Based on our Q1 2026 commentary for the Return Stacked ETF suite, Corey Hoffstein and Adam Butler provide a detailed analysis of the strong quarter for trend following and carry, with a particular focus on the energy complex's impact. The conversation also explores the unique diversification benefits of merger arbitrage and provides a three-year retrospective on the efficacy of their trend replication models.

Topics Discussed

• Overview of the Return Stacked ETF suite's growth and the core concept of capital efficiency
• In-depth look at the trend following strategy, highlighting its three-year success in replicating the managed futures category beta
• Analysis of the Carry strategy's strong Q1 performance, primarily driven by geopolitical events affecting the energy markets
• Discussion of the Merger Arbitrage strategy as a unique diversifier against traditional credit risk
• Examination of the RSSX ETF, which stacks a risk-balanced overlay of gold and Bitcoin on U.S. equities
• Demonstration of the new Portfolio Visualizer tool for modeling and understanding Return Stacking concepts
• Explanation of why broad market diversification, not just shorting equities, provides crisis alpha in trend strategies
• Discussion on the complementary relationship between Trend and Carry strategies in different market environments

The performance data quoted above represents past performance. Past performance does not guarantee future results. The investment return and principal value of an investment will fluctuate so that an investor's shares, when sold or redeemed, may be worth more or less than their original cost, and current performance may be lower or higher than the performance quoted above.

For prospectus and performance and risks visit the fund pages.

RSST – https://www.returnstackedetfs.com/rsst-return-stacked-us-stocks-managed-futures/

RSIT - https://www.returnstackedetfs.com/rsit-international-stocks-managed-futures/

RSBT – https://www.returnstackedetfs.com/rsbt-return-stacked-bonds-managed-futures/

RSSY – https://www.returnstackedetfs.com/rssy-return-stacked-us-stocks-futures-yield/

RSBY – https://www.returnstackedetfs.com/rsby-return-stacked-bonds-futures-yield/

RSBA – https://www.returnstackedetfs.com/rsba-return-stacked-bonds-merger-arbitrage/

RSSB – https://www.returnstackedetfs.com/rssb-return-stacked-global-stocks-bonds/

RSSX – https://www.returnstackedetfs.com/rssx-return-stacked-us-stocks-gold-bitcoin/

BTGD – https://quantifyfunds.com/stackedbitcoingoldetf/btgd/

RSSX does not invest directly in Bitcoin or Gold.

Investors should carefully consider the investment objectives, risks, charges and expenses of the Return Stacked® U.S. Stocks & Gold/Bitcoin ETF. This and other important information about the ETF is contained in the prospectus, which can be obtained by calling 1-844-737-3001 or clicking here. The prospectus should be read carefully before investing.

The Return Stacked® U.S. Stocks & Gold/Bitcoin ETF is distributed by Foreside Fund Services, LLC, Member FINRA/SIPC. Foreside is not related to Tidal, Newfound, or ReSolve.

Definitions:

Duration: refers to the average life of a debt instrument and serves as a measure of that instrument’s interest rate risk. Beta: how much an investment moves vs. a benchmark (like the market). Alpha: refers to returns above that of a passive market benchmark SocGen: is a common abbreviation for Société Générale S.A. Trend Index: tracks returns from trend-following strategies, aiming to capture gains from sustained market price movements across assets. FTSE 100 Index: Financial Times Stock Exchange 100 Index DAX index: Deutscher Aktienindex is the benchmark stock market index of the Frankfurt Stock Exchange Nikkei 225 or Nikkei Stock Average is the leading stock market index for the Tokyo Stock Exchange (TSE) Alpha merger Index: tracks returns from merger arbitrage strategies, aiming to capture deal-related profits independent of the broader market.

A fund’s NAV is the sum of all its assets less any liabilities, divided by the number of shares outstanding. The market price is the most recent price at which the fund was traded.

Investments involve risk. Principal loss is possible. Unlike mutual funds, ETFs may trade at a premium or discount to their net asset value. Brokerage commissions may apply and would reduce returns. Bitcoin Investment Risk: The Fund’s indirect investment in bitcoin, through futures contracts and Underlying Funds, exposes it to the unique risks of this emerging innovation. Bitcoin’s price is highly volatile, and its market is influenced by the changing bitcoin network, fluctuating acceptance levels, and unpredictable usage trends. Not being a legal tender and operating outside central authority systems like banks, bitcoin faces potential government restrictions. The value of bitcoin has historically been subject to significant speculation, making trading and investing in bitcoin reliant on market sentiment rather than traditional fundamental analysis. Blockchain Technology Risk: Blockchain technology, which underpins bitcoin and other digital assets, is relatively new, and many of its applications are untested. The adoption of blockchain and the development of competing platforms or technologies could affect its usage. 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. 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. 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. Digital Asset Risk: Digital assets like bitcoin, designed as mediums of exchange, are still an emerging asset class and are not presently widely used as such. They operate independently of any central authority or government backing and are subject to regulatory changes and extreme price volatility. Equity Market Risk: By virtue of the Fund’s investments in equity securities, equity ETFs, and equity index futures agreements, the Fund is exposed to equity securities both directly and indirectly which subjects the Fund to equity market risk. Common stocks are generally exposed to greater risk than other types of securities, such as preferred stock and debt obligations, because common stockholders generally have inferior rights to receive payment from specific issuers. Equity securities may experience sudden, unpredictable drops in value or long periods of decline in value. This may occur because of factors that affect securities markets generally or factors affecting specific issuers, industries, or sectors in which the Fund invests. Gold Investment Risks: The Fund will not invest directly in gold but will gain exposure through gold futures contracts and Underlying Funds. These investments are subject to significant risk due to the inherent volatility and unpredictability of the commodities markets. The value of these investments is typically derived from the price movements of physical gold or related economic variables. 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. 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. 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 Fund Risk: The Fund’s investment strategy, involving indirect exposure to bitcoin and gold through one or more Underlying Funds, is subject to the risks associated with bitcoin as well as gold. Shareholders in the Fund bear both their proportionate share of expenses in the Fund and, indirectly, the expenses of the Underlying Funds.

Tidal Investments, LLC (“Tidal”) serves as investment adviser to the Funds and the Funds’ Subsidiary.

Newfound Research LLC (“Newfound”) serves as investment sub-adviser to the RSST, RSBT, RSSY, RSBA, RSSB, RSSX and RSIT.

ReSolve Asset Management SEZC (Cayman) (“ReSolve”) serves as futures trading advisor to the Return Stacked® Bonds & Managed Futures ETF (RSBT), Return Stacked® U.S. Stocks & Managed Futures ETF (RSST), Return Stacked® US Stocks & Futures Yield ETF (RSSY), Return Stacked® Bonds & Futures Yield ETF (RSBY), Return Stacked® U.S. Stocks & Gold/Bitcoin (RSSX), and Returned Stacked® International Stocks & Managed Futures (RSIT).

Quantify Chaos Advisors, LLC (“Quantify”) serves as the sub-adviser to the STKd 100% Bitcoin & 100% Gold ETF (BTGD).

Quantify has entered into a brand licensing agreement with Newfound and Resolve, granting Quantify the right to use the “STKd” brand, a derivative of Return Stacked®. Neither the Trust or the Advisor is a party to this agreement. In exchange for the branding rights, Quantify will pay Newfound and Resolve a fee based on the percentage of the Fund’s unitary management fee.

The Return Stacked® ETFs Suite is distributed by Foreside Fund Services, LLC, Member FINRA/SIPC. Foreside is not related to Tidal, Newfound, ReSolve or Quantify.

I go back to the dot com bubble, when dot com rolled over in

2

mid 2000, it was long energies, long

metals that carried the portfolio

3

for the next five, six years.

4

It's not the ability to short

equities that that often gives you

5

that equity bear market offset.

6

It's the ability to be long other markets.

7

Corey Hoffstein: Hello everyone.

8

Welcome to the Q1 2026 Stacked Unpacked.

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My name is Corey Hoffstein, CEO of

Newfound Research and co-founder

10

of the Return Stacked ETF suite.

11

And it is my absolute pleasure to

be joined my by my good friend and

12

colleague, Adam Butler, CIO of ReSolve

Asset Management and fellow co-founder

13

of the Return Stacked ETF suite.

14

Adam, great to be joined

by you this quarter.

15

Excited to dive into the performance and

drivers of returns and our different ETFs.

16

I think this is, uh, man, what

a difference a quarter makes.

17

Right.

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Adam Butler: Yeah.

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Absolutely.

20

welcome everyone.

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It's, uh, great to get a chance

to nerd out Corey and, nice to

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continue to deliver good news all.

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Corey Hoffstein: And before we

dive right in, just a reminder

24

that you can submit comments.

25

We will try to address

them in a timely manner.

26

If there's something we can

address in real time, we will.

27

Otherwise, we'll hold comments

and questions until the end.

28

without further ado,

I'm gonna dive right in.

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This is meant to be a

recap of what we saw in Q1.

30

This is, this commentary is

available at returnstackedETFs.com.

31

If you want to go through it yourself,

we're gonna try to hit all the

32

highlights and maybe discuss sort of

what we're seeing in the important

33

charts and graphs that we put in here.

34

very excited to finish the

quarter at just under 1.2

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billion.

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Uh, excited to say today

we opened the day with 1.3

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billion, so we continue to see

really strong growth in the suite.

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We're incredibly grateful for everyone

who has allocated either their own

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money or allocated money on behalf

of their clients into these products.

