Episode 204

full
Published on:

31st May 2024

Navigating Market Volatility: Mastering Managed Futures and Carry Strategies

In this episode, ReSolve team members Adam Butler and Rodrigo Gordillo discuss the concept of market volatility and its implications for investment strategies. They delve into the intricacies of Carry strategies, their impact on portfolio returns, and how to navigate market volatility effectively.

Topics Discussed

• The concept of Carry in the investment world and its potential applications

• The role of Trend and Yield in creating a fund

• The importance of understanding the Carry strategy and approach

• The impact of economic risk on Carry signals and expected future returns

• Building Carry strategies using time spreads or calendar spreads

• The influence of Absolute Carry and Relative Value Carry on performance

• The effect of estimated real trade frictions on returns

• The correlation between Carry and other assets in a portfolio

• The performance of Carry in different market regimes

• The benefits of diversification and the role of Carry in enhancing portfolio returns

This episode provides valuable insights into the world of market volatility and Carry strategies. It highlights the importance of understanding these concepts for effective investment decision-making and portfolio management. A must-listen for anyone interested in deepening their understanding of market dynamics and investment strategies.

This is “ReSolve’s Riffs” – published on YouTube Friday afternoons to debate the most relevant investment topics of the day, hosted by Adam Butler, Mike Philbrick and Rodrigo Gordillo of ReSolve Global* and Richard Laterman of ReSolve Asset Management.

*ReSolve Global refers to ReSolve Asset Management SEZC (Cayman) which is registered with the Commodity Futures Trading Commission as a commodity trading advisor and commodity pool operator. This registration is administered through the National Futures Association (“NFA”). Further, ReSolve Global is a registered person with the Cayman Islands Monetary Authority.

Transcript
Rodrigo Gordillo:

Welcome.

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Welcome everybody.

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Welcome to our, latest webinar

covering Managed Futures

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Carry: A Practitioner's Guide.

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before we begin, we're going to give

everybody a little time to get settled in.

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Make sure that everybody's signing

up and, I've seen the participant

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count go up quite quickly.

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So, it looks like we may be

ready in a couple of minutes.

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Adam Butler: How's everybody doing today?

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This whole webinar format is not

so good for my presentations.

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You know, I'm struggling to

picture everybody naked over

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Rodrigo Gordillo: the

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Adam Butler: webinar.

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I guess it's only you, Rod,

and that's no good for me.

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Rodrigo Gordillo: So I wonder, I want

to make sure I can, yeah, the Q and A.

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How's everybody doing today?

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Feel free to get into the q and a

chat box and start testing to see

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whether we can get your questions,

as we wait for people to come by.

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What we really wanna do in this

webinar is Adam and, Andrew

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wrote it very technical paper.

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We're gonna go through a lot of stuff,

but I'm gonna be, Adam's co-pilot here.

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So I'm gonna try to channel everybody

that's sitting in their seats right

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now trying to think through whether.

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You know, they might be

asking questions throughout.

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I'll try to be that co pilot and ask

those questions, but please do answer.

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so do ask questions.

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I'll be reading them and I'll see if, if

I can help get that answer for you guys.

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Adam, are you saying Rod

isn't good enough to look at?

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Exactly right.

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Like if he's going to look at a

naked person, you'd think at this

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point it'd be his business partners.

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Feel comfortable with it.

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Adam Butler: It's just getting old.

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I have to say that I've been looking

forward to presenting on carry for years.

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This is my favorite, most

misunderstood strategy.

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So it's great to get

it out in the sunlight.

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Rodrigo Gordillo: Is it possible

to have a fund that is trend

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and yield no stocks and bonds?

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It certainly is possible.

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we'll be talking less about product

today and we'll be talking about

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more conceptually the, the carry

strategy and the carry approach.

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Just to kind of introduce this

because I think one of the reasons we

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were, I'm really pumped about this.

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I know Adam's been dying to talk about

this for years is that Even three years

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ago, nobody wanted to talk about trend.

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It seems like that, that there's

been a big uptake on trend.

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General audiences are

starting to understand it.

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They see the value in it.

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And, very few people know about carry.

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So lots to talk about.

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There's, I'm so excited about this for

many reasons we're going to cover, but,

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yeah, I think there's many applications

to this concept in the investment world.

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Adam Butler: All right.

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We better roll because,

we've got a lot to cover.

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Rodrigo Gordillo: All right.

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So you want to pop up that presentation,

Adam, since you can be doing most of it.

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Adam Butler: Okay, let's do it.

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Rodrigo Gordillo: All right.

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So we have a lot to cover today

and we're going to try to get us

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through it as much as possible.

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We are covering a white paper that has

a lot of output and a lot of back tests.

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And so lots of this will be just kind of

reiterating the concepts through charts.

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So even though there's a lot of slides,

we'll try to get through them quickly.

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but if we go to the next slide,

Adam, why, you know, should you

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be listening to me as a host?

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I am Adam Butler's business partner.

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Been together with him and

Michael Philbrick since:

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I've been in the business for almost

20 years now, and I'm president of

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Resolve Asset Management, Global.

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Been a-co contributor to a lot of

white papers and podcasts and blog

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posts on Resolve and, you know,

writing articles as well now on the

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return stack, website and, and so on.

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So been managing quantitative

investment strategies for many years.

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And today I'm going to help facilitate

the conversation with the co authors.

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If we go to the next slide, Adam.

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So for those who haven't read the

white paper, I would encourage

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you to click on the link.

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Maybe Ani can push that through for

you guys to be able to click on that.

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If it's not, if you haven't already,

it'll be a good thing to have side by

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side as we go through this presentation.

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and the white paper was

written by Adam Butler.

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Our CIO here at Resolve Global and Dr.

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Andrew Butler, our resident PhD in

Resolve Asset Management Canada.

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yes, they are related.

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Genius does run in the genes.

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So our two propeller heads did

a fantastic job at creating a

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comprehensive review and framework for

different ways of looking at a carry.

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And everything that we're going

to present in this presentation,

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all the performance stats will

be sourced from this white paper.

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So just, click on that.

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There's also data that you can download.

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So if you can kind of double check

everything that we review here.

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Adam Butler: We should also mention

there's an advisor, summary of this

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on the InvestResolve blog, which

is a little bit more accessible.

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We've cut out some of the more, nebulous

sections of the white paper and made

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it just grounded a little bit more.

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So, feel free to check that out too.

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Rodrigo Gordillo: and Ani, you can put

the link to that in the chat as well.

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If we could next slide, Adam, for me,

you know, as always with, any sort of

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work that you do with the investment

in the investment universe, Adam,

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the next slide, I still don't see it.

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we have to be cognizant of, all

of the important disclaimers.

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We're going to be presenting

a lot of hypothetical results.

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This is merely a research project that

tries to shine a light on a premium that

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may add value to people's portfolios.

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There's many ways to skin this cat

by no means it is a, an offer to,

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buy a fund or anything like that.

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So really it's about

covering that research.

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Next slide for me, Adam.

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So please do read those disclaimers

and recognize that there is risks in

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everything that we do in this space.

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And then I'll tell you quickly

what we're going to tell you.

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We're going to talk about what

is basic carry, how we define the

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three basic definitions of carry.

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How we can practically implement all

these carry strategies in a portfolio and

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incorporating with other asset classes.

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And then from then on, we'll really go

through some analytical framing, you

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know, how to put these things together

to make them work in real life with

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real trading, and then from then on,

it'll be back test showing performance

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analysis scenario and regime analysis.

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So a couple of case studies on

the return stacking side and then

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conclude with some questions.

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Okay, so next slide for me, Adam.

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Before we do begin, let's

start with a little poll.

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Ani, would you mind

pushing through that poll?

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I want the audience to, I'm just trying

to get a gauge as to how many people

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had heard about Diversified Carry

before downloading our white paper or

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being in this, webinar or the invite.

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And also if you can answer the second

question, which is if you had heard

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a carry, how many of you do you

currently invest in a carry strategy?

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Give it a couple of minutes there.

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I've never done a poll, so I'm just

gonna let that linger there for a bit.

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And maybe we can come back to it, Adam.

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but, Ani, you let me

know when it goes, when

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Adam Butler: Yeah, I think Ani closes it

out and then it shows you the results.

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So, it's probably long enough.

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It's only two.

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Rodrigo Gordillo: Yeah, Ani, let's go.

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Two quick questions.

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Let's see if we can find the answers.

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Okay, what do we have?

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So, have you heard about

diversified care before?

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Yes.

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So most people, about two

thirds have said, yes.

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One third said, no, that's a good ratio.

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that's probably above average.

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We have an above average

intelligent crowd here today.

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And you currently invest in diversified

carry strategies only around 20%.

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So that's kind of what we would expect.

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hopefully, you know, we certainly do and

have been talking about carry strategies

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and have those in our back pocket.

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And if you go to our website, you

can find some, but, more and more

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solutions will be coming out very soon.

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All right, so this is good to know.

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Let's hand it over to

our lead author here.

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Adam, why don't you take it

away and tell us what Carry is.

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Adam Butler: Okay.

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What is Carry?

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Yeah, so Rodrigo is going to step in

and ask questions and seek clarity

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if I kind of missed something.

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But let's start with basic definition.

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Carry is what you expect to return on

an asset if the price doesn't change.

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In the white paper, we use an

apartment building investment to

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illustrate the concept, right?

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Because you buy an apartment building,

typically you're going to own it

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for many years, maybe decades.

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Maybe you're not so concerned

with what the price will be when

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you sell it in 20 or 30 years.

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In the meantime, it is generating

a lot of cash flow for you, the

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rents on the apartments, right?

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Well, going a little bit more into public

markets, equities are expected to deliver

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cash flows in the form of dividends.

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Even equities that don't currently

pay dividends are priced on the

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basis that eventually they're going

to return cash flow to investors.

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Bonds.

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Almost all of them pay a coupon.

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That is the carry on bonds.

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And we're going to demonstrate that

in the concept of futures markets,

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commodities, equities, currencies, bond

futures, all of these can be expected

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to pay or, absorb carry at, at different

points in time for different reasons.

