Navigating Market Volatility: Mastering Managed Futures and Carry Strategies

So I'm gonna try to channel everybody that's sitting in their seats right now trying to think through whether. You know, they might be asking questions throughout. I'll try to be that co pilot and ask those questions, but please do answer. so do ask questions. I'll be reading them and I'll see if, if I can help get that answer for you guys. Adam, are you saying Rod isn't good enough to look at? Exactly right.

Like if he's going to look at a naked person, you'd think at this point it'd be his business partners. Feel comfortable with it.

It seems like that, that there's been a big uptake on trend. General audiences are starting to understand it. They see the value in it. And, very few people know about carry. So lots to talk about. There's, I'm so excited about this for many reasons we're going to cover, but, yeah, I think there's many applications to this concept in the investment world.

Been together with him and Michael Philbrick since 2011. I've been in the business for almost 20 years now, and I'm president of Resolve Asset Management, Global. Been a-co contributor to a lot of white papers and podcasts and blog posts on Resolve and, you know, writing articles as well now on the return stack, website and, and so on. So been managing quantitative investment strategies for many years. And today I'm going to help facilitate the conversation with the co authors.

If we go to the next slide, Adam. So for those who haven't read the white paper, I would encourage you to click on the link. Maybe Ani can push that through for you guys to be able to click on that. If it's not, if you haven't already, it'll be a good thing to have side by side as we go through this presentation. and the white paper was written by Adam Butler. Our CIO here at Resolve Global and Dr. Andrew Butler, our resident PhD in Resolve Asset Management Canada. yes, they are related.

Genius does run in the genes. So our two propeller heads did a fantastic job at creating a comprehensive review and framework for different ways of looking at a carry. And everything that we're going to present in this presentation, all the performance stats will be sourced from this white paper. So just, click on that. There's also data that you can download. So if you can kind of double check everything that we review here.

There's many ways to skin this cat by no means it is a, an offer to, buy a fund or anything like that. So really it's about covering that research. Next slide for me, Adam. So please do read those disclaimers and recognize that there is risks in everything that we do in this space. And then I'll tell you quickly what we're going to tell you. We're going to talk about what is basic carry, how we define the three basic definitions of carry.

How we can practically implement all these carry strategies in a portfolio and incorporating with other asset classes. And then from then on, we'll really go through some analytical framing, you know, how to put these things together to make them work in real life with real trading, and then from then on, it'll be back test showing performance analysis scenario and regime analysis. So a couple of case studies on the return stacking side and then conclude with some questions.

Okay, so next slide for me, Adam. Before we do begin, let's start with a little poll. Ani, would you mind pushing through that poll? I want the audience to, I'm just trying to get a gauge as to how many people had heard about Diversified Carry before downloading our white paper or being in this, webinar or the invite. And also if you can answer the second question, which is if you had heard a carry, how many of you do you currently invest in a carry strategy? Give it a couple of minutes there.

I've never done a poll, so I'm just gonna let that linger there for a bit. And maybe we can come back to it, Adam. but, Ani, you let me know when it goes, when

hopefully, you know, we certainly do and have been talking about carry strategies and have those in our back pocket. And if you go to our website, you can find some, but, more and more solutions will be coming out very soon. All right, so this is good to know. Let's hand it over to our lead author here. Adam, why don't you take it away and tell us what Carry is.

Maybe you're not so concerned with what the price will be when you sell it in 20 or 30 years. In the meantime, it is generating a lot of cash flow for you, the rents on the apartments, right? Well, going a little bit more into public markets, equities are expected to deliver cash flows in the form of dividends. Even equities that don't currently pay dividends are priced on the basis that eventually they're going to return cash flow to investors. Bonds. Almost all of them pay a coupon.

That is the carry on bonds. And we're going to demonstrate that in the concept of futures markets, commodities, equities, currencies, bond futures, all of these can be expected to pay or, absorb carry at, at different points in time for different reasons. So let's get into an example. All we've done here is. Sort of illustrated a simple futures market. One futures market that has a, let's say it's copper, right? Copper is currently trading at 3 dollars and 50 cents in a spot market.

So if you're going to go buy. A ton of copper, you're going to pay 350 a pound, say, right. And then we've got a future on copper and you, someone wants to buy the future on copper, to take delivery in September. And that's the point that's sort of out on the right here, right? So here's the spot price and here's the futures price. And, they're paying a little bit less. In the future, then the current spot price for dynamics that currently exist in the, in this market, which we'll get into.

And then over time, if the price of copper doesn't move, if it stays where it is, we would expect the futures price to rise to eventually hit the price of copper. And therefore this market where the price of the future in the future is lower than the spot price or the near term futures market contract, we expect that to have positive carry as the price converges to spot over time, right?

So in this case, we're sort of saying we're going to earn a little over 3 dollars as this distant future becomes less distant over time in terms of time as time rolls forward. But futures markets can take many shapes. So you'll, you'd imagine copper futures. You might be able to buy copper for delivery and maybe, you know, it's May now, maybe you can buy copper for delivery in June, in September and December, in June of 2026.

