at the bottom left of that, you can download the holdings in an Excel file. Okay, so I have reorganized these to kind of make a bit more sense.
But what you’ll find is you’ll find a variety of positions of the futures contracts, as well as the ETF, the bond ETF that we hold. And if you look at the Bond ETF, it’s fairly straightforward. It’s 50% of the holdings go to stock ticker AGG right now. And then if we look at the contracts that we mentioned that we’re gonna use to replicate the other 50% of the bond holdings, it’s the two year, the five year, the 10 year, and the US long.
But what has been confusing is that the weightings for those four contracts, As of today, for example, or I guess as of yesterday’s trading, which was Wednesday the 29th of March, the weightings were negative 54% on the two year, positive 46 on the five year, and negative 13% on the 10 year, and positive 13% on the long bond.
So how do I disaggregate that? Well, and a simple thing to do is just you’re gonna subtract, you’re gonna grab that holding, and add back 12 and a half percent for each contract. And what you end up, if you kind of do this simple math, you end up getting your 50% from AGG. You add up the 12 and a half for each one of those contracts, that’s your a hundred percent exposure to bonds.
And so if you want to figure out what the weighting for the active positioning is on the trend side, you’re simply doing negative 54, you know, minus 12 and a half percent. You get negative 66% for the two year, plus 34 for the five year, negative 25 for the 10 year, and 1%, for the long bond. All right?
So that’s, that’s a simple way to disaggregate it. And then the rest is just the positions that you would hold for a traditional CTA.
[00:56:28] Corey Hoffstein: And just to add a little bit of clarity, where is that 12 and a half percent coming from right now? On the bond side, the strategy, we are doing an equal eight ladder of 2, 5, 10 and long bond. In the future, as the fund continues to grow and we are able to introduce more granularity with the futures contracts relative to the asset size, we are hoping to dial that in more explicitly to track the duration and key rates of the US aggregate market over time.
But today it is, the position looks like about 50% in AGG plus 12.5% in each of the treasury futures.
[00:57:01] Rodrigo Gordillo: That’s right. All…
[00:57:03] Adam Butler: Now guys, the weights don’t add up to…
[00:57:04] Corey Hoffstein: One of the questions
[00:57:06] Adam Butler: Why that is?
[00:57:09] Corey Hoffstein: Yeah, Adam, as the managed futures expert, why don’t you talk about that?
[00:57:15] Adam Butler: Yeah. So the way futures work is that we have, we need to post a small amount of collateral to get, what ends up being a fairly large exposure to the underlying market. So for example, if we wanted a hundred dollars of exposure to, uh, S&P 500 futures, we may only want to, need to post about $5 of collateral in order to get that a hundred dollars of, of exposure, right?
So I’ve got $5 of collateral posted, I’ve got a hundred dollars of exposure. If the market moves by 1%, then I get 1% times a hundred percent is a full 1% of that move. Just having $5 of exposure. Right. So, you know, the way that managed futures funds operate is they trade a wide variety of different markets.
Those markets often have very different risk profiles. Obviously the two year treasury, uh, bond future has a much lower risk profile or volatility profile than say natural gas or crude oil. But we want, when, when one market is trending and another market is trending, we want each of those markets to have approximately the same risk budget in the portfolio, right?
We have kind of the same, um, confidence in that positioning, and therefore we want to have a prospect with the same amount of risk. Well, in order to get a meaningful amount of risk in two year treasury bonds, we need to take on a little bit of extra leverage, right? And so, managed futures funds will often show some amount of leverage.
It might be, you know, 3X leverage. Might be higher than that from time to time. If the portfolio is quite diversified, it holds a lot of lower risk bonds, and then of course there’s longs and shorts in the portfolio. So if you just add up the total exposure of the longs and the total exposure of the shorts, it actually may end up looking like a fairly low net exposure.
But of course, you know, the aggregate absolute exposure will be larger, right? Because you, you know, you’ve got some leverage on the long side, some leverage on the short side. There is a possibility that the longs and the shorts could go against you at the same time and you end up losing or gaining on both sides at once.
