Episode 22

E22. Alpha Unchained: What the Data Says About Portable Alpha's Institutional Moment - Descript

Return stacking and portable alpha are no longer niche strategies — they're going mainstream.

In this episode, we cut through the noise and unpack the latest institutional survey data to separate hype from reality.

Corey Hoffstein, CEO & CIO of Newfound Research and Co-Founder & Portfolio Manager of the Return Stacked® ETF Suite, sits down with special guest Shane McCarthy, CFA, Global Head of the Client & Partner Group at LAB Quantitative Strategies, to go beyond the theory and into what the latest institutional survey data actually reveals about where portable alpha stands right now — and where it's headed.

What You Will Learn:

  • Why portable alpha has expanded well beyond pensions — into endowments, OCIOs, family offices, and wealth channels — and what the latest survey data reveals about AUM growth in the space
  • What allocators are actually optimizing for, and how survey data breaks down their primary objectives
  • Which alpha sources are winning, how much overlay exposure institutions are taking, and why a single alpha source may not be enough
  • The three implementation structures in use today, how fee and liquidity terms compare, and what beta instrument trade-offs matter most in practice

Don't miss the extended Q&A, where Corey and Shane go deep on instrument selection, alpha durability, illiquidity tolerance, and the nuances of overlay sizing.

Transcript
Corey Hoffstein:

Welcome everyone.

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My name is Corey Hoffstein.

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I am the CEO here at Newfound Research

and co-founder of Return Stacked ETFs,

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and I am absolutely delighted and

excited today to be joined by Shane

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McCarthy to discuss the state of the

portable alpha, or as we like to call

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it, the return stacking landscape.

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Shane is the global head of

the client and partner group

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at Lab Quantitative Strategies.

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LABQs is a Denver based quantitative

asset manager They spun out of one of the

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world's largest family offices where the

founding team managed capital at scale

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for over 15 years, and their key focus

is on portable alpha, combining diverse

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sources of alpha with capital efficient

beta in a liquid risk managed portfolio.

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Shane and I have known each other for

a couple years, but back in October,

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Shane actually opened our Return Stacking

Symposium with a presentation on the

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state of the portable alpha landscape.

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Since then, a number of consultants and

banks have released surveys of large

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pensions, endowments and family offices,

as well as other institutions on their

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use and adoption of portable alpha.

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And so, almost six months later, and

armed with this new data, we thought it

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would be a really good opportunity to

share where the industry stands today

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and the usage trends that are emerging.

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Now, before I turn it over to Shane to

begin walking through that data, I'm gonna

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start with a little bit of housekeeping.

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And with that we're gonna pop up a poll

while I talk through the housekeeping.

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this is a poll about

adoption of portable alpha.

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I assume everyone on this call has at

least a, a moderate interest, but just

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outta curiosity, we sort of wanna get a

sense of where people's interest lies.

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From a housekeeping perspective

from, for those of you who are not

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familiar with the Zoom platform,

you should see at the bottom of

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your Zoom window, a q and a button.

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This will allow you to ask

questions throughout the webinar.

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I will be keeping my

eye on those questions.

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Those that are incredibly timely,

I will try to bring up to Shane

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throughout the presentation.

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Otherwise, we will hold them and

try to address them towards the end.

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I also want to share that LABQs recently

published a white paper called Portable

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Alpha Risk First Alpha Durability.

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It's all about building resilient,

portable alpha solutions.

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You can find that on

their website, lab-qs.com

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under the media and research section.

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Okay, let's take a look at this poll.

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The poll is, are you currently

using Portal Alpha or Return

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Stacking solutions today?

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31% of you?

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Yes.

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And looking to expand usage?

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24%.

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Yes.

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Happy where you are.

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9%.

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No.

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But actively looking to add 28.

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No.

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But researching.

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Thank you for joining.

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Glad you're here.

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7% just outright, no, not sure what

you're doing on a call about portable

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alpha, but always nice to know that

there's, uh, some dissenting voices here.

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Hopefully we can convince you to move

to a No, to a no, but researching.

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Shane, ready to turn it over to you here.

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I know we've got a lot of exciting

survey data to go through before

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we go through that though.

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Again, with, uh, a variety

of folks in the audience.

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Some very familiar with Portable Alpha,

maybe some first learning about it

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and researching it for the first time.

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Can you maybe start off with a little

bit about what is Portable Alpha?

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Why are institutions turning towards

this portfolio construction technique?

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Shane McCarthy: Absolutely.

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And uh, you know, thanks

for this opportunity.

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again, my name is Shane McCarthy

and, uh, the lab portion of Lab

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Quantitative Strategies actually

stands for Liquid Alpha Beta.

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And so we are focused on this type of,

uh, portfolio construction approach.

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Um, we did spin out of the family office

a number of years ago and, uh, continue

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to manage institutional portfolios.

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What is portable Alpha is the key

question, and I actually do have a

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slide on that coming up here in a few.

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I'll start with that and then we can skip

over it as we go through the deck today.

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But tremendous opportunity.

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It's a very timely conversation.

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Um, we're seeing a lot of

oppress and research around it.

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you know, portable alpha, we think about

it as more of a portfolio construction

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technique rather than a specific strategy.

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We think about it as more of a system.

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And so included in that is there's

a beta component, let's say

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equities and a passive approach.

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There's alpha something that's UNC

correlated to equity and beta, but

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returns, you know, there's a lot

of other parts that go into it.

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It could be risk management, it could be

execution, it could be rebalancing and

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operations and collateral management.

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And basically the objective is to

separate equity beta returns, which

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are cheap and commoditize, as we all

know, from skill-based alpha returns.

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Which are more scarce and expensive.

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So we like to think about it

in more of like a simplistic

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real estate example approach.

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Um, I think we're all, you know,

personally, um, have had these types of

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experiences where you buy a home, let's

say it's a million dollars to keep it

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simple on the math, we call that the beta.

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You have two choices.

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You can pay the full amount for the,

the purchase price in cash, or you

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can put down, let's say 20%, you

can get a mortgage and invest at

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least most of the remaining amount.

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You may want to keep some around for

payments or upkeep and that sort of

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thing, but most of it you can go and

invest in something that's completely

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uncorrelated and unrelated to the

house and we'll call that alpha.

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And so your investments with that,

with that, with that unencumbered

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cash effectively needs to exceed the

financing costs of the mortgage and

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you're looking to earn that excess return.

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It's good to invest in something that's

not correlated with the home price.

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And if you do it correctly, you can

get exposure to both the house and the

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investments and allow for your dollars

to work better, uh, and harder for you.

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And so that's the idea

behind Portable Alpha.

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It's really, it's an

outcome based approach.

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And if it's structured

correctly, it can be durable.

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It could be a consistent outperformer

relative to a, a beta benchmark.

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Conceptually it's simple, but

operationally it, it's, it's anything

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but, and so we'll go, we'll, we'll go into

that a little bit more here in the deck.

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I'll talk a little bit about

what, you know, what the

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areas we're gonna cover today.

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we already covered what is portable alpha.

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We'll talk a little bit about

its positioning inside of

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a liquid market portfolio.

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Then we'll talk a little bit about

how it compares to traditional

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approaches that we commonly find

in the liquid market component.

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And then we'll jump into why Portable

Alpha, who's investing in portable Alpha,

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some of the investment choices around it

because it is a very customizable approach

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to your liquid market book, some of the

implementation choices that we're seeing

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inside of the institutional industry.

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And then lastly, just

implications for allocators in

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more before looking approach.

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So before we get into a lot of those

details, I thought it made sense.

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Just, uh, start at the big picture,

kinda the macro level and, and just

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talk about portable alpha and a

little bit, even about its history.

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It's been around since the 1980s,

so going on nearly 40 years.

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Demand in portable alpha has grown a lot.

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It did a lot in the two thousands.

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It receded a bit around the GFC and

then we saw a lot of strong interest

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over the last number of years, and

that that's reflected in the number

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of research that we see, a number

of the new structures that we see.

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And so it's definitely gaining

momentum here, the last couple years.

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Previously it was only institutional,

so it was, it requires, it's,

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it's a fairly complex operational

infrastructure and the trading behind it.

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And so typically it was more on

the pension side in the early days.

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And, and it is slowly, you know,

decade, over decade, it's grown more to

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encompass endowments and foundations.

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And now even more so in the last,

you know, last number of years.

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It's incorporating in wealth

channels and OCIO and family

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office and that sort of thing.

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You can see in the first bullet point

there that we, you know, the estimates

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around the GFC were about 75 billion.

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it did recede.

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There was some challenges with, with,

uh, during that time with portable alpha

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and we'll talk a little bit about that.

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And now we've seen a resurgence

in estimates as of today are, are

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roughly a hundred billion dollars.

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And it could be, it could be more.

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It's kind of hard to measure.

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And that kind of re relates to

the, the fragmentation point there.

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There's a whole ecosystem behind it.

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It's not necessarily a specific

type of bucket or type of strategy.

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It's more of a portfolio

construction framework and approach.

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And so it can be somewhat fragmented.

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I would say that the banks have done

a really nice job on aggregating

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research around that, talking to the

institutional allocator community.

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Some names that come to mind include

Barclay's Capital Solutions, their

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strategic consulting group, Morgan

Stanley, UBS, and a handful of others.

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They've done a nice job on that.

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It is a little bit, you know, again,

because of the fragmentation and

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how you define mandates, it can be

difficult to aggregate the overall AUM.

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Sometimes it can be double counted.

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There's things between the beta and

the alpha, on how you measure that.

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There's a lot of SMAs

and bespoke solutions.

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There's commingled solutions and

sometimes, frankly, these can be

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muddled with currency overlays or

completion account overlays to maintain

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strategic asset allocation weights.