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So let's get into an example.

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All we've done here is.

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Sort of illustrated a

simple futures market.

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One futures market that has a,

let's say it's copper, right?

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Copper is currently trading at 3

dollars and 50 cents in a spot market.

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So if you're going to go buy.

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A ton of copper, you're going

to pay 350 a pound, say, right.

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And then we've got a future on copper and

you, someone wants to buy the future on

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copper, to take delivery in September.

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And that's the point that's sort

of out on the right here, right?

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So here's the spot price and

here's the futures price.

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And, they're paying a little bit less.

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In the future, then the current spot price

for dynamics that currently exist in the,

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in this market, which we'll get into.

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And then over time, if the price of copper

doesn't move, if it stays where it is,

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we would expect the futures price to rise

to eventually hit the price of copper.

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And therefore this market where the

price of the future in the future is

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lower than the spot price or the near

term futures market contract, we expect

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that to have positive carry as the price

converges to spot over time, right?

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So in this case, we're sort of saying

we're going to earn a little over

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3 dollars as this distant future

becomes less distant over time in

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terms of time as time rolls forward.

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But futures markets can take many shapes.

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So you'll, you'd imagine copper futures.

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You might be able to buy copper for

delivery and maybe, you know, it's

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May now, maybe you can buy copper

for delivery in June, in September

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and December, in June of 2026.

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And so you can plot the price of each

of these different futures markets.

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On a chart going out through time.

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And that describes the term

structure of that futures market.

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So in this case, you know, the

contracts going out into the future are

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priced at successively lower prices.

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And as you go out sort of far enough,

they begin to rise a little bit.

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And that's just very typical futures

markets tend to have a curve in them,

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reflecting the supply demand dynamics of

the market at different points in time.

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Rodrigo Gordillo: Right.

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And so this has got kind of just

thinking about putting the two charts

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that we just went through together here.

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There's many opportunities to

measure carry, assess carry to

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define what carry is for this

particular fictitious contract, right?

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And you're going to get, you're

going to get a reading on that.

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And carry is really about.

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You're making allocation decisions

based purely on that yield, that futures

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yield, much like if you think about in,

trying to select securities based on

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some sort of a shareholder yield, right?

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So I know that these are done very well.

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Meb Faber has done a lot

of work on this, right?

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You're just measuring the type of

yield that the company as a whole is

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pushing out and selecting those assets.

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Solely on that, not on price momentum,

not on value, just purely on that.

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And while much like, shareholder

yield provides positive expectancy

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above cash, we find the same

thing when we select based purely

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on this type of futures yield.

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Adam Butler: Right.

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And in this case, this futures curve is

what we might call backward dated, where

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the few, the prices in the future are

lower than the nearer term or spot price.

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And again, with this future market, we

would expect this to deliver positive

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carry as these distant futures begin

to converge on the higher spot price

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over time, all things equal, right?

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Of course, it never works

out exactly like that.

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The price is, The near term

contract and spot change over time.

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The prices of the distance contracts

change over time, but on average, we

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expect this general drift to occur.

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Just like on average, we expect

equities to have a positive drift,

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but they go up and down over time.

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Rodrigo Gordillo: And two things on that.

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Number one, the, on this shape of the

curve in that case, We're backward

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aided, we're going long those contracts.

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If it's flipped on the opposite

side where it's upward sloping,

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it would be the opposite.

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We'd be looking to short

those contracts, right?

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Cause those will, they will

gravitate towards zero.

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And yes, just to round off what you

said, shareholder yield, finding a stock

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that has a strong shareholder yield

does not guarantee that the price plus

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shareholder yield is going to make you a

positive return at the end of the year.

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It just tends to be that way over time

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Adam Butler: on average.

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carry, it's sort of lived outside the

Overton window for several decades.

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There, you know, there were lots of

managed futures funds that did either

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indirectly or directly use carry as

a signal to inform their portfolios.

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And in fact, when we survey the offering

documents for a variety of funds in

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the SOC gen, CTA index, We find that

carry is mentioned second only to trend

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in terms of the frequency that it's

mentioned as a signal that it informs

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the, the trades that they make and the

portfolios that they hold over time.

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So, you know, it's not as esoteric

as, as many people believe.

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And it also, in a managed futures

context, is, Considerably different

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than what many old timers might remember

as being the sort of idea of currency

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carry, which for a while was the

idea of, shorting the currencies in

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low yielding, regions, like the U.S.

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dollar or the Japanese yen and buying

emerging market currencies that typically

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have, Higher local interest rates, right?

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So that's not the carry that

we're that we are implementing

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currency carry in broadly that way.

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But when you expand a canvas to

include equities, bonds, and a wide

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variety of different commodities,

the carry strategy takes on a very

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different profile as you'll see.

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So what drives carry?

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We talked about equities and

bonds, you know, in equities,

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it's the dividend yield.

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That is reflected in the futures

term structure for bonds.

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It's the, we're only dealing with

government bonds in this context.

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So it's the, you know, whether the

bond cash treasury term structure

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or the guilt term structure.

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or the bund term structure

in Europe, for example, has a

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positively sloping yield curve.

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So if the 10 year yield is higher than

the three month treasury, for example,

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that would, we would sort of consider

that to be a positive yield curve, and

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it would have positive carry in bonds.

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At the moment, you know, we're

in a bit of a strange situation

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where near term yields Are actually

higher than most longer term yields.

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So bonds currently are typically

measured to have negative carry.

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but again, that's rather unusual

over the past 30, 40 years.

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In commodities, there's a convenience

yield, which is sort of the convenience

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that the speculators offer to producers

in order to take on the price risk.

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So producers can sell their production

forward, have some certainty about

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the price that they're going to get

for that production, and they can

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go and raise capital for to invest

in new projects, that sort of thing.

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And in currencies, it's just

the difference between the.

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the short term interest rate in the

jurisdiction you're borrowing in.

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In our case, we're only using U.

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S.

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dollar crosses.

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We're always borrowing in the U.

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S.

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dollar to invest in a foreign

currency or borrowing in a

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foreign currency to invest in U.

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S.

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dollars, depending on which of

those has a higher interest rate.

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Now, I'm not going to dwell on this.

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This is just why do equities and bonds

need to have a positive long term carry?

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Well, because in order to invest in

equities and bonds, You need to move from

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very liquid cash into illiquid securities.

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You don't know what you're going

to be able to sell those securities

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at some point in the future.

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If you need liquidity quickly, you may

have to take a hit on the price you

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would realize for those securities.

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There's also inflation uncertainty.

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We don't know what inflation will

be like in the future and you need

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to be compensated for locking your

money up for a long period of time.

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And also you also, you need

to defer consumption, right?

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Instead of buying something that you

want today, you're deferring consumption.

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Putting it in savings vehicles or in

investments, hoping that those investments

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will grow over time, but you need

to defer what you want to buy today.

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So that's standard stocks and bonds.

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Commodities, just to dig in a little

further, it's very accretive for commodity

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producers to sell their production

forward often many years into the future.

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Imagine, a mining company wants

to develop a new copper mine.

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And.

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By the time you get the environmental

permitting, all of the engineering spec'd

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out, you do all the assays, et cetera,

to figure out what kind of mine you want

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to build, it's probably 10 or 15 years

before you get to first production.

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So the copper companies will sell a

good portion of the expected production

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from those mines forward in order to

block in the economics or a substantial

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portion of the economics on that project.

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And they have many projects going

on in many different regions for

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many different metals, et cetera.

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Energy companies are doing the same thing.

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Grain producers are doing the same thing.

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And this is highly accretive because

it lowers the, variability of

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their earnings over time and gives

investors certainty and that higher

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certainty for investors lowers the

cost of capital to the producer.

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They're able to go to the debt market and

raise money at lower interest rates and

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go to the equity market and raise money at

higher multiples, lower cost of capital,

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higher ROI to the producer over time.

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So it's kind of a win situation.

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Speculators are providing, they're

insuring the producers against

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price fluctuations and they earn

a premium on this insurance.

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And that's why we expect this over time.

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Now, the commodity premium can be

positive or negative depending on

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the short term dynamics in a market.

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We saw energy prices go negative in

early:

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when there were all these pipelines

leading to storage facilities and the

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storage facilities were totally full

and they would, were selling oil at

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negative prices in order to make room

for new oil coming from pipelines

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that had to go somewhere, right?

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So there's short term supply demand

and dynamics that can make the term

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structure for commodities positive or

negative And make it more attractive

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to be short than long or vice versa

and that's why in carry strategies,

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sometimes you want to be long a market

if it has positive expected carry short

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:

of market, if it has negative expected

carry, if you're short of market that has

361

:

negative expected carry, you're expecting

to earn a positive return on that.

362

:

Rodrigo Gordillo: Yeah.

363

:

So I'll just kind of tie

this all up in a bow here.

364

:

I think generally speaking, we

think that carry signals do provide

365

:

insight into future expected

returns because they should be

366

:

compensated sources of economic risk.

367

:

So, while these things may

get crowded at times, right?

368

:

If too many people go into this one trade

in a particular market, the yen, U.S.

369

:

trade or whatever, it's not rational

economically for a risk premium

370

:

like carry to get arbitraged away.

371

:

Because As Adam kind of alluded

to here, there are players, there

372

:

are willing participants here that

are getting economic benefit for

373

:

hedging their risk and the other

side for taking that risk, right?

374

:

So it would require for this not to

be a risk premia, it would require

375

:

parties to be, willing to bear risk

with zero expected compensation, which

376

:

is not how the economy works, right?

377

:

So I think that's a good basis

for this whole carry thing.

378

:

Adam Butler: Yeah, so carry is

more of a classical risk premium,

379

:

then it's a lot harder to make

that same sort of case for trend.

380

:

There are different reasons

why we think trend exists.

381

:

Carry it's a little bit clearer

that this is a risk based premium.

382

:

So, for the purpose of our

experimentation, we use this diverse

383

:

universe of different global equity

markets, major global government

384

:

bond indices, a variety of major

currencies and, commodities in

385

:

the energy and metal sectors.

