FidelityConnects: Factor investing: The quant edge for today’s markets

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Hello, and welcome to Fidelity

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Connects.

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I'm Marilyne Bardaji, District Vice

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President of Sales.

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The Federal Reserve has slashed

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their benchmark interest rate by 25

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basis points.

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Citing labor market weakness and

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continued margin pressure, this is

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the third and final rate cuts of

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2025.

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With the yield curve beginning to

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re-steepen and economic activity

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softening, the shift sets the

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tone for how investors should think

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about positioning into 2026 and

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beyond.

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Our next guest.

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Says this environment only

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reinforces the stretch for quality

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and momentum, two factors

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he believes are best suited for the

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K-shaped economy.

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Joining me now to unpack what this

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may mean for factory leadership,

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including how AI and tariffs may

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shape the path ahead, is Fidelity

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Head of Quantitative Index

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Solutions, Bobby Barnes.

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Welcome, Bobby.

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Thank you.

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Thank you for joining us all the way

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from Boston

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That's indeed, it's good to be here.

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Thank you for having us.

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Bobby, it's quite an eventful day

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today.

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Both the Bank of Canada and the Fed

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met for the last time this year to

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decide how they go about interest

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rates and we'll get to it.

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But before we do, I'd like you to

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talk to us about the quantitative

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research team. So how did the team

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come about?

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What is it exactly that you do?

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And that data, is it only used

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for our quant products or

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is it also used by some of our

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fundamental, you know, portfolio

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managers here at Fidelity?

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Sure, yeah, there's a lot to unpack

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there.

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So I'll start with my favorite

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story, which is that, unbeknownst

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to a lot of people, Fidel has been

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doing quant for a very long time.

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So we hired our first one back in

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1965, and his job

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was to help the firm understand

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how to use the computer, because

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there was only one back in those

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days.

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But if we fast forward,

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the, in particular, I would talk

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about how the...

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Quant took shape around the

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mid 2000s because that's more

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similar to what it is today.

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And so historically Quant had been

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an independent silo

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separate from our fundamental

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department.

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And then in the mid-2000s is when

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they integrated the two together to

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identify socks that are attractive

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both fundamentally and

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quantitatively.

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And so that's how I spent

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most of my career.

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I started full-time in 2009.

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Working alongside with many

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of the portfolio managers that

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Fidelity Canada knows

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and has money invested with.

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And I created the

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models to stock the quant models

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using the best ideas and

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approaches, both quantitatively and

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fundamentally.

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And that is those insights that led

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to the factor ETFs

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that we ended up launching, both

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here in Canada and in the

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U.S.

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Having said that, where we are

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now is even more integrated.

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And so, depending on

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which specific quant team you're

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talking about, we've got teams

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that are like the ones that I

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started on, we call them the

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embedded equity team,

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where you're working one-on-one with

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quant portfolio managers.

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We also have, because quant

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naturally is very technically

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in kind, we

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used our quant expertise to

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build technologies to help

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augment the fundamental job.

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And so what that might look like

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would be, as you can imagine,

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our fundamental analysts who are

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experts in

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every area or industry across

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the globe, they publish tremendous

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amounts of research daily.

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And one of the things, technologies

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we've built is an

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AI engine that will

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help portfolio managers summarize

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all the research that's published

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internally and elevate

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the most attractive ideas

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that they should add to their

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portfolio.

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So that's one way of

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enhancing the portfolio management

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job. We do the same thing with

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analysts, where if you think about

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the day-to-day job of an analyst,

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you're on earnings calls and

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you're summarizing the information

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that is presented by management

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on those calls.

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There are only so many hours in a

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day, so you can't sit in on all the

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calls. And so we've built systems

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that will do that

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for the analyst.

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And again, summarize all the

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relevant information to help speed

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up the number of rocks that they can

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uncover. As we like to call it.

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Right.

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You've also said when we spoke to

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Prep this Call that you do work

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alongside, you know, portfolio

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managers like Will Danov, Joel

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Fillinghouse.

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So how do they use that research?

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You mentioned, you, know,

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making it easier to read some of

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the, you know, Atlas reports and

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whatnot, but how do they look at the

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data that you provide for them?

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So the job of a quantitative analyst

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that are partnered with

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our portfolio managers, like a Will

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and a Joel, is twofold.

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One is to provide stock selection

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ideas.

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And then the other is to help them

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with portfolio construction.

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The former, however, usually

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what happens, like if I'm working

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with any portfolio

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manager in my prior

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role, because now I'm managing the

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ETF business, but we still have

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other quantitative analysts who

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are working directly with those

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portfolio managers on a day-to-day,

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they will sit with a

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will and say, okay, Will, talk

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to me about your investment

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philosophy. How would you articulate

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that? And then the job of the quant

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is to take

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what's said, and translate that

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to, OK, if

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Will just said, I like

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companies

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that have durable modes and

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are compounders over time.