And so you can plot the price of each of these different futures markets. On a chart going out through time. And that describes the term structure of that futures market. So in this case, you know, the contracts going out into the future are priced at successively lower prices. And as you go out sort of far enough, they begin to rise a little bit.

And that's just very typical futures markets tend to have a curve in them, reflecting the supply demand dynamics of the market at different points in time.

You're making allocation decisions based purely on that yield, that futures yield, much like if you think about in, trying to select securities based on some sort of a shareholder yield, right? So I know that these are done very well. Meb Faber has done a lot of work on this, right? You're just measuring the type of yield that the company as a whole is pushing out and selecting those assets. Solely on that, not on price momentum, not on value, just purely on that.

And while much like, shareholder yield provides positive expectancy above cash, we find the same thing when we select based purely on this type of futures yield.

The prices of the distance contracts change over time, but on average, we expect this general drift to occur. Just like on average, we expect equities to have a positive drift, but they go up and down over time.

And yes, just to round off what you said, shareholder yield, finding a stock that has a strong shareholder yield does not guarantee that the price plus shareholder yield is going to make you a positive return at the end of the year. It just tends to be that way over time

And in fact, when we survey the offering documents for a variety of funds in the SOC gen, CTA index, We find that carry is mentioned second only to trend in terms of the frequency that it's mentioned as a signal that it informs the, the trades that they make and the portfolios that they hold over time. So, you know, it's not as esoteric as, as many people believe.

And it also, in a managed futures context, is, Considerably different than what many old timers might remember as being the sort of idea of currency carry, which for a while was the idea of, shorting the currencies in low yielding, regions, like the U.S. dollar or the Japanese yen and buying emerging market currencies that typically have, Higher local interest rates, right? So that's not the carry that we're that we are implementing currency carry in broadly that way.

But when you expand a canvas to include equities, bonds, and a wide variety of different commodities, the carry strategy takes on a very different profile as you'll see. So what drives carry? We talked about equities and bonds, you know, in equities, it's the dividend yield. That is reflected in the futures term structure for bonds. It's the, we're only dealing with government bonds in this context. So it's the, you know, whether the bond cash treasury term structure or the guilt term structure.

or the bund term structure in Europe, for example, has a positively sloping yield curve. So if the 10 year yield is higher than the three month treasury, for example, that would, we would sort of consider that to be a positive yield curve, and it would have positive carry in bonds. At the moment, you know, we're in a bit of a strange situation where near term yields Are actually higher than most longer term yields. So bonds currently are typically measured to have negative carry.

but again, that's rather unusual over the past 30, 40 years. In commodities, there's a convenience yield, which is sort of the convenience that the speculators offer to producers in order to take on the price risk. So producers can sell their production forward, have some certainty about the price that they're going to get for that production, and they can go and raise capital for to invest in new projects, that sort of thing. And in currencies, it's just the difference between the.

the short term interest rate in the jurisdiction you're borrowing in. In our case, we're only using U. S. dollar crosses. We're always borrowing in the U. S. dollar to invest in a foreign currency or borrowing in a foreign currency to invest in U. S. dollars, depending on which of those has a higher interest rate. Now, I'm not going to dwell on this. This is just why do equities and bonds need to have a positive long term carry?

Well, because in order to invest in equities and bonds, You need to move from very liquid cash into illiquid securities. You don't know what you're going to be able to sell those securities at some point in the future. If you need liquidity quickly, you may have to take a hit on the price you would realize for those securities. There's also inflation uncertainty.

We don't know what inflation will be like in the future and you need to be compensated for locking your money up for a long period of time. And also you also, you need to defer consumption, right? Instead of buying something that you want today, you're deferring consumption. Putting it in savings vehicles or in investments, hoping that those investments will grow over time, but you need to defer what you want to buy today. So that's standard stocks and bonds.

Commodities, just to dig in a little further, it's very accretive for commodity producers to sell their production forward often many years into the future. Imagine, a mining company wants to develop a new copper mine. And. By the time you get the environmental permitting, all of the engineering spec'd out, you do all the assays, et cetera, to figure out what kind of mine you want to build, it's probably 10 or 15 years before you get to first production.

So the copper companies will sell a good portion of the expected production from those mines forward in order to block in the economics or a substantial portion of the economics on that project. And they have many projects going on in many different regions for many different metals, et cetera. Energy companies are doing the same thing. Grain producers are doing the same thing.

And this is highly accretive because it lowers the, variability of their earnings over time and gives investors certainty and that higher certainty for investors lowers the cost of capital to the producer. They're able to go to the debt market and raise money at lower interest rates and go to the equity market and raise money at higher multiples, lower cost of capital, higher ROI to the producer over time. So it's kind of a win situation.