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Obviously, this is something

that we believe very strongly in.

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This is a, a new tool set that we think

really helps people rethink portfolio

42

construction and we're really enthused

to see the adoption within the industry.

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So thank you very much.

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We're incredibly grateful and, and we look

forward to, dare I say, the next billion.

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I'm gonna dive right in.

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We're gonna hit these ETFs one by one.

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Some of these we're gonna spend

a little bit more time on.

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the first I wanna start off with

is probably our simplest and yet

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the most flexible ETF we offer.

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This is the return stack global

stocks and bonds ETF RSSB.

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RSSB provides a dollar of global

equity and a dollar of US treasury

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exposure for every dollar invested.

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The idea here isn't so much that you would

use this ETF to try to stack bonds on your

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existing stock bond portfolio, but rather

use it as a capital efficiency tool.

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So, as a really simple example, if you

were to say have 60% stocks, 40% bonds.

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You could sell 10% of your stocks

and 10% of your bonds and put 10% of

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that freed up capital into RSSB, that

10% in RSSB would've give you the

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effective exposure of the 10% stocks

and the 10% bonds that is missing.

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But now you'd have 10% freed

up sitting in cash with which

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you can do whatever you want.

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And when you allocate that

freed up cash to some other

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investment, it is effectively

stacked on top of your portfolio.

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So we like to think of RSSB

as our low cost Swiss army

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knife of capital efficiency.

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And the goal here is simply to track

as closely as possible a 100 100

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portfolio comprised of a hundred percent

passive global equities, plus a hundred

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percent of a US treasury benchmark.

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in figure one, you can see here

over the prior 12 months, the black

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line is that total index benchmark

and then the green line is both.

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We have a version of RSSB

price and RSSB nav and we can

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see we tracked quite closely.

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If we zoom out to just look at

summary statistics really quickly.

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Again, the goal here is not to

be prescriptive about returns,

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but rather to use this as a tool.

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The idea would be to have the sense

inception returns, track that a hundred

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hundred as closely as possible after fees.

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I believe we are almost perfectly 35

bips behind the 100 100 cents inception,

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which is where we would like to be.

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So we are, uh, very enthused again about

our ability to track our benchmark.

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Our stated objective here and

RSSB is our largest ETF creeping

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up on almost 500 million.

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I think simply because of this

flexibility, it is our simplest ETF to

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understand and frankly, it has the most

flexibility in what you can do with it

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and things you can stack and creative

things you can do in your portfolio.

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And so it's no surprise that this

is our most popular ETF to date.

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Adam Butler: I mean, I don't think

we should, be too prescriptive

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here, but like, I, I think it's

worth visiting a couple of potential

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popular use cases for this, right?

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I mean, obviously the return stack suite,

we don't cover all potential diversifiers.

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Also, advisors have special relationships

and, and, and styles and strategies

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and managers that they like.

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So the idea is you can trim back,

let's say if you sell down 20% of

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your, 50 50 stock bond portfolio,

you put 10% back into RSSB.

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Now you've, you, you're right back up

to your full exposure to your 50 50

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portfolio, but you've also got 10% free

to add your favorite manager or, uh,

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you know, maybe your client's got a

purchase that they're trying to fund.

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They can, they can extract those

funds and go and deploy them,

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to some sort of purchase, right?

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So just a couple of, of really simple

and and popular use cases for this kind

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of Swiss, Swiss Army knife product.

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Corey Hoffstein: Yeah.

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I would say where we see it most

frequently can is when, when.

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An allocator that we're working with

already has a suite of alternative

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funds that they've vetted, right?

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Their team has already

done the due diligence.

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They might have three or

four alternative funds.

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Maybe they have an alternative model

that they're comfortable with, and rather

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than doing diligence on our alternatives,

and I would put our alternatives toe

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to toe with anyone else's, of course.

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But instead of if, if they already have a

suite of alternatives they're comfortable

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with and yet wanna figure out how to stack

those alternatives, RSSB is the solution.

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It gives them the ability to take

those alternatives that they're

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already comfortable with and, and use

them in a return stacking framework.

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So let's now move on and talk about

some of the alternatives we offer.

115

And again, one of the most

popular is our trend line.

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We have the Return Stack Bonds and Managed

Futures ETF just hit its three year

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anniversary in, February, early February.

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And as well as our Return Stacked

US Stocks and Managed Futures ETF,

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which will be hitting its three

year anniversary, uh, in September.

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Now, these two funds, every dollar

you give them based on their name,

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they'll either give you a dollar

of bonds or a dollar of US stocks,

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plus a dollar of a managed futures

trend following strategy on top.

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Now, our approach to this trend following

strategy is a replication based approach.

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We are trying to hit what we would

call sort of the category average of

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systematic trend following managers.

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So if you were to look at something

like, say the SocGen Trend Index

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or the Morningstar systematic

trend category, that is the type

128

of return we're trying to generate.

129

We are trying to provide effectively the

beta of the managed futures category.

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And there's two ways we do this.

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We use what's called a top down approach,

where we're effectively looking at

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prior returns and trying to figure out

what sort of portfolio configuration

133

would've led to those returns.

134

And then there's the bottom up

approach where we're actually running

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a trend following process and all the

parameterization of that process about

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trend speeds and which markets we trade

in, all that sort of stuff, and how much

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weight we give each market in each sector

is determined to try to fit the long-term

138

return characteristics of the category.

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And then we blend those two approaches.

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What we're really enthused to see,

and this is unique in this quarter's

141

commentary, is looking at the

three years of live track record we

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now have doing this in our funds.

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and what what we're very happy about

is the original thesis we had, which

144

was each of these different replication

approaches has efficacy as on a standalone

145

basis, but process diversification

should lead us to a place of a better

146

result and a better fit absolutely

came out in the realized numbers.

147

So we run three approaches, two

top-down approaches, one with a smaller

148

universe, one with a larger universe.

149

We also run the bottom up approach,

and when we look at their correlation

150

to say the SocGen Trend Index or their

individual tracking error to the SocGen

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Trend Index, we see substantially higher

numbers than a blended approach that

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takes the target weight results of,

of all three and blends them together.

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When we look at the actual three year

results here, what we have in the black

154

line over the last three plus years is the

SocGen trend index and the green line is

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the blended net approach that we apply.

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And then we can see the individual

gray lines actually represent the

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individual replication models.

158

And we can see at any given time some

models are performing better than others.

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The top down small performed

best over this full period, but

160

there were certainly sub periods.

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It was the worst performer.

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It arguably had one of the worst fits,

even though it was the best performer.

163

But we can see the blended result

ended up almost perfectly at the

164

end of the day at the same point

with a high degree of correlation.

165

So this is something that, you

know, again, three years isn't

166

the end all, be all of of time

periods to measure something over.

167

But given the volatility we saw in the

trends category over the period, given

168

the dispersion among managers that we saw

as well, uh, you know, we're very, very

169

happy and pleased with this result in

trying to deliver trend beta, and I think

170

we delivered upon that mandate quite well.

171

Adam Butler: I think it's worth mentioning

that, you know, three years is not

172

nearly enough time to determine whether

a strategy can can generate alpha, but it

173

is a very substantial time to determine

whether something delivers a beta.

174

And you know, I think, I think we've

done some internal analysis and we've

175

also sort of examined it against the

historical modeling that we did, right?

176

'cause we can go back several decades

to see how well this combination

177

approach has worked in the past.

178

To track the SG trend index or you know,

a variety of other index, uh, indices.

179

And so we had a lot, had a fair

amount of confidence going in.

180

First of all, that the model

was theoretically sound.

181

We'd also validated it on several decades

of historical context and is really,

182

you know, fulfilling to see this in,

in three years out a sample delivering

183

effectively the same tracking error

and, and correlation that we observed in

184

sample during testing and modeling stages.

185

Right?

186

So, you know, it's a really nice

validation over three years and, you know,

187

I continue to come back to a question

of why managers are taking benchmark

188

risk with, you know, trying to select

individual managers in this space when low

189

cost beta alternatives with the specific

objective of minimizing that tracking

190

error to the benchmark, are available

in these kinds of liquid packages.

191

Corey Hoffstein: Yeah, I, one of the

figures that I love and, and we put

192

this in every commentary, and though

it's usually on a quarterly basis, but

193

this shows the full three years, is the

relative performance of each approach

194

as well as the blended approach versus

that SocGen trend index benchmark.

195

So you can think of it sort of as

taking the green and gray lines here

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and dividing it by the black line.

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And so when the line is going down,

it's underperforming SocGen trend.

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When it's going up, it's

outperforming perfect replication

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would be a, a flat horizontal line.

200

And one of the things right,

I think we can see is that.

201

The individual gray lines, while they have

a degree of correlation to each other,

202

there are certainly periods where they zig

and zag in their own idiosyncratic way.

203

And I think that's really clear, for

example, over the last year with, with

204

what I, the top down small, which is

the top line there where you can see

205

a huge pop during the tariff tantrum

period, as I like to call it, last April.

206

This was massive outperformance, I

would argue, and as, and we wrote in

207

the commentary for that quarter, like

this was not skill, this was luck.

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This was this, this being misallocate,

not tracking the index, but getting

209

lucky in not tracking the index and

then subsequently bled most of that

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performance back very different than

say the what, the top down large, or, or

211

the, uh, bottom up did over that period.