386

:

We didn't include any, grains or

softs or other more, out there,

387

:

commodity sectors for, you know,

liquidity reasons, et cetera.

388

:

In practice, there are commodities within

other sectors that are plenty liquid.

389

:

That, you know, could be used in

scalable carry strategies, but

390

:

this was our experimental universe.

391

:

Rodrigo Gordillo: And just as we go

into a lot of the analytics here,

392

:

I think this is a good question

somebody's asked for us to clear up.

393

:

So the question asked is it considered

a carry trade when, for example,

394

:

commodity, a commodity pool owns

treasuries as a form of collateral

395

:

for the futures contract, right?

396

:

So this is, what he's alluding to

is that if you X ray a fully funded

397

:

futures strategy or commodity strategy,

it is anywhere between 80 and 90%

398

:

Treasuries, short term treasuries

that you're earning yield on.

399

:

And then the remaining cash is

used as collateral to buy and

400

:

sell those futures contracts.

401

:

And so I guess I'll get my 2 cents

out Adam and then maybe you can

402

:

correct me, but it's important to

note that what we're going to be

403

:

presenting here is excess returns.

404

:

So we are not including the carry on

cash that would exist if we were to port

405

:

this strategy over to a traditional fund.

406

:

So this is, am I right in saying

this is excess returns, Adam?

407

:

And so what excess returns

mean is the returns above cash.

408

:

it's what you would get, if you

were to just run the strategy

409

:

without any cash yield whatsoever.

410

:

So it's not the, to answer your

question, this is the yield you get

411

:

on the treasuries in a pool is not

considered carry in the traditional

412

:

sense, in the sense that we're

going to be talking about here.

413

:

Now, can we make a case for

it being carry if you're fully

414

:

funding a fund that uses carry?

415

:

Yeah, I guess you could say that

it is a carry, but it has no

416

:

specific, quantitative strategy.

417

:

It's just, it just happens to be

along for the ride rather than it

418

:

being an explicit bet on carry.

419

:

Adam Butler: Yeah, that's

a really good point.

420

:

So how do you build carry strategies?

421

:

There's actually a few

different ways to do it.

422

:

One way is using time spreads or

calendar spreads where you want to be

423

:

totally neutral exposure to a market.

424

:

And you will just, for example, go

long the near term contract and short

425

:

the far contract, and then just take

the ride of the short term contract.

426

:

the longer term contract converging to

the shorter term contract over time.

427

:

That's one, way to do it.

428

:

Another is cross sectional carry.

429

:

We're going to go through that in quite

a bit of detail, which is typically

430

:

implemented at the sector level.

431

:

So for example, if you've got eight

different equity markets, you're running

432

:

a cross sectional equity carry strategy.

433

:

You're going to be long for equity markets

and short for equity markets all the time

434

:

to main, maintain that sector neutrality.

435

:

And same for long and short

energy markets, long and short

436

:

bond markets, et cetera, right?

437

:

So that's a cross sectional

or sector neutral strategy.

438

:

And then the third way is a time

series carry strategy, which is the

439

:

one that we're gonna spend the most

time on here today, where you're

440

:

allowing the portfolio to get, you

know, a little bit more crowded.

441

:

In the, on the long side, if most of

the markets in a sector or most of the

442

:

markets in the portfolio have positive

expected carry and you're allowing, you

443

:

know, get more short in on a net basis.

444

:

If more of those markets, have

negative expected carry than

445

:

positive expected carry, right?

446

:

So again, time series, strategies

allow for sector exposure to drift

447

:

higher or lower into negative territory

over time in response to how the

448

:

underlying markets are, you know,

expressing positive or negative carry.

449

:

Whereas a sector neutral strategy.

450

:

All the markets in the sector could

have positive expected carry, but you're

451

:

still enforcing the constraint that

half of them need to be held short in

452

:

order to eliminate any sector exposure.

453

:

Okay.

454

:

And we'll see how that impacts

strategy performance over time.

455

:

So within these, cross sectional

or time series strategies, we also

456

:

divide it up in terms of measuring

carry on an absolute basis.

457

:

Which is what we've been talking about

so far is the term structure of the

458

:

futures for a market positive sloping,

implying negative carry or negative

459

:

sloping, implying positive carry.

460

:

so that's sort of absolute carry

and have a more traditional way

461

:

of people thinking about it, but

there's also a relative value carry.

462

:

So if we look at the very

long term average of the term

463

:

structure, so for example, gold

is usually in, has a positively

464

:

sloping term structure, slightly

positively sloping term structure.

465

:

So the carry for gold in an

absolute sense, usually implies

466

:

negative, slight negative carry.

467

:

But if instead you look at the long

term average term structure and you

468

:

measure carry relative to that long

term average, then when it's above

469

:

average carry, then you'd go long.

470

:

When it's below average

carry, you'd go short.

471

:

and so it's just a slightly

different cut on this concept.

472

:

Then there's how you want to

transform that carry signal, right?

473

:

So a really simple way would say,

well, I want to be one unit long.

474

:

If the, or one volatility unit long,

as we'll talk about a little bit

475

:

later, if carry is positive, one

volatility unit short, if its carry

476

:

is negative, that's binary signals.

477

:

Or we could be long or short in proportion

to the, just the strength of the raw carry

478

:

measure, or that the degree to which carry

is above or below its long term average.

479

:

And then also we can rank the

markets in, in the portfolio by

480

:

their carry as well and use the

rank score, positive or negative

481

:

rank score as their, carry measure.

482

:

So there's all these different sort

of ways to skin the cat and they all

483

:

deliver, they all sort of capture the

same underlying phenomenon, but they do

484

:

things from slightly different angles.

485

:

And therefore they provide some

diversification benefits when

486

:

you combine them all together in

a portfolio, as we'll discuss.

487

:

So just to reinforce this

concept of absolute carry.

488

:

This is, again, just kind of

what we've already been talking

489

:

about most of the time so far.

490

:

These two futures markets, these term

structures, imply negative carry in

491

:

both cases, but the blue line has

a higher negative carry or expected

492

:

negative carry than the black line

in this case on an absolute basis.

493

:

So this is like raw or absolute carry.

494

:

In contrast,

495

:

Rodrigo Gordillo: Can you

go back for a second, Adam?

496

:

Adam Butler: Sure.

497

:

Rodrigo Gordillo: So what you're

saying here is there's two contracts.

498

:

So in a carry portfolio, that's trying to

decide whether to invest based on carry.

499

:

All things equal.

500

:

If they have the same volatility, same

type of correlation, the blue line at the

501

:

top would receive a higher weighting than

the black line, but they both receive a

502

:

negative would be shorting both of them

because they, they are, they, you know,

503

:

they're going to go from the high price

in the future and roll down to spot.

504

:

Is that fair?

505

:

Adam Butler: Yeah, that's a good point.

506

:

And so if it were a binary, transform,

then actually they would both be short

507

:

and have the same volatility adjusted

weight in the portfolio, right?

508

:

if they were ranked or if we were using

the raw score, then the market represented

509

:

by the blue line would be expected to

have a higher, negative weight in the

510

:

portfolio than the black line, right?

511

:

For the reasons it's discussed.

512

:

So that's good.

513

:

Now this is relative value carry.

514

:

We call it carry Z because

we're actually doing a Z score.

515

:

And a Z score is just what is the

current value relative to the mean value.

516

:

So that difference divided by the

amount that value varies over time or

517

:

the volatility of that value over time.

518

:

Okay.

519

:

So that's why we sort of use

carry Z score and relative value

520

:

carry kind of interchangeably.

521

:

Rodrigo Gordillo: Let me clear

that up a little bit more.

522

:

What do you mean by mean value?

523

:

So basically the, where is the carry

today relative to a historical average?

524

:

Adam Butler: Exactly.

525

:

Yeah.

526

:

So we just take the historical average

of the entire term structure, and then

527

:

we look at, well, is it, is the carry

higher or lower than what it, what the

528

:

carry typically is over time, right?

529

:

So in this case, the blue line represents,

higher than average negative carry.

530

:

The green line, while it also indicates

negative carry, it's lower than

531

:

negative, average negative carry.

532

:

And therefore we would be short the

blue line and long the green line in

533

:

this case, because we're now measuring

carry relative to its long term average

534

:

black line, not on an absolute basis.

535

:

Okay.

536

:

Okay.

537

:

So now the fun part, we're going to start

with an examination of whether, carry has

538

:

existed in each individual market sector.

539

:

So equities, bonds, and

different commodity sectors

540

:

and currencies on their own.

541

:

And then we're going to kind of begin

to combine things together and see

542

:

how that everything kind of works

together in a stepwise fashion.

543

:

So this will reinforce, because

we're dealing with markets in sectors

544

:

that have very different ambient

risk, like obviously bonds are

545

:

going to have very different long

term average volatility than say

546

:

natural gas or crude oil or copper.

547

:

we're going to, we're going to

scale all of the markets in each

548

:

portfolio to have the same volatility.

549

:

And then we're also going to scale

the volatility of each portfolio

550

:

to have the same target of 10

percent annualized volatility.

551

:

And when we scale them every

single day, we're evaluating the

552

:

volatility of the underlying markets.

553

:

They're correlation to one another.

554

:

And then we're using those estimates

to scale that portfolio to, the

555

:

target that best approximates

what we've estimated from the

556

:

portfolio in the very recent past.

557

:

Rodrigo Gordillo: Right.

558

:

So in that sense, you're not letting

the maniacs take over the asylum, right?

559

:

You're making sure that your bets

are equalized across the sector.

560

:

And then you also don't want to have any

asylum be too big over another asylum.

561

:

And you're getting that kind

of like you're equalizing

562

:

the risk for the assignments.

563

:

Adam Butler: So that all the

sectors have the same volatility.

564

:

Exactly.

565

:

But this is why, even though

we're scaling to target 10 percent

566

:

volatility in these portfolios, it

never actually gets to exactly 10%.

567

:

Because there's some error in our

estimation of what the portfolio

568

:

volatility is going to be in the next

period, every time we estimate it.

569

:

Right.

570

:

So we get close.