Speculators are providing, they're insuring the producers against price fluctuations and they earn a premium on this insurance. And that's why we expect this over time. Now, the commodity premium can be positive or negative depending on the short term dynamics in a market.

We saw energy prices go negative in early 2020 during the COVID crash when there were all these pipelines leading to storage facilities and the storage facilities were totally full and they would, were selling oil at negative prices in order to make room for new oil coming from pipelines that had to go somewhere, right?

So there's short term supply demand and dynamics that can make the term structure for commodities positive or negative And make it more attractive to be short than long or vice versa and that's why in carry strategies, sometimes you want to be long a market if it has positive expected carry short of market, if it has negative expected carry, if you're short of market that has negative expected carry, you're expecting to earn a positive return on that.

Because As Adam kind of alluded to here, there are players, there are willing participants here that are getting economic benefit for hedging their risk and the other side for taking that risk, right? So it would require for this not to be a risk premia, it would require parties to be, willing to bear risk with zero expected compensation, which is not how the economy works, right? So I think that's a good basis for this whole carry thing.

We didn't include any, grains or softs or other more, out there, commodity sectors for, you know, liquidity reasons, et cetera. In practice, there are commodities within other sectors that are plenty liquid. That, you know, could be used in scalable carry strategies, but this was our experimental universe.

So this is, what he's alluding to is that if you X ray a fully funded futures strategy or commodity strategy, it is anywhere between 80 and 90% Treasuries, short term treasuries that you're earning yield on. And then the remaining cash is used as collateral to buy and sell those futures contracts. And so I guess I'll get my 2 cents out Adam and then maybe you can correct me, but it's important to note that what we're going to be presenting here is excess returns.

So we are not including the carry on cash that would exist if we were to port this strategy over to a traditional fund. So this is, am I right in saying this is excess returns, Adam? And so what excess returns mean is the returns above cash. it's what you would get, if you were to just run the strategy without any cash yield whatsoever.

So it's not the, to answer your question, this is the yield you get on the treasuries in a pool is not considered carry in the traditional sense, in the sense that we're going to be talking about here. Now, can we make a case for it being carry if you're fully funding a fund that uses carry? Yeah, I guess you could say that it is a carry, but it has no specific, quantitative strategy. It's just, it just happens to be along for the ride rather than it being an explicit bet on carry.

Another is cross sectional carry. We're going to go through that in quite a bit of detail, which is typically implemented at the sector level. So for example, if you've got eight different equity markets, you're running a cross sectional equity carry strategy. You're going to be long for equity markets and short for equity markets all the time to main, maintain that sector neutrality. And same for long and short energy markets, long and short bond markets, et cetera, right?

So that's a cross sectional or sector neutral strategy. And then the third way is a time series carry strategy, which is the one that we're gonna spend the most time on here today, where you're allowing the portfolio to get, you know, a little bit more crowded. In the, on the long side, if most of the markets in a sector or most of the markets in the portfolio have positive expected carry and you're allowing, you know, get more short in on a net basis.

If more of those markets, have negative expected carry than positive expected carry, right? So again, time series, strategies allow for sector exposure to drift higher or lower into negative territory over time in response to how the underlying markets are, you know, expressing positive or negative carry. Whereas a sector neutral strategy.

All the markets in the sector could have positive expected carry, but you're still enforcing the constraint that half of them need to be held short in order to eliminate any sector exposure. Okay. And we'll see how that impacts strategy performance over time. So within these, cross sectional or time series strategies, we also divide it up in terms of measuring carry on an absolute basis.

Which is what we've been talking about so far is the term structure of the futures for a market positive sloping, implying negative carry or negative sloping, implying positive carry. so that's sort of absolute carry and have a more traditional way of people thinking about it, but there's also a relative value carry.

So if we look at the very long term average of the term structure, so for example, gold is usually in, has a positively sloping term structure, slightly positively sloping term structure. So the carry for gold in an absolute sense, usually implies negative, slight negative carry. But if instead you look at the long term average term structure and you measure carry relative to that long term average, then when it's above average carry, then you'd go long.

When it's below average carry, you'd go short. and so it's just a slightly different cut on this concept. Then there's how you want to transform that carry signal, right? So a really simple way would say, well, I want to be one unit long. If the, or one volatility unit long, as we'll talk about a little bit later, if carry is positive, one volatility unit short, if its carry is negative, that's binary signals.

Or we could be long or short in proportion to the, just the strength of the raw carry measure, or that the degree to which carry is above or below its long term average. And then also we can rank the markets in, in the portfolio by their carry as well and use the rank score, positive or negative rank score as their, carry measure.

So there's all these different sort of ways to skin the cat and they all deliver, they all sort of capture the same underlying phenomenon, but they do things from slightly different angles. And therefore they provide some diversification benefits when you combine them all together in a portfolio, as we'll discuss. So just to reinforce this concept of absolute carry. This is, again, just kind of what we've already been talking about most of the time so far.