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What does that mean quantitatively?

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And then develop a model that's

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really custom tailored to Will and

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his process.

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And so that's what I did over

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the course of many years.

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And many of our quantitative

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analysts are still doing that today.

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And that's where that will look like,

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is they'll surface those ideas that

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are custom tailored to the portfolio

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manager based off of their

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investment philosophy, but then also

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help them create a portfolio based

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off those ideas with

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the idea of maximizing exposure

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to the most attractive stocks while

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minimizing any unintended risks.

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So how advisors here in Canada know

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you is through the all-in-one ETFs

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or the factor, as we call them, the

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factor ETFs.

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Can you talk a bit about how those

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factors went for this year?

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What do you see, you know, working

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well for 2026?

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So what are your perspectives?

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Ah, yeah.

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So it's been a very interesting

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year.

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And especially when I look at,

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you know, we've got a global

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offering here in Canada.

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And so there, you now, what's worked

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has somewhat rhymed

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depending on the region.

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But there are subtle nuances, you

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across regions.

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And so the way to think about that

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is to first orient around

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the economic cycle and where each

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region is within the

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business cycle.

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The U.S. Is currently in late cycle.

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It's kind of where we've been since.

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Call it 2002,

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sorry, 2022 and

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2023,

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Canada and Europe

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are actually closer

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to being an early cycle.

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And so what that has meant from a

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factor perspective is that the

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best performing factors in both

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Canada and in

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Europe have actually been value.

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And momentum has done very well as

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well in both of those regions.

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Whereas the US market,

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because it's late, value typically

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doesn't do as well in the US Market.

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And so the best performing factor

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year to date has been momentum

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and quality, which is usually

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what also does quite

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well during late cycle.

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It did well at the start of the

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year, but because of some of the

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tariff tantrum and in particular

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the recovery after the tarif

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tantrum.

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It has not done as well because

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that's been more characterized as by

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a junk rally, if you will, in the

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U.S. Market specifically.

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Right. So do you think that for the

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US for 2026, I

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think I mentioned it's also the same

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two factors, right?

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Momentum and quality that you see

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working well.

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Yes. So my forecast would

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be an overweight to momentum and

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quality for the reasons that I

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mentioned, you know, kind of

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anchoring in on the cycle,

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not only where we are in a cycle,

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but what I think will likely be the

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cycle that we were in, that we will

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be in in 2016.

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And so, you know, with I think

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we're going to be in an elongated

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late cycle, which means there's

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still there's positive growth,

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but growing at a slower rate.

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And, so, high quality companies with

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high profit margins.

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They tend to do the best in that

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environment.

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And the thing is there's still risk

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to margins. So, you know, you kind

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of said it at the open where

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there are risks to margin

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compression for some companies.

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And so in that environmental, you

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typically want to shade higher

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quality because they have higher

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margins and have more room

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to flex if they need to.

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Similarly, momentum

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is a slightly different narrative.

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That typically, the trend is

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your friend is the axiom that

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usually goes along with that.

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And unless we have a big change

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in the trend that we've been in

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in 2025, then I would

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have dropped like that out to 2026

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as well.

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And the last point I would make

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there is that with the

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momentum portfolio in particular,

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it has a lot of exposure to AI.

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And that's been I think

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that's top of mind to a lot of

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people. So it's no surprise there.

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I also think it still has

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legs. I think it's still has a

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runway to continue into

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2026 because these are, you

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know, very long projects that

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people are embarking on in doing

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the AI build out.

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We can talk about, let's

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talk about the AI trend now and go

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back to the factor later.

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So obviously somebody who wants

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exposure to AI, you said momentum,

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what can they expect to get?

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And what's your thought, are we in a

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bubble? Do you have any thoughts on

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that?

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Yes, I have many thoughts.

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So the first thing that you have to

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understand about AI is

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a lot of people, when they

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talk AI, they just

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associate that with Mag-7,

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but there are

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very different parts of AI.

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And so if I only break it down,

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most of the Mag- 7,

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they're doing the spending to build

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out AI, and I call it AI

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as a service.

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If you go on Google right now and

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ask a question, you can get an

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answer from the Google

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AI.

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But no one, for the most part, is

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making any money off of that.

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That's much farther in the future.

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And so, to the extent that people

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are worried about when are these

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companies going to start making

money,

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I actually would submit, okay,

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ignore that for now.