571

:

But we rarely get dead on, right?

572

:

And then we're just scaling, use a fairly

near term estimate of volatility based

573

:

on what happened over the last 40 days.

574

:

And we're using, because it's an

exponentially weighted moving average,

575

:

the nearer term returns matter a bit more

in our estimate than the returns that are

576

:

more distantly in the future, in the past.

577

:

Rodrigo Gordillo: And

you talk about the floor.

578

:

Adam Butler: Oh, yeah.

579

:

The floor just means that there are

some times when, you know, a market

580

:

seems to have just extraordinarily low

volatility over a short period of time.

581

:

And when you're deep in that low

volatility tail, that's often a

582

:

sign that you're misjudging the

true volatility of the market.

583

:

So we never let our estimate of volatility

go below the fifth percentile of our

584

:

measured volatility over the full

period of history prior to that date.

585

:

Rodrigo Gordillo: So that you're

not levering up a single security

586

:

that has never been, never shown or

exhibited that low level correlation,

587

:

or not never, but very rarely.

588

:

Adam Butler: Okay.

589

:

So again, these are just sort of

starting on, sector neutral or

590

:

cross sectional start strategies and

strategies that are using absolute

591

:

or raw carry to measure carry, right?

592

:

So raw carrying currencies and all the

way up through raw carrying equities.

593

:

Now you can see that enforcing

sector neutrality has a penalty.

594

:

We do not want to take on any sector risk.

595

:

And, you know, that's okay across most

of the sectors historically, but a few

596

:

of the sectors have either very low or

slightly negative historical returns

597

:

if you're not willing to take on some

sector risk when the, the carry skews

598

:

towards long or skews towards short

in any given sector over time, right?

599

:

they still all do relatively well

with the exception of equities.

600

:

but not quite as well as we'll see when

we adjust the measure of carry for,

601

:

you know, against the long term average

carry for each market in the sector.

602

:

We're still holding the sectors market

neutral in this case, but we're sorting

603

:

them based on the degree to which

they're, the carry is above or below the

604

:

long term average within each sector.

605

:

And this seems to have, deliver better

performance over the very long term.

606

:

Now on a time series sense.

607

:

Now we're allowing the sector exposure

to drift positive or drift negative.

608

:

If there's a preponderance of markets

that have positive carry or negative

609

:

carry at any given moment, right?

610

:

We do that using raw carry as our

signal, then the performance generally

611

:

improves across the board and we see

the same phenomenon with relative value

612

:

or carry Z, signals where allowing

that sector exposure to drift higher

613

:

or lower is long-term accretive.

614

:

As we're now accepting more sector risk

as well, when we aggregate up all of

615

:

the sectors together and we just look at

the cross-sectional carry for equal risk

616

:

weighting all of the different sectors

and are using a cross-sectional, portfolio

617

:

approach, then you can see that the carry

Z outperforms the, the regular carry,

618

:

which is consistent with what we kind

of saw at the individual sector level.

619

:

And when you combine the regular carry and

the relative value carry Z signals into an

620

:

ensemble for sector neutral strategies, it

actually rolls up pretty well with a long

621

:

term Sharpe ratio of around 0.55, right?

622

:

But still it doesn't compare to the

performance of time series strategies

623

:

where we're now allowing sector

exposure to drift over time, both

624

:

raw carry and carry Z strategies.

625

:

Both perform very well

on a time series basis.

626

:

When you roll them up together,

they do even better with a

627

:

sharp ratio in the range of 0.

628

:

9.

629

:

And even when you combine the sector

neutral strategies with the time

630

:

series strategies, because of the low

correlation, you still preserve the

631

:

majority of the performance you get

from the pure time series strategies.

632

:

when you combine everything together,

just the power of diversity and

633

:

ensembling, which we're going to

discuss as we go forward, we pretty

634

:

well use ensembles in all of our

strategies everywhere for this reason.

635

:

It should be noted by the way, because

we brought up the idea of you know,

636

:

raw signals, binary signals, and rank

signals, that in each of these cases,

637

:

we're just combining strategies based

on raw, strategies based on binary,

638

:

and strategies based on rank all

together within individual sectors,

639

:

within individual cross sectional

versus time series ensembles.

640

:

And within the total

ensemble portfolio, right?

641

:

So this is gives you a general idea of

the performance of all of these time

642

:

series and cross sectional portfolios.

643

:

over time you see the, you know, the

cross, one of these cross sectional

644

:

portfolios, just didn't perform very well.

645

:

Again, if you're not willing to accept

sector risk, then you're removing

646

:

what turns out to be a meaningful

component of the carry signal over time.

647

:

So that was individual sectors.

648

:

Most managers also sort of contemplate

or actually focus their portfolio

649

:

management on the total portfolio

and not just on individual sectors.

650

:

So in this case, we're allowing,

let's say, you know, all of the.

651

:

energy markets had negative carry, but

all of the bond markets had positive

652

:

carry or some mix, whatever we're allowing

those markets that have positive carry,

653

:

to be held in positive weight in those

markets with negative carry to be held

654

:

in negative weight in the portfolio

without sector constraints, right?

655

:

It's just, you're going to be held in

the direction of your raw carry or your

656

:

relative value carry in the portfolio.

657

:

We're going to show an inverse volatility

weighted version of this, which is just

658

:

using, instead of just applying inverse

volatility weighting at the sector level.

659

:

Now we're going to apply this

at the total portfolio level.

660

:

So we're measuring the volatility

of every market in the portfolio.

661

:

The exposure is going to be

the carry score, or the carry Z

662

:

score, divided by that market's

volatility estimate at that moment.

663

:

And then we're going to scale the,

Exposure of all markets in the

664

:

portfolio to hit a target of 10 percent

annualized volatility based on our

665

:

best estimates at any given moment.

666

:

Okay.

667

:

So that's naive or inverse

volatility weighting.

668

:

We're also going to explore a mean

variance optimization of the same concept.

669

:

In that case, we're trying to maximize

the total amount of both long carry

670

:

exposure and negative carry exposure.

671

:

So short exposures while simultaneously

trying to minimize the total

672

:

portfolio volatility, right?

673

:

The way that you would in a

typical mean variance optimization.

674

:

So it's just a carry score

is our return estimate.

675

:

And we're just trying to minimize

the total portfolio volatility while

676

:

maximizing our exposure to carry.

677

:

So the naive weight inverse

volatility, and then an optimization

678

:

we're going to get to after that.

679

:

So starting with the

inverse volatility waiting.

680

:

So now we're only exploring

time series versions of this.

681

:

We're going to leave the sectoral

sector neutral versions of these behind.

682

:

We're going to accept the fact

that we're going to have some

683

:

Sector exposure over time.

684

:

If all of the markets in a given or

most of the markets in a given sector

685

:

have positive carry, we're going to

have positive exposure to that sector.

686

:

And we're just going to live with that.

687

:

And we're going to also harvest

the excess premium we've got

688

:

from accepting that risk.

689

:

So looking at.

690

:

normal carry, but now examining just using

the carry score as a continuous signal,

691

:

or binary carry, is it positive or is

it negative, and then rank carry, so the

692

:

score becomes the rank, then you can see

all of these do quite well, you know,

693

:

in this case, the raw carry doesn't do

as well as the rank carry, the binary's

694

:

somewhere in the middle, we're going to

see that this is random noise, and that

695

:

all of these Carry signals and transforms

are basically, they all give you

696

:

approximately the same strength of signal.

697

:

It's just, some of them have done

worse or better recently or what

698

:

have you, but it's just noise.

699

:

So exploring the same thing for relative

value carry, we see, you know, a

700

:

different, well, we're preserving the

order here in terms of sharp ratio, but

701

:

the relative value carry in this case

tends to do a little better than the,

702

:

raw carry in some cases, a little worse

in other cases, again, emphasizing that

703

:

we are using all of these different cuts

at the same phenomenon, not because any

704

:

of them have better or worse expectancy

over time, but because they all do

705

:

slightly different things at different

times and diversify one another, but

706

:

they all do well as you can sort of

see from their long term profile.

707

:

Now transitioning to mean

variance optimized portfolios.

708

:

We're again considering both volatility

and correlation to minimize portfolio risk

709

:

while maximizing total portfolio carry.

710

:

Just using raw carry

with various transforms.

711

:

All do very well, and they tend to

do a little bit better than the naive

712

:

portfolios that are not accounting

for correlation differences over time.

713

:

Carry Z showing equally strong performance

with mean variance optimization.

714

:

And you can see these are a little bit

more tightly grouped over time, then the

715

:

inverse volatility or naive weighting,

again, they do slightly better than

716

:

naive portfolio weightings, but for the

most part, it's just noise and what is

717

:

better is to combine a naive weighting,

which makes fewer assumptions about

718

:

the portfolio with the mean variance

optimization, which makes a couple of

719

:

more assumptions about the portfolio.

720

:

Mainly that we, that correlation

estimates are a little bit persistent.

721

:

So when we're measuring the current

correlations, those correlations

722

:

are likely to be approximately

the same in the next period.

723

:

Combining those different approaches

is highly creative, right?

724

:

For diversification reasons.

725

:

And when we do combine them, we

observe smoother performance, higher

726

:

sharp ratios over time, right?

727

:

So we're just, this is just building up

again to our final meta, meta ensemble,

728

:

but just focusing on all of the different

inverse volatility portfolios, right?

729

:

using regular carry, all of them

using relative value carry, Z carry.

730

:

And when you combine them

both, you go from about a 0.

731

:

85 sharp to a one sharp.

732

:

This is just with the inverse

volatility, but ensembling.

733

:

Right.

734

:

And there's the green line above

both of the, constituent ensembles.

735

:

Rodrigo, I don't know if that's confusing.

736

:

Yeah.

737

:

Rodrigo Gordillo: No.

738

:

So I just want to, I don't think it's

confusing, but I think for those who

739

:

haven't read our research in the past.

740

:

I think it's important to put a

stake on the ground right here and

741

:

make sure that everybody understands

the difference between over

742

:

optimizing and narrowly data mining.