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So sometimes it can be hard

on, on how you define it.

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I would say that the customization

around this, it, it's really the norm

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and it's really a feature, it's not a

bug and it, it is meant to, it makes

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it harder to implement, but it's, it

makes it much easier to integrate into

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a strategic asset allocation approach.

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The level of capability around

it, it's needed, to be successful.

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And again, we'll talk about that.

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There's different areas around that.

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I would say that it's penetrating a lot

of different channels though, so it's not

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a purely institutional product anymore.

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It's going into the well channels, OCIO

family offices to name a, name a few.

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And I would say that, you know, it's

been around for a long time and sometimes

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it's surprisingly misunderstood.

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So it's worth the time to get to know.

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It can be a highly effective

tool inside of a portfolio.

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I've already described

what is Portable Alpha.

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This is sort of a visual around that, to

talk about, to just kinda show the overall

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exposure, given your investment outcome.

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And then again, the allocation behind it.

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It's pretty simple.

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You have that you, you, you have

20%, let's say in an allocation

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that you keep as cash margin and you

use that to get a full a hundred.

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If you put a hundred dollars in,

you're trying to get a hundred dollars

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of equity, beta exposure, let's say,

but you only need 20 of cash margin.

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You keep a cash reserve of another 20%

and then it allows you through that

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unencumbered cash to allocate to an

alpha engine and deliver tracking error

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and excess return over the benchmark.

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Okay, so this is an important

one I thought and, and I just

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wanted to briefly touch on this.

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This is a liquid markets kind of overview

and, and we all face these types of

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challenges in the liquid market book.

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There's a ton of demands on this portion

of the portfolio and we've all experienced

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'em in a lot of different ways.

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For most allocators, this is part of

this is they're expected to do a lot.

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You have capital calls in

your private market book.

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You have client liquidity needs, you

have taxes, you have opportunistic

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trading, estate planning, a

number of different challenges.

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And so this is often treated

as like a passive exposure and

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portable alpha reframes that.

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It turns a liquid portfolio into

something that can generate additional

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return, but do it very differently

than the traditional approaches.

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And then over the last couple

years, and even in the, in the more

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recent we've seen slowing private

equity distributions, we've seen

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recent pressures in private credit.

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And so it amplifies the challenges

and the needs that we find in

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the liquid market portfolio.

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This slide here is, is really a

comparison to traditional investment

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approaches inside the liquid market book.

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And so.

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You can see there.

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The first one is you, you have an

opportunity through portable alpha

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in the techniques around it to

improve the return per unit or risk.

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Yes, an investor cannot eat sharpe, I

believe in that, but it is a powerful way

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to get more return and smooth the path.

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It's cash efficient or it's more cash

inefficiencies in a traditional approach

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with a fully funded, uh, exposures.

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And so it takes less cash to

get the same type of exposure.

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And again, that goes back to

even that real estate example

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that I brought up earlier.

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You can effectively use all those

proceeds to have home price appreciation

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and exposure there, as well as

exposure to other asset classes.

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The alpha bucket, it's very

regime agnostic, portable alpha.

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And so what does that mean?

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In a traditional approach let's say 60 40.

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That seems to be something,

an industry standard.

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No doubt it's provided strong

returns, particularly in the

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last few years since 2000.

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It's annualizing 7%.

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It's running at a 10%

volatility and about a 0.5

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sharpe.

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However, it has had three different

periods over these 25 years

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where it's down more than 20%.

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And we think that that's a key

measure on investor behavior and

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where investors potentially can make

bad decisions at the wrong time.

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So some of these drawdowns in 2022

with the inflation scare, we saw it

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down 20% in the early two thousands,

the dot com, we saw it down 22%.

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And then O, of course, in the GFC

of '07 and '08, we saw it down 32%.

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That's on a monthly return basis.

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If you measure it on a daily return,

you could add another a hundred to

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200 basis points on top of that.

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And that's a US-centric view.

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If you look at Global 60 40,

it's even a larger drawdown.

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We see that as three to 400

basis points more that we're

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realized in a drawdown over time.

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So in any event, there's no perfect

way to this, but Port portable

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Alpha can compliment what's

inside your liquid market book.

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On the behavioral bias side, everyone's

looking for beta exposure and they,

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and they also like diversifiers.

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We find that it can be very challenging on

what exposure do I want at any given time.

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There are periods where Alpha works

and there are periods where beta works

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and it can take that behavioral bias

and that decision making off the table,

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by cash efficiently combining beta

and alpha together into one portfolio.

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You can stay invested, you don't miss out.

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You can arguably reduce return,

or sorry, the risk within the

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portfolio relative to the benchmark.

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And then lastly, the excess return.

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A lot of investors and it works,

security selection, manager selection.

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It can be hard though, and we find that

a lot of times excess return generated

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by that may not be persistent over time.

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Excess return generated by portable alpha

is a completely different way of doing it.

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It's a structuring edge.

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It's allocating to assets and

trying to exceed the financing costs

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embedded with the beta exposure.

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Corey Hoffstein: To jump in here, Shane,

I saw a great quote actually earlier

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today from Justin Young at MIMCO.

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He was on a panel at a recent AQ

derivatives event, and he was quoted as

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saying, when you look at top quartile

managers in large cap US equities,

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median performance is negative alpha.

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Mm-hmm.

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Whereas if you look at bottom quartile

hedge funds, they almost all beat cash.

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Right.

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And so when you talk about where can

you generate excess returns from that

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traditional approach, it is very hard.

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Manager selection is very hard in

that very crowded part of the market.

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Even if you choose the worst hedge funds,

they generally outperform the financing

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required for portable alpha to work.

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So that's, that's right.

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That structuring advantage

you're talking about here.

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I really appreciate you setting the table,

laying that foundation for this talk.

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Now I really want to dive

into the meat and potatoes of

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what these surveys are saying.

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So I was hoping, given the context of what

Portable Alpha is and what it's trying

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to achieve, can you talk a little about,

a little bit about who is using it today

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and maybe the objectives that they're

trying to meet, why are they using it?

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Shane McCarthy: Mm-hmm.

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I'll start with the why Corey, I think

it's, it's very important to begin there.

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you know, as we talk to investors

and we, and we understand the surveys

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and the research behind it, a lot

of it is just a market backdrop.

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You know, arguably the equity markets

at the high end of the range of, from a

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valuation perspective, credit spreads are

tight and who knows where we go from here.

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But now more than ever, structure matters.

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you know, from a portfolio crowding

perspective, again, allocators

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want access to diversifying

strategies with no disruptions, and

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they have a fully deployed book.

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So this is a way to

better manage all that.

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On the capital efficiency side, it

just, it's a better usage of dollars.

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It, it allows you to work harder,

arguably not take more risk.

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And meet the challenges that we, we

talked about on that liquid market slide.

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I think the sophistication of allocators

is just continuing to increase.

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They think very holistically about it.

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They think about it as a system

and a framework, and they allow,

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they don't get so focused on if one

thing is up and one thing is down.

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It's more of a system kind of built

together to again, generate that

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excess return over a benchmark.

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And then lastly is a customization.

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The more, the more allocators

build capability, the more they

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have a governance structure, the

more they understand what their

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investment outcomes should be,

they're able to customize it more.

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And that can be around the tracking

error or the volatility of the active

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risk around that benchmark, their

overall risk, the return expectations,

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and there's less tied to an index, they

can focus again on portfolio outcomes.

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An integration to a strategic

asset allocation approach.

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On the next slide,

there's actually a survey.

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It's from UBS, about a year old now.

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And it, it talks about, you know,

what, what are allocators looking for?

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And it's very clear that they're looking

for excess return over an index and

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they're looking for an operational

efficiency of a combined product.

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And so it's very clear there, there was

actually a recent, uh, research report

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put out by Morgan Stanley who did a

nice job, very similar type of survey.

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And there over 60% of the participants

are looking for excess return, and

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another 20 are looking for capital

efficiency and maintaining a be target.

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So we find those are the two common

themes from a survey perspective

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in the institutional space.

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Okay, so who's investing?

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Like I said earlier, historically

it's been institutional investors.

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If you go all the way back to the

eighties again, it was more of a pension

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focused, sort of a niche, approach.

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And now it's, it's expanded

to a wide variety of channels.

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you know, I think that these numbers show

that it's not just about adoption, but

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it's also about the conviction of it.

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And so institutions have historically

focused on capital efficiency and

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portfolio construction and wealth

channels, and focused more on enhancing

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returns without increasing the

headline risk of the overall portfolio.

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And so you can see here we're seeing a lot

of adoption and conviction in the advisor

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and consultant community continued in the

E&F and the pension on the institutional

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side and all the way in between.

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And so it, it's, it's relatively,

diversified at this point.

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Then this, I thought this

was an interesting one.

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This is an allocator tenure of how

long they're invested in portable

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alpha and yeah, 40% of investors

have been in it more than five years.

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That's great.

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You can see that there on the right.

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However, what I thought was most

interesting was, look at the less than

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one year, almost 30% of the survey

said they are better understanding it

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and now they're looking to, you know,

they, they put money to work and it's

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still a relatively short tenure, but

they're starting to put money to work

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there and they're understanding it.

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So I, I thought that was interesting.

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Corey Hoffstein: Earlier on you talked

about the customization that portable

364

:

alpha affords, you can sort of mix and

match different benchmarks and you can

365

:

mix and match different alpha sources.

366

:

You know, given these different

objectives though, though collectively

367

:

it looks like just beating the market

remains the headline objective.

368

:

Can you talk a little bit about,

what betas institutions are looking

369

:

to replace, what sort of alphas

they're using, maybe how much

370

:

they're introducing of those alphas.