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Because, you know,

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the the most of them that are

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spending the money to build it out,

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they're actually highly profitable

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already. So I don't worry about

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whether or not they're going to make

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money eventually.

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It's neither here or there, in my

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opinion.

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What's more important about AI is

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what I

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call the enablers.

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And so what's happening is to do

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the build out that's happening at

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the MaxEvan level, they are spending

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a lot of money and that money

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they're spending ends up being

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revenue for somebody else.

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That's where, if you look year to

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date, for example, those

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enablers who are

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doing the picks and shovels of

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building for the service providers,

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their earnings are inflecting

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tremendously.

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And along with that, because we

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always say that stocks follow

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earnings, their stock prices have

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done tremendously well in 2025.

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And so these build-outs, there was a

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number I saw where

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I think globally there are, and

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don't hold me exactly to these

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numbers, but globally, I think there

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are about anywhere between 2,000

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and 3,000 data centers.

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That number needs to double over

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the next two to three years.

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And so that's going to create a lot

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of business opportunity for those

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enablers.

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So you're saying those Max 7, those

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big companies are feeding the

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smaller ones.

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Yes, so what does

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So what does that mean? Does that

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mean you have, because I heard you

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say you don't necessarily like small

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caps, what does that mean in terms

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of perspective filters for those

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smaller companies?

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So there's a subtle nuance there

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that I should clarify because

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they are smaller than the Mag-7,

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but for their individual industries,

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they're actually the biggest ones.

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And so the way to think about that

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is, Mag- 7 is

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mostly tech, those names,

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but when they buy

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a microchip for AI,

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you need a world-class microchips.

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And so,

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the best microchipped provider

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is basically the bigger one, the

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bigger company.

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So you're not, you know, you're not

[00:12:19.503]

buying the smaller microchip

[00:12:20.671]

provider. So then after you've

[00:12:22.373]

bought your microchips, we're okay.

[00:12:23.374]

Where are you going to put them? I'm

[00:12:24.175]

gonna put them in the data center,

[00:12:25.076]

which is basically a warehouse.

[00:12:27.144]

And the warehouse gets hot because

[00:12:28.546]

there are a whole lot of microchops

[00:12:30.114]

in there. I need to cool it.

[00:12:32.049]

Similar thing. Okay.

[00:12:33.184]

So when I, um,

[00:12:35.086]

spend money on the HVAC company to

[00:12:37.254]

do the cooling.

[00:12:38.489]

You know, it's the biggest

[00:12:40.591]

and the best HVAC company.

[00:12:42.226]

And so all HVAD companies are

[00:12:43.694]

smaller than the MAG-7, but you're

[00:12:45.229]

still not, it not the case that I'm

[00:12:47.064]

choosing the small HVAT

[00:12:49.333]

company.

[00:12:50.368]

And so for that reason,

[00:12:52.203]

if you segment the market by

[00:12:54.205]

market cap, like, well, you say,

[00:12:56.007]

okay, give me the biggest companies

[00:12:57.475]

within each industry.

[00:12:59.744]

It's the bigger ones within each

[00:13:01.045]

industry that are doing well year to

[00:13:02.413]

date. And I think we'll, because of

[00:13:04.148]

the reasons we're talking about, and

[00:13:05.883]

will likely continue to be the...

[00:13:08.185]

The beneficiaries and the

[00:13:09.754]

outperformers in 2026.

[00:13:11.856]

And so you don't want to, controlling

[00:13:12.857]

for industry, you don't want to

[00:13:14.658]

shade down in size.

[00:13:16.761]

Hello investors, we'll be back to

[00:13:18.462]

the show in just a moment.

[00:13:19.797]

I wanted to share that here at

[00:13:21.098]

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your podcasts.

[00:13:45.656]

Now back to today's show.

[00:13:48.292]

You look at data, ratios,

[00:13:50.494]

numbers. Do you see a lot of

[00:13:52.163]

similarities or differences with

[00:13:53.864]

2000 for people wondering,

[00:13:55.699]

you know, if we are in a bubble,

[00:13:57.735]

what are your thoughts on today

[00:13:59.203]

versus 2000?

[00:14:00.571]

So your question is

[00:14:02.473]

dead on where I'm spending most of

[00:14:04.441]

my mental calories.

[00:14:05.709]

I do see a lot

[00:14:07.545]

of similarities between now and

[00:14:09.547]

2000.

[00:14:11.048]

I guess if I take a quick step back,

[00:14:13.117]

because I just realized I didn't

[00:14:14.285]

answer one of your questions about a

[00:14:15.653]

bubble, I think we are

[00:14:17.688]

gonna be in one

[00:14:19.523]

or have one, but I think

[00:14:21.458]

were on the earlier innings of it

[00:14:22.893]

right now.