Right? So I guess the point is that while we get one unit of exposure to the managed futures program, what that really means is, the managed futures strategy typically runs at an average volatility of 13%, and these are the total positions that we need to have in the portfolio in order to provide the same kind of long-term risk return profile, as you would expect from an allocation of one unit to the underlying benchmark.
[01:00:07] Rodrigo Gordillo: That’s right. And on the flip side of levering up the two year, cuz the volatility’s so low, we’re also not levering up necessarily high volatile commodities. In fact, you are getting a much smaller exposure to those things. And to get the same amount of risk that you would on a levered or two year portfolio.
So, it’s just about trying to equate the levels of risk that we get across the contracts plus, plus or minus trend strength. But yeah, I mean, it is that profile. Another question that is asked is what is the, the risk profile on the managed futures side? You know, we’re trying, currently we’re replicating the SocGen Trend Index, which runs just over 13% annualized, uh, standard deviation.
Right. So, that is the unit that we are stacking on top of the bonds.
[01:01:04] Corey Hoffstein: Another question we get pretty frequently on the bond side is about distributions. Often people are using bonds for income. One of the things we should really clarify here is that we are not expecting to make monthly or quarterly distributions. The current distribution schedule of this portfolio is annual.
Doesn’t mean that might not change in the future, but our goal is to replicate the bond beta and because we have to use treasury futures to get a significant portion of that bond beta and treasury futures do not pay a distribution, we are simply trying to give the total return of the bond beta.
We’re not trying to replicate the income stream that you might see if you were holding just the bonds. And so this, if you’re using bonds purely for income, I don’t think this is necessarily a good replacement. In that sense, this is likely to be something that’ll pay you an annual distribution on both the income and tax side.
[01:01:56] Rodrigo Gordillo: Right, and I think the last and, and very important question is, you know, this is traded through an exchange traded fund and a lot of people have questions on how to trade exchange traded funds, that are just kind of starting off, that may at first blush not seem very liquid. You know, maybe Corey, you can talk a little bit about kind of what, how people should think about any exchange traded fund, and their actual liquidity, and how to capture the real liquidity underneath versus what may be seen on the surface.
[01:02:31] Corey Hoffstein: Yeah. ETFs, unlike mutual funds are prime, are traded on the exchange, which means that there is a market maker often on the other side, whose job is really to keep tight bid/asks and provide volume in the order book. The reality is most ETFs are as liquid as they’re underlying. So if you had, say, a very simple example, an ETF that tracked the S&P 500. Well, the S&P 500 is incredibly liquid, very easy for market makers to hedge their positions, and we would expect that to be an ETF that could absorb a lot of volume. On the other hand, market makers run a business and they have to dedicate capital to making markets in each fund that they make markets on. If an ETF only does say a hundred thousand dollars in average daily volume, a market maker isn’t gonna dedicate 50 million to standing orders in that order book.
It would be capital inefficient for them. So they’re gonna look at how much volume is trading every day in terms of how much activity, or how much capital to dedicate to standing orders in the order book. So what does that mean? Well, it means that if you have an E ETF like RSBT, that ostensibly has incredibly liquid underlying markets, that should be very easily hedged both on the bond side and the futures side.
There is the potential to have a very tight trade executed because market makers should be able to create very tight bid/ask spreads, but they’re not leaving a tremendous amount of standing volume in the ETF. They’re not leaving tens of millions of dollars in the order book right now because it is a new ETF, and the average volume is significantly lower than that.
So in terms of people who are trying to allocate, what this means is you should be able to allocate very easily using limit orders and you can, should be able to allocate in size very easily using limit orders or calling a trading desk and asking them to get quotes from a variety of market makers and execute on your behalf.
You should be able to get very tight fills. If, however, you were to hit the order book with a market order that is magnitudes larger than the average daily volume, you will unfortunately, likely get a print that is, you know, significantly above or below NAV, depending on whether you’re buying or selling.