371

:

Shane McCarthy: Absolutely.

372

:

I'll start with where they

position portable alpha.

373

:

So again, it's in the liquid market book.

374

:

We, you know, this survey here

shows that because of the beta one

375

:

profile, most allocators position

it as a public equity exposure.

376

:

Um, it approves the efficiency

of the equity allocation.

377

:

It can differentiate again how

you generate that excess return.

378

:

this is from Barclays.

379

:

They actually had a recent survey in

Q1 of 26 here, and it was actually

380

:

80% of those survey participants

view it in a public equity space.

381

:

So we actually see an increase

relative to this survey here.

382

:

And so.

383

:

Again, it's something where they

could position it as an alt hedge fund

384

:

allocation, but I think we're gonna find

that more where you have institutions

385

:

that are looking for higher tracking

error for whatever reason, and so

386

:

there's a little bit more of, it's

not behaving like an index per se.

387

:

Building blocks of portable alpha.

388

:

You know, there, the beauty of this

is that it's customizable and, and you

389

:

can put together, you can mix and match

different things as you model it out

390

:

and as you structure your portfolio

to meet your investment outcomes.

391

:

It's really not a one size fits all.

392

:

As you can see here you know, there's some

building blocks that are very familiar to

393

:

all of us, right across equities, whether

it's US-centric or global fixed income.

394

:

There's obviously you can do

single or multi-asset class.

395

:

You can even add in commodities and

currencies and other beta markets as well.

396

:

and so we find in the surveys

that, you know, US-centric

397

:

investors have a home bias.

398

:

They predominantly try to get more of

a US beta component built into their

399

:

portfolio, whereas the rest of the

world has more of a global mandate,

400

:

maybe more like a world or an ACWI.

401

:

Beta instruments have really,

the, the breadth of them have

402

:

increased over time as well.

403

:

And so to put on the cash efficient

beta exposure, you can do that through

404

:

futures, you can do that through swaps.

405

:

There's ETFs to name a few.

406

:

and then on the alpha side, you know,

I'm gonna save some of this for a future

407

:

slide where we're gonna talk, we're gonna

look a little bit at the individual hedge

408

:

fund strategies and where the demand

is across the institutional industry.

409

:

But these are some examples on equity

market neutral, multi-Strat trend.

410

:

And again, you're looking for an

alpha component that can exceed

411

:

your financing costs of your beta.

412

:

What you don't see in this slide though,

is more illiquid type of, investments.

413

:

And so that could be private equity,

it could be private credit, it could be

414

:

real estate, and that's for good reason.

415

:

There's a lot of risk because

there's embedded beta in there.

416

:

There's leverage embedded in there,

and there are illiquid structures,

417

:

and so there could be some,

there's some challenges to that.

418

:

Okay, so this is a really good survey for,

again, from UBS and it talked about what,

419

:

what are the, you know, the clear leaders

from a hedge fund strategy standpoint?

420

:

There's a range of

different opportunities.

421

:

The breadth of the hedge fund industry has

really grown over the last 20, 25 years.

422

:

So there's a, there's a number

of different types of strategies,

423

:

and again, you can mix and match

it in a lot of different ways.

424

:

Some of these in isolation though,

can actually create a lot of tracking

425

:

error and it can be too much relative

to what the investment outcome

426

:

needs to be given the allocator

and, and what they're looking for.

427

:

Some of them, there may not be

enough alpha in there to exceed

428

:

the financing cost of the beta.

429

:

And so again, it's the

beauty of portable alpha.

430

:

You can mix and match this

in a lot of different ways.

431

:

You can see here on the

left side that equity market

432

:

neutral is by far the leader.

433

:

Nearly 90% of the survey participants

use it in a portable alpha construct.

434

:

So it's the most common, it may

not be the most complete solution.

435

:

And we can talk a little bit

about that here in a, a few

436

:

minutes if, if it makes sense.

437

:

we think about it like, Corey, you

mentioned the Alpha Durability paper

438

:

that we wrote and is on our website,

and we think about it a lot in a few

439

:

different ways around trying to get

different properties, in equal risk

440

:

weighting those properties, to allow for

an alpha engine that generates a strong

441

:

risk adjusted return, can do it over

the financing cost of the beta, but also

442

:

has protection properties built in, in

the event that we see equity drawdowns

443

:

and we need, you know, components of the

alpha engine to, to perform at that time.

444

:

Corey Hoffstein: Well, I wanna, I

wanna pause on this slide, Shane.

445

:

because I think there's a lot

to unpack here and the types

446

:

of alphas people are using.

447

:

What this slide doesn't show and

what I haven't seen any of the

448

:

survey data really show is, is how

institutions are thinking about

449

:

combining these different alpha sources.

450

:

So, I wanna ask you a question and then

we've had some actually great, really

451

:

great questions come in through the

q and a reminder that that's there.

452

:

I'm gonna, I'm gonna ask two of them on

this slide 'cause I think it's relevant.

453

:

But I know that LABQs has adopted this

convergent versus divergent strategy

454

:

framework and thinking about mixing and

matching strategies that fall into those

455

:

two buckets from a risk perspective

and using that and blending them to

456

:

help meet objectives of your clients.

457

:

Can you talk a little bit about, maybe

give some examples of different type

458

:

of strategies that fall into each

bucket, why you think of it that way,

459

:

and how you think about combining them?

460

:

Shane McCarthy: Absolutely.

461

:

Uh, you know, like I said, we, we think

about it in having an equal risk approach

462

:

between convergent and divergent.

463

:

And so let me define those

two a little bit more.

464

:

So convergent, you know, if you

look at this list of strategies

465

:

here, we think about that as

market neutral, mean reversion.

466

:

It, it's basically a fundamentally driven

strategy that's designed to make money

467

:

under most normal market periods, which

we all find most of the time, right.

468

:

Where it can struggle is in dislocations.

469

:

And so the characteristics around

convergent are typically lower volatility.

470

:

It can be a higher win percentage,

but the losses are quicker and deeper

471

:

and it can tend to like double down

on fundamental views of fundamental

472

:

point of view in the event that

it goes, a trade goes against 'em.

473

:

So it effectively has

like concave profiles.

474

:

They're typically low capacity,

high alpha, high sharpe ratio type

475

:

strategies, but with it they can be,

they can get exposed to crowding factor.

476

:

De-leveraging unwinds and the, and

what we call negative skew, where

477

:

they can give back a lot very quickly.

478

:

So some examples in this slide here

would be equity market neutral,

479

:

fixed income, relative value,

statistical arbitrage, merger arb,

480

:

are a couple examples of convergent.

481

:

We think about that group though as

again, performing well in most normal

482

:

periods it's got a positive carry.

483

:

And in a portable alpha construct, it's

meant to exceed your financing costs.

484

:

On the flip side is divergent, that's a

completely different type of property.

485

:

We find that in trend following, there's

different flavors of global macro.

486

:

There can be systematic or discretionary.

487

:

There can be directional or

relative value, but generally

488

:

global macro fits in there as well.

489

:

And so there, it's not fundamentally

based strategies, it's based more on pure

490

:

price trend trending markets.

491

:

it's, it is got more of a, like a, what

we call a smile effect to it, and there's,

492

:

they're more convexity built in there.

493

:

And so there, they're meant to

de, they're designed to make

494

:

money in more stress environments

and what we call crisis alpha.

495

:

They typically run in a little bit

higher volatility than convergent.

496

:

They have a lower winning percentage,

so there's lots of small losses,

497

:

but at the same time, they're

systematically driven and they cut

498

:

risk very quickly if they're wrong.

499

:

And so there are more high capacity given

the types of instruments that they trade.

500

:

The breadth of markets can be hundreds

and hundred, hundreds of them, and

501

:

then they compliment conversion.

502

:

And that's more of a protective feature

that can be built into a portable alpha

503

:

program that, again, sits next to that

carry component of the convergent.

504

:

We blend all those together and what we're

trying to do is generate a consistent,

505

:

durable alpha return stream that can

outpace the financing costs and generate,

506

:

again, a lot of it can be dependent on

how much alpha you allocate inside of

507

:

your portable alpha program, but it's

very much dependent on your volatility

508

:

of your alpha, the sizing of your

alpha, and then again, how you mix the

509

:

conversion and diversion type properties.

510

:

Corey Hoffstein: I wanna address some

of the questions that have come up here.

511

:

two in particular really seem

relevant to this slide, so,

512

:

so I want to address those.

513

:

And we have a number of attendees here

who are, who are not institutional,

514

:

they're financial advisors and, and

wealth managers who are trying to figure

515

:

out how to take this concept and apply

it to clients that maybe don't have

516

:

this perpetual lifespan of an endowment.

517

:

Right.

518

:

Maybe are more modeled as short term

pensions to a certain degree with,

519

:

with some unknown flexible liabilities.

520

:

And, and the question here is around, you

know, if you're talking about convergent

521

:

versus divergent for an individual.

522

:

Investor, you know, would you think about

skewing, convergent or divergent during

523

:

different parts of their life cycle?

524

:

Would you think potentially about

convergent for accumulation and

525

:

divergent for decumulation where risk

management's a little more important?

526

:

And I, and I know you don't focus

specifically on the wealth channel,

527

:

Shane, but as someone who, who is,

you know, thinking constantly about

528

:

this balance of convergent, divergent,

do you have any thoughts there?

529

:

Shane McCarthy: It's a

really good question.

530

:

I, I would say that we are very

intentional in line item focused on

531

:

building a portfolio holistically.

532

:

And we don't, we don't moderate

the risk exposures between the two.

533

:

So again, we, we equal risk to

the two and we think that they're

534

:

very complimentary to each other.