These two futures markets, these term structures, imply negative carry in both cases, but the blue line has a higher negative carry or expected negative carry than the black line in this case on an absolute basis. So this is like raw or absolute carry. In contrast,

We call it carry Z because we're actually doing a Z score. And a Z score is just what is the current value relative to the mean value. So that difference divided by the amount that value varies over time or the volatility of that value over time. Okay. So that's why we sort of use carry Z score and relative value carry kind of interchangeably.

And therefore we would be short the blue line and long the green line in this case, because we're now measuring carry relative to its long term average black line, not on an absolute basis. Okay. Okay. So now the fun part, we're going to start with an examination of whether, carry has existed in each individual market sector. So equities, bonds, and different commodity sectors and currencies on their own.

And then we're going to kind of begin to combine things together and see how that everything kind of works together in a stepwise fashion. So this will reinforce, because we're dealing with markets in sectors that have very different ambient risk, like obviously bonds are going to have very different long term average volatility than say natural gas or crude oil or copper. we're going to, we're going to scale all of the markets in each portfolio to have the same volatility.

And then we're also going to scale the volatility of each portfolio to have the same target of 10 percent annualized volatility. And when we scale them every single day, we're evaluating the volatility of the underlying markets. They're correlation to one another. And then we're using those estimates to scale that portfolio to, the target that best approximates what we've estimated from the portfolio in the very recent past.

And then we're just scaling, use a fairly near term estimate of volatility based on what happened over the last 40 days. And we're using, because it's an exponentially weighted moving average, the nearer term returns matter a bit more in our estimate than the returns that are more distantly in the future, in the past.

And, you know, that's okay across most of the sectors historically, but a few of the sectors have either very low or slightly negative historical returns if you're not willing to take on some sector risk when the, the carry skews towards long or skews towards short in any given sector over time, right? they still all do relatively well with the exception of equities.

but not quite as well as we'll see when we adjust the measure of carry for, you know, against the long term average carry for each market in the sector. We're still holding the sectors market neutral in this case, but we're sorting them based on the degree to which they're, the carry is above or below the long term average within each sector. And this seems to have, deliver better performance over the very long term. Now on a time series sense.

Now we're allowing the sector exposure to drift positive or drift negative. If there's a preponderance of markets that have positive carry or negative carry at any given moment, right? We do that using raw carry as our signal, then the performance generally improves across the board and we see the same phenomenon with relative value or carry Z, signals where allowing that sector exposure to drift higher or lower is long-term accretive.

As we're now accepting more sector risk as well, when we aggregate up all of the sectors together and we just look at the cross-sectional carry for equal risk weighting all of the different sectors and are using a cross-sectional, portfolio approach, then you can see that the carry Z outperforms the, the regular carry, which is consistent with what we kind of saw at the individual sector level.

And when you combine the regular carry and the relative value carry Z signals into an ensemble for sector neutral strategies, it actually rolls up pretty well with a long term Sharpe ratio of around 0.55, right? But still it doesn't compare to the performance of time series strategies where we're now allowing sector exposure to drift over time, both raw carry and carry Z strategies. Both perform very well on a time series basis.

When you roll them up together, they do even better with a sharp ratio in the range of 0. 9. And even when you combine the sector neutral strategies with the time series strategies, because of the low correlation, you still preserve the majority of the performance you get from the pure time series strategies.

when you combine everything together, just the power of diversity and ensembling, which we're going to discuss as we go forward, we pretty well use ensembles in all of our strategies everywhere for this reason.

It should be noted by the way, because we brought up the idea of you know, raw signals, binary signals, and rank signals, that in each of these cases, we're just combining strategies based on raw, strategies based on binary, and strategies based on rank all together within individual sectors, within individual cross sectional versus time series ensembles. And within the total ensemble portfolio, right?

So this is gives you a general idea of the performance of all of these time series and cross sectional portfolios. over time you see the, you know, the cross, one of these cross sectional portfolios, just didn't perform very well. Again, if you're not willing to accept sector risk, then you're removing what turns out to be a meaningful component of the carry signal over time. So that was individual sectors.

Most managers also sort of contemplate or actually focus their portfolio management on the total portfolio and not just on individual sectors. So in this case, we're allowing, let's say, you know, all of the.

energy markets had negative carry, but all of the bond markets had positive carry or some mix, whatever we're allowing those markets that have positive carry, to be held in positive weight in those markets with negative carry to be held in negative weight in the portfolio without sector constraints, right? It's just, you're going to be held in the direction of your raw carry or your relative value carry in the portfolio.

We're going to show an inverse volatility weighted version of this, which is just using, instead of just applying inverse volatility weighting at the sector level. Now we're going to apply this at the total portfolio level. So we're measuring the volatility of every market in the portfolio. The exposure is going to be the carry score, or the carry Z score, divided by that market's volatility estimate at that moment.