212

And so in terms of just trying to

track closely to the category, again,

213

the blend allows us to average out

all that idiosyncratic noise or, or

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a high degree of that idiosyncratic

noise to try to get closer to target.

215

uh, and I think the last three years

have been a great case study of that.

216

So we, we look forward and hopefully

over the next, you know, two years, we'll

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we'll do a five year retrospective and

then a 10 year, and hopefully we'll,

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we'll continue to see strong results.

219

um, co goes directly to Q1 and I'll,

I'll go through this quickly, trend

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posted another positive quarter after

a couple of frustrating years, trends

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returned over the last, call it, 12

months have been, uh, much, much better,

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particularly from the bottoms of April.

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It's had a very strong performance

driven not just by equities, but

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driven by exposure to metals.

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More recently, some exposure to energies.

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So it's been, it's been, a good time

over the last, call it 10 months to have

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trend as an overlay in the portfolio.

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Uh, again, this we can

see in, in figure four.

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The green line is our model

approach to replicating the category

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black as the SocGen trend index.

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High degree of correlation,

good degree of fit.

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Point to point, this is

exactly what we're looking for.

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And again, this is, these are the type

of results we're trying to deliver,

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uh, in actually providing exposure

to this category as an overlay.

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We can see, again, using that relative

performance, it's never a perfect fit.

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But what we're ultimately hoping for

is that blended approach is certainly a

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better fit over the full period than any

of the individual approaches, which again,

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I think we see here from a positioning

and return contribution perspective in

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Q1, what we, what we've seen is that

we entered with something like fixed

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income, positive weights, transition

to negative weights over the quarter.

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equities, we substantially

reduced weights over the quarter.

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We saw a pickup in exposure to

energies, somewhat of a pullback in an

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exposure to metals, and sort of mixed

change in what we saw in currencies.

244

One of the things I want to remind people

of here is that, lemme make sure I can

245

do this correctly, is that, we actually

have all of this live on our website.

246

So if you go to our return stacked ETFs

dot com and go to, let's say the RSST

247

ETF page every single day not only can

you download the notional weights of what

248

we're holding, this is true for every ETF,

but to make it easier to interpret what's

249

in actually in the driver's seat, we

show the actual risk allocations by asset

250

class as well as market that we trade.

251

So as of yesterday, we can

see that equities capture

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about 32% of our current risk.

253

In the managed futures program,

energies are about 25%.

254

Metals are only about eight and a half.

255

Currencies are are just about

nothing, and bonds are negative 10%.

256

This is something that gets

updated every single day.

257

So if you are curious about how the

strategy is positioned and what's actually

258

in the driver's seat, I think this is a

great way to look at it intra quarter.

259

And what's important here is that these

are, again, risk adjusted weights.

260

When you look at the notional weights,

how much we actually have allocated This

261

can be a little bit misleading 'cause a

low volatility market, we might have to

262

have a really big position in to have it

have an impact versus a high volatility

263

market like say oil right now we might

have a very small position in, and that

264

small position in something like oil might

have the same risk as a large position in

265

something like five year US treasuries.

266

We do all the work of translating that to

put 'em on an equal basis when we, when

267

we do this risk weighting on the website.

268

So again, for anyone looking to

see what's happening on a live

269

basis, I highly recommend taking

a look at, at the actual website.

270

So now going back to the commentary, lemme

just make sure that goes up on the page.

271

There

272

we

273

Adam Butler: gonna start

talking about Carry now, or

274

Corey Hoffstein: Yeah.

275

We're gonna quickly jump to Carry.

276

There's, again, look,

keeping our eye on the time.

277

one of the things I do want to point

out though is just from a contributions

278

perspective, I think there was a

lot of people who expected that

279

equities were sort of the big driver

in over the last, call it 12 months.

280

that actually really wasn't the case.

281

We can see that over the last year,

metals were a really big driver.

282

Energy was a positive driver.

283

Yes, equities were a driver, but this

is once again the, the breadth of, the

284

markets we trade in the trend program.

285

There were a significant number of

contributors over the year and, and

286

that's why the breadth is important.

287

Uh, Adam, I wanna pause really quickly.

288

There was a question here about

the possibility of the investment

289

universe expanding into more markets.

290

Um, this is something we have looked into.

291

There's, there's sort of two answers here.

292

One, we need to make sure the impact

it has on the goodness of fit.

293

Um, there's a lot of research that

shows that when you are trying to

294

track the sort of beta of trend, you

actually don't need that many markets.

295

And as you add more and more markets,

it actually complicates the math problem

296

of trying to track the benchmark.

297

That said, there might be one or two key

markets that we might look to introduce.

298

Um, not anytime in the short

future, but it's something we've

299

been, we have been exploring.

300

And if we can get comfortable with it,

you might see one or two new markets come

301

in that we do think would improve the

goodness of fit, uh, to, to the category.

302

Adam, anything you wanna add there?

303

Adam Butler: Yeah.

304

The, the other quick thing is

that, you know, the benchmarks we

305

track, it, these are the, these

are very, very large managers.

306

The largest managers in

the world, typically.

307

In fact, definitionally, they are in this

OC gen trend index and large managers

308

are sort of definitionally restricted

to allocating a majority of their risk

309

to the most liquid markets, right?

310

So if we were to, to, to go too far

out the tail in, into more esoteric

311

markets or less liquid markets, what

we're doing is now adding a bunch of

312

markets that most of the managers that

are in the index that we track can't

313

actually allocate a lot of risk to.

314

So we're adding markets that they're

not trading in very large size.

315

And, and that also complicate

the math of, of tracking.

316

So there's definitely

a, a, a balance here.

317

I think we're pretty close to, to

the right balance, but we're always,

318

you know, reevaluating whether we're

missing something or whether there's

319

opportunities for improvement.

320

And we'll change it as

we go, as that warrants.

321

Corey Hoffstein: Yeah.

322

One of the questions here, and

then I wanna get to Carry is,

323

um, someone's surprised that we

still have a position in gold.

324

So gold is down quite a bit from the high.

325

Why?

326

Why do we still have a long position?

327

you know, look, gold's from the highs

is down about 15%, give or take.

328

But if we zoom out over a nine month

period, you know, go back to last

329

summer, late last summer, September,

it's still up about 45%, right?

330

And so when we talk about trend following.

331

and, and the type of trends

that these managers trade.

332

Intermediate trend is sort of

where things tend to fall out.

333

So the long intermediate to

long trend is still intact.

334

Now that said, our risk adjusted

weight in gold has come way down.

335

I think it's down over 50% from its high.

336

So we have seen, you know, some

of the shorter term trends that we

337

trade and just volatility adjusting.

338

Position wise, it has come way

down as all exploded as gold,

339

uh, rallied so dramatically.

340

But if you zoom out to more of a nine to

12 month trend, uh, I think most people

341

would agree that the trend remains intact.

342

And so it's no surprise in my opinion that

the model still has some gold exposure.

343

Adam Butler: Yep.

344

Nothing to add there.

345

Absolutely.

346

Corey Hoffstein: All right,

let's move on to Carry.

347

This is, um.

348

You know there, there's a lot to

digest here 'cause this is one we've

349

been writing a lot about, trying

to build intuition for people as to

350

what Carry is, with lots of examples.

351

It's frankly been a bit of a

frustrating run, but this was

352

a heck of a quarter for Carry.

353

Adam Butler: It has been.

354

And you know, the, the challenge with

carry is that you, you get caught on,

355

a, a bunch of false starts, right?

356

So Q4, 2025 was a really good

example of, we had a couple of

357

conflicts that were initiated, right?

358

We had these geopolitical events.

359

markets reacted, they got fearful,

they repriced the, the energy complex

360

and, and other market segments, right?

361

But the conflicts petered

out pretty rapidly, right?

362

The, the Venezuelan conflict

petered out almost immediately.

363

The Iran, war lasted just a few days.

364

So, you know, we, we

had this, these sort of.

365

risk events and the market sort of

tightening, especially in the futures

366

in, in the energy complex and leading

to a short term, you know, risk on

367

position and energies especially.

368

And then that reversed because the

conflict ended really quickly, right?

369

Now, in contrast in Q1, we had a, a major

conflict, emerge and it was sustained

370

and there were real, in the real world

shortages that persisted and there were

371

real consumers of energy products that

became very concerned about not having

372

enough, inventory on hand, jet fuel

or diesel for shipping or, you know,

373

for, for a wide variety of gasoline.

374

And therefore you had these consumers that

were bidding up prices on the front end.

375

And so you had this convenience

yield, this difference between the

376

front month or spot and futures

contracts that mature further down

377

the pipe, really rising substantially

right to, historically high level.

378

And that led to a very strong carry

signal suggesting that we should

379

be quite long the energy complex.

380

And this chart that we're showing here

shows how that carry signal strengthened,

381

pretty rapidly after the onset of the

Iran war and has persisted, and therefore,

382

you know, because that's persisted and

the front month energy prices actually

383

rose very substantially under that

persistent high carry, the carry strategy

384

was able to capitalize on that, right?

385

and the other markets in the portfolio,

there were a few others that contributed.

386

positively as well, but about 18% of that

22, 23% rise in the carry strategy in Q1

387

came from the energy complex, and this is

exactly the type of profile that we hope

388

to see for these types of strategies.

389

Right?

390

When do we most want these

diversifying stacks to pay off?

391

Well, when the other, sleeves in the

portfolio are having a difficult time.