535

:

They definitely serve different

purposes in the portfolio.

536

:

and so we keep it much

more of a consistent risk

537

:

budgeting, approach to that.

538

:

I guess tactically you could do that.

539

:

I, I, if you know that the profile

of your client I is changing over

540

:

time, but that, that's philosophically

from a portfolio construction

541

:

standpoint, that's not how we do it.

542

:

We, we like to keep those

attributes and those properties

543

:

very consistent throughout.

544

:

Corey Hoffstein: I'll answer

anecdotally from our side, and we

545

:

have a new blog post with a, a tool

embedded in it that allows people to

546

:

play around with some optimization.

547

:

But, but what we find is, you know,

for folks who are really focused on

548

:

generating excess returns, it, if

you run an optimization, you do not

549

:

get rid of divergent strategies.

550

:

Those divergent strategies play an

important role in, in maximizing

551

:

the compound growth rate.

552

:

And similarly, if you tilt your

objective all the way towards capital

553

:

preservation, which is so key for

people in that decumulation stage,

554

:

generating consistent excess returns the

way convergence strategies do is also

555

:

meaningfully important for them, right?

556

:

Generating a little bit of excess

turnover year gives them more flexibility.

557

:

So you, what I find in, in running all

sorts of scenario analysis is you never

558

:

really get rid of one side or the other.

559

:

They both play an important role.

560

:

one of the questions here, Shane, is on

the portable alpha building block side.

561

:

Has there been anything that you've

seen that's been really innovative for

562

:

the alpha strategies outside of, say,

multi-strat or global macro, some sort

563

:

of new uncorrelated strategy that's,

that's popping up more and more?

564

:

Shane McCarthy: Not

off the top of my head.

565

:

There's, there's a lot more though

from a moving away from strategy

566

:

implementation per se, but more

about the structuring side of it.

567

:

We find a lot of innovation from

the banks on how to get access

568

:

to the alpha return streams and

be more capital efficient there.

569

:

Some allocators actually want more

leverage embedded in the alpha component.

570

:

and so there's different

ways of going about that.

571

:

and so yeah, that's what we're seeing

is more, it's more on the structuring

572

:

side and again, to the improvement of

capital efficiency, the improvement

573

:

of risk management and all the tools

around the instruments that can be used.

574

:

Corey Hoffstein: Yeah.

575

:

Some of the stuff we're seeing in, in

the conversations we're having around

576

:

trying to find really idiosyncratic return

sources, obviously that's the holy grail.

577

:

catastrophe bonds potentially

as an example of, of one fairly

578

:

idiosyncratic return stream.

579

:

The where the rubber meets the road

though is always managing the liquidity

580

:

mismatch of how you're accessing your

beta versus how you're accessing your

581

:

alpha and how you can rebalance those.

582

:

And there's a long storied history of,

of why this approach fell out of favor

583

:

in 2008 because of those illiquidity

mismatches and, and misunderstanding

584

:

of, of correlations in the tail.

585

:

So, we've had some more questions pop up.

586

:

I'm gonna keep us moving address

those questions at the end.

587

:

so let's,

588

:

Shane McCarthy: let's, hey, can I, and can

I, just on that last point, absolutely.

589

:

Chime in, you know, it's, uh, the,

the GFC what was, again, it was

590

:

a, it was a challenging period

in the history of portable alpha.

591

:

and a lot of it was caused

by bad implementation.

592

:

You know, the alpha was correlated

with beta as a market regime shifted.

593

:

And so there was a lot of left tail

equity beta built into the alpha engine.

594

:

Uh, the alpha structures were too

illiquid and, or they got gated and

595

:

locked up exactly the wrong time.

596

:

And then we find examples of

ineffective collateral management

597

:

around the derivative beta book.

598

:

So if you have insufficient cash to fund

it, or you're, and then you're ultimately

599

:

forced to sell it at the trough, we

call that monetization of volatility.

600

:

And that's the last thing you

wanna do is sell at the bottom.

601

:

And so if you get the structuring right,

if you get the implementation right.

602

:

Execution, the risk management, it

can be a very effective tool, but you

603

:

have to get all those pieces kind of

in that system and framework approach.

604

:

You gotta piece those together.

605

:

Corey Hoffstein: Alright, so one of

the questions that comes up in every

606

:

single implementation call I have with

our clients is, how much should I do?

607

:

Okay, I, I really like this idea,

but how much should I stack on top

608

:

of my strategic asset allocation?

609

:

So I'm curious, what do the surveys say

about when an institution is adopting

610

:

this, how much capital are they putting

to work in this type of strategy?

611

:

Shane McCarthy: Yeah, it's a

very, very important question.

612

:

And again, it's very much dependent

on your overall profile, your overall

613

:

portfolio, and how you think about

your willingness and or ability to

614

:

take excess return over a benchmark.

615

:

Most everybody wants to enhance the

portfolio and they wanna do that

616

:

without disrupting index exposure.

617

:

I think sometimes a common mistake

can be that they're trying to

618

:

maximize alpha rather than thinking

about the interaction between alpha

619

:

and beta and how that outcome will

ultimately look on a realized basis.

620

:

There's not really a right or wrong here.

621

:

Again, it's just dependent on,

it's a design choice and it's

622

:

dependent on what you're looking for.

623

:

And again, it's functional.

624

:

If you're alpha sizing the volatility

of that alpha and the correlations

625

:

to the beta, most surveys show

that at least in the institutional

626

:

space, they're comfortable with

modest degrees of tracking error.

627

:

And so you can see here that you know,

per $100 of, of the alpha exposure per

628

:

$100 of beta, you find that over 50%

of 'em are allocating anywhere between

629

:

20-25 to 50 or zero to 50, in Alpha.

630

:

And so we find that pretty

consistently year over year.

631

:

Again, if the alpha's too large,

it can start to behave very

632

:

differently from the index.

633

:

And so we find a lot of of reasons

why people may or may not want that.

634

:

You know, in the institutional space

more the pensions and sovereign wealth

635

:

funds, we find it more of a moderate

overlay in that kind of 25 to 50.

636

:

It typically have, you know,

a strong governance structure.

637

:

They have board oversight, they have

consultant frameworks, and they have

638

:

a lower tolerance for tracking error.

639

:

And the private banks and the wealth

platforms, as we get more data around

640

:

that, we're also seeing more of a

moderate overlay, you know, client

641

:

stability considerations, model

portfolio constraints, you know,

642

:

even benchmark sensitivity seems

to be in that more moderate range.

643

:

Same thing with advisors and consultants.

644

:

And then as you expand the tracking

error, you know, you find that more

645

:

in endowments and, and foundations

and they just typically have

646

:

more flexibility than pensions.

647

:

They run diversified portfolios

and they're a little bit less rigid

648

:

on, on the benchmark constraints.

649

:

And then on the far end of the

spectrum where there's higher

650

:

tracking error, you see that more

in like family offices, right?

651

:

They can typically, they don't

have as much benchmark constraint.

652

:

They have longer time horizons and,

and you know, typically a simpler

653

:

governance structure as well.

654

:

And so there can be a range.

655

:

It's really just dependent on the channel.

656

:

Corey Hoffstein: If I can step in here,

Shane, really quickly just go back to

657

:

that slide because I think a lot of

people get caught off guard by this.

658

:

One of the examples I always like

to give is, you know, if you were

659

:

just doing long only active equity

managers, you can think about that as

660

:

an implicit portable alpha solution.

661

:

You're getting the benchmark

plus some sort of dollar neutral,

662

:

long short portfolio on top.

663

:

The stuff they're underweight

is your implicit shorts.

664

:

The stuff they're overweight relative to

the benchmark is their implicit longs.

665

:

And when you look at sort of the average

active equity manager, right, you probably

666

:

are getting an active share of about,

you know, 50%, which implies exposure of

667

:

$50 for every a hundred dollars of beta.

668

:

So a lot of people get caught off

guard with, wow, this seems like a lot.

669

:

And obviously the tracking error

component really matters as to a

670

:

hundred percent of low tracking error

is very different than, you know, a

671

:

hundred percent of high tracking error.

672

:

But this is not totally different

than what you see when you talk

673

:

about long only active managers.

674

:

The amount of active

exposure per unit of beta.

675

:

Shane McCarthy: Yeah, absolutely.

676

:

And again, it's just a

differentiated approach too to

677

:

generate that excess return.

678

:

So it's security selection and or

structuring excess return, approach.

679

:

And that's the beauty of it.

680

:

It can be very

complimentary to each other.

681

:

Corey Hoffstein: So I think you

have a slide next Shane, yeah.

682

:

That talks about the, the

actual tracking error.

683

:

I'd love to, I'd love you to dive

into this, the expectations around

684

:

what sort of tracking error they're

willing to take and the, and the

685

:

return that they're expecting for it.

686

:

Shane McCarthy: Yeah, I thought

this was a really good one.

687

:

again, it's about design

choice, customization.

688

:

I think investors are again, increasingly

comfortable with a, you know,

689

:

there some level of tracking error.

690

:

So on the left side there

you have this target portable

691

:

alpha tracking error survey.

692

:

And you know, you find that 40% of

the survey participants are in that

693

:

kind of zero to 4% of active risk

above and beyond the benchmark.

694

:

And then another 33% are in

that kind of four to 6% range.

695

:

There's a few that are in that six to

eight starting to get relatively high, and

696

:

then, you know, north of 8% on a tracking

error basis, it really starts to tail off.

697

:

On the right side, you see

the target alpha return for

698

:

the portable alpha strategies.

699

:

And there most of the survey participants

are in that kind of four to 8% range,

700

:

and then it falls off after that.

701

:

And that's, that's a good,

that's a good level to be at.