And then we're going to scale the, Exposure of all markets in the portfolio to hit a target of 10 percent annualized volatility based on our best estimates at any given moment. Okay. So that's naive or inverse volatility weighting. We're also going to explore a mean variance optimization of the same concept. In that case, we're trying to maximize the total amount of both long carry exposure and negative carry exposure.

So short exposures while simultaneously trying to minimize the total portfolio volatility, right? The way that you would in a typical mean variance optimization. So it's just a carry score is our return estimate. And we're just trying to minimize the total portfolio volatility while maximizing our exposure to carry. So the naive weight inverse volatility, and then an optimization we're going to get to after that. So starting with the inverse volatility waiting.

So now we're only exploring time series versions of this. We're going to leave the sectoral sector neutral versions of these behind. We're going to accept the fact that we're going to have some Sector exposure over time. If all of the markets in a given or most of the markets in a given sector have positive carry, we're going to have positive exposure to that sector. And we're just going to live with that. And we're going to also harvest the excess premium we've got from accepting that risk.

So looking at.

normal carry, but now examining just using the carry score as a continuous signal, or binary carry, is it positive or is it negative, and then rank carry, so the score becomes the rank, then you can see all of these do quite well, you know, in this case, the raw carry doesn't do as well as the rank carry, the binary's somewhere in the middle, we're going to see that this is random noise, and that all of these Carry signals and transforms are basically, they all give you approximately the same

strength of signal. It's just, some of them have done worse or better recently or what have you, but it's just noise.

So exploring the same thing for relative value carry, we see, you know, a different, well, we're preserving the order here in terms of sharp ratio, but the relative value carry in this case tends to do a little better than the, raw carry in some cases, a little worse in other cases, again, emphasizing that we are using all of these different cuts at the same phenomenon, not because any of them have better or worse expectancy over time, but because they all do slightly different things at

different times and diversify one another, but they all do well as you can sort of see from their long term profile. Now transitioning to mean variance optimized portfolios. We're again considering both volatility and correlation to minimize portfolio risk while maximizing total portfolio carry. Just using raw carry with various transforms. All do very well, and they tend to do a little bit better than the naive portfolios that are not accounting for correlation differences over time.

Carry Z showing equally strong performance with mean variance optimization. And you can see these are a little bit more tightly grouped over time, then the inverse volatility or naive weighting, again, they do slightly better than naive portfolio weightings, but for the most part, it's just noise and what is better is to combine a naive weighting, which makes fewer assumptions about the portfolio with the mean variance optimization, which makes a couple of more assumptions about the portfolio.

Mainly that we, that correlation estimates are a little bit persistent. So when we're measuring the current correlations, those correlations are likely to be approximately the same in the next period. Combining those different approaches is highly creative, right? For diversification reasons. And when we do combine them, we observe smoother performance, higher sharp ratios over time, right?

So we're just, this is just building up again to our final meta, meta ensemble, but just focusing on all of the different inverse volatility portfolios, right? using regular carry, all of them using relative value carry, Z carry. And when you combine them both, you go from about a 0. 85 sharp to a one sharp. This is just with the inverse volatility, but ensembling. Right. And there's the green line above both of the, constituent ensembles. Rodrigo, I don't know if that's confusing. Yeah.

And it may seem like all these layers that Adam's been talking about is about, you know, getting more narrow and more optimized, but in fact, it's the complete opposite. It is the idea of trying to be broadly correct about capturing the carry signal rather than being specifically wrong and assessing all of these individual parameters. Finding the one that had the best back test and choosing that one, right?

So an example that I often use with regard to the value of being humble about your ability to capture any signal, the way we're doing here through ensembles is, I'm sure everybody a couple of years ago heard that the, that we captured as humanity, the first image of a black hole and the headline said the event horizon telescope captures the first image of a black hole. And it was a very well defined black hole. It's exactly what we imagined high def. It was a beautiful image.

What few people know is that wasn't one telescope. The event horizon telescopes is actually hundreds of telescopes across the world in many different sites that are capturing different types of signals, radio waves, infrared, you know, they're all measuring the black hole in their own way. And what the team had to do is over a couple of months in the U.S. is grab all of that data. Put it together, eliminate the error terms. And what they got was that beautiful image that we received in the news.

Any single telescopes image, if you watch the, there's a documentary on Netflix is garbage. It's doesn't make a lot of sense. It's kind of the outline, right? So it really is ensembles is the most robust way that we have found as humanity in terms of noise to ratio, noise to signal, to make sure that we are broadly correct about what we're trying to do.

And so that's all we're doing here with at the portfolio level. Great point. So now it's just the optimization. It's also, I think, worth saying that when we're portfolio optimizing, we do this every single day, right? So we're, you know, it's today. We look back over the last Several days, several months, we're estimating the, variances and correlations of between all the different markets at that time. We're estimating the carry and we're forming a new portfolio.