392

Equities responded with a risk off

posture, When the war was initiated,

393

bonds did as well as markets began

to fear sustain inflation from a

394

potential persistent blockage or

embargo on the Strait Of Hormuz.

395

And so bonds sold off, equity sold

off, but the energy complex, which was

396

largely responsible for this risk on

posture and this inflation expectation

397

spike went on to more than compensate.

398

Right?

399

And so, you know, the, the carry strategy

more than offset the losses in bonds and

400

the losses in equities over that period.

401

At the same time, because we're, we're

paying attention to both the strength

402

of the carry signal and the expansion

and contraction and the risk of the

403

instruments that we're trading, we've

got a strengthening carry signal.

404

But because the volatility of the

energy complex also expanded pretty

405

substantially higher volatility means

that we need to contract exposure

406

to sustain our target level of risk.

407

So it, that risk expansion competes

with the increase in the strength

408

of the carry signal and, you know,

serves as a mediating factor.

409

As the carry has kind of

stabilized, but risk has, you

410

know, been, been sustained higher.

411

That overall position in, in energies

has contracted somewhat right?

412

And that's the natural ebb and flow and

the evolution of the weights in carry

413

that we expect to see and that, that we've

designed the strategy to capitalize on.

414

Right.

415

Anything you wanna

416

Corey Hoffstein: one of the things,

one of the things that's come up,

417

one of the question is, is when.

418

People's presumption is that this

situation with the Strait of Hormuz

419

is just gonna suddenly fix itself,

not fix itself, it will be fixed

420

and suddenly the Strait will be

open, oil will be flowing again.

421

And that allocating to something

like Carry right now would then

422

lead to substantial drawdowns.

423

Curious your, your thoughts on

that, that balance of, okay,

424

we've got a very steep curve.

425

What the market is pricing in, what

the carry signals say versus Right.

426

Bearing the risk of a supply crunch

and being stepping in and providing

427

the liquidity to that market, you

know, earning a risk premium for

428

that versus, you know, everyone's

expectation that, oh, this is, this is

429

suddenly going to reprice very quickly

and we're gonna be caught off sides.

430

And, you know, a big 22% return

in, in Q1 is going to become a

431

negative 20% return next quarter.

432

Adam Butler: Yeah.

433

I mean, what, what I think is most

important to realize is that the carry

434

signals are, are derived at root by what

the most experienced and knowledgeable

435

players in the markets are doing to hedge

their own supply demand dynamics, right?

436

You've got real consumers of these

products who've got actuaries, risk

437

managers, managers in various different

product lines, all making their forecasts.

438

They're as close to the metal as anybody

can be in markets in order to have the

439

best information and the, the fastest

reaction to changes information of anybody

440

in the marketplace, and all we're doing

is responding to the signals that those

441

experienced people that are closest to the

metal are sending via their own actions

442

in terms of how much they are preferring

to have, excess inventory on hand versus

443

how much they're willing to wait and pay

for cheaper crude, for example, a little

444

bit down the, down the line, right?

445

So, you know, if anything I am taking

advantage or, or I would be looking to

446

take advantage of the acute attention

that these players are paying to

447

these markets at the moment, and be

relying on the way that our, our,

448

our signals are viewing these markets

in order to capitalize on these

449

changes in views and adapt over time.

450

Corey Hoffstein: I think one of the

interesting things to also point out

451

is that if, again, if you go to the

RSBY or RSSY website pages, right?

452

You can see energy is a meaningful

contributor of our risk adjusted

453

weights, but it is by no means

like the only contributor, right?

454

We have positions in metals and equities

and bonds, and yes, energy's moved quite

455

a bit, but they weren't, they're, they're

not the, they're not in the driver's seat

456

per se, entirely of, of the portfolio.

457

Again, the idea here is that we're

constantly trying to balance risk

458

across all these different markets in

line with the strength of the signals.

459

Energies by far and away have

the most, the strongest signals.

460

but in the interest of diversification,

like their, their weight is actually

461

substantially below where their

theoretical weight could be given

462

the strength of their signals.

463

And we actually recently this

quarter added a scatter plot.

464

I'm gonna see if I can quickly

share my screen to the RSSY page.

465

RSBY as well.

466

And hopefully this is showing up.

467

And you can see this is the carry

score in the portfolio weights.

468

And you can go market by market

and see what its implied.

469

Carry score is, we're using some

math to back out a single carry

470

score in the portfolio versus

its risk adjusted target weight.

471

And you can see the

energy complex over here.

472

And despite having really high carry

scores, they are not, you know, so

473

heavily overweighted relative to other

things that have lower carry scores.

474

And this is a mix of, constraints

built into the optimizer as well as the

475

optimization process, trying to manage

diversification within the strategy.

476

And that leads to a situation where

energies are an important driver.

477

The other sectors are also contributing

a fair amount of risk, both positive

478

and negative to the portfolio

and from a directional basis.

479

So again, these are, these are all on the

website published daily, should be updated

480

daily with the most recent, scores.

481

The, this is a simplified view.

482

Again, we're using some math here to

back out sort of a single uniform score.

483

We use dozens to hundreds of different

carry measures under the hood to try

484

to find different ways of capturing

carry from these futures markets.

485

But this backs out sort of a single

snapshot view to just get a sense of

486

how these markets are being positioned

relative to the strength of their carry

487

and how we're trading off risk versus

return potential in the portfolio.

488

Adam Butler: just, just highlight a couple

of those dots that are in the lower right

489

quadrant there, which have positive carry

stores, but, but negative weights, right?

490

Corey Hoffstein: Yeah, so

natural gas is an example here.

491

you know, again, it's always

hard to, to say what an optimizer

492

is doing specifically, but this

does have a positive carry score,

493

but is being used negatively.

494

You know, I would guess that the optimizer

is using this to offset again, the

495

very positive exposures we have in the

496

Adam Butler: Yeah, that's right.

497

It's got a, it's got a slightly

positive, carry score, but it is, it's

498

a great diversifier against the general

energy risk and its diversification

499

utility now exceeds its expected

return utility in carry units.

500

And so it's, it's held short as a

diversifier rather than held being

501

held in the long book as a return.

502

As a return source.

503

Right.

504

And that's the, that's the nature

of the optimizer doing its work.

505

Corey Hoffstein: And we can see that

really clearly with the equities.

506

All of the equities have

negative carry right now.

507

But you have things like, the dax,

the NASDAQ 100 and, and the NI K 2 25

508

being held long while the Euro stocks

50 S&P 500, S&PTSX 60, the Canadian

509

market and the FS C 100 are being held

short and effectively, even though they

510

all have negative carry scores, right?

511

You're capturing somewhat of a spread

here, the spread in carry between these

512

markets and the up top versus the markets

down bottom, and you're, and you're

513

trading them against each other and

effectively, more or less, dare I say,

514

neutralizing the equity beta component

on sort of on average with these markets.

515

And this all comes out again from

the optimization process, trying

516

to find where, how it can maximize

the carry, given the amount of

517

risk it's allowed to take on.

518

Adam Butler: Yep.

519

Yeah, so that's a really good example

just to demonstrate how correlation

520

is also taken into, into account.

521

Right.

522

And, you know, so, so no surprise,

obviously the energy sector has been the

523

largest source of return attribution.

524

but, bonds have also been

contributed positively.

525

equity allocations have

contributed positively.

526

And, you know, it's just been really

nice to see how the, how the portfolio

527

has evolved in actually a fairly

intuitive way when you, when you

528

actually account for the expansion

and risk and the, the change in

529

characteristics over, the last few months.

530

So, doing its job.

531

Corey Hoffstein: Keeping

an eye on the time here.

532

I'm gonna keep moving.

533

There's a couple of questions that we

will get to at the end if people wanna

534

stick around, um, that have come up here.

535

But I wanna move on to, the Return

Stack Bonds and Merger Arbitrage ETF.

536

The idea behind this ETF is that for

every dollar invested, you're gonna

537

get a dollar of exposure to core US

treasuries, plus a dollar of exposure

538

to a merger arbitrage strategy.

539

And I would argue that sort of the

best comp to this portfolio would

540

be a, a corporate bond fund, right?

541

When you think about corporate bonds,

really what you're getting there is core

542

US treasuries plus a credit risk premium.

543

Here with something like RSBA, we're

trying to give you US treasuries

544

plus a merger arb risk premium.

545

And we think Merger ARB represents a

unique and very defensible risk premium.

546

Uh, something that tends to be less

correlated to credit, less correlated

547

to equity markets in general, uh,

and something we can argue why

548

should persist and be pervasive.

549

Um, and so then it's just a really a

question of how you're implementing

550

the merger arbitrage strategy.

551

Uh, our merger arbitrage strategy tracks

the Alpha Beta Merger Arbitrage Index.

552

This is a firm that was running a merger

arbitrage hedge fund that, uh, we hired

553

to translate their hedge fund strategy

into an index that we then use to track.

554

It's a machine learning based model

that trains on the history of US based

555

deals, all sorts of characteristics

to determine what they think both the

556

time horizon of deal closure is as well

as the probability of deal closure,

557

and uses that to figure out what

the expected return of the deal is.

558

And so long as the announced deal hits

an expected return threshold of 400

559

basis points above the risk-free rate,

we include it within the portfolio.

560

We saw a decent amount

561

We introduced four new positions

throughout the quarter, and

562

we closed out two deals.

563

you know, again, every deal that's

closed that doesn't fall apart

564

represents, uh, an accretive

positive return to the portfolio.