702

:

again, to exceed your financing costs

on the beta and to control how much

703

:

tracking error you want ultimately

in your portable Alpha program.

704

:

Corey Hoffstein: Shane, can you talk

a little bit about how people are

705

:

implementing Portable Alpha today?

706

:

We talked about how 2008, there was

sort of a structural mismatch in

707

:

how Portable Alpha was implemented.

708

:

There's been some innovations in

the way it's being delivered today.

709

:

Can you talk about what the survey

data says around what those approaches

710

:

are and how they're being adopted?

711

:

Shane McCarthy: Absolutely.

712

:

So there's three primary ways to

implement portable alpha, at least

713

:

we've ex, we've seen this in the

institutional industry and it really

714

:

ranges from simple to very complex.

715

:

And each of them come

with trade-offs, right?

716

:

Just like anything in life, simplicity,

control, costs, things like that.

717

:

And so that we find that the

sophisticated investors are more

718

:

geared toward direct implementation,

which is that third option there.

719

:

And that's where the institution will

have an alpha engine that they oversee

720

:

directly, and they've built the execution,

the technology, the infrastructure, the

721

:

risk management, the collateral management

around the beta component as well.

722

:

And they can manage the

whole system, if you will.

723

:

Like we talked about earlier.

724

:

On the opposite side would

be the one stop shop.

725

:

And we're seeing a plethora of

different products coming out right

726

:

now in the hedge fund space around

launching new funds and launching,

727

:

launching new share classes around that.

728

:

And so there it could be SMAs

feeder funds, share classes.

729

:

and, and again, you know,

like that construct, it's,

730

:

it's very capital efficient.

731

:

if you think about like a share class,

a dedicated portable alpha share class,

732

:

there can be some cross-contamination

risk because it's utilizing the

733

:

unencumbered cash inside the fund.

734

:

Where some of those investors who are

disinvested in another share class

735

:

for the Alpha engine only, some of

that gets used as part of the beta.

736

:

And so it constrains how much alpha

they can ultimately take in that

737

:

share class and the selection of

the beta for that share class.

738

:

And then in the middle there

is outsourcing to providers.

739

:

And we've seen this, this is something

that's been in the industry for

740

:

quite some time and that's where

the banks and or different solution

741

:

providers can execute the beta on

your, on behalf of the allocator.

742

:

And so that can be in swaps or futures,

they can manage the collateral around it.

743

:

And then the allocator has

their own hedge fund book.

744

:

It's a little bit more

fragmented, if you will.

745

:

and so it requires the allocator to

make sure to consolidate the whole

746

:

system together because they've

outsourced at least certain components

747

:

of the portable Alpha program.

748

:

Preferences around it.

749

:

This survey right here, you can see

that it is kind of split between one

750

:

stop shop and an allocator direct.

751

:

Again, the pensions are more in

the allocator direct and the one

752

:

stop shop is what we're seeing.

753

:

A, a lot of growth in that, from

a supply standpoint with, with

754

:

the, in the hedge fund community.

755

:

And really it just comes down to the

internal resources, your capability and

756

:

your governance structure around that

and what you're realistically able to do.

757

:

Morgan Stanley actually did put out a

recent report here in Q1 and they, they

758

:

unpacked the one stop shop even more.

759

:

And, you know, investors are

preferring the dedicated funds.

760

:

They, some of 'em want

SMAs with these managers.

761

:

Some of 'em go down the

the share class route.

762

:

But it's predominantly

more of a dedicated fund.

763

:

that it, it has the alpha engine,

has the beta component, they're

764

:

packaged together, and all the

execution and all the structuring

765

:

around it resides within the manager.

766

:

On a, a similar note, you know, uh, within

the one stop shop and the hedge fund

767

:

community, these, I thought this would

be interesting just to see what type of

768

:

terms we're, finding across the industry

as it relates to, you know, having, a

769

:

portable alpha program with a manager.

770

:

And so, you know, the manager

management fees there, there's

771

:

kind of a wide range there 50

basis points all the way up to 2%.

772

:

I think the performance fee, you

know, somewhere in that 15 to 20%,

773

:

but I would highlight it's alpha only.

774

:

we do find some research that shows

that most, majority of it is paid on

775

:

all periods for the alpha, but some,

there's only, you know, you're only

776

:

paid on outperformance in up periods.

777

:

And so there can be, there's a kind, kind

of different structuring around that.

778

:

the hurdle rate, it's effectively the

beta market, so you're only paying for the

779

:

scarce alpha and, and you're paying above

and beyond your be your beta benchmark.

780

:

On a liquidity terms you want to

keep it tight monthly to quarterly.

781

:

Again, you don't want anything

that's extremely illiquid in

782

:

there and lockups and all that.

783

:

So it's typically monthly or quarterly.

784

:

And then from a notice period

perspective, you also want to keep

785

:

that tight, and relatively short.

786

:

And so we find that mostly

in the 30 to 45 day period.

787

:

Corey Hoffstein: All right, Shane,

so we're coming towards the end here.

788

:

I wanna leave some time for

questions, but you know, if you

789

:

were to wrap this up and say sort.

790

:

What are the surveys saying about where

things are and where they're going?

791

:

Can you sort of maybe put a final bow

on this and, and, you know, as, as

792

:

these surveys have asked people about

their adoption, what are the trends

793

:

that we're seeing start to emerge?

794

:

Shane McCarthy: Yeah, I think the

overall strategic direction of the

795

:

industry is embracing it, not only

adoption, but conviction behind it.

796

:

And I think that's just been a lot

of understanding research around

797

:

it and, um, and just getting

allocators comfortable with it.

798

:

And they view it as a core portfolio tool.

799

:

you know, the, the edge is increasingly

how you implement it, and there's a,

800

:

there's a lot of different providers

out there and you know, whether it's

801

:

the beta component side of it or a

hedge fund doing it holistically.

802

:

And so it's not, it's, it is

really about how you implement it.

803

:

not necessarily just the

alpha that you select.

804

:

I think allocators honestly are

thinking about it more holistically,

805

:

and they want capital efficiency as a

core driver of excess return, allowing

806

:

their dollars to, you know, meet those

challenges in the liquid market portfolio.

807

:

I think that there's a

lot to be said about that.

808

:

and it's adoptions.

809

:

It's very, it's broadening, it's

across the investor landscape now.

810

:

We're seeing it in the wealth channels.

811

:

We're continuing to see increasing

demand in the institutional space.

812

:

And so I, I, I would imagine that

that would continue from here.

813

:

And it, again, if it's structured

correctly, it can enhance your

814

:

returns and diversify your liquid

market uh, traditional approaches.

815

:

Corey Hoffstein: Well,

thank you for that, Shane.

816

:

I gotta say this is the first time

I think I've done a webinar where

817

:

I have a number of questions that

are quite literal paragraphs.

818

:

So I think people are, are

excited to ask you some questions.

819

:

I think the survey data has, uh, has

caused people, you know, there's a

820

:

lot of interest in this and so I, I'm

gonna start working through these.

821

:

I'm gonna first say, we'll probably

gonna likely tip over the hour, so

822

:

to everyone who is joining and has

to sign off, thank you so much.

823

:

We are gonna try to get

through all these questions.

824

:

There's about five of them.

825

:

and if you have to sign off, don't worry.

826

:

There will be a replay and you

can, you can catch up to this.

827

:

So.

828

:

I'm gonna start with a question here,

Shane, I think really taps into the

829

:

customizable nature of portable alpha.

830

:

and, and this is a pretty niche

question, but it's when institutions

831

:

build a portable alpha program, how

should they decide what instrument

832

:

to use for the initial beta leave?

833

:

Listed futures, total return swaps,

or a fully funded ETF allocation?

834

:

How do the trade-offs compare on capital

efficiency financing, drag collateral

835

:

and liquidity management tracking error

governance burden, and the ability to

836

:

rebalance around alpha manager cash flows?

837

:

And based on the survey data, is

there anything that allocators

838

:

are actually landing on today?

839

:

Um, I have some some anecdotal

thoughts, but would love to hear

840

:

what you're seeing as, as you're

implementing this for clients.

841

:

Shane McCarthy: Do, do

you wanna start, Corey?

842

:

And I'll take it from there.

843

:

Corey Hoffstein: Yeah.

844

:

So I, I, I'll give a very quick

answer, which is, this is gonna

845

:

depend on a couple of things.

846

:

It's gonna depend on your liquidity needs.

847

:

Um, it's gonna depend on operations

and it's gonna depend on taxes.

848

:

So just as a very simple trade off, if

you are a taxable versus a non-taxable

849

:

entity, a non-taxable entity might

be able to use something like futures

850

:

very easily, where a taxable entity

might want to go for a long-term total

851

:

return bullet swap to try to capture

those long-term capital gains rather

852

:

than the 60 40 treatment of futures.

853

:

Now, that's a trade off of

credit risk with a bank.

854

:

Maybe some illiquidity depends

on is the access, accessibility

855

:

and all that sort of stuff.

856

:

So like taxable versus non-taxable

is going to be a big driver.

857

:

And then you're gonna have

financing drag, right?

858

:

So whether you're funding with, you know,

through futures or swaps or getting borrow

859

:

against your existing assets, box spreads.

860

:

You know, there's all sorts of ways

in which you can find financing, uh,

861

:

that all have different embedded rates.

862

:

There are firms that really

specialize in minimizing those rates.

863

:

But again, it's gonna come down to

the expertise and comfort of managing

864

:

all those different components.

865

:

So what I, what I would say I see in

practice is a lot of swaps, 'cause a

866

:

lot of the institutions that I talk

to are effectively, non-taxable.

867

:

And so therefore, you know, they can

just do a total return swap, not have to

868

:

deal with the bullet swap issue either.