743

:

And creating a robust portfolio

that is likely to work out of

744

:

sample, meaning in real life.

745

:

And it may seem like all these

layers that Adam's been talking

746

:

about is about, you know, getting

more narrow and more optimized, but

747

:

in fact, it's the complete opposite.

748

:

It is the idea of trying to be

broadly correct about capturing

749

:

the carry signal rather than being

specifically wrong and assessing

750

:

all of these individual parameters.

751

:

Finding the one that had the best back

test and choosing that one, right?

752

:

So an example that I often use with regard

to the value of being humble about your

753

:

ability to capture any signal, the way

we're doing here through ensembles is, I'm

754

:

sure everybody a couple of years ago heard

that the, that we captured as humanity,

755

:

the first image of a black hole and the

headline said the event horizon telescope

756

:

captures the first image of a black hole.

757

:

And it was a very well defined black hole.

758

:

It's exactly what we imagined high def.

759

:

It was a beautiful image.

760

:

What few people know is

that wasn't one telescope.

761

:

The event horizon telescopes is actually

hundreds of telescopes across the world

762

:

in many different sites that are capturing

different types of signals, radio

763

:

waves, infrared, you know, they're all

measuring the black hole in their own way.

764

:

And what the team had to do is

over a couple of months in the U.S.

765

:

is grab all of that data.

766

:

Put it together,

eliminate the error terms.

767

:

And what they got was that beautiful

image that we received in the news.

768

:

Any single telescopes image,

if you watch the, there's a

769

:

documentary on Netflix is garbage.

770

:

It's doesn't make a lot of sense.

771

:

It's kind of the outline, right?

772

:

So it really is ensembles is the most

robust way that we have found as humanity

773

:

in terms of noise to ratio, noise to

signal, to make sure that we are broadly

774

:

correct about what we're trying to do.

775

:

Adam Butler: Yeah, no, that's

a really great metaphor.

776

:

and I love it that you saw

the opportunity to use that.

777

:

And this is just the most widely

document phenomenon in, data

778

:

science and machine learning.

779

:

So the winners of Kaggle competitions

invariably every time are

780

:

using ensemble type techniques.

781

:

All right.

782

:

It's just vastly superior to view a

problem from a wide variety of different

783

:

angles and aggregate the signals up when

you aggregate the signals, you reduce

784

:

the noise and emphasize the signal.

785

:

And so that's all we're doing

here with at the portfolio level.

786

:

Great point.

787

:

So now it's just the optimization.

788

:

It's also, I think, worth saying

that when we're portfolio optimizing,

789

:

we do this every single day, right?

790

:

So we're, you know, it's today.

791

:

We look back over the last Several days,

several months, we're estimating the,

792

:

variances and correlations of between

all the different markets at that time.

793

:

We're estimating the carry and

we're forming a new portfolio.

794

:

Then we move forward one step, we

look back again, and we, you know,

795

:

we're, we use that information

to form a brand new portfolio.

796

:

So we're constantly rebalancing into

a portfolio seeking to emphasize

797

:

or maximize carry while minimizing

portfolio volatility, right?

798

:

So when we're doing that, you know, when

we ensemble all the different transforms

799

:

of raw carry, We do very well, carries the

relative value that does well when you put

800

:

them together, you go from kind of a 0.

801

:

9 sharp ratio to almost a 1.

802

:

1 sharp ratio.

803

:

Historically gain just the power

of approaching it with ensembles

804

:

and the ensemble line above

either of the constituents line

805

:

scaled to the same volatility.

806

:

Now, you know, an actual question

to ask at this point is, well, you

807

:

don't know if you've been reading the

disclaimers, but they're all showing

808

:

gross, returns gross of estimated

trading costs and commissions.

809

:

So, you know, it's a good question.

810

:

Well, do these returns survive?

811

:

Estimated real trade frictions, real trade

slippage, commissions paid, et cetera.

812

:

And, so, you know, we've been

nning future strategies since:

813

:

So we've got seven or eight years of

live data from our own trading that

814

:

we are able to use to get really good

estimates on the cost of trading these.

815

:

And then there are papers that

we lean on for the cost of.

816

:

You know, trade frictions on

different markets going back

817

:

to earlier points in history.

818

:

And we're able to net these out

and get estimated net results.

819

:

It's also important to know that we

are, we do with some smoothing, right?

820

:

So when we ensemble all of these

different, approaches together, they

821

:

all recommend slightly different

Portfolios at any given time.

822

:

And what that means is it averages

out the amount of trading that

823

:

you need to do from day to day.

824

:

So that alone sort of reduces the amount

of trading and therefore the amount of

825

:

trade friction that you experience, the

amount of commission you pay, and that

826

:

demands you place on the market to absorb

the liquidity that you're sourcing.

827

:

We also smooth the waste through

time using a 5 day exponentially

828

:

weighted moving average.

829

:

We find that smoothing like this has no

effect on performance, but does have a

830

:

nice effect on reducing trading frictions.

831

:

so when we apply these smoothing

and ensembling techniques and we

832

:

also embed our, trade slippage

estimates, then we see that we lose

833

:

about 1 percent a year in terms of

returns, which works out to about 0.

834

:

1 sharp ratio.

835

:

and everything kind of just drops by

1%, you know, slightly larger drawdown,

836

:

slightly lower sharp ratio, et cetera.

837

:

But I mean, this is just a tremendously

resilient strategy once you back

838

:

out estimating trading costs.

839

:

Right.

840

:

so a common question is great.

841

:

But if carry is very highly correlated to

the other assets I hold in my portfolio,

842

:

it may not be very useful still.

843

:

Right.

844

:

So it's important to wonder

how the correlation experience

845

:

for carry evolves over time.

846

:

Here we plot the,

rolling one year or late.

847

:

Oh, sorry.

848

:

Rolling three year correlation between

the carry strategy and the S& P 500.

849

:

And the U S 10 year treasury future.

850

:

And you can see that, you know, it

does go through multi year periods

851

:

where bonds have a positively sloping

yield curve and our carry bond

852

:

exposure is predominantly positive.

853

:

equities, the dividend yield on

most global equity markets is higher

854

:

than their local short term rates.

855

:

And so they have positive carry.

856

:

And so it, you know, we have

a proper ponderance of long

857

:

equity exposure or vice versa.

858

:

Right.

859

:

So it does fluctuate over time.

860

:

That said the long term average

correlation between stocks and

861

:

bonds and carry is about zero.

862

:

Yeah, sorry,

863

:

the correlation between carry and

trend is in the neighborhood of 0.

864

:

3 to 0.

865

:

4, depending on the, the frequency

that you're measuring at.

866

:

Right?

867

:

So, whether you measure daily returns

or monthly returns, et cetera,

868

:

it's in the neighborhood of 0.

869

:

3 to 0.

870

:

4, which is still very much in

the range of a strategy that is.

871

:

Where two strategies can be combined and

be nicely complementary to one another,

872

:

which we'll see a little bit later on.

873

:

Now, it's important to examine how Carry

performs in different market regimes.

874

:

And we define regimes in a few

different ways, but a common way Is

875

:

inflation currently trending higher

than expected or lower than expected?

876

:

And is growth currently coming

in a little higher than expected

877

:

or a little lower than expected?

878

:

And therefore we can divide things broadly

in this kind of four different regimes.

879

:

And I think, Rodrigo, you had a poll

question that you wanted to ask.

880

:

Rodrigo Gordillo: Yeah, Ani, if you don't

mind pushing the next poll question,

881

:

why don't you go to the next slide?

882

:

the question is, Given everything

that we've reviewed, where do you

883

:

think, carry loses money, right?

884

:

Cause everything, everything that this

chart shows is really, you know, we

885

:

can expect gold and commodities to do

well in rising inflation environments,

886

:

but we can likely expect them to lose

money generally in lower inflation

887

:

environments and low growth environments.

888

:

And so there's winners and losers.

889

:

Even when you think about trend following,

you know, we can be very clear about.

890

:

When there are very persistent

trends, almost all the time when

891

:

there's a bear market, you can count

on trend to, to likely be there

892

:

and provide really strong offset.

893

:

So there's an intuition there.

894

:

I'm just curious to know from the crowd,

what the intuition is for carry here.

895

:

What is the, what regime

does it lose money in?

896

:

All right, given that we

have Not a lot of time, Ani.

897

:

Why don't you push that through?

898

:

Okay.

899

:

All right.

900

:

So that's interesting.

901

:

Okay.

902

:

So we got pretty evenly distributed.

903

:

Why don't we show, what we

actually found there, Adam?

904

:

Adam Butler: Yeah.

905

:

So in fact, we generated the equity line

for the carry strategy, conditioning

906

:

on each of these different regimes.

907

:

And so each of these lines represents

the cumulative growth of the carry

908

:

strategy only during periods that are

aligned with, you know, inflationary

909

:

growth, deflationary growth, inflationary

stagnation, or Deflationary stagnation.

910

:

So the flat periods here are when the

strategy is not in that regime, right?

911

:

And then it moves up or down based

on how it performs conditioned

912

:

on being in that regime.

913

:

And what we see is that in broad strokes,

carry is not really very sensitive

914

:

to any of these, these broad regimes.

915

:

and that's partly due to the fact

that Because of the diversity

916

:

of markets, That are held in the

portfolio and the propensity for

917

:

the portfolio to be relatively

diversified most of the time, it ends

918

:

up having a very stable return stream.

919

:

We don't have a lot of really big,

monthly or quarterly losses or gains.

920

:

And so that the historical frequency

distribution, if you kind of compare

921

:

it to trend or to stocks, is a little

bit more normal or Gaussian in shape,

922

:

which is kind of the holy grail of

what you, I mean, people would maybe

923

:

prefer positive skew and I can get

behind that, but you know, just avoiding

924

:

negative skew, we think is a big win.

925

:

And when you, again, when you

combine carry with trend, with

926

:

equities, with bonds, Then that

distribution becomes even more normal.

927

:

it's also, you know, curious,

how does carry perform during the

928

:

best and worst period for stocks?