565

So that's great.

566

I think one of the things I, I want

to talk about really is this figure.

567

So what figure 14 shows is the

isolated excess return of credit

568

versus the isolated excess return

of the alpha beta merger arbitrage

569

index since RSBA's inception.

570

So when I talk about the isolated

excess return of credit, what

571

I'm effectively saying is take

corporate bonds and hedge out all the

572

underlying interest rate exposure.

573

What you're left over is with return

that's purely coming from the credit

574

spread, so changes in the credit

spread, as well as the excess yield that

575

you're generating for that credit risk.

576

Then in green, right, you're

effectively, simply getting, well,

577

what are, how are deals compressing

with the, merger risk premium?

578

How, how are, what are you returning?

579

I think what we can see is,

is two very, well, I'll say

580

three very important things.

581

the first is that substantially

lower volatility in the alpha beta

582

merger arbitrage index versus credit.

583

This is something I just think, again,

when you take a basket of idiosyncratic

584

deals and you hold them together,

it's no surprise that you tend to

585

have a lower volatility profile than

something like credit, which on average

586

has much more exposure to what's

happening collectively in the economy.

587

We can see over the period that it

did ultimately outperform credit.

588

We, we've started this fund

in fairness, at a point where

589

spreads have been quite tight.

590

They remain quite tight.

591

I think, again, it's a good argument for

why you should diversify against credit.

592

If we started this fund when spreads

were very, very high, I wouldn't expect

593

to necessarily see this outperformance.

594

But, you know, again, we're, we're

happy to have delivered excess returns

595

versus credit over this period.

596

But the thing I want to address is this

question that comes up a lot, which is

597

okay, we often say that the correlation

of merger arbitrage should be low to

598

credit and should be low to equities,

and certainly lower to equities than

599

the correlation between credit and

equities because you're combining all

600

of these idiosyncratic deals together.

601

And when you combine all these

idiosyncratic deals, and these deals

602

don't really have a lot to do with what's

happening necessarily in the economy.

603

More to do with, you know, what's

the regulatory environment like?

604

is it likely that the deal's gonna go

through earlier or later than expected?

605

All of that sort of stuff.

606

Are regulator's gonna intervene?

607

And you're combining a

whole bunch of those.

608

It's, it's no, in my opinion, no surprise

that you would expect low correlation.

609

But you do see some correlation.

610

And one of the things I, I wanna

try to provide some insight into

611

is like, why do you see correlation

between merger arb and equities when

612

you wouldn't necessarily expect the

deals to have day-to-day correlation?

613

And the answer is because how

the deals are priced, right?

614

So when a deal is announced, there's going

to be the pre trading price, but prior to

615

announcement that the stock was trading

at, and then the acquisition price.

616

And the stock is going to jump up towards

the acquisition price, taking into account

617

both the time value of money for when

the deal is expected to be closed and

618

the probability that the market thinks

the deal is going to close at, right?

619

And that how far it jumps is

effectively giving you in course

620

terms like the probability that the

market thinks the deal's gonna close.

621

But the deal's not closing

tomorrow, the deal's closing in

622

six months or maybe 12 months, or

maybe even 18 months or two years.

623

And over that time, the market

is going to move up and down.

624

And in the case that the deal

does fall apart, the stock is

625

going to fall to some price.

626

Now you typically assume it's gonna

fall to the pre-announcement price.

627

And then it's the pre-announcement price

adjusted by what the market has done.

628

So if that stock has a beta of one to

the market, for example, and the market

629

is going up over time, well, you would

actually expect the price, uh, that

630

it's trading at to get closer and closer

and closer to the acquisition price.

631

'cause the price it would fall to

if the deal fell apart, is actually

632

higher and higher and higher.

633

If the deal's gotten less

risky, your downside is lower.

634

But let's say all of a sudden the market

drops 50% and you expect, well, if the

635

deal fell apart, the price that we would

be falling to would actually be 50% lower.

636

Well, it's no surprise that the spread

then would actually widen a bit.

637

Now this is all gonna take into account,

you know, again, the time value of

638

money when we expect the deal to close.

639

Um, if we're expecting the deal to

close in a week, the deal might be

640

less sensitive to what's happening

in the market if we expect the

641

deal to close in six months.

642

But there's a low probability

of it closing, right?

643

It might, may, might be much

more sensitive to the market.

644

So all that plays in, but it's not,

it's not sensitive to the market because

645

the market falling apart necessarily

means more deals are gonna fail.

646

It's not inherently true.

647

These deals are very hard to get out of,

and unless the acquirer goes bankrupt,

648

they're typically going through.

649

It's simply that it's an

adjustment of risk, right?

650

All else held equal if the market

sells off and the price at which

651

the deal would fall to goes lower

than the spread should widen.

652

For us, that actually represents

a great opportunity for

653

the way our strategy works.

654

I mentioned that we added four

deals, uh, throughout the quarter.

655

two deals closed throughout the quarter.

656

We ended the quarter about 60% allocated

at the right, at the end of quarter,

657

after quarter turn, we added two more

deals, and these were deals that we

658

had passed over previously, but the

market had been so volatile in March.

659

And because equities had sold off, the

deals had actually widened out relative

660

to the a, the takeout price and actually

covered now our required return target.

661

And so we were able to take advantage

of short-term market volatility

662

to add those names 'cause they now

met our expected return threshold.

663

Um, so you do see some correlation and

it's, again, what I wanna stress is

664

it's not the reason people typically

expect you have correlation equities.

665

It's not 'cause the deal is

necessarily gonna fall apart.

666

It's simply because the price,

the risk is changing and that has

667

to get priced into the spread.

668

Adam Butler: I think too, it's just

quickly something to emphasize here,

669

like you, you've done your best to kind

of back out some of the impacts that

670

investors would actually experience

with an allocation of credit.

671

Like you've backed out

interest rate risk here, right?

672

On the black line.

673

Right.

674

But most investors can't back,

it's hard to, to back that out.

675

Right.

676

You don't, you don't typically get that.

677

And at the moment, people are actually

relatively fearful of duration and,

678

and fearful of interest rate risk.

679

Well, we talked to a lot of

advisors who are reticent to

680

put more bond risk on, right.

681

the, I think what's the weighted average

duration of these expected deal closures?

682

You, you, you're under a year.

683

Well, under a

684

Corey Hoffstein: Yeah, well.

685

Adam Butler: yeah.

686

So, so this is actually quite a,

a, a low duration credit index

687

with very low correlation to your

other normal credit indices, right?

688

So it's, it's a very nice

diversifier and it also provides

689

another escape hatch for you to, to

provide bond-like returns without.

690

Having that sort of duration exposure that

you would typically have to get by, you

691

know, in, in most other bond-like indices?

692

Right.

693

So at this moment, I mean, there's a lot

of reasons why merger ARB is attractive,

694

but at this moment I think it's especially

attractive for that group of investors

695

who are fearful of future inflation

and, and are unhappy with needing to

696

go out and have to allocate to duration

to get their normal, bond allocation.

697

Corey Hoffstein: Yeah, I

mean, this allows you to swap.

698

If you have duration, you're

gonna maintain your duration

699

and add the merger ARB on top.

700

But I think for us, what we're

particularly excited about is, is

701

in the short period we've had it

that sort of year and a quarter

702

that this fund has been live.

703

it has delivered excess returns relative

to both US treasuries and US corporates.

704

And, and I don't think the opportunity

to continue diversifying risk away

705

from corporates has diminished at all.

706

Spreads remain quite tight in US

corporates relative to history.

707

And so, uh, for folks who are looking to

diversify into another very defensible

708

risk premium, but have, you know, a

strategy that's going to look at around

709

the same risk in total volatility

as that corporate bond portfolio.

710

I think this is a very

compelling offering.

711

Adam Butler: Yeah, if you don't

want stack duration, this is

712

a really nice diversifier.

713

Corey Hoffstein: Yep.

714

All right, Adam, let's talk about RSSX.

715

Our, our newest ETF.

716

Adam Butler: Yeah, so

we've got, this is great.

717

This is a hundred percent

allocation to US equities and then

718

a risk adjusted or risk weighted

allocation to both gold and Bitcoin.

719

And, we love this because, you know,

equities do respond reasonably well

720

to moderate levels of inflation, but

historically, once inflation expectations

721

tick substantially above kind of 4%,

and especially if they tick materially

722

above 6%, then equity's also begin to

suffer right alongside bonds, right?

723

But that's right around the time

that historically hard assets like

724

gold and potentially Bitcoin might

really into kick into gear, right?

725

So you've got this really nice both

empirical diversification stocks,

726

gold and Bitcoin historically have

kind of, on average, about a zero

727

correlation to one another if you kind

of look back over a regional horizon.

728

But also they provide like a nice,

a nice structural diversification.

729

And when you risk balance the allocation

between gold and Bitcoin on average,

730

historically you'd be looking at

kind of somewhere between 70 and

731

80% gold and then 20 to 30% Bitcoin.

732

And that adapts over time as the,

the volatility of Bitcoin evolves

733

and the volatility of gold evolves.

734

And actually this quarter was a really

nice case study for that because the

735

gold volatility expanded so substantially

that even though we use a relatively

736

long-term lookback to measure the

relative volatilities, that vol

737

expansion gold was still substantial

enough to actually have an impact.

738

And so the allocation of Bitcoin

crept up a little bit in the

739

portfolio, the allocation of gold.