869

:

They can just make it very easy one

and done with a bank, get the very

870

:

precise exposure, not have to deal

with, you know, weird financing

871

:

happening in the futures market.

872

:

They can lock in known financing

rates, which gives 'em some

873

:

certainty on the hurdle.

874

:

So there's a lot of attraction there.

875

:

I don't think I've seen anything in

the survey data Shane, that says what

876

:

institutions are adopting at large.

877

:

But, but curious as to what you're seeing.

878

:

Shane McCarthy: I haven't seen that

either at the instrument level,

879

:

uh, from a survey perspective.

880

:

but I would say, and I, I can talk

about how we, how we do it here.

881

:

We, we, you know, very much, you,

you listed out the instruments

882

:

that we think about as well, right?

883

:

Swaps, total return

swaps, futures, and ETFs.

884

:

We, we predominantly, for our core beta

allocation, we use total return swaps.

885

:

We think about it as that has

the lowest tracking error from

886

:

a beta component, to the index.

887

:

And so, and we think about it from

a tax efficiency standpoint as well.

888

:

So we also use bullet swaps.

889

:

We try to do it more than 12 months,

so we get the long-term capital

890

:

gains features built into that.

891

:

There are rebalancing components

to the vehicles that we run, and

892

:

so we trade futures, we trade

about 150, 160 markets as well.

893

:

So we can use that as a way to

rebalance in addition to maybe ETFs.

894

:

from a tax efficiency

standpoint, futures are great.

895

:

You get the 1256 tax treatment, uh, which

is a 60 40 long-term short-term cap gain.

896

:

And so we like the tax benefits of

both of them for different reasons.

897

:

I think from a a financing

perspective, we typically, you know,

898

:

like we, we put down anywhere up

to 20%, on the total beta exposure.

899

:

And so what you're doing there

relative to like futures is you're

900

:

putting down more upfront, but you're

having less variability on a mark to

901

:

market variation, margin perspective.

902

:

In futures, you know, let's take an S&P

500, you know, contract traded at the CME.

903

:

I think it's somewhere in that five

to 10% of initial margin to put down.

904

:

And then you have the mark to market

and you're doing that all the time.

905

:

It's fine.

906

:

You don't ha, it's not, it's very much

more cash efficient than swaps, let's say.

907

:

But you know, the banks, they

can raise margin requirements.

908

:

The exchanges can raise margin

requirements and that can be at

909

:

the, at the worst time when your

equity beta is in a drawdown.

910

:

So we like a little bit more

instability on margin with swaps.

911

:

We like the tax efficiency around that.

912

:

We use futures for rebalancing and

then we keep a cash reserve built into

913

:

our programs so that we, you know,

we think about it very much on what's

914

:

the frequency of rebalancing alpha and

beta, and what is our expected drawdown?

915

:

And so we look historically at that

beta benchmark that we're targeting.

916

:

We incorporate slippage into that.

917

:

And we're basically.

918

:

We're keeping a cash reserve around that.

919

:

And then, you know, within that waterfall

we're also to that divergent point.

920

:

We have a part of the portfolio that's

expected to pop at the right time

921

:

during that equity stress drawdown.

922

:

And so the whole waterfall

is uniquely designed.

923

:

and so, you know, it, it can really range.

924

:

It, it's just dependent on your

sophistication on what you want to trade.

925

:

futures are very easy.

926

:

Anybody can set up a FCM account

very, you know, seamlessly, swaps.

927

:

You happen to, you know,

they're more over the counter.

928

:

So you have to go with

is to counterparties and,

929

:

there's traded differently.

930

:

But you, it does allow a little

bit more customization in the

931

:

swap, uh, market versus futures.

932

:

And so there's this a range of different

factors that an allocator should

933

:

consider as it relates to the choosing

of how to implement a beta component.

934

:

Corey Hoffstein: You started to talk

a little bit about stress testing in

935

:

your waterfall setup there, Shane.

936

:

And that kind of leads into the

next question here, which is that

937

:

leveraged strategies can introduce

systemic risk if broadly adopted.

938

:

Do you think the usage of portable

alpha, if broadly adopted,

939

:

could pose systemic risks?

940

:

If so, what macro prudential frameworks

or aggregate metrics would you rely

941

:

on to monitor the compounding threats

of synthetic leverage, basis risk, and

942

:

structural illiquidity across the system?

943

:

Essentially is there any way to

know if it would be prudent to scale

944

:

back on portable alpha based on

how broadly utilized it has become?

945

:

Shane McCarthy: Yeah, I, I don't view it

as a systematic risk to, to the industry.

946

:

you know, I, I lived

through the credit crisis.

947

:

I saw, you know, the

mortgage backed market.

948

:

I saw collateralized

debt obligations to CDOs.

949

:

I saw CDS.

950

:

And there was a lot of

interrelationships during that time.

951

:

There's CDO squares.

952

:

There's a lot of just overlap.

953

:

here I, I, I don't see it that way.

954

:

Like the leverage built in is basically

to get the long only equity bait exposure

955

:

and it, it's more of a structuring thing

so that that unencumbered cash can go.

956

:

And again, as long as you design

the alpha engine the right way, you

957

:

methodically go through all the waterfall

tiers of your portable alpha program

958

:

and you stress test it the right way.

959

:

Again, it, it, it can be a

robust structure if you risk

960

:

manage it the right way.

961

:

You know, candidly, you can

even, you know, if you're in an

962

:

equity beta drawdown, let's say.

963

:

you, you can actually even relax,

relax some of the assumptions around

964

:

the beta one profile if you want.

965

:

Now you don't want to take it too

far 'cause then you're effectively

966

:

taking down the beta target at the

time that you're in a trough and

967

:

it's hard to climb back out of.

968

:

But we find that most of these

allocators, at least historically and

969

:

in the institutional space, they're,

you know, they have plenty of funding.

970

:

they can have backstop mechanisms

that are built into the

971

:

port portable alpha program.

972

:

They reserve a lot of cash.

973

:

They have a very targeted tracking error.

974

:

And to the point that I made

earlier, they're not trying

975

:

to maximize alpha necessarily.

976

:

They're trying to do it in

a very thoughtful way, but

977

:

in a risk controlled way.

978

:

And so if you're very careful around

it and you're careful around the

979

:

implementation and structuring, then

even if you get into certain issues,

980

:

it's very idiosyncratic to that investor.

981

:

It's not a complete unwind,

uh, of the whole industry.

982

:

Corey Hoffstein: Yeah, I'll add that,

you know, portable alpha as a, as a

983

:

construction concept, it's a very, you

know, template concept, but the way you

984

:

actually implement it, as we've addressed

in this webinar, is highly customized.

985

:

And so you might see some of these,

crowding effects show up in different

986

:

ways in the different alpha strategies.

987

:

Obviously you'd see the

alpha disappear, right?

988

:

That's, but you know, when there's

volatility, that might take a couple

989

:

years to figure out whether the

alpha's truly disappeared, disappeared.

990

:

In the beta side, if too many people are

asking for leverage, ultimately that's

991

:

going to be a cost that's gonna show up

in the funding spreads, which is going

992

:

to increase the hurdle rate of the alpha.

993

:

So as portable alpha de, you know,

there's increasing demand for it, unless

994

:

there's increasing balance sheet support

from counterparties who are willing

995

:

to be on the other side of the beta

trade to, to make it capital efficient.

996

:

Um, that financing rate will

go up and up and up and then

997

:

ultimately make it unattractive.

998

:

So there are some natural market

mechanisms that balance this out.

999

:

but I think we're, we're very far

away from that from a true, you

:

01:01:54,461 --> 01:01:56,321

know, can this create systemic risks?

:

01:01:56,321 --> 01:01:59,201

Again, it, as long as there's

diversification across what people are

:

01:01:59,201 --> 01:02:03,431

using the alpha for and people are being

prudent about how they're building in

:

01:02:03,431 --> 01:02:08,031

buffers and margin and liquidity for the

beta, and they're not matching totally

:

01:02:08,031 --> 01:02:14,061

illiquid things, there, in my opinion,

isn't a huge amount of, of systemic

:

01:02:14,061 --> 01:02:16,071

risk that that can actually happen here.

:

01:02:16,071 --> 01:02:18,531

There's so much diversification

in implementation.

:

01:02:18,981 --> 01:02:19,911

Um, you don't really,

:

01:02:20,001 --> 01:02:20,511

Shane McCarthy: I agree,

:

01:02:20,511 --> 01:02:21,351

Corey Hoffstein: get that effect.

:

01:02:21,471 --> 01:02:26,271

Shane McCarthy: You design the Alpha

engine the right way and you manage

:

01:02:26,271 --> 01:02:30,141

the collateral side of it and the

waterfall around the beta side.

:

01:02:30,501 --> 01:02:34,431

Again, the leverage that's embedded in

portable alpha is to give you that long

:

01:02:34,431 --> 01:02:36,741

only beta exposure, very cash efficiently.

:

01:02:37,101 --> 01:02:42,051

It enables the structure and,

arguably it's enabling the

:

01:02:42,051 --> 01:02:43,881

separation of alpha and beta.

:

01:02:43,881 --> 01:02:48,531

So if you design a, a really sound

alpha engine, it separates that, that

:

01:02:48,531 --> 01:02:52,341

leverage allows you to allocate to

that and separate that out and isolate

:

01:02:52,341 --> 01:02:54,591

the properties between beta and alpha.

:

01:02:55,011 --> 01:02:57,291

And it, it, it's, it's a

better overall portfolio.

:

01:02:57,546 --> 01:03:01,851

You, you can see too that, you know,

even relative to a benchmark, you

:

01:03:01,851 --> 01:03:06,591

can design an alpha engine to reduce

the risk relative to that index.