And this is no different in our ETF or any ETF on the market. You know, again, the ultimate liquidity is determined by the underlying, but that secondary volume is an important component to how thick the order book is and the less secondary volume there is, the more careful you need to be executing.
You should be able to still get filled, very close to NAV with a tight bid/ask spread, so long as the underlying are sufficiently liquid. But you don’t want to throw a massive order that’s multiples of the average daily volume using a market order. Unfortunately, no matter what you trade, you’re likely gonna have a bad time.
[01:05:33] Rodrigo Gordillo: Yeah, look, it’s, it’s like catching the market makers off side. They are, they’re putting a bunch of bets and using the capital efficiently across everything that they’re market makers for. They can’t be attentive to every single trade that’s on, and they’re not gonna be fast enough to deal with size immediately.
But if you were to tap ’em on the shoulder and say, hey, big size is coming, they’ll be able to cover that and help you out, right? So that’s a major, it’s just about the speed. If you’re putting in a large size and any ETF that has, you know, that doesn’t, that the market maker’s putting in the average size and you’re gonna do five times the average size, then you’re gonna hit other business and make a lot of other people richer that are waiting for those offside bids and asks.
So yeah, just it’s as liquid as it, as the underlying. Be careful about how you’re putting your orders in. Think about market orders, contact your desk if it’s size, and I think you, there’s going to be the liquidity that you need.
[01:06:35] Adam Butler: A quick tip for those listening to the podcast. A handful of the markets are, they trade in Europe, and therefore are less liquid after European close. That’s typically not a big deal during the week. But on Friday afternoon, that can be a little bit more impactful. So if you do want to put a larger order in and get very, very close to NAV, you’re, it’s gonna be fine all the time, but you might squeak in a little bit closer to NAV on Friday if you trade before noon.
[01:07:07] Rodrigo Gordillo: Perfect. Okay. I think we covered it all. Anything else that came to mind, that we didn’t plan on talking about guys?
[01:07:16] Corey Hoffstein: Just want to say thank you to anyone who’s stuck with us for a little over an hour now. We appreciate your interest in the funds and return stacking in general. And if you have any questions, you can contact any of us. We’re always happy to chat and provide more color on the fund or how it can be used in an advisor’s portfolio.
[01:07:35] Rodrigo Gordillo: Excellent. Thanks guys.
[01:07:42] Corey Hoffstein: Okay.
[01:07:47] Rodrigo Gordillo: All right.
Long-Short: Long-short managed futures strategies look to profit by going long or short according to fundamentals and/or technical market signals. When an asset’s price is trending lower, trend traders may decide to enter into a short position on that asset. Conversely, when an asset is trending upward, trend traders may enter into a long position. The goal is to capture gains by analyzing various indicators, determining an asset’s direction, and then executing an appropriate trade.
Beta: For the purposes of this presentation “beta” is broadly defined as the returns achieved by the broad market index of a particular asset class. For example, when describing US equity “beta” it tends to refer to the S&P 500 index, when referring to US Bond “beta” it tends to refer to the Bloomberg US Aggregate Bond Index.
Indexes are unmanaged and do not have fees. One cannot invest directly in an index.
For a full list of holdings, click here.
Investors should carefully consider the investment objectives, risks, charges and expenses of the Return StackedTM Bonds & Managed Futures ETF. This and other important information about the ETF is contained in the prospectus, which can be obtained by calling 1-310-498-7655 or clicking here. The prospectus should be read carefully before investing.
Investing involves risk including possible loss of principle.