740

came down a little bit and that was really

helpful because, you know, there was a

741

bit of a narrative violation that happened

on the onset of this war in the Gulf.

742

I think probably the logical expectation

going in was a gold would rally and that

743

Bitcoin might sell off because Bitcoin

has been a bit of a risk on risk off

744

asset, over the past couple of years.

745

But the opposite happened.

746

And actually gold really had quite a

steep sell off, but Bitcoin started

747

to really, bounce higher and that,

that, that bounced kind of accelerated

748

as the, as the war proceeded.

749

And I'm not gonna try to explain

that, but it's just really nice to see

750

that, you know, we can tell ourselves

stories, and have expectations, but

751

really what we want to emphasize

is structural diversification.

752

And while the story didn't play out

the way we might've expected, the

753

diversification potential played out

exactly as we might've hoped, right?

754

And so the, the move in Bitcoin

higher offset to a meaningful

755

extent the sell off in gold.

756

And we saw a much smoother, line right

than we might expect from the fact that

757

we've got three assets, each of which has

quite a bit of volatility on their own.

758

But because of that diversification,

they do a nice job of smoothing return

759

when they're held together, right?

760

I mean, an expectation, if you were to

hold these three assets and they were

761

perfectly correlated, you'd be looking

at a volatility of about 40% on the

762

portfolio, but in expectation because

those three assets are, have about a zero

763

expected correlation with one another

that 40% volatility comes all the way

764

down to sort of 20 to 25% volatility.

765

Right.

766

Much more manageable.

767

And that's exactly what you see.

768

I mean, look at the, the black line

there relative to the experience of the

769

yellow, the green, and the blue lines.

770

Right.

771

I just think it's remarkable to

actually see that diversification

772

play out in real time and attenuate

that volatility experience.

773

This is really the, the, the

portfolio being much better than

774

the sum of its individual parks

because of that diversification.

775

Playing out.

776

Corey Hoffstein: There's the

narratives we tell ourselves versus

777

what markets actually do and, and I

think a lot of people would've said

778

the flight to safety in gold would've

been the obvious trade in March.

779

And maybe because it was obvious,

that's why it fell apart, right?

780

People were selling their gold perhaps

to shore up the dollars they needed or,

781

you know, to fund the exposure elsewhere.

782

I don't think anyone would've guessed

that Bitcoin would've been flat up

783

over that meaningful risk off period.

784

But, you know, again, this is why having

humility in, in enjoying long-term

785

structural diversification and trying to

balance the volatility of these assets

786

as in the overlay, um, I think is a, is

a great way and, and particularly why we

787

designed this strategy the way we did.

788

Adam Butler: Yep.

789

Corey Hoffstein: Despite all that

volatility, you know, again, compared to

790

just an s and p benchmark since inception,

and take these numbers with a large grain

791

of salt because it is less than a year.

792

you know, since inception still over

700 basis points annualized on the s

793

and p, it's been a good period for gold.

794

A bad period, horrible

period frankly, for Bitcoin.

795

Peak to trough had a

50% drawdown just about.

796

But still that risk weighted balance

between gold and Bitcoin more

797

than offset that drawdown with,

with the rally we saw in gold.

798

And that's exactly, you know, we designed

this that way so that neither asset

799

was completely driving the portfolio.

800

All right, we're hitting 50 minutes.

801

One of the things we want to do before

we go, and there's a whole bunch of

802

questions here Adam, so hopefully you

got some time to stick around after the

803

hour turns and we can talk about this.

804

But I wanna, I wanna share one more

thing that we published this quarter,

805

which is on our returnstacked.com

806

site.

807

We introduced a new tool, so

if you go to returnstacked.com

808

and go to tools, we launched what's

called the Portfolio Visualizer.

809

And if you launch the visualizer,

you'll be taken to a widget that

810

allows you to explore basically

return stacking concepts.

811

What you can do in a fairly isolated

manner is choose some sort of base

812

ranging from a hundred percent stocks, 0%

bonds, all the way to 0% bonds, a hundred

813

percent stocks, and then you can choose

some sort of allocation for your stack.

814

So let's say I wanted to explore what

a 50% managed futures, 50% merger arb

815

stack look like on top of my 60 40.

816

And I was willing to go

up to a 30% stack size.

817

We can see what the equity curves

would've historically looked like.

818

We can look at some

performance statistics.

819

These are nice to have.

820

But I think what's more useful from

an experience perspective is looking

821

at things like the rolling returns.

822

How, what periods would the stacked

portfolio have an outperformed

823

the strategic benchmark?

824

What does it feel like

over any 12 month period?

825

What does it feel like over a.

826

You know, longer horizon,

period, call it five years.

827

Right?

828

Let's look at the drawdowns.

829

How do these things compare?

830

How long would they have been?

831

When would you have had a bigger

drawdown in the stacked portfolio

832

versus the stock bond blend?

833

How long was the longest drawdown

in each of these portfolios?

834

You can look by calendar year, right?

835

How many years would it have

underperformed in a row?

836

How many years would've

it outperformed in a row?

837

What years that you care about that you

838

for me, that diversification just did not

839

bad would your relative return have been?

840

Is that something that you could stomach?

841

And then the opportunity to just look

at sort of the, the stacked blend in

842

isolation to look at the equity curve.

843

What would that have looked like?

844

How, how did it correlate to your stock

bond mix over a given period to get a

845

sense of, you know, how does, how stable

were those correlations over time?

846

All this, you know, again, in

a fairly isolated manner, but

847

to build the intuition, I think

it's a pretty powerful tool.

848

And then there's two things you can do.

849

There's a link to share if you want to

basically copy this and send it to someone

850

or send it to us to, if you're trying

to explore an idea, whoever loads that

851

link, we'll get this exact stock bond mix.

852

And the other thing you can do is you

can generate a summary PDF, that's

853

gonna take your exact blend, put it

into a PDF, take all these graphs and

854

charts and build out a really nice

looking PDF that you can walk away with.

855

Explore a little bit later.

856

Of course, you can always

discuss the stack you're building

857

with one of our consultants.

858

If you click on this, it'll send the

exact stack you've built so they know

859

what you're talking about, and you

can set up a meeting with them to

860

discuss what you're working on and,

and the goals you're trying to achieve.

861

So this is something we published

a little over a month ago.

862

We've seen a really big pickup in usage

and adoption, which we'd love to see.

863

Again, we're just trying to provide

the tools to help people build some

864

intuition as to how these things look

and the trade-offs that come in when

865

you choose different bases versus

different stacks and different stack

866

sizes and different stack combinations.

867

It all leads to different outcomes

and, and what stack size and what

868

blend is appropriate for you or your

clients, or a particular client is

869

gonna be very based on their risk

appetite, risk tolerance, and their

870

ultimately their goals and objectives.

871

And so this is a tool that lets us

explore some of those degrees of freedom.

872

We have to get an idea of how

things would've played out.

873

Adam Butler: We should also note

that there's an even more flexible

874

and robust tool coming down the pipe

that we'll be launching imminently.

875

And so we would encourage you to go to

the site and sign up for that now, and

876

we'll let you know when that's available.

877

And, we're pretty excited about it.

878

there's a lot of new tools

that we've got on the burner.

879

This one is just extraordinarily

helpful and useful.

880

And, so come to the site,

sign up and, and get access to

881

all the future tools as well.

882

If you're an advisor.

883

Corey Hoffstein: Yeah, the more

advanced version will basically

884

allow you to build any base stack,

any base portfolio you want using.

885

I think it's like three

dozen different indices.

886

Any stack you want using three

different dozen different indices.

887

really powerful.

888

Uh, so, so stay tuned for that.

889

We'll have, you know, obviously varying

levels of trying to build intuition.

890

Sometimes a little bit of constraint.

891

It does is helps you build that base

intuition before you really dive

892

deep and, and customize and explore.

893

Alright, Adam, we have

a lot of questions here.

894

I'm gonna start by saying

thank you everyone for, for

895

sticking with us this long.

896

we have probably maybe a dozen, half a

dozen questions I, I want to get to here.

897

But for those of you who have to

leave, thank you for your time.

898

We really appreciate it.

899

If you do have any questions,

please go to return stack.com,

900

go to the contact section.

901

Um, you can fill out a contact form

or get in touch directly with your

902

regional consultant and they can

answer any questions you have, whether

903

it's about our products or anything

else, return stacking related.

904

and again, thank you for your time.

905

We're just gonna stay here

and try to get through as many

906

of these questions as we can.

907

And if you have to leave, this will have

a replay eventually and you can tune

908

in and hear the q and uh, afterwards.

909

So again, thank you Adam.

910

I wanna start uh, the very first

question we got was, uh, I know you

911

can't give specifics, but do you guys

have plans to expand the ETF lineup?

912

really it is tough to talk about because

we are technically in the quiet period.

913

We have an ETF that we have

filed for that filing is public.

914

So I can say that we have filed for an

international equity and managed futures,

915

ETF I cannot state our exact plans on

when we intend or hope to launch that

916

fund, but we did file for that, call it,

I don't know, 65 days ago, 60 days ago.

917

Um, so that is public.

918

You can go find that filing, uh,

in the SEC's Edgar database and,

919

and look up all the details there.

920

Again, it is not an effective filing.

921

I cannot tell you if or

when it will go effective.

922

Um, but that is a product we have

intentions to launch and we do in

923

intend to continue to build out the

suite in different combinations of,

924

of bases and stacks so that we can

provide maximum flexibility to people

925

building return stacking portfolios.