[00:14:25.095]

And if you just listen to

[00:14:27.498]

what the Mag-7 or the,

[00:14:30.801]

the AI spenders,

[00:14:33.504]

the ones who are spending to do the

[00:14:34.772]

build out, listen to what they say

[00:14:36.106]

to you.

[00:14:37.107]

They basically said to you they're

[00:14:38.909]

going to overspend because they

[00:14:40.878]

view the risk of

[00:14:43.180]

coming in second as being bigger

[00:14:45.215]

than the risk overspending on the

[00:14:46.950]

buildout.

[00:14:49.019]

They're going overspent.

[00:14:51.088]

Overspent is going to be too much

[00:14:53.090]

spending and

[00:14:55.559]

thereby a bubble.

[00:14:57.594]

And they're leveraging right now,

[00:14:59.463]

right, with the bond issues.

[00:15:01.632]

They are, and

[00:15:03.667]

that worries me some.

[00:15:06.336]

Most of the Max 7,

[00:15:08.939]

however, they're very profitable.

[00:15:10.641]

They have super

[00:15:12.709]

large cashflow.

[00:15:13.744]

So while they're leveraging to

[00:15:16.113]

finance some of this build out, I

[00:15:17.881]

think they're gonna be okay.

[00:15:18.982]

There is a subset of

[00:15:20.951]

private companies, however

[00:15:23.387]

that you have to consider

[00:15:25.589]

beside the Max7.

[00:15:28.392]

So OpenAI, Anthropic.

[00:15:32.362]

XAI, they're also doing

[00:15:34.498]

the same spending, but the

[00:15:35.933]

difference between them and the MAX

[00:15:36.800]

7 is they don't have

[00:15:38.669]

any profits and they're raising the

[00:15:40.604]

same amount of debt.

[00:15:41.405]

So that's the part that concerns

[00:15:43.273]

me about

[00:15:45.409]

the debt that's being raised.

[00:15:47.578]

But we'll see how that ends for

[00:15:49.580]

them. But if you look downstream,

[00:15:51.648]

to the companies,

[00:15:53.517]

the enablers that I talked about,

[00:15:56.386]

when I think about what's

[00:15:58.288]

the runway for their

[00:16:01.225]

profitability and their revenues.

[00:16:05.495]

The risk, I think, is

[00:16:07.664]

any business they're getting from

[00:16:09.833]

the private AI companies

[00:16:12.369]

in

[00:16:14.271]

the event that those companies

[00:16:16.106]

aren't able to access financing in

[00:16:17.741]

the way that they have before,

[00:16:19.242]

that's going to cause trouble

[00:16:20.978]

downstream to the HVAC company

[00:16:23.313]

and the data center

[00:16:25.315]

build out company.

[00:16:27.951]

So that's the risk for them.

[00:16:29.553]

And then the other

[00:16:32.055]

similarity to the dot

[00:16:33.991]

com, the 2000.

[00:16:36.626]

The thing about the dot com

[00:16:38.528]

is they,

[00:16:40.731]

first of all, valuations

[00:16:42.632]

got crazy. Like we were valuing

[00:16:44.434]

companies based off eyeballs, like

[00:16:45.769]

that, that part was crazy.

[00:16:47.604]

But there was an element

[00:16:49.773]

of fundamentals, there were

[00:16:51.541]

companies that were making money.

[00:16:52.976]

So back back then, we were laying a

[00:16:54.878]

bunch of fiber in the ground, right?

[00:16:57.080]

For the internet.

[00:16:58.348]

So it was a similar thing.

[00:16:59.816]

It's not the case that the company

[00:17:01.218]

that was digging the holes to lay

[00:17:02.285]

the fiber, they were making a lot of

[00:17:03.687]

money. But what happened was

[00:17:05.522]

you had the parallel,

[00:17:07.924]

the overbuild out.

[00:17:09.760]

And so once too

[00:17:12.062]

much fiber had been laid,

[00:17:14.364]

the company they had earned a lot of

[00:17:15.765]

profits from that, their

[00:17:17.634]

revenues dissipated or

[00:17:19.636]

evaporated because they didn't even

[00:17:20.837]

lay net new fiber.

[00:17:22.239]

We weren't using the fiber we

[00:17:23.206]

already laid. So that's my concern

[00:17:24.908]

in this environment.

[00:17:26.109]

Like, okay, if I'm investing in the

[00:17:27.878]

company that's, you

[00:17:29.880]

know, laying the connections between

[00:17:32.048]

data centers, which is actually, you

[00:17:33.583]

know obviously a thing.