:

01:03:06,801 --> 01:03:10,911

So you can take down drawdowns, you

can take down the volatility of the

:

01:03:10,911 --> 01:03:16,971

overall program, again, relative to

the index, but that, that reflects

:

01:03:16,971 --> 01:03:21,441

incorporating different things like a

convergent and a protective, divergent

:

01:03:21,441 --> 01:03:24,831

type of property and blending those

two together in thoughtful ways

:

01:03:25,701 --> 01:03:27,921

Corey Hoffstein: Every time I think we're,

we're getting through the question, Shane.

:

01:03:27,921 --> 01:03:30,021

I keep getting more added, so, you know.

:

01:03:30,201 --> 01:03:33,081

We'll, well I guess we'll stay here as

long as the questions keep coming in.

:

01:03:33,441 --> 01:03:35,781

Someone wrote in, uh, two

quick questions for you.

:

01:03:35,811 --> 01:03:38,541

Understanding that liquidity

is a core tenet of your

:

01:03:38,541 --> 01:03:40,841

approach, given the L in lab.

:

01:03:41,111 --> 01:03:44,231

Can you speak to the underlying

liquidity profile of the

:

01:03:44,231 --> 01:03:46,181

alpha piece of your solutions?

:

01:03:46,181 --> 01:03:50,351

What is your tolerance for illiquidity

within the alpha component?

:

01:03:50,471 --> 01:03:54,461

In other words, what's the worst

liquidity profile you'll entertain

:

01:03:54,461 --> 01:03:59,031

in the allocations you talk about

making, part of your alpha engine?

:

01:03:59,721 --> 01:04:01,791

And the second question is related

to fees, but maybe we can, we

:

01:04:01,791 --> 01:04:05,151

can touch on this first, this,

this, you know, how illiquid will

:

01:04:05,151 --> 01:04:06,651

you get in the pursuit of alpha?

:

01:04:07,671 --> 01:04:11,511

Shane McCarthy: We think

about it in 90 days or less.

:

01:04:11,541 --> 01:04:15,921

And that's because the strategies

that we run, it allows for us to

:

01:04:15,921 --> 01:04:19,971

rebalance the alpha and the beta

component on a quarterly basis.

:

01:04:20,151 --> 01:04:21,411

And so we, we do that.

:

01:04:21,831 --> 01:04:25,731

And so we think about the modeling

of the beta and rolling three

:

01:04:25,731 --> 01:04:29,961

month intervals, calendar quarters,

we go back decades and decades.

:

01:04:30,231 --> 01:04:31,761

And again, we try to stress that.

:

01:04:32,781 --> 01:04:37,941

That rebalancing policy between beta and

alpha, it's, typically about a quarter.

:

01:04:38,481 --> 01:04:42,421

We do, we're very thoughtful

around the alpha, components

:

01:04:42,421 --> 01:04:43,891

that are built into the engine.

:

01:04:44,281 --> 01:04:49,111

And so we trade a lot of exchange

traded features already on our platform

:

01:04:49,321 --> 01:04:51,151

with our systematic strategies.

:

01:04:51,481 --> 01:04:55,681

And then we structure a lot of these

other strategies to be very thoughtful

:

01:04:55,681 --> 01:04:59,941

around being able to liquidate very

quickly the cross margin with our

:

01:04:59,941 --> 01:05:02,251

other components in the alpha engine.

:

01:05:02,581 --> 01:05:06,121

And again, we wanna keep it at 90

days or less so that we can rebalance

:

01:05:06,121 --> 01:05:07,591

the alpha and beta very thoughtfully.

:

01:05:09,192 --> 01:05:11,862

Corey Hoffstein: The second question was,

was about fees, which that question came

:

01:05:11,862 --> 01:05:15,762

in before we, we got to the fee slide,

so hopefully the fee slide addressed it.

:

01:05:16,162 --> 01:05:20,152

question here, and this is actually

reminiscent to me of the new sort of

:

01:05:20,182 --> 01:05:25,702

emergence of the, the total portfolio

approach that is gaining traction taken

:

01:05:25,702 --> 01:05:32,032

from Canadian pensions and, and being

adopted by US institutions where instead

:

01:05:32,032 --> 01:05:35,392

of looking at things as separate asset

classes, you know, they're looking at

:

01:05:35,422 --> 01:05:39,592

things in terms of more of a factor lens

and how they apply to the portfolio.

:

01:05:39,592 --> 01:05:44,332

And so the question here is, does Shane

view convergent and divergent strategies

:

01:05:44,332 --> 01:05:48,352

almost as their own asset classes, rather

than thinking about it as, say, equity

:

01:05:48,352 --> 01:05:52,852

market neutral or relative value as

separate asset classes or strategies,

:

01:05:53,002 --> 01:05:56,842

would you really just classify them

as a single convergent asset class?

:

01:05:58,606 --> 01:06:03,076

Shane McCarthy: We, we focus on the

statistical properties of what convergent

:

01:06:03,076 --> 01:06:07,186

offers relative to what divergent offers.

:

01:06:07,186 --> 01:06:07,306

So.

:

01:06:07,981 --> 01:06:10,651

I think asset class

would, would be a stretch.

:

01:06:10,651 --> 01:06:15,936

We just, we think about it, it goes back

to this durability of an alpha engine.

:

01:06:16,386 --> 01:06:21,006

We want a positive carry component

with, and it's a risk budgeting approach

:

01:06:21,006 --> 01:06:25,416

where we want a certain percentage of

our portfolio risks to be allocated

:

01:06:25,416 --> 01:06:29,196

to strategies that are designed

to make money in normal periods.

:

01:06:29,616 --> 01:06:33,546

And, and then the remainder of the

risk budget is to go into stuff

:

01:06:33,546 --> 01:06:35,106

that are more protective in nature.

:

01:06:35,466 --> 01:06:38,976

And so we think about it as a

portfolio construction framework.

:

01:06:39,396 --> 01:06:41,226

Rather than an asset class.

:

01:06:41,686 --> 01:06:46,301

and, and so we, we take these properties

and, and as we underwrite them and

:

01:06:46,301 --> 01:06:50,051

we include them in our alpha engine,

we're very much focused on that.

:

01:06:50,261 --> 01:06:51,671

Is something additive?

:

01:06:51,941 --> 01:06:56,861

Does it fit in one of those buckets

and is it meeting our expectations

:

01:06:56,861 --> 01:07:01,361

on what that type of property is and

what it can deliver as it relates to

:

01:07:01,361 --> 01:07:06,371

the alpha engine in isolation or in

the broader portable alpha construct?

:

01:07:07,811 --> 01:07:08,021

Corey Hoffstein: All right.

:

01:07:08,021 --> 01:07:12,221

Two questions left here, Shane, unless

someone answer asks a surprising new one.

:

01:07:12,701 --> 01:07:17,681

given that portable alpha is seeing a

reemergence, are we seeing that the people

:

01:07:17,711 --> 01:07:23,471

offering portable alpha solutions are

primarily upstart firms or are we seeing

:

01:07:23,471 --> 01:07:29,831

portable alpha solutions being offered

by sort of your premier hedge funds?

:

01:07:30,461 --> 01:07:30,971

Shane McCarthy: Both.

:

01:07:31,841 --> 01:07:34,961

There's a lot of Premier hedge

funds that are, are doing it.

:

01:07:35,051 --> 01:07:39,116

Uh, they're launching new share

classes, to meet the demand that we're

:

01:07:39,116 --> 01:07:40,616

seeing in the institutional space.

:

01:07:41,166 --> 01:07:45,966

you know, we typically see a global

equity benchmark, like in ACWI or world

:

01:07:45,966 --> 01:07:48,106

as, the choice for the beta component.

:

01:07:48,796 --> 01:07:52,636

And then again, they use their own

alpha engine as the alpha side of it.

:

01:07:53,776 --> 01:07:57,526

We believe in a multi-strategy approach

through this convergent, divergent

:

01:07:57,886 --> 01:07:59,716

implementation approach on Alpha.

:

01:08:00,226 --> 01:08:03,526

some of these designs that you're

seeing with these, whether it's

:

01:08:03,526 --> 01:08:06,826

premier or startup hedge funds,

it can be a single alpha source.

:

01:08:07,276 --> 01:08:10,246

And again, if it's convergent

in nature, you're getting that

:

01:08:10,246 --> 01:08:12,826

exposure under normal periods.

:

01:08:13,936 --> 01:08:16,276

You're losing out though on some

of the protective features that are

:

01:08:16,276 --> 01:08:18,046

built in with a divergent property.

:

01:08:18,406 --> 01:08:23,116

And so, you know, you, you can go

into it, it's a seamless transaction,

:

01:08:23,426 --> 01:08:25,256

to a share class from a hedge fund.

:

01:08:25,645 --> 01:08:27,895

And again, there's sort of

cross contamination risk,

:

01:08:27,895 --> 01:08:29,156

like I mentioned earlier.

:

01:08:29,501 --> 01:08:30,401

But it's seamless.

:

01:08:30,401 --> 01:08:35,291

And then you package all the operational

complex complexities inside the manager

:

01:08:35,321 --> 01:08:37,121

and allow them to do all that for you.

:

01:08:38,231 --> 01:08:38,441

Corey Hoffstein: All right.

:

01:08:38,441 --> 01:08:39,581

Last question.

:

01:08:39,640 --> 01:08:42,341

And it's a question going back

to the slide about alpha exposure

:

01:08:42,341 --> 01:08:43,691

per a hundred dollars of beta.