Then we move forward one step, we look back again, and we, you know, we're, we use that information to form a brand new portfolio. So we're constantly rebalancing into a portfolio seeking to emphasize or maximize carry while minimizing portfolio volatility, right?

So when we're doing that, you know, when we ensemble all the different transforms of raw carry, We do very well, carries the relative value that does well when you put them together, you go from kind of a 0. 9 sharp ratio to almost a 1. 1 sharp ratio. Historically gain just the power of approaching it with ensembles and the ensemble line above either of the constituents line scaled to the same volatility.

Now, you know, an actual question to ask at this point is, well, you don't know if you've been reading the disclaimers, but they're all showing gross, returns gross of estimated trading costs and commissions. So, you know, it's a good question. Well, do these returns survive? Estimated real trade frictions, real trade slippage, commissions paid, et cetera. And, so, you know, we've been running future strategies since 2016.

So we've got seven or eight years of live data from our own trading that we are able to use to get really good estimates on the cost of trading these. And then there are papers that we lean on for the cost of. You know, trade frictions on different markets going back to earlier points in history. And we're able to net these out and get estimated net results. It's also important to know that we are, we do with some smoothing, right?

So when we ensemble all of these different, approaches together, they all recommend slightly different Portfolios at any given time. And what that means is it averages out the amount of trading that you need to do from day to day. So that alone sort of reduces the amount of trading and therefore the amount of trade friction that you experience, the amount of commission you pay, and that demands you place on the market to absorb the liquidity that you're sourcing.

We also smooth the waste through time using a 5 day exponentially weighted moving average. We find that smoothing like this has no effect on performance, but does have a nice effect on reducing trading frictions. so when we apply these smoothing and ensembling techniques and we also embed our, trade slippage estimates, then we see that we lose about 1 percent a year in terms of returns, which works out to about 0. 1 sharp ratio.

and everything kind of just drops by 1%, you know, slightly larger drawdown, slightly lower sharp ratio, et cetera. But I mean, this is just a tremendously resilient strategy once you back out estimating trading costs. Right. so a common question is great. But if carry is very highly correlated to the other assets I hold in my portfolio, it may not be very useful still. Right. So it's important to wonder how the correlation experience for carry evolves over time.

Here we plot the, rolling one year or late. Oh, sorry. Rolling three year correlation between the carry strategy and the S& P 500. And the U S 10 year treasury future. And you can see that, you know, it does go through multi year periods where bonds have a positively sloping yield curve and our carry bond exposure is predominantly positive. equities, the dividend yield on most global equity markets is higher than their local short term rates. And so they have positive carry.

And so it, you know, we have a proper ponderance of long equity exposure or vice versa. Right. So it does fluctuate over time. That said the long term average correlation between stocks and bonds and carry is about zero. Yeah, sorry, the correlation between carry and trend is in the neighborhood of 0. 3 to 0. 4, depending on the, the frequency that you're measuring at. Right?

So, whether you measure daily returns or monthly returns, et cetera, it's in the neighborhood of 0. 3 to 0. 4, which is still very much in the range of a strategy that is. Where two strategies can be combined and be nicely complementary to one another, which we'll see a little bit later on. Now, it's important to examine how Carry performs in different market regimes.

And we define regimes in a few different ways, but a common way Is inflation currently trending higher than expected or lower than expected? And is growth currently coming in a little higher than expected or a little lower than expected? And therefore we can divide things broadly in this kind of four different regimes. And I think, Rodrigo, you had a poll question that you wanted to ask.

Even when you think about trend following, you know, we can be very clear about. When there are very persistent trends, almost all the time when there's a bear market, you can count on trend to, to likely be there and provide really strong offset. So there's an intuition there. I'm just curious to know from the crowd, what the intuition is for carry here. What is the, what regime does it lose money in? All right, given that we have Not a lot of time, Ani. Why don't you push that through?

Okay. All right. So that's interesting. Okay. So we got pretty evenly distributed. Why don't we show, what we actually found there, Adam?

And then it moves up or down based on how it performs conditioned on being in that regime. And what we see is that in broad strokes, carry is not really very sensitive to any of these, these broad regimes. and that's partly due to the fact that Because of the diversity of markets, That are held in the portfolio and the propensity for the portfolio to be relatively diversified most of the time, it ends up having a very stable return stream.

We don't have a lot of really big, monthly or quarterly losses or gains. And so that the historical frequency distribution, if you kind of compare it to trend or to stocks, is a little bit more normal or Gaussian in shape, which is kind of the holy grail of what you, I mean, people would maybe prefer positive skew and I can get behind that, but you know, just avoiding negative skew, we think is a big win.

And when you, again, when you combine carry with trend, with equities, with bonds, Then that distribution becomes even more normal. it's also, you know, curious, how does carry perform during the best and worst period for stocks? So what we've done here is sorted the, returns on the S& P 500 into their worst quintiles on their left, going all the way up to their best 20 percent of, orders on their, on the right.