Derivatives Risk. Derivatives are instruments, such as futures contracts, whose value is derived from that of other assets, rates, or indices. The use of derivatives for non-hedging purposes may be considered to carry more risk than other types of investments. Cayman Subsidiary Risk. By investing in the Fund’s Cayman Subsidiary, the Fund is indirectly exposed to the risks associated with the Subsidiary’s investments. The futures contracts and other investments held by the Subsidiary are subject to the same economic risks that apply to similar investments if held directly by the Fund. The Subsidiary is not registered under the 1940 Act, and, unless otherwise noted in the Fund’s Prospectus, is not subject to all the investor protections of the 1940 Act. Bond Risks. The Fund will be subject to bond and fixed income risks through its investments in U.S. Treasury securities, broad-based bond ETFs, and investments in U.S. Treasury and fixed income futures contracts. Changes in interest rates generally will cause the value of fixed-income and bond instruments held by Fund (or underlying ETFs) to vary inversely to such changes. Commodity Risk. Investing in physical commodities is speculative and can be extremely volatile. Commodity-Linked Derivatives Tax Risk. The tax treatment of commodity-linked derivative instruments may be adversely affected by changes in legislation, regulations, or other legally binding authority. As a registered investment company (RIC), the Fund must derive at least 90% of its gross income each taxable year from certain qualifying sources of income under the Internal Revenue Code. If, as a result of any adverse future legislation, U.S. Treasury regulations, and/or guidance issued by the internal Revenue Service, the income of the Fund from certain commodity-linked derivatives, including income from the Fund’s investments in the Subsidiary, were treated as non-qualifying income, the Fund may fail to qualify as RIC and/or be subject to federal income tax at the Fund level. The uncertainty surrounding the treatment of certain derivative instruments under the qualification tests for a RIC may limit the Fund’s use of such derivative instruments. Commodity Pool Regulatory Risk. The Fund’s investment exposure to futures instruments will cause it to be deemed to be a commodity pool, thereby subjecting the Fund to regulation under the Commodity Exchange Act and the Commodity Futures Trading Commission rules. Because the Fund is subject to additional laws, regulations, and enforcement policies, it may have increased compliance costs which may affect the operations and performance of the Fund. Credit Risk: Credit risk refers to the possibility that the issuer of a security will not be able to make principal and interest payments when due. Changes in an issuer’s credit rating or the market’s perception of an issuer’s creditworthiness may also affect the value of the Fund’s investment in that issuer. Currency Risk: Currency risk is the risk that changes in currency exchange rates will negatively affect securities denominated in, and/or receiving revenues in, foreign currencies. The liquidity and trading value of foreign currencies could be affected by global economic factors, such as inflation, interest rate levels, and trade balances among countries, as well as the actions of sovereign governments and central banks. Foreign and Emerging Markets Risk. Foreign and emerging market investing involves currency political and economic risk. Leverage Risk: As part of the Fund’s principal investment strategy, the Fund will make investments in futures contracts to gain long and short exposure across four major asset classes (commodities, currencies, fixed income, and equities). These derivative instruments provide the economic effect of financial leverage by creating additional investment exposure to the underlying instrument, as well as the potential for greater loss. Non-Diversification Risk. The Fund is non-diversified, meaning that it is permitted to invest a larger percentage of its assets in fewer issuers than diversified funds. Underlying ETFs Risk. The Fund will incur higher and duplicative expenses because it invests in bond ETFs. The Fund may also suffer losses due to the investment practices of the underlying bond ETFs. New Fund Risk. The Fund is a recently organized with no operating history. As a result, prospective investors do not have a track record or history on which to base their investment decisions.
Toroso Investments, LLC (“Toroso*) serves as investment adviser to the Funds and the Funds’ Subsidiary.
Newfound Research LLC (“Newfound*) serves as investment sub-adviser to the Funds.
ReSolve Asset Management SEZC (Cayman) (“ReSolve*) serves as futures trading advisor to the Fund and the Funds’ Subsidiary,
The Return StackedTM Bonds & Managed Futures ETF is distributed by Foreside Fund Services, LLC, Member FINRA/SIPC. Foreside is not affiliated with Toroso, Newound, or ReSolve.
*ReSolve Global refers to ReSolve Asset Management SEZC (Cayman) which is registered with the Commodity Futures Trading Commission as a commodity trading advisor and commodity pool operator. This registration is administered through the National Futures Association (“NFA”). Further, ReSolve Global is a registered person with the Cayman Islands Monetary Authority.