929

:

So what we've done here is sorted the,

returns on the S& P 500 into their

930

:

worst quintiles on their left, going

all the way up to their best 20 percent

931

:

of, orders on their, on the right.

932

:

Okay.

933

:

And you can see, obviously the light

blue line is the S& P 500 in its worst

934

:

quarters, it does the worst, right?

935

:

But turns out carry and trend do just

fine during the worst quarters for,

936

:

or have historically done just fine.

937

:

Interestingly, in the second

worst quarter, neither carry nor

938

:

trend really does much, right?

939

:

In, then in the sort of, top three

quintiles, not quarter, quintiles, The

940

:

carry and trend both have a tendency

to do reasonably well and obviously

941

:

these are very good quarters for stocks.

942

:

For bonds we see a similar profile

generally sort of agnostic to the how

943

:

bonds are doing in any given quarter.

944

:

Both trend and carry tend to do relatively

well even in the worst bond quarters

945

:

and then they go on to do actually

quite well in the best bond quarters.

946

:

And then you wanted to

add to those, Rodrigo, or

947

:

Rodrigo Gordillo: no, just kind

of broad, broadly speaking,

948

:

we're kind of on time here.

949

:

So,

950

:

Adam Butler: yeah, let

me sort of zip through.

951

:

We just wanted to go through

the profile of these strategies

952

:

during the worst drawdown periods

for both equities and bonds.

953

:

So this is the, October,

:

954

:

So the S and P 500 global financial

crisis drawdown, and you can see

955

:

carry It was kind of like going

sideways for the early part and then

956

:

went on to deliver nice returns.

957

:

during the tech rec, Carry did very well.

958

:

Very nice offset.

959

:

COVID crash was particularly

challenging for Carry.

960

:

It was probably the most challenging

period for Carry, as the, authorities

961

:

both on the fiscal side and on the

central bank side were way behind

962

:

in terms of implementing policy

to keep up with the news flow.

963

:

And, what we find is that carry strategies

are a little bit more susceptible

964

:

to miscommunication or blunders.

965

:

by central banks, right?

966

:

So, WEN has carried on particularly

badly when central banks have either

967

:

been behind the curve or they've been

misreading the messaging from the markets.

968

:

And in this case, obviously, the

authorities were very behind the

969

:

curve during the COVID crash, and then

they moved extremely aggressively,

970

:

probably more than the market

expected, immediately after the crash

971

:

and and things went in a different

direction than the market expected

972

:

and that wasn't very good for carry.

973

:

Eventually evened out and went

on to deliver very solid gains.

974

:

For treasuries, This is just

the post COVID bond bear market.

975

:

so actually that wasn't too bad for Carry.

976

:

Recovering from the

global financial crisis.

977

:

So Carry did fairly well during the

global financial crisis, but once

978

:

the global authorities stepped in,

they implemented quantitative easing,

979

:

markets began to settle, then Carry

kind of went sideways, struggled

980

:

for a little bit before recovering.

981

:

This is the one to focus

on, the bond massacre of 94.

982

:

Because this is a, an example of where

the Fed was miscommunicating or not

983

:

communicating with the market about their

intentions and about their expectations.

984

:

And they came in with a ver with

a surprise rate rise at aggressive

985

:

surprise rate rise, caught the

bond market off guard, and.

986

:

You know, bonds basically

crashed overnight and

987

:

everyone was sort of offside.

988

:

and that was an example of where carry

kind of struggled in the short term before

989

:

again, going on, and doing very well.

990

:

we'd be, I think, leaving people,

wondering if we also didn't examine how

991

:

carry worked alongside trend and alongside

equities of bonds in a stacking framework.

992

:

So, you know, because carry and trend

both have low correlation to both

993

:

stocks and bonds, They're just both

really accretive when stacked on stocks.

994

:

And here you see both carry stacked

on stocks, trend stacked on stocks,

995

:

and a 50 50 combination of carry

and trend stacked on stocks.

996

:

Obviously, all three looking

very attractive historically.

997

:

Same story stacking on top of

bonds, just very attractive.

998

:

And, turning up a negative return over

the recent bond bear market period

999

:

into reasonable positive returns.

:

01:04:09,029 --> 01:04:14,369

Just isolating the performance of

carry and trend stacks on equities,

:

01:04:14,849 --> 01:04:21,499

obviously boosting equity returns,

lowering equity risk, or not

:

01:04:21,859 --> 01:04:27,819

boosting equity risk by a meaningful

amount, despite the higher returns.

:

01:04:28,674 --> 01:04:32,954

And trend and carry combining to be a

little better than either on its own.

:

01:04:34,044 --> 01:04:40,724

Similar with, with bonds and just

combining everything together.

:

01:04:40,724 --> 01:04:47,244

50 50 stocks, bonds, 50 50 carry

trend, just has a, an astonishingly

:

01:04:47,964 --> 01:04:50,169

attractive historical profile.

:

01:04:50,949 --> 01:04:51,089

Rodrigo Gordillo: Yeah.

:

01:04:51,089 --> 01:04:54,069

And what's important here when we

think about stacking is a lot of people

:

01:04:54,079 --> 01:04:55,719

think, okay, I'm stacking returns.

:

01:04:55,719 --> 01:04:57,199

I'm also stacking a lot of risk.

:

01:04:57,229 --> 01:05:01,419

But I think what we need to point

out here is how little, extra

:

01:05:01,419 --> 01:05:06,439

risk is taken to stack a hundred

percent of these factors, right?

:

01:05:06,439 --> 01:05:14,029

So in the first column there 18.09,

S& P 500 plus, you know, 10 percent

:

01:05:14,029 --> 01:05:16,399

volatility targeted carry is at 20.

:

01:05:16,399 --> 01:05:17,529

66.

:

01:05:17,538 --> 01:05:23,709

So not a lot more risk is taken to double

the returns, from:

:

01:05:23,709 --> 01:05:28,549

With all the caveats that, you know, it

can at any given time correlate and so on.

:

01:05:28,549 --> 01:05:32,619

But it is the benefits of diversification,

the zigging and the zagging.

:

01:05:33,179 --> 01:05:33,359

Right?

:

01:05:33,359 --> 01:05:38,299

Two asset classes and or strategies

that make positive, have positive

:

01:05:38,299 --> 01:05:41,829

outcomes, have an expected positive

return, but move differently from

:

01:05:41,829 --> 01:05:46,699

each other to create lower, low

volatility, high return, strategies.

:

01:05:46,719 --> 01:05:51,422

So examine that table, examine it

in the white paper and, and then

:

01:05:51,422 --> 01:05:54,824

reach out for questions if you want

to get more granular than that..

:

01:05:54,839 --> 01:05:57,205

Adam Butler: Yeah, I think it's

worth adding quickly that, just

:

01:05:57,205 --> 01:05:59,773

think of a carry on equities, right?

:

01:05:59,773 --> 01:06:01,323

So carry versus trend on equities.

:

01:06:01,903 --> 01:06:04,443

So you think about an equity

bull market, equities are rising.

:

01:06:04,963 --> 01:06:09,423

As they rise over time, they're

getting further away from what, you

:

01:06:09,423 --> 01:06:15,183

know, levels where trend would flip

from being long to short, right?

:

01:06:15,723 --> 01:06:18,713

Carry is a little different

as equities rise and rise

:

01:06:18,713 --> 01:06:21,673

toward a peak in a bull market.

:

01:06:22,298 --> 01:06:27,668

The equity dividend yield

is getting lower and lower.

:

01:06:28,348 --> 01:06:34,098

And oftentimes as we're coming into,

a peak in equities, it's corresponding

:

01:06:34,098 --> 01:06:35,908

with the Fed raising rates.

:

01:06:35,908 --> 01:06:37,428

The economy is getting too hot.

:

01:06:37,798 --> 01:06:41,818

The Fed is raising rates so that

the yield on cash is rising.

:

01:06:41,818 --> 01:06:46,758

Well, then the yield on stocks is

declining at some point, the yield on cash

:

01:06:46,758 --> 01:06:50,293

is exceeds the dividend yield on equities.

:

01:06:50,633 --> 01:06:56,483

So while trend continues to buy into

the equity rally, there's a point

:

01:06:56,493 --> 01:07:02,283

at which Carry comes in and starts

getting short equity markets as the

:

01:07:02,283 --> 01:07:04,803

cash return exceeds the dividend yield.

:

01:07:05,163 --> 01:07:10,093

So it ends up being at least mechanically

having the potential to be a nice offset

:

01:07:10,493 --> 01:07:12,563

for what's going on the trend side.

:

01:07:12,573 --> 01:07:16,163

That's just one example how,

you know, carry can mechanically

:

01:07:16,163 --> 01:07:19,333

diversify trend in equity markets.

:

01:07:19,333 --> 01:07:21,913

And there are different types of

examples in different sectors.

:

01:07:22,573 --> 01:07:24,253

Rodrigo Gordillo: And look,

another question that just kind

:

01:07:24,253 --> 01:07:28,163

of falls across the same vein

here, which is roughly speaking.

:

01:07:28,163 --> 01:07:32,913

The question is about carry, trend,

gold, you know, should gold be

:

01:07:32,943 --> 01:07:34,613

avoidable if you can allocate to carry.

:

01:07:34,663 --> 01:07:40,368

and, you know, our view has always been,

these are all idiosyncratic risks that

:

01:07:40,388 --> 01:07:43,648

you should probably add to your portfolio

because we don't know the answer to that.

:

01:07:43,648 --> 01:07:48,208

And in fact, I remember vividly a recent

gold and was it two or three years

:

01:07:48,208 --> 01:07:54,398

ago when gold was rallying and, you

know, trend strategies were long gold.

:

01:07:54,628 --> 01:07:56,118

And carry was shorted.

:

01:07:56,148 --> 01:07:59,468

Carry was wrong because the

carry was negative for gold.

:

01:07:59,478 --> 01:08:04,078

So no, I don't think necessarily if

gold is going, is doing its thing,

:

01:08:04,158 --> 01:08:08,188

there will be times when carry is dead

wrong on that strategy, I promise you.