Okay. And you can see, obviously the light blue line is the S& P 500 in its worst quarters, it does the worst, right? But turns out carry and trend do just fine during the worst quarters for, or have historically done just fine. Interestingly, in the second worst quarter, neither carry nor trend really does much, right?

In, then in the sort of, top three quintiles, not quarter, quintiles, The carry and trend both have a tendency to do reasonably well and obviously these are very good quarters for stocks. For bonds we see a similar profile generally sort of agnostic to the how bonds are doing in any given quarter. Both trend and carry tend to do relatively well even in the worst bond quarters and then they go on to do actually quite well in the best bond quarters. And then you wanted to add to those, Rodrigo, or

It was probably the most challenging period for Carry, as the, authorities both on the fiscal side and on the central bank side were way behind in terms of implementing policy to keep up with the news flow. And, what we find is that carry strategies are a little bit more susceptible to miscommunication or blunders. by central banks, right? So, WEN has carried on particularly badly when central banks have either been behind the curve or they've been misreading the messaging from the markets.

And in this case, obviously, the authorities were very behind the curve during the COVID crash, and then they moved extremely aggressively, probably more than the market expected, immediately after the crash and and things went in a different direction than the market expected and that wasn't very good for carry. Eventually evened out and went on to deliver very solid gains. For treasuries, This is just the post COVID bond bear market. so actually that wasn't too bad for Carry.

Recovering from the global financial crisis. So Carry did fairly well during the global financial crisis, but once the global authorities stepped in, they implemented quantitative easing, markets began to settle, then Carry kind of went sideways, struggled for a little bit before recovering. This is the one to focus on, the bond massacre of 94.

Because this is a, an example of where the Fed was miscommunicating or not communicating with the market about their intentions and about their expectations. And they came in with a ver with a surprise rate rise at aggressive surprise rate rise, caught the bond market off guard, and. You know, bonds basically crashed overnight and everyone was sort of offside. and that was an example of where carry kind of struggled in the short term before again, going on, and doing very well.

we'd be, I think, leaving people, wondering if we also didn't examine how carry worked alongside trend and alongside equities of bonds in a stacking framework. So, you know, because carry and trend both have low correlation to both stocks and bonds, They're just both really accretive when stacked on stocks. And here you see both carry stacked on stocks, trend stacked on stocks, and a 50 50 combination of carry and trend stacked on stocks.

Obviously, all three looking very attractive historically. Same story stacking on top of bonds, just very attractive. And, turning up a negative return over the recent bond bear market period into reasonable positive returns. Just isolating the performance of carry and trend stacks on equities, obviously boosting equity returns, lowering equity risk, or not boosting equity risk by a meaningful amount, despite the higher returns.

And trend and carry combining to be a little better than either on its own. Similar with, with bonds and just combining everything together. 50 50 stocks, bonds, 50 50 carry trend, just has a, an astonishingly attractive historical profile.

With all the caveats that, you know, it can at any given time correlate and so on. But it is the benefits of diversification, the zigging and the zagging. Right? Two asset classes and or strategies that make positive, have positive outcomes, have an expected positive return, but move differently from each other to create lower, low volatility, high return, strategies.

So examine that table, examine it in the white paper and, and then reach out for questions if you want to get more granular than that..

And oftentimes as we're coming into, a peak in equities, it's corresponding with the Fed raising rates. The economy is getting too hot. The Fed is raising rates so that the yield on cash is rising. Well, then the yield on stocks is declining at some point, the yield on cash is exceeds the dividend yield on equities. So while trend continues to buy into the equity rally, there's a point at which Carry comes in and starts getting short equity markets as the cash return exceeds the dividend yield.

So it ends up being at least mechanically having the potential to be a nice offset for what's going on the trend side. That's just one example how, you know, carry can mechanically diversify trend in equity markets. And there are different types of examples in different sectors.

And in fact, I remember vividly a recent gold and was it two or three years ago when gold was rallying and, you know, trend strategies were long gold. And carry was shorted. Carry was wrong because the carry was negative for gold. So no, I don't think necessarily if gold is going, is doing its thing, there will be times when carry is dead wrong on that strategy, I promise you.

And so the idea of just eliminating, if you believe that these, that assets that you can stack on top are one of two things, are have a positive risk premia and are lowly correlated to everything else. Any one of those two will, will be a benefit. If you expect gold to be, you know, zero returning real returns, but you can stack it on top and it happens to be non correlated to everything else. It is accretive to the portfolio. So I think the answer is always yes and.

it's always been carry. And there's enough, video footage of Adam just pounding the table on this over the years that, you know, it's true. And we've been at, we have used it for, for a long time right now. So now the question is, you know, is this webinar is one of the things that, will give us a good reading as to whether there is an appetite for it. I hope there is.

and if you design it properly, you design it thoughtfully, you do ensembles, then it can be just as a creative, not caveat emptor. It is normally distributed roughly. It has volatility. It will have drawdowns, right? So if you do a 10 vol, Let's say it's a sharp of one. A good heuristic here is to say, okay, so the return is 10%. What is a three standard deviation event for strategy at 10 vol? It could be like 10 minus 10 is zero minus 10.