[00:17:35.886]

You know, if we get to the place

[00:17:37.187]

where we have too many data centers

[00:17:38.722]

you no longer that

[00:17:40.690]

that that particular company, their

[00:17:42.325]

economic prospects might diminish.

[00:17:43.927]

And so that's the risk.

[00:17:45.128]

Right.

[00:17:45.929]

But having said all of that, I

[00:17:47.964]

do think we're in earlier

[00:17:49.900]

innings versus later.

[00:17:51.635]

But it's something that I'm keeping

[00:17:52.535]

a watchful eye on.

[00:17:53.737]

Yeah, so the market could go up for

[00:17:55.272]

a while, that momentum could

[00:17:56.640]

continue for a while.

[00:17:58.108]

You've talked about areas of concern

[00:17:59.709]

or where we're trying to be more

[00:18:01.211]

careful.

[00:18:02.245]

Let's talk about areas of

[00:18:03.313]

opportunities.

[00:18:04.114]

You had a thought on tariffs, right,

[00:18:05.649]

and the potential for them not to be

[00:18:07.384]

implemented or approved,

[00:18:09.386]

right by the

[00:18:11.588]

Supreme Court. So what are your

[00:18:12.589]

thoughts on tariffs?

[00:18:13.223]

Yes.

[00:18:14.124]

So the tariffs is a very interesting

[00:18:15.558]

discussion.

[00:18:18.061]

And let me first frame

[00:18:19.896]

what's transpired over 25.

[00:18:23.633]

Because my entire

[00:18:25.735]

process is anchored on earnings

[00:18:27.103]

revisions. I always want to be

[00:18:28.905]

invested in the companies where

[00:18:30.407]

revisions are going higher, which

[00:18:31.875]

means things are getting better.

[00:18:33.209]

Fundamentally, things are going

[00:18:34.110]

better.

[00:18:35.178]

As we've traversed through 25,

[00:18:37.580]

at the start of year was kind of the

[00:18:39.282]

extension of the.

[00:18:41.785]

The AI trade from 2024,

[00:18:44.187]

you know, things were hunky-dory.

[00:18:46.222]

When we had the tariff

[00:18:47.090]

announcements, across the board,

[00:18:49.392]

earnings revisions for, you

[00:18:51.394]

know most stocks went down, all

[00:18:53.196]

right? And that's why the market

[00:18:53.997]

went down.

[00:18:54.931]

But then when we had a tariff

[00:18:56.966]

pause, what happened was,

[00:18:58.968]

you now, and rightfully so,

[00:19:01.304]

analysts said, okay, there's not

[00:19:03.273]

gonna be as much margin compression,

[00:19:04.808]

let me take estimates back up again.

[00:19:06.576]

And so that's where you had the

[00:19:07.610]

recovery that we experienced from...

[00:19:10.780]

Call it April 8th to present.

[00:19:13.750]

And so sitting where we are right

[00:19:14.918]

now,

[00:19:16.920]

tariffs for me are, it's kind of my

[00:19:18.688]

wild card. And so I just shared

[00:19:20.723]

with you what my outlook is for

[00:19:23.726]

2026.

[00:19:25.528]

And I would say that

[00:19:27.497]

that outlook assumes

[00:19:29.766]

the status quo, which is that you

[00:19:31.634]

keep the tariffs that you have right

[00:19:33.136]

now.

[00:19:34.537]

Ironically, it just, I'm

[00:19:36.439]

not a legal person,

[00:19:38.341]

but so in my humble layperson's

[00:19:40.476]

view. I think that the

[00:19:43.179]

tariffs that are being reviewed by

[00:19:44.447]

the Supreme Court right now are

[00:19:46.449]

going to be shot down.

[00:19:48.651]

Because they were put in place under

[00:19:49.786]

the premise that we had a

[00:19:51.888]

global emergency, which is kind

[00:19:53.756]

of a high bar to prove

[00:19:55.758]

that globally we were in an

[00:19:58.061]

economic emergency.

[00:19:58.895]

Tell me if you've heard this but I

[00:20:00.163]

heard that there's a way for them

[00:20:02.098]

to, if that doesn't work out,

[00:20:05.335]

to find a different way for them to

[00:20:06.936]

be implemented would be a hundred

[00:20:08.671]

fifty days and maximum fifteen

[00:20:10.373]

percent.

[00:20:11.474]

Yes. So they have a variety

[00:20:13.509]

of different ways to put some of

[00:20:15.244]

them back on.

[00:20:16.946]

And it's going to take a while

[00:20:18.381]

because there's a lot of red tape

[00:20:19.515]

and procedures to get there.