:

01:08:08,608 --> 01:08:12,338

And so the idea of just eliminating,

if you believe that these, that

:

01:08:12,378 --> 01:08:15,748

assets that you can stack on top

are one of two things, are have a

:

01:08:15,748 --> 01:08:18,268

positive risk premia and are lowly

correlated to everything else.

:

01:08:19,198 --> 01:08:21,327

Any one of those two

will, will be a benefit.

:

01:08:21,898 --> 01:08:27,818

If you expect gold to be, you know,

zero returning real returns, but you

:

01:08:27,818 --> 01:08:30,667

can stack it on top and it happens to

be non correlated to everything else.

:

01:08:30,728 --> 01:08:32,138

It is accretive to the portfolio.

:

01:08:32,238 --> 01:08:34,837

So I think the answer is always yes and.

:

01:08:35,388 --> 01:08:38,308

Adam Butler: And the average

long term correlation of gold

:

01:08:38,358 --> 01:08:40,268

to stocks and bonds is zero.

:

01:08:41,298 --> 01:08:44,778

The average correlation of gold

to carry and trend is zero.

:

01:08:45,848 --> 01:08:49,747

It just protects against 'em, it's

the only thing that can protect

:

01:08:49,747 --> 01:08:51,528

against a certain kind of risk.

:

01:08:52,228 --> 01:08:54,508

I think gold belongs in every portfolio.

:

01:08:55,038 --> 01:09:01,608

And, you know, obviously talk to your

advisor, but to me, yeah, it's highly

:

01:09:01,608 --> 01:09:06,098

complimentary along with all of these

other diversification opportunities.

:

01:09:07,098 --> 01:09:09,688

Rodrigo Gordillo: Why don't we wrap

it up, Adam, and then we'll see if we

:

01:09:09,688 --> 01:09:11,218

have, you know, you go ahead with the

:

01:09:11,218 --> 01:09:13,667

Adam Butler: benefit of carry

strategies in the portfolio.

:

01:09:13,667 --> 01:09:14,988

and yeah, we can take questions.

:

01:09:15,247 --> 01:09:15,788

Rodrigo Gordillo: Yeah, obviously.

:

01:09:15,788 --> 01:09:17,448

Look, we're just to reiterate, right.

:

01:09:17,448 --> 01:09:20,428

In conclusion, I think carry has

a unique place in the portfolio.

:

01:09:20,428 --> 01:09:26,688

It is an under loved strategy that, I

think many people have tried to bring

:

01:09:26,688 --> 01:09:31,087

to market and failed, and we're trying

to like, do our best to really present a

:

01:09:31,087 --> 01:09:33,587

thoughtful case for why it is so unique.

:

01:09:33,598 --> 01:09:34,577

Why it's so useful.

:

01:09:34,798 --> 01:09:37,468

If you're at, people ask me all the

time, you have your bonds, you have

:

01:09:37,478 --> 01:09:40,577

your equities, you have your trend,

what's the next thing you would do?

:

01:09:40,988 --> 01:09:42,288

it's always been carry.

:

01:09:42,348 --> 01:09:46,148

And there's enough, video footage of

Adam just pounding the table on this

:

01:09:46,148 --> 01:09:47,707

over the years that, you know, it's true.

:

01:09:47,707 --> 01:09:51,417

And we've been at, we have used

it for, for a long time right now.

:

01:09:51,417 --> 01:09:55,238

So now the question is, you know,

is this webinar is one of the things

:

01:09:55,238 --> 01:09:58,708

that, will give us a good reading as

to whether there is an appetite for it.

:

01:09:58,738 --> 01:09:59,448

I hope there is.

:

01:09:59,998 --> 01:10:03,478

and if you design it properly,

you design it thoughtfully, you

:

01:10:03,488 --> 01:10:07,978

do ensembles, then it can be just

as a creative, not caveat emptor.

:

01:10:08,038 --> 01:10:09,748

It is normally distributed roughly.

:

01:10:10,088 --> 01:10:11,478

It has volatility.

:

01:10:11,528 --> 01:10:13,088

It will have drawdowns, right?

:

01:10:13,088 --> 01:10:16,548

So if you do a 10 vol, Let's

say it's a sharp of one.

:

01:10:16,778 --> 01:10:20,348

A good heuristic here is to

say, okay, so the return is 10%.

:

01:10:20,378 --> 01:10:23,678

What is a three standard deviation

event for strategy at 10 vol?

:

01:10:23,678 --> 01:10:25,978

It could be like 10 minus

10 is zero minus 10.

:

01:10:26,448 --> 01:10:29,327

Two standard deviation is negative

10 minus 10 is negative 20.

:

01:10:29,388 --> 01:10:32,128

You know, something a bit higher than

that is probably a good heuristic as

:

01:10:32,128 --> 01:10:33,768

to what to expect in terms of drawdown.

:

01:10:34,318 --> 01:10:38,508

One hopes it doesn't happen at the same

time as what you're matching it up with.

:

01:10:38,618 --> 01:10:39,018

Okay.

:

01:10:39,018 --> 01:10:40,338

So there is risk involved.

:

01:10:40,338 --> 01:10:46,988

This is not a, Panacea, it is a unique

diversifier to add to other many things.

:

01:10:47,878 --> 01:10:50,198

So, just recap.

:

01:10:50,198 --> 01:10:51,408

Look, we do a lot of this stuff.

:

01:10:51,458 --> 01:10:52,968

we tend to go long form.

:

01:10:52,988 --> 01:10:54,278

We're 15 minutes over the webinar.

:

01:10:54,298 --> 01:10:55,858

That's not surprising to me at all.

:

01:10:56,188 --> 01:10:58,408

It's a miracle we got here in

such a short amount of time.

:

01:10:58,408 --> 01:10:58,608

I thought it

:

01:10:58,608 --> 01:10:59,508

Adam Butler: was a 90 minute webinar.

:

01:10:59,908 --> 01:11:01,138

I thought we were doing so well.

:

01:11:01,398 --> 01:11:03,818

Rodrigo Gordillo: No, sadly that's,

that's incorrect, but people are here.

:

01:11:03,818 --> 01:11:04,468

So that's good.

:

01:11:04,468 --> 01:11:05,428

If you want to learn more.

:

01:11:05,723 --> 01:11:07,113

Go to our website, investresolve.

:

01:11:07,133 --> 01:11:07,583

com.

:

01:11:07,923 --> 01:11:09,163

we have just revamped it.

:

01:11:09,163 --> 01:11:11,663

So there's a lot of research

for you guys to dig into.

:

01:11:11,673 --> 01:11:13,303

The white paper is available there.

:

01:11:13,303 --> 01:11:15,293

The executive summary is available there.

:

01:11:15,653 --> 01:11:18,313

There's a couple of videos of

Adam kind of like in two minutes

:

01:11:18,313 --> 01:11:22,508

describing the benefits of risk

parity versus carry, you know, there's

:

01:11:22,508 --> 01:11:23,848

some interesting dynamics there.

:

01:11:23,848 --> 01:11:25,158

I've answered a few questions.

:

01:11:25,558 --> 01:11:29,428

I typed out as Adam was talking a few

questions about risk parity and carry.

:

01:11:29,438 --> 01:11:32,238

If anybody wants to take a look at

those, we have our book available on

:

01:11:32,238 --> 01:11:37,608

Amazon, and then you can explore our

strategies that, that span far and wide

:

01:11:37,698 --> 01:11:42,077

across, you know, evolution strategies,

which is, All encompassing, long, short

:

01:11:42,077 --> 01:11:43,998

market, neutral managed future strategy.

:

01:11:43,998 --> 01:11:45,268

You have a carry program.

:

01:11:45,708 --> 01:11:49,128

You have more kind of all terrain

strategies, all types of stacking stuff.

:

01:11:49,128 --> 01:11:51,938

So take a look at our

strategies page, explore that.

:

01:11:52,358 --> 01:11:54,318

if you have any questions,

you can reach out to the team.

:

01:11:54,758 --> 01:11:58,478

and, yeah, I'll see if I can,

the last couple of seconds here.

:

01:11:58,478 --> 01:11:59,888

There's a few more questions, Adam.

:

01:12:00,178 --> 01:12:00,508

is there.

:

01:12:00,948 --> 01:12:04,178

Is there any risk that keeps carry?

:

01:12:04,178 --> 01:12:05,048

I'm going to combine two.

:

01:12:05,048 --> 01:12:05,448

Okay.

:

01:12:05,528 --> 01:12:08,628

Earlier on in the presentation,

there's a question about, and I think

:

01:12:08,628 --> 01:12:09,818

this is super important to address.

:

01:12:10,128 --> 01:12:14,788

are you worried about the, short

volatility character of carry with that's

:

01:12:14,998 --> 01:12:17,498

he assumed, I think this was early on

before you went through everything.

:

01:12:18,068 --> 01:12:20,868

and then this other question is what

is the risk that keeps you up at night?

:

01:12:21,178 --> 01:12:21,448

Right.

:

01:12:21,448 --> 01:12:23,518

So let's address both of those.

:

01:12:24,648 --> 01:12:24,818

Adam Butler: Yeah.

:

01:12:24,818 --> 01:12:25,238

I mean,

:

01:12:25,548 --> 01:12:27,678

Rodrigo Gordillo: does carry

have a short volatility tilt?

:

01:12:28,368 --> 01:12:30,598

Adam Butler: Carry, yeah.

:

01:12:30,598 --> 01:12:32,678

Shortfall carry.

:

01:12:33,288 --> 01:12:39,827

If you run carry on individual sectors

like currencies or equities or bonds, then

:

01:12:39,827 --> 01:12:44,268

you do see some left tail events for sure.

:

01:12:44,378 --> 01:12:46,768

And there's good reasons why they occur.

:

01:12:47,098 --> 01:12:50,128

because there's a flight to

quality during financial crises.

:

01:12:51,118 --> 01:12:51,678

the magic.

:

01:12:51,678 --> 01:12:55,818

in these carry strategies is

the diversity of the holdings.

:

01:12:56,778 --> 01:13:02,368

It's that when there's a crisis in

equities, often there's an offsetting

:

01:13:02,628 --> 01:13:09,228

move in bonds, or there's an

offsetting move in gold or energies.