Two standard deviation is negative 10 minus 10 is negative 20. You know, something a bit higher than that is probably a good heuristic as to what to expect in terms of drawdown. One hopes it doesn't happen at the same time as what you're matching it up with. Okay. So there is risk involved. This is not a, Panacea, it is a unique diversifier to add to other many things. So, just recap. Look, we do a lot of this stuff. we tend to go long form. We're 15 minutes over the webinar.

That's not surprising to me at all. It's a miracle we got here in such a short amount of time. I thought it

I typed out as Adam was talking a few questions about risk parity and carry. If anybody wants to take a look at those, we have our book available on Amazon, and then you can explore our strategies that, that span far and wide across, you know, evolution strategies, which is, All encompassing, long, short market, neutral managed future strategy. You have a carry program. You have more kind of all terrain strategies, all types of stacking stuff. So take a look at our strategies page, explore that.

if you have any questions, you can reach out to the team. and, yeah, I'll see if I can, the last couple of seconds here. There's a few more questions, Adam. is there. Is there any risk that keeps carry? I'm going to combine two. Okay. Earlier on in the presentation, there's a question about, and I think this is super important to address. are you worried about the, short volatility character of carry with that's he assumed, I think this was early on before you went through everything.

and then this other question is what is the risk that keeps you up at night? Right. So let's address both of those.

And, as a result of that, you actually do observe a, quite a normal, return distribution on carry in stark contrast to the, I think, boogeyman version that those who had heard of carry a few decades ago had in their mind. and. What keeps me up at night? I think what keeps me up at night is that people would lean too heavily into any one strategy. You know what the miracle here is the ability to combine stocks and bonds and, you know, maybe gold with carry and trend and.

You know, hopefully other diversifying strategies that, continue to become available and that maybe some of them we will bring to market over time. But, you know, none of these strategies, including equities, in my opinion, should be held in isolation.

the real magic here is combining all of them together and relying on the fact that they all deliver their returns for different reasons at different times based on different types of risk and will therefore manifest their risks at different times and average out to deliver a much more reliable and smooth return stream to get you more reliably to your financial objectives.

You make an assumption that the, that returns are commensurate to risk, that all assets that you're going to be investing in have the same sharp ratio. So you're not making a return assumption whatsoever. You're assuming that all the assets you're investing in have a positive expect a positive risk premium. always right.

And the reason that risk parity has become popular, because it was the thing that I think at least when Dalio talked about it, it was what he was going to do when he died, that he didn't want anybody to screw up. It's a low maintenance, high conviction strategy over a long period of time, right? It's probably, from a theoretical perspective, the best thing you could do if you can't touch your portfolio, except for a rebalance here and there, over 10 years, 20 years, and 30 years, right?

And I think where people get confused is, Well, you could do this to improve it and that to improve it. Yes. But now it's an active strategy that you have to maintain. And if you die, you have to trust the person to maintain that thing. All right. So there's a place for risk parity. Also, there's a place to, to assume that those assumptions are correct. Carry is actually an actively managed approach that doesn't assume that there's positive risk premium all the time.

It can short bonds when it's appropriate to short bonds that risk parity will not do based on the carry reading. And so there's two things. And number one, it removes the shorting constraint. And number two, it doesn't make an assumption that anything is stable. And ultimately though, you need an active manager that knows how to do this day in and day out. Right? So do they compliment each other? Absolutely. The correlation between risk parity and carry is also quite low.

It uses the same universe, but it just. And that's, that's, let's see if there's any other questions and then we can close it up. lots of questions about product, which we cannot answer sadly in this venue. If you have any questions, please reach out independently over, Twitter. So if you guys have any questions, reach out at info at investresolve. com or reach out to Adam for any, carry white paper, specific questions at GestaltU, my Twitter handle is at RodGordilloP.

And, And, you know, we write, talk about this all the time. If you have not been a listener of a Resolve Riffs podcast, you should. We have a Resolve Masterclass series that talks about this 12 episodes that walks through all the elements of this that you guys can listen to. It's a separate channel.

We've recently launched a new channel that if you haven't signed up for, I would sign up for now, the first episode was killer, second episode's coming up soon, the Get Stacked Investment Podcast with Corey Hofstein, our partner in crime and a lot of this, this stuff. So, yeah, we will, we have talked about this. We'll take any other questions that we didn't get to today and see if we can address those in one of those two podcast series.

So with that, I think Adam, thank you so much for your time. I think you worked your butt off for this one, you and Andrew. Mr. Andrew Butler, I know you're out there, buddy. well done. great paper, great effort. I know that you've lost, you almost got divorced a couple of times to get this out the door. So kudos to you. Well done. And I think the investment world is all the better for it.