:

01:08:44,291 --> 01:08:48,731

And the question here is, how can the

portable alpha work if it's only on 25 or

:

01:08:48,731 --> 01:08:52,241

50 cents, uh, of alpha per unit of nav?

:

01:08:52,781 --> 01:08:56,140

Is there enough idio risk to

exceed the cost of financing

:

01:08:56,140 --> 01:08:57,191

that a hundred dollars of beta?

:

01:08:57,191 --> 01:09:02,441

Or do those alpha percents really only

apply for very volatile CTA strategies?

:

01:09:02,441 --> 01:09:06,390

And I think this, this is a really, it's

a nuanced question, but it ties into the

:

01:09:06,390 --> 01:09:12,451

idea of, you know, a a dollar of alpha is

not the same across strategies that have

:

01:09:12,451 --> 01:09:14,881

very different, uh, levels of idio risk.

:

01:09:15,571 --> 01:09:15,961

Shane McCarthy: Yep.

:

01:09:16,921 --> 01:09:18,631

So, yeah, it's a really good question.

:

01:09:18,691 --> 01:09:22,560

and it's very dependent on the

construction of the alpha engine,

:

01:09:22,651 --> 01:09:26,791

what type of, uh, volatility you're

running at within the Alpha Engine.

:

01:09:26,911 --> 01:09:30,241

and ultimately what, you know, what,

what are the financing costs embedded

:

01:09:30,241 --> 01:09:31,560

in the portable Alpha program?

:

01:09:31,951 --> 01:09:33,661

And that is definitely not stable.

:

01:09:34,060 --> 01:09:38,736

you, you know, we talked about swaps

in futures, in swaps, you know, it's

:

01:09:38,736 --> 01:09:40,145

a secured overnight funding rate.

:

01:09:40,326 --> 01:09:42,725

d so that's been around since:

:

01:09:42,996 --> 01:09:46,626

You find that as a financing rate, more

or less, it kind of tracks fed funds.

:

01:09:47,166 --> 01:09:50,946

Uh, in the early days from

inception in:

:

01:09:50,946 --> 01:09:52,716

of in that one to 2% range.

:

01:09:53,196 --> 01:09:58,656

It declined, uh, through the COVID period,

basically flat, you know, maybe 50 bips.

:

01:09:59,226 --> 01:10:05,106

And then with the inflation spike and

fed hiking rates through 22 and 23, you

:

01:10:05,106 --> 01:10:09,546

saw that SOFR rate and you pay a spread

over that, to be clear too, to the banks.

:

01:10:09,936 --> 01:10:14,016

So, but the base, SOFR rate

went up, you know, near 5%.

:

01:10:14,586 --> 01:10:18,126

Now, some of these divergent

and convergent strategies can

:

01:10:18,126 --> 01:10:19,686

be impacted in different ways.

:

01:10:20,331 --> 01:10:24,021

On the divergent side, they're

very cash efficient, right?

:

01:10:24,021 --> 01:10:28,461

So they sit on a lot of unencumbered cash

and setting aside the alpha component

:

01:10:28,461 --> 01:10:32,781

of it, their base return can go up

because they're sitting on that cash.

:

01:10:33,231 --> 01:10:36,441

Or maybe in trend following, they

can trade the directionality of

:

01:10:36,441 --> 01:10:40,371

the short term rate market and make

some money in that uh, on that side

:

01:10:40,371 --> 01:10:44,991

of stuff, on the convergence side,

they're lower capacity, they're

:

01:10:44,991 --> 01:10:46,821

more highly levered type of trades.

:

01:10:47,001 --> 01:10:49,251

So there's a financing

cost embedded in there.

:

01:10:49,701 --> 01:10:54,591

It can cause more dispersion if we see

rate volatility, which can be good for

:

01:10:54,591 --> 01:10:58,791

convergence strategies, but the financing

rates could be an offset to that if

:

01:10:58,791 --> 01:11:01,191

you see elevated, uh, rates in there.

:

01:11:01,461 --> 01:11:04,431

So it's very, very much

dependent on the SOFR rate.

:

01:11:04,791 --> 01:11:08,116

and, and then also, you know, again,

how you design your alpha engine

:

01:11:08,536 --> 01:11:11,776

and sometimes that 25% or less.

:

01:11:12,176 --> 01:11:16,891

It, it may not always, give you that

excess return positive tracking error.

:

01:11:17,251 --> 01:11:19,621

And so you have to have a

willingness to take that and there

:

01:11:19,621 --> 01:11:21,001

can be variability around that.

:

01:11:21,751 --> 01:11:24,031

Corey Hoffstein: The other subtle

nuance I'll add here is, is there's

:

01:11:24,031 --> 01:11:27,661

a very big difference if a hundred

percent of your beta is being

:

01:11:27,661 --> 01:11:31,291

achieved synthetically versus a mix

of synthetic and cash exposure, right?

:

01:11:31,291 --> 01:11:36,601

If you're only adding an overlay of $25

of alpha for a hundred of beta, you might

:

01:11:36,601 --> 01:11:43,561

be able to put 50 to $60 of that beta in

cash beta exposure, and then you're not

:

01:11:43,561 --> 01:11:48,541

incurring a borrow rate or a financing

rate, which makes the hurdle rate, you

:

01:11:48,541 --> 01:11:51,061

know, much lower for the total portfolio.

:

01:11:51,361 --> 01:11:55,681

So there are a lot of implementation

nuances here and that's why it's

:

01:11:55,681 --> 01:11:57,991

worth talking, talking to the

experts about how they're doing it.

:

01:11:58,021 --> 01:12:00,511

So, well, we finally made it

through all the questions.

:

01:12:00,511 --> 01:12:02,971

I appreciate everyone who stuck

around for an extra, 15 minutes.

:

01:12:02,971 --> 01:12:05,161

It was the vast majority of you.

:

01:12:05,191 --> 01:12:06,991

So I hope that that was useful.

:

01:12:06,991 --> 01:12:08,821

Really appreciate the detailed question.

:

01:12:08,821 --> 01:12:10,756

Shane, this has been phenomenal.

:

01:12:10,756 --> 01:12:13,186

I appreciate you walking us

through what all the new survey

:

01:12:13,186 --> 01:12:14,866

data says about the adoption.

:

01:12:15,016 --> 01:12:18,436

If folks wanna learn more

about LABQs and and what you're

:

01:12:18,436 --> 01:12:19,876

doing, where can they find you?

:

01:12:21,136 --> 01:12:21,626

Shane McCarthy: Yeah, at LAB-Qs.com.

:

01:12:23,266 --> 01:12:27,526

And, you know, I would add

into that we are about a month

:

01:12:27,526 --> 01:12:32,026

or two out from developing an

educationally focused website.

:

01:12:32,056 --> 01:12:33,436

It's portable alpha.com.

:

01:12:33,436 --> 01:12:35,146

Can't get it any easier than that.

:

01:12:35,626 --> 01:12:38,446

And we're, uh, you know,

nearing completion on that.

:

01:12:38,896 --> 01:12:42,346

And so I'd encourage everybody to, you

know, when it's up and running to go

:

01:12:42,346 --> 01:12:46,786

out there and we're gonna put, you know,

a lot of, uh, education around what

:

01:12:46,786 --> 01:12:48,436

this means and how to think about it.

:

01:12:48,436 --> 01:12:51,886

And we're gonna continue to kinda

focus in this area and, and try to,

:

01:12:52,166 --> 01:12:53,906

promote the technique as much as we can.

:

01:12:53,906 --> 01:12:55,676

So I'd encourage you to go look at that.

:

01:12:56,591 --> 01:12:59,891

Corey Hoffstein: And for folks tuning in

who are looking to implement this in the

:

01:12:59,891 --> 01:13:03,791

wealth space, I'll remind you we have

tons of resources at returnstackedetfs.com

:

01:13:04,785 --> 01:13:07,695

So if you're looking to learn more

about how those can work and how

:

01:13:07,695 --> 01:13:10,215

those can be applied in the portfolios

you're developing for clients,

:

01:13:10,545 --> 01:13:11,975

please go to returnstacked.com

:

01:13:12,105 --> 01:13:13,905

and get in touch with

one of our consultants.

:

01:13:14,415 --> 01:13:16,395

Alright, everyone, thank

you for your time today.

:

01:13:16,395 --> 01:13:17,415

Really appreciate it.

:

01:13:17,415 --> 01:13:18,885

Have a wonderful rest of your day.

:

01:13:20,145 --> 01:13:20,695

Shane McCarthy: Thanks Corey.

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Profile picture for Rodrigo Gordillo

Rodrigo Gordillo

Rodrigo Gordillo is the President and Portfolio Manager at ReSolve Asset Management Global, an alternative asset management firm specializing in globally diversified systematic investment strategies. He co-founded ReSolve Asset Management Inc. in 2015 and expanded to ReSolve Asset Management Global in 2021. Starting his career at John Hancock focusing on pensions, Gordillo transitioned to the ultra-high-net-worth sector with i3 Advisors Inc. He held significant roles at Macquarie Private Wealth, Dundee Goodman Private Wealth, and Richardson GMP, enhancing his expertise in investment decisions and client wealth management.
Profile picture for Corey Hoffstein

Corey Hoffstein

Corey Hoffstein is the CEO and Chief Investment Officer of Newfound Research, a quantitative investment and research firm based in the Greater Tampa Bay Area, United States. Hoffstein co-founded Newfound Research with the aim of assisting investors in proactively managing investment risks through diversification, specifically by leveraging Return Stacking™ strategies. The firm specializes in managing alternative strategies and capital-efficient solutions, enabling the implementation of these innovative investment concepts. In addition to his role at Newfound Research, Hoffstein also serves as a Portfolio Manager at Return Stacked® Portfolio Solutions.