926

Adam Butler: Right.

927

We've got another question here

about the introduction of grain

928

markets in the, the futures lineup.

929

So grains have more rigid CFTC limits.

930

We can't trade them in the

same size at front month.

931

A lot of managers do trade back

month contracts in order because

932

they have much larger, limits

than the front month contracts.

933

And that would typically be what

you'd find maybe in, in some, hedge

934

fund style two and 20 products.

935

We have investigated that.

936

and we, we do some back month

grains in, in some other products.

937

The reality is when we look at the

replication suite, they don't add,

938

they don't explain a lot of, extra

variance of the benchmark index.

939

and so, you know, adding them

doesn't add a lot of extra margin,

940

but it does add a substantial amount

of extra operational complexity.

941

And so it's not something that we're,

clamoring to do at the moment, but

942

it's definitely on the research agenda.

943

And, you know, for consideration

sometime down the line.

944

Corey Hoffstein: Yeah.

945

I think to add to that, we, we

found, I think soybean was maybe

946

of the AGs the largest traded and

maybe having the largest impact.

947

But when you consider it would be

the 28th market we trade, it doesn't

948

suddenly become a huge position.

949

It, it stays like a one 28th risk

position and from there it's just, it

950

has a marginal impact, but it's hard

to really extract whether that's.

951

Noise or true value.

952

when we look at really what is the

major factors that are driving the

953

beta, it's no surprise, it's, it's

things like gold oil, equity, beta, the

954

10 year US treasury, euro dollar, yen

dollar, like those are the big drivers.

955

And in, and the reason they're the

big drivers is because when you have

956

a really big crisis, most of the

long tail stuff ends up correlating

957

with the big macro drivers, which

get picked up in those markets.

958

And so when you look at, like, when the

category really moves, you don't have a

959

lot of, it's not a tremendous number of

like factors that are driving things.

960

It's one or two factors that are

picked up by just a couple of markets.

961

And so, continuing to add markets tends to

make I think what research, which suggests

962

more of an absolute return product and

less of a product that is convex to macro

963

environments, which is what the beta sort

of category return tends to look like.

964

very specific question here.

965

Do you have a document that shows

how much of the bond component or

966

government obligations for tax purposes?

967

Uh, yes we do.

968

Uh, please send us a message

directly and I can send you a PDF.

969

We don't have that on the website

at the moment, but that is something

970

I can send to you directly.

971

Uh, hoping to improve our tax reporting

972

this stuff available on the website..

973

Adam Butler: Corey, as Convergent herb

strategies can have nonlinear fat left

974

tails during liquidity crisis, how do

you expect RSBA to behave in a GFC or.com

975

style crisis?

976

That's a

977

Corey Hoffstein: Yeah, so I think, again,

it depends on the, on the type of crisis.

978

Dot com is very different than GFC, right?

979

But regardless, you know, if you have a

deal that's closing in a year and over

980

that year the market sells off 50%, or

it sells off 50% very quickly and spends

981

its time down there, like the spread is

going to blow out meaningfully for any

982

deal, even if the probability of that

deal getting closed doesn't change.

983

That gets exacerbated in like a true

liquidity crunch like the GFC where

984

people have to sell out of every position.

985

They have to fund positions

elsewhere, come up with cash.

986

And so you see spreads

blow out wider and wider.

987

So there is some left tail.

988

Some of it again, is just.

989

The repricing effects.

990

I discussed that in a big drawdown, right?

991

you're going to have certain

deals just get wider and wider.

992

But again, these deals are,

tend to be somewhere between six

993

months and two years in length.

994

The deals we've had on, I think, have

been much closer to six to nine months.

995

Some of them have been as short as three

months, if I'm not mistaken, right?

996

If you have a market sell off over a

two year period, but you have a bunch of

997

deals that keep closing in six months,

they, they're gonna be fighting that, that

998

need for the deal to approach the deal

price versus, you know, the spread being

999

forced wider by the market going down.

01:02:53,507 --> 01:02:58,307

It's not as big an impact versus

a very sudden sharp sell off.

01:02:58,337 --> 01:03:00,977

You would expect to see all deals widen.

01:03:01,407 --> 01:03:06,687

GFC again being the liquidity crunch

element of that is, is unique.

01:03:06,777 --> 01:03:09,417

And when you have a liquidity

crunch market wide, yes, you're

01:03:09,417 --> 01:03:11,037

gonna see deal spreads blowout.

01:03:11,397 --> 01:03:13,347

Again, not necessarily because

the probability of the deal.

01:03:13,347 --> 01:03:14,037

Closure change.

01:03:14,067 --> 01:03:18,297

Closure change is just maybe with the bath

water, people need to come up with cash.

01:03:18,517 --> 01:03:18,937

Adam Butler: Yeah.

01:03:18,937 --> 01:03:23,197

And, and also I think you'd

probably expect the, the deal

01:03:23,197 --> 01:03:26,737

frequency to slow down substantially

during, during recessions or

01:03:26,737 --> 01:03:27,847

during liquidity events, right?

01:03:28,387 --> 01:03:30,291

Just, capital gets more expensive.

01:03:30,291 --> 01:03:36,727

People begin to, to, to pull in their

risk budgets and, so that might limit

01:03:37,147 --> 01:03:39,157

expected returns over those periods.

01:03:39,267 --> 01:03:42,777

that's less of a risk exposure

and more of just a, you know,

01:03:43,017 --> 01:03:44,907

lack of return opportunities.

01:03:45,387 --> 01:03:48,987

But what happens then is, is

typically that those same acquisition

01:03:48,987 --> 01:03:53,572

targets have the same strategic

accreative value to the acquirers.

01:03:53,962 --> 01:03:59,362

So there tends to be like a, a cluster

then of, of major deals that happens

01:03:59,362 --> 01:04:04,542

as, as those credit spreads close and

as the the liquidity event, moderates,

01:04:04,612 --> 01:04:07,912

which makes more, that makes up for

what happened during that interim time.

01:04:08,822 --> 01:04:10,022

Corey Hoffstein: Adam,

we got a question here.

01:04:10,232 --> 01:04:10,622

We get.

01:04:10,982 --> 01:04:12,422

One of the things I love

about these quarterlies is

01:04:12,422 --> 01:04:13,712

we get really into the weeds.

01:04:13,772 --> 01:04:16,512

Uh, we got a question here about the

trading costs differences between

01:04:16,512 --> 01:04:19,452

the three trend systems and are there

differences in liquidity that drive

01:04:19,452 --> 01:04:26,132

higher trading costs for, between the

top down, say small universe and the

01:04:26,132 --> 01:04:32,282

top down larger universe where we're

trading 27 contracts versus a much

01:04:32,282 --> 01:04:35,612

smaller amount of contracts and those

contracts tend to be more liquid.

01:04:35,612 --> 01:04:38,882

So I dunno, if you want to, if you

want to comment there, I, all I will

01:04:38,882 --> 01:04:43,112

say is like measuring trading costs.

01:04:43,532 --> 01:04:48,692

I know this is, this has been a topic on

a lot of trend following podcasts lately.

01:04:49,532 --> 01:04:54,002

I think people make measuring trading

costs sound a lot easier than it truly is.

01:04:55,172 --> 01:04:57,512

Because when you talk about

measuring trading costs, there's a

01:04:57,512 --> 01:04:59,642

lot of what if that goes into it.

01:04:59,642 --> 01:05:02,522

There's obviously the very explicit

trading costs that you can easily

01:05:02,522 --> 01:05:07,172

measure, which is, you know, what are

the actual like commissions you pay?

01:05:07,922 --> 01:05:11,612

And those are things you can negotiate and

try to get better rates than other people

01:05:11,612 --> 01:05:13,892

and, and the way you work with brokers.

01:05:14,221 --> 01:05:19,532

But then there's the question of, if I

choose to say, implement my trade as a

01:05:19,562 --> 01:05:26,702

twap over intraday, I might have lower

market impact, but my actual price of

01:05:26,702 --> 01:05:33,602

execution may be worse than if I had

just had a higher impact and dumped

01:05:33,602 --> 01:05:34,502

it all at the beginning of the day.

01:05:35,522 --> 01:05:35,942

Right?

01:05:36,422 --> 01:05:38,312

Is that good or bad execution?

01:05:38,312 --> 01:05:41,732

Well do, if you don't have a view

as to the beginning, the market

01:05:41,732 --> 01:05:45,242

where the market's going, intraday,

like, you know, it might just be

01:05:45,242 --> 01:05:47,642

the cost of the trade sometimes.

01:05:47,642 --> 01:05:49,712

For example, I've heard people talk about.

01:05:50,552 --> 01:05:53,012

Running what's called a taker

versus a maker algorithm.

01:05:53,012 --> 01:05:55,562

Are you crossing the spread

to implement your trade?

01:05:56,162 --> 01:05:59,102

Well, if you cross the spread,

that's an explicit cost.

01:05:59,402 --> 01:06:02,312

People might say, well, I

run a, I'm, I'm patient.

01:06:02,642 --> 01:06:03,992

I let people come to me.

01:06:04,471 --> 01:06:08,612

Well, if you let people come to you, but

the real price of the asset has moved

01:06:08,612 --> 01:06:12,452

and they're, you know, sort of quote

unquote taking through you, yes, you

01:06:12,452 --> 01:06:16,232

didn't have to cross the spread, but you

got traded at a price that's incorrect.