:

01:13:09,673 --> 01:13:12,383

Or metals or what have you.

:

01:13:12,663 --> 01:13:17,943

And, as a result of that, you actually

do observe a, quite a normal, return

:

01:13:17,943 --> 01:13:26,073

distribution on carry in stark contrast

to the, I think, boogeyman version

:

01:13:26,263 --> 01:13:31,663

that those who had heard of carry a

few decades ago had in their mind.

:

01:13:32,033 --> 01:13:32,503

and.

:

01:13:33,833 --> 01:13:34,843

What keeps me up at night?

:

01:13:36,163 --> 01:13:39,633

I think what keeps me up at night

is that people would lean too

:

01:13:39,633 --> 01:13:43,433

heavily into any one strategy.

:

01:13:43,673 --> 01:13:50,603

You know what the miracle here

is the ability to combine stocks

:

01:13:50,743 --> 01:13:56,733

and bonds and, you know, maybe

gold with carry and trend and.

:

01:13:57,398 --> 01:14:03,028

You know, hopefully other diversifying

strategies that, continue to become

:

01:14:03,028 --> 01:14:06,708

available and that maybe some of them

we will bring to market over time.

:

01:14:07,338 --> 01:14:12,668

But, you know, none of these

strategies, including equities, in my

:

01:14:12,668 --> 01:14:14,577

opinion, should be held in isolation.

:

01:14:14,952 --> 01:14:21,903

the real magic here is combining all of

them together and relying on the fact

:

01:14:21,903 --> 01:14:26,353

that they all deliver their returns for

different reasons at different times

:

01:14:26,353 --> 01:14:31,333

based on different types of risk and

will therefore manifest their risks

:

01:14:31,333 --> 01:14:37,702

at different times and average out

to deliver a much more reliable and

:

01:14:37,702 --> 01:14:43,688

smooth return stream to get you more

reliably to your financial objectives.

:

01:14:44,958 --> 01:14:46,338

Rodrigo Gordillo: Yeah,

that's a great answer, Adam.

:

01:14:46,368 --> 01:14:47,548

I wouldn't add anything more to that.

:

01:14:49,548 --> 01:14:54,018

The, there was one question

about risk parity and carry,

:

01:14:54,058 --> 01:14:55,168

and we talked a lot about that.

:

01:14:55,228 --> 01:14:59,438

there's, if you look up, you know,

risk parity, carry in YouTube,

:

01:14:59,438 --> 01:15:03,888

you'll see us talk a lot about

this and the complementarity of it.

:

01:15:04,138 --> 01:15:07,958

And so the question is risk parity

to be replaced by carry or not?

:

01:15:07,978 --> 01:15:10,148

I just kind of see this

as two separate things.

:

01:15:10,623 --> 01:15:13,683

When you think about risk parity,

you make certain assumptions.

:

01:15:13,723 --> 01:15:19,213

You make an assumption that the, that

returns are commensurate to risk, that

:

01:15:19,423 --> 01:15:22,733

all assets that you're going to be

investing in have the same sharp ratio.

:

01:15:22,733 --> 01:15:24,933

So you're not making a

return assumption whatsoever.

:

01:15:25,473 --> 01:15:29,763

You're assuming that all the assets

you're investing in have a positive

:

01:15:29,763 --> 01:15:31,363

expect a positive risk premium.

:

01:15:31,643 --> 01:15:32,563

always right.

:

01:15:33,233 --> 01:15:36,143

And the reason that risk parity has

become popular, because it was the

:

01:15:36,143 --> 01:15:40,643

thing that I think at least when

Dalio talked about it, it was what

:

01:15:40,643 --> 01:15:43,202

he was going to do when he died, that

he didn't want anybody to screw up.

:

01:15:44,338 --> 01:15:48,158

It's a low maintenance, high

conviction strategy over a

:

01:15:48,158 --> 01:15:50,368

long period of time, right?

:

01:15:50,368 --> 01:15:53,788

It's probably, from a theoretical

perspective, the best thing you could do

:

01:15:53,788 --> 01:15:57,778

if you can't touch your portfolio, except

for a rebalance here and there, over 10

:

01:15:57,778 --> 01:15:59,238

years, 20 years, and 30 years, right?

:

01:16:00,028 --> 01:16:03,603

And I think where people get confused

is, Well, you could do this to

:

01:16:03,603 --> 01:16:04,463

improve it and that to improve it.

:

01:16:04,463 --> 01:16:04,673

Yes.

:

01:16:04,673 --> 01:16:06,683

But now it's an active strategy

that you have to maintain.

:

01:16:06,713 --> 01:16:09,073

And if you die, you have to trust

the person to maintain that thing.

:

01:16:09,153 --> 01:16:09,343

All right.

:

01:16:09,343 --> 01:16:10,943

So there's a place for risk parity.

:

01:16:11,243 --> 01:16:13,863

Also, there's a place to, to assume

that those assumptions are correct.

:

01:16:14,653 --> 01:16:20,883

Carry is actually an actively managed

approach that doesn't assume that there's

:

01:16:20,883 --> 01:16:22,033

positive risk premium all the time.

:

01:16:22,653 --> 01:16:29,053

It can short bonds when it's appropriate

to short bonds that risk parity will

:

01:16:29,053 --> 01:16:31,283

not do based on the carry reading.

:

01:16:32,143 --> 01:16:32,923

And so there's two things.

:

01:16:32,963 --> 01:16:34,773

And number one, it removes

the shorting constraint.

:

01:16:34,833 --> 01:16:38,952

And number two, it doesn't make an

assumption that anything is stable.

:

01:16:39,483 --> 01:16:43,313

And ultimately though, you need

an active manager that knows how

:

01:16:43,313 --> 01:16:44,443

to do this day in and day out.

:

01:16:44,763 --> 01:16:45,013

Right?

:

01:16:45,013 --> 01:16:46,963

So do they compliment each other?

:

01:16:47,013 --> 01:16:47,613

Absolutely.

:

01:16:47,613 --> 01:16:50,603

The correlation between risk

parity and carry is also quite low.

:

01:16:50,813 --> 01:16:52,613

It uses the same universe, but it just.

:

01:16:53,908 --> 01:16:57,638

And that's, that's, let's see

if there's any other questions

:

01:16:57,638 --> 01:16:58,628

and then we can close it up.

:

01:16:59,728 --> 01:17:03,827

lots of questions about product, which

we cannot answer sadly in this venue.

:

01:17:03,888 --> 01:17:07,298

If you have any questions, please

reach out independently over, Twitter.

:

01:17:07,298 --> 01:17:10,698

So if you guys have any questions,

reach out at info at investresolve.

:

01:17:10,718 --> 01:17:14,118

com or reach out to Adam for

any, carry white paper, specific

:

01:17:14,118 --> 01:17:19,608

questions at GestaltU, my Twitter

handle is at RodGordilloP.

:

01:17:20,168 --> 01:17:23,938

And, And, you know, we write,

talk about this all the time.

:

01:17:23,948 --> 01:17:27,348

If you have not been a listener of

a Resolve Riffs podcast, you should.

:

01:17:27,678 --> 01:17:30,998

We have a Resolve Masterclass series

that talks about this 12 episodes

:

01:17:30,998 --> 01:17:33,748

that walks through all the elements

of this that you guys can listen to.

:

01:17:33,748 --> 01:17:34,838

It's a separate channel.

:

01:17:35,188 --> 01:17:38,118

We've recently launched a new channel

that if you haven't signed up for, I

:

01:17:38,118 --> 01:17:40,827

would sign up for now, the first episode

was killer, second episode's coming up

:

01:17:40,827 --> 01:17:46,688

soon, the Get Stacked Investment Podcast

with Corey Hofstein, our partner in

:

01:17:46,688 --> 01:17:48,268

crime and a lot of this, this stuff.

:

01:17:48,368 --> 01:17:50,478

So, yeah, we will, we

have talked about this.

:

01:17:50,488 --> 01:17:53,978

We'll take any other questions

that we didn't get to today and

:

01:17:53,978 --> 01:17:57,258

see if we can address those in

one of those two podcast series.

:

01:17:57,858 --> 01:18:00,838

So with that, I think Adam,

thank you so much for your time.

:

01:18:00,928 --> 01:18:04,278

I think you worked your butt off

for this one, you and Andrew.

:

01:18:04,548 --> 01:18:04,868

Mr.

:

01:18:04,868 --> 01:18:06,738

Andrew Butler, I know

you're out there, buddy.

:

01:18:06,778 --> 01:18:07,488

well done.

:

01:18:07,538 --> 01:18:08,698

great paper, great effort.

:

01:18:08,698 --> 01:18:10,878

I know that you've lost, you

almost got divorced a couple of

:

01:18:10,888 --> 01:18:12,198

times to get this out the door.

:

01:18:12,198 --> 01:18:13,958

So kudos to you.

:

01:18:13,958 --> 01:18:14,657

Well done.

:

01:18:14,678 --> 01:18:18,018

And I think the investment

world is all the better for it.

:

01:18:19,907 --> 01:18:20,498

Adam Butler: Thanks for coming.

:

01:18:21,038 --> 01:18:21,538

Rodrigo Gordillo: Thanks everyone.

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About the Podcast

Resolve Riffs Investment Podcast
Welcome to ReSolve Riffs Investment Podcast, hosted by the team at ReSolve Global*, where evidence inspires confidence.
These podcasts will dig deep to uncover investment truths and life hacks you won’t find in the mainstream media, covering topics that appeal to left-brained robots, right-brained poets and everyone in between. In this show we interview deep thinkers in the world of quantitative finance such as Larry Swedroe, Meb Faber and many more, all with the goal of helping you reach excellence. Welcome to the journey.

*ReSolve Global refers to ReSolve Asset Management SEZC (Cayman) which is registered with the Commodity Futures Trading Commission as a commodity trading advisor and commodity pool operator. This registration is administered through the National Futures Association (“NFA”). Further, ReSolve Global is a registered person with the Cayman Islands Monetary Authority.