[00:20:21.451]

And to your point, some of the have

[00:20:22.552]

caps. And so in

[00:20:24.587]

my mind, if

[00:20:26.556]

it gets struck down, two things are

[00:20:28.324]

going to happen.

[00:20:29.525]

The first is that it's gonna

[00:20:31.394]

be, especially if they get struck

[00:20:32.829]

down and it's been deemed that

[00:20:35.231]

they need to be paid back.

[00:20:36.933]

That's going be tremendous economic

[00:20:39.035]

stimulus.

[00:20:40.369]

To these companies that are getting

[00:20:42.305]

these dollars back.

[00:20:45.374]

And that kind of

[00:20:47.243]

negates my outlook partially

[00:20:49.412]

is from a factor perspective for

[00:20:51.147]

2026.

[00:20:52.148]

Because when the money comes back,

[00:20:53.916]

it's the weakest companies that that

[00:20:55.785]

money is gonna be most helpful for.

[00:20:57.753]

And so now you don't want the high

[00:20:59.422]

quality company, you actually want

[00:21:00.690]

the smaller cap, which I said I

[00:21:03.025]

otherwise don't like.

[00:21:04.293]

You wanna be in the smaller, riskier

[00:21:06.529]

companies because that stimulus

[00:21:08.331]

is going to be a huge...

[00:21:09.999]

Helpful tailwind for them.

[00:21:12.401]

But to your point about,

[00:21:14.837]

okay, well, what if they come back

[00:21:15.705]

on again? What if they just find

[00:21:16.639]

another way to put the same tariff

[00:21:17.607]

back on?

[00:21:18.941]

For that reason, it's going to take

[00:21:21.177]

time, but I think they're absolutely

[00:21:23.079]

going to do that.

[00:21:24.247]

And so I think that

[00:21:28.384]

it reduces the amount of time

[00:21:30.419]

that that trade can persist,

[00:21:33.155]

that you have the risk rally.

[00:21:35.091]

For 150 days,

[00:21:37.026]

exactly the amount of time it takes

[00:21:38.527]

them to put it back on.

[00:21:39.896]

And then you kind of get back to

[00:21:42.064]

the status quo where we are now.

[00:21:43.499]

And so I could see a scenario where

[00:21:45.234]

in 2026, you could

[00:21:47.169]

have two

[00:21:49.138]

different paradigms.

[00:21:50.940]

It's like, okay, it got struck down,

[00:21:53.209]

risk on,

[00:21:55.378]

markets inflate, party.

[00:21:57.847]

And then when they eventually get

[00:21:59.348]

put back on again, it's like okay,

[00:22:01.017]

and now we're back to the status

[00:22:02.151]

code that we're.

[00:22:03.152]

Essentially yet today and the

[00:22:04.787]

prescription would be for momentum

[00:22:06.222]

and quality to be the key

[00:22:08.157]

factors for outperforming.

[00:22:09.225]

Still, momentum and quality.

[00:22:10.926]

Yeah.

Yeah, on the back end of

[00:22:13.262]

this stimulus from getting your

[00:22:15.097]

tariff money back.

[00:22:15.698]

Right. You did say something also

[00:22:17.600]

about a deja vu model that

[00:22:19.668]

you use.

[00:22:20.803]

So I think people like to know that

[00:22:22.805]

we can try to predict,

[00:22:24.907]

obviously, or no one has a crystal

[00:22:25.941]

ball, but there's something that

[00:22:27.810]

you use just based on ratios called

[00:22:29.879]

the deja vu models.

[00:22:31.080]

Can you explain what that is?

[00:22:32.748]

Yeah, so I always

[00:22:34.650]

like to keep things simple.

[00:22:36.952]

So the Deja Vu model looks

[00:22:39.155]

at 15 different macroeconomic

[00:22:41.724]

variables.

[00:22:42.892]

And let me just pick one for

[00:22:45.728]

illustrative purposes.

[00:22:47.496]

If you take unemployment and

[00:22:49.832]

just plot it through time,

[00:22:51.767]

it has a pattern, it kind of

[00:22:53.669]

goes up in recessions and then goes

[00:22:55.271]

down for most of the rest of

[00:22:57.072]

the cycle. And then it kind goes up

[00:22:58.674]

into the next recession again.

[00:23:00.042]

And so that way.

[00:23:01.477]

Pattern of the chart,

[00:23:03.312]

if you think about it, I can

[00:23:05.214]

look at unemployment today, just the

[00:23:07.216]

level, and look back

[00:23:09.185]

at points in time and say,

[00:23:11.120]

what other points were we at this

[00:23:12.555]

level?

[00:23:13.389]

And keep it very simple.

[00:23:15.191]

And so if I do that for

[00:23:18.194]

all 15 variables,

[00:23:20.829]

and so we look at, I mentioned

[00:23:21.931]

unemployment, but you can think

[00:23:23.499]

about the ISM, which is an

[00:23:25.100]

expression of economic activity.

[00:23:27.970]

It also kind of has a wave

[00:23:29.872]

pattern to it.

[00:23:30.973]

And so if I take all 15

[00:23:32.942]

of them and the levels that they are

[00:23:34.777]

today and say, okay,

[00:23:36.745]

that kind of creates a fingerprint,

[00:23:39.248]

you know, 15 different levels.

[00:23:40.416]

And so I look at historically,

[00:23:42.251]

where are the points historically

[00:23:43.886]

where those 15 different levels were

[00:23:45.788]

at similar points as they are today.

[00:23:48.090]

And it's really cool because

[00:23:50.326]

then I can extract out,

[00:23:52.328]

okay, these are the 10 most

[00:23:54.296]

similar points to today.

[00:23:56.098]

And it does a fairly good job

[00:23:57.933]

of

[00:23:59.935]

identifying where you are in

[00:24:01.737]

the economic cycle today

[00:24:03.572]

based off of those historical

[00:24:05.607]

similar periods.

[00:24:07.176]

And the reason that's important is

[00:24:09.745]

macro timing is hard

[00:24:11.747]

and people don't

[00:24:13.949]

like to do it because it is hard.

[00:24:15.651]

But the thing is.

[00:24:19.088]

After the fact, whatever macro

[00:24:21.023]

environment you were in, it's going

[00:24:22.891]

to affect your portfolio.

[00:24:24.326]

So even though it's hard to do,

[00:24:26.829]

you still should do it to have some

[00:24:28.630]

forecast. You can't get by with no

[00:24:30.332]

forecast, it's the punchline.

[00:24:32.935]

And so that's the model and how

[00:24:34.937]

we use it.

[00:24:36.572]

And it does say that

[00:24:38.440]

where we are today, and this has

[00:24:40.075]

been so for a while, it says that

[00:24:42.277]

the U.S. Economy is in where

[00:24:44.113]

we from these macro variables.

[00:24:46.715]

It looks most like

[00:24:48.584]

the late cycles of prior years.

[00:24:51.987]

My question to you was about those

[00:24:53.956]

indicators that you use, right?

[00:24:55.324]

So they're leading indicators,

[00:24:56.959]

probably.

[00:24:58.660]

How does the, does it change

[00:25:00.796]

over time? Do some leading

[00:25:02.364]

indicators as the cycle changes,

[00:25:05.167]

um, do some relationships go,

[00:25:07.035]

you know, changed and

[00:25:09.037]

make a leading indicator

[00:25:11.106]

not as useful that you have

[00:25:12.941]

to, you change that model

[00:25:14.343]

essentially is what I'm trying to

[00:25:15.611]

ask based on the fact that

[00:25:17.379]

relationships over certain

[00:25:18.847]

indicators will change or not be as

[00:25:20.716]

important. To lead or predict

[00:25:22.618]

going forward.

[00:25:23.218]

So that's an interesting nuance.

[00:25:26.154]

It, they aren't leading

[00:25:28.190]

indicators per se.

[00:25:29.958]

And so the way to think about it

[00:25:32.261]

more so is the

[00:25:35.597]

term that gets used is now casting.

[00:25:38.300]

So, you know, if I go back to my

[00:25:39.668]

example of unemployment in the

[00:25:41.637]

U.S. Right now, unemployment is at

[00:25:43.105]

4.3%.

[00:25:44.873]

You know, and so I'm just looking

[00:25:46.975]

at the prior points

[00:25:49.244]

historically that the unemployment

[00:25:50.912]

was at 4 .3.

[00:25:52.514]

That's all it's all you're doing.

[00:25:54.082]

And there's no prediction per

[00:25:56.218]

se in and of itself.

[00:25:57.619]

But the way that we use it

[00:25:59.454]

to make a prediction is I

[00:26:01.289]

find all those periods historically

[00:26:02.858]

where the unemployment was at 4.3

[00:26:04.760]

and then ask the following question

[00:26:06.795]

or the follow up question,

[00:26:08.764]

what did the market do one year

[00:26:10.699]

forward from all those points in

[00:26:11.933]

time? And so that becomes

[00:26:14.069]

the prediction,

[00:26:16.238]

if at all.

[00:26:17.038]

But the macro variables themselves,

[00:26:19.408]

though, aren't leading indicators

[00:26:21.343]

that are predicting

[00:26:23.678]

the economic cycle in any kind of

[00:26:25.280]

way, if that makes sense.

[00:26:26.882]

Absolutely.

[00:26:27.849]

Bobby, we have only a few minutes

[00:26:29.151]

left and you're the brains behind

[00:26:31.052]

those factors, right?

[00:26:31.953]

So let me spend the last few minutes

[00:26:33.188]

that we have talking about those

[00:26:34.723]

factors.

[00:26:35.690]

Can you talk a bit about how they

[00:26:36.825]

differ, you know, versus other

[00:26:38.460]

indicators or other factors

[00:26:40.562]

that other companies might have?

[00:26:42.497]

What makes us a bit different?

[00:26:44.232]

Yeah, so it gets down

[00:26:46.067]

to Fidelity's DNA.

[00:26:48.270]

Number one, we're an active

[00:26:50.238]

manager. We think about

[00:26:52.507]

the world actively and

[00:26:54.376]

for any portfolio that gets created,

[00:26:57.312]

we are very intentional about

[00:26:59.147]

what active bet versus

[00:27:01.116]

the benchmark are we making with

[00:27:03.385]

the idea of identifying

[00:27:05.353]

the stocks that are going to

[00:27:06.187]

outperform the benchmark.

[00:27:07.289]

We do that quantitatively and we do

[00:27:08.790]

that fundamentally.

[00:27:10.225]

So that's the first way

[00:27:12.027]

that we were different.

[00:27:13.061]

And that really informs our

[00:27:14.663]

portfolio construction.

[00:27:16.064]

But if I go a little deeper,

[00:27:18.433]

okay, you know, Bobby, that's how

[00:27:20.035]

you create your portfolio.

[00:27:20.902]

But how do you choose

[00:27:22.904]

the stocks within the portfolio?

[00:27:25.040]

Same thing. We are taking our

[00:27:27.242]

insights.

[00:27:28.176]

You know, we've got all these

[00:27:29.311]

industry experts on the fundamental

[00:27:30.946]

side.

[00:27:31.846]

We've got, you now, all these

[00:27:32.814]

talented quants on the quantitative

[00:27:34.582]

side.

[00:27:35.383]

And we take the

[00:27:37.452]

best approaches from from

[00:27:39.721]

each side.

[00:27:40.789]

And that's what informs our how we

[00:27:42.590]

go about selecting stocks.

[00:27:44.893]

And so just kind of make that

[00:27:45.894]

concrete with an example.

[00:27:48.129]

With value, we are

[00:27:50.065]

very thoughtful on how we identify

[00:27:52.434]

a value stock

[00:27:54.436]

that we think is going to outperform

[00:27:55.437]

over time.

[00:27:56.805]

We don't take the traditional

[00:27:58.373]

active, I'm sorry, the traditional

[00:28:00.008]

passive approach, whereas we just

[00:28:01.843]

value a company based off of the

[00:28:03.244]

book. I can tell you

[00:28:05.180]

from my days of working alongside

[00:28:07.015]

various fundamental portfolio

[00:28:08.716]

managers, there are many industries

[00:28:10.585]

where price to book is literally the

[00:28:12.287]

worst way to value a company.

[00:28:14.522]

And so we don't do that.

[00:28:16.191]

And so the approach that we use here

[00:28:19.160]

in Canada and the U.S., we look at

[00:28:21.463]

price to tangible book because it's

[00:28:23.298]

a more conservative view of

[00:28:24.866]

valuation and does a

[00:28:26.701]

better job of assessing a margin of

[00:28:28.636]

safety based off of valuation.

[00:28:31.940]

Next, we look at price to free cash

[00:28:33.675]

flow. And so what I'll tell you

[00:28:34.809]

about that is if you can only do one

[00:28:36.578]

thing, that's the one to do because

[00:28:38.179]

cash is king.

[00:28:39.280]

And if a company is cheap versus the

[00:28:40.882]

cash flow that it's bringing in,

[00:28:42.617]

that is the best expression of

[00:28:44.686]

valuation.

[00:28:46.120]

And then the next two will be priced

[00:28:48.122]

to the next 12-month earnings with

[00:28:49.791]

the idea that you want to have some

[00:28:51.092]

valuation that incorporates the

[00:28:52.861]

future fundamentals of a company.

[00:28:56.197]

And I'm

[00:28:59.234]

going to

[00:29:01.469]

is that the price of cash, free cash

[00:29:03.171]

flow, price of tangible book,

[00:29:05.073]

EV to EBITDA, which is

[00:29:07.308]

another expression of valuation,

[00:29:09.277]

but is expressed from the statement,

[00:29:12.413]

from the income statement versus the

[00:29:14.849]

other variables that I mentioned

[00:29:16.417]

that are expressions of valuation

[00:29:17.986]

but from other financial statements.

[00