01:06:16,232 --> 01:06:19,862

And if you look at the ticks after

your trade, you've actually lost

01:06:19,862 --> 01:06:21,392

money relative to where you traded.

01:06:21,902 --> 01:06:22,982

It is in Incredi.

01:06:22,982 --> 01:06:26,642

And these are, I know some of this might

not make sense to many people listening,

01:06:26,642 --> 01:06:34,232

but the point is measuring trading costs

is incredibly difficult and nuanced.

01:06:34,232 --> 01:06:37,742

And I think a lot of the conversation

that's been going on in some popular

01:06:37,742 --> 01:06:41,702

podcasts around the trading costs of

trend following are just substantially

01:06:41,702 --> 01:06:43,742

missing the details of some of this.

01:06:44,072 --> 01:06:48,782

Um, and I, I don't think it's

easy to say, like one system

01:06:48,782 --> 01:06:51,677

has more or less trading costs.

01:06:51,677 --> 01:06:54,377

You generally expect higher liquidity

instruments to have lower trading

01:06:54,377 --> 01:06:58,187

costs, but if you're trading them in

larger size, 'cause you have fewer

01:06:58,187 --> 01:07:01,817

instruments, you might have more

impact because you're making bigger

01:07:01,817 --> 01:07:03,557

trades even though they're more liquid.

01:07:03,887 --> 01:07:09,287

So it's, it's not easy to say and it

requires a ton of detailed analysis.

01:07:10,082 --> 01:07:13,412

Adam Butler: I mean, look,

execution matters a lot.

01:07:13,742 --> 01:07:18,466

And, you know, we've been trading

01:07:18,736 --> 01:07:21,076

and we learned a lot over that period.

01:07:21,076 --> 01:07:27,736

And we have renegotiated with our, our

service providers, and we've improved

01:07:27,736 --> 01:07:29,686

our execution algorithms over time.

01:07:29,686 --> 01:07:33,496

And that continues to be an ongoing

battle that is well worth fighting.

01:07:33,706 --> 01:07:37,966

There's also some averaging

that goes on, right?

01:07:37,966 --> 01:07:40,396

So we don't trade those three

models in three different accounts.

01:07:40,396 --> 01:07:41,716

We trade them all in the same account.

01:07:41,716 --> 01:07:46,396

So you might have the, the medium sized

model might be saying we should be

01:07:46,396 --> 01:07:50,566

adding to our two year treasury position.

01:07:50,986 --> 01:07:55,306

The the nine asset model might

be saying we should be lowering

01:07:55,306 --> 01:07:56,836

exposure to the two year treasuries.

01:07:57,136 --> 01:08:01,156

And our bottom up model might be

saying, you know, no, no change today.

01:08:01,396 --> 01:08:06,226

So, you know, while both those models

may be arguing for a change because

01:08:06,226 --> 01:08:09,736

they're arguing for a change in opposite

directions, they average out and it

01:08:09,736 --> 01:08:13,666

ends up that there's actually no, no

trade in that market today, right?

01:08:13,966 --> 01:08:15,676

So you do get a lot of

this trade averaging.

01:08:16,095 --> 01:08:23,386

We also do a lot to, stabilize

our, our estimates for our models.

01:08:23,996 --> 01:08:27,626

And we also do, impose some

smoothing, the smoothing.

01:08:28,241 --> 01:08:29,651

Actually does two things.

01:08:29,770 --> 01:08:35,681

Obviously it lowers the amount of

daily trading, but also empirically

01:08:35,770 --> 01:08:37,901

it improves the fit, right?

01:08:37,961 --> 01:08:41,621

So it has this kind of, you know,

you don't actually, you don't see

01:08:41,621 --> 01:08:45,640

this very often, honestly, where

you make a decision to try to slow

01:08:45,640 --> 01:08:49,541

down your, your trading, you're not

gonna be as reactive to the signals.

01:08:50,031 --> 01:08:54,020

that actually helps in terms

of, of your performance from

01:08:54,020 --> 01:08:55,191

a tracking year perspective.

01:08:55,551 --> 01:08:57,470

And it also lowers your trading costs.

01:08:57,711 --> 01:09:01,491

So, you know, this is kind of

a happy, coincidence with the

01:09:01,491 --> 01:09:03,151

tracking, models that we run.

01:09:03,151 --> 01:09:04,951

So there's a lot going on.

01:09:05,011 --> 01:09:06,901

We take execution very seriously.

01:09:07,441 --> 01:09:10,557

There are some beneficial ways to

the way that we model things and,

01:09:10,607 --> 01:09:12,227

we'll continue to improve over time.

01:09:13,051 --> 01:09:16,721

Corey Hoffstein: We do have some actual

hard numbers that we think we can sort

01:09:16,721 --> 01:09:20,711

of back out as to what our trading costs

have been over the last three years.

01:09:21,131 --> 01:09:25,152

but again, I, I'm not, I don't wanna

share those hard numbers with, without

01:09:25,152 --> 01:09:28,692

the caveat of, like other people talking

about hard numbers might be measuring

01:09:28,692 --> 01:09:31,332

them entirely differently than we are.

01:09:31,542 --> 01:09:35,082

And you can be, someone can say their

trading costs are 10 basis points.

01:09:35,261 --> 01:09:38,022

Someone might say they're 200 basis

points and they're just measuring

01:09:38,022 --> 01:09:39,702

completely different trading costs.

01:09:39,702 --> 01:09:44,711

And so to me it's, it's a conversation

that unless everyone at the table agrees

01:09:44,711 --> 01:09:48,642

as to how trading costs are measured, it's

not a conversation, frankly, worth having.

01:09:49,022 --> 01:09:49,232

Adam Butler: And a

01:09:49,631 --> 01:09:51,822

Corey Hoffstein: Good news is all

of those are baked into returns.

01:09:51,852 --> 01:09:53,051

Just look at the returns, right.

01:09:53,682 --> 01:09:54,372

It's all in there.

01:09:55,052 --> 01:09:55,292

Adam Butler: Yeah.

01:09:55,292 --> 01:09:57,962

I mean, a manager that gets access

to a strategy via swap, you don't

01:09:57,962 --> 01:09:59,402

even see the, the, the trading costs.

01:09:59,402 --> 01:10:01,532

They all happen behind the

scenes, you know, like it's,

01:10:01,532 --> 01:10:03,362

there's, it's complicated.

01:10:04,286 --> 01:10:06,446

Corey Hoffstein: one of the questions

here, Adam, is can you tell me how often

01:10:06,446 --> 01:10:10,406

RSBT and RSBY correlate with equities?

01:10:10,406 --> 01:10:15,476

Do you find that the futures normally

level off when the market runs higher?

01:10:15,716 --> 01:10:17,006

Sort of two questions there.

01:10:17,246 --> 01:10:18,326

Um, you wanna address this one?

01:10:19,711 --> 01:10:25,951

Adam Butler: So the correlation with

equities tends to be about zero on

01:10:25,951 --> 01:10:30,451

average over the long term for both the

trend strategy and the carry strategy.

01:10:30,931 --> 01:10:36,901

It's worth mentioning that carry and trend

correlate on average of about kind of 0.2

01:10:36,901 --> 01:10:37,891

to 0.3,

01:10:38,141 --> 01:10:40,871

historically over the,

over the long term, right?

01:10:41,471 --> 01:10:49,901

But by their nature and the ability for

the entire portfolio to adjust to changes

01:10:49,931 --> 01:10:56,981

in trends in the, in the equity complex,

in changes in carry in the equity complex,

01:10:57,311 --> 01:11:04,866

there will be time varying correlation,

to equities across both carry and trend.

01:11:05,406 --> 01:11:10,746

Now, conveniently and we continue to

say that, you know, in our opinion,

01:11:11,046 --> 01:11:15,666

the best way to allocate to trend and

carry is to allocate to both together.

01:11:16,326 --> 01:11:22,806

And that's because they view the markets

from very different angles and oftentimes

01:11:23,376 --> 01:11:28,116

for the very reason that that equities are

rising a lot and therefore the dividend

01:11:28,116 --> 01:11:31,536

yield on equities is, is often declining.

01:11:31,536 --> 01:11:36,076

If that, rise is, is relatively,

happens to a relatively short

01:11:36,106 --> 01:11:41,626

horizon, well, because then the

dividend yield is, is shrinking,

01:11:42,016 --> 01:11:44,056

the carry signal is also shrinking.

01:11:44,056 --> 01:11:48,856

At some point, if equities

rise enough, and especially if

01:11:49,246 --> 01:11:52,486

short-term interest rates are f

are also falling at the same time.

01:11:53,071 --> 01:11:58,051

The dividend yield relative to the

funding cost may flip negative, at

01:11:58,051 --> 01:12:02,971

which point you've got carry showing

a negative allocation or certainly a

01:12:02,971 --> 01:12:06,511

negative signal relative to equities.

01:12:06,511 --> 01:12:10,501

While, while trend has a positive

signal relative to equities and you,

01:12:10,591 --> 01:12:12,931

you often have one offsetting the other.

01:12:13,201 --> 01:12:16,921

And what's great is that often happens,

you know, during especially strong

01:12:16,921 --> 01:12:19,321

spikes, higher inequities, right?

01:12:19,621 --> 01:12:24,871

The carry strategy is kind of moderating

the equity allocation that would

01:12:25,021 --> 01:12:29,581

you'd otherwise be getting from that,

that that major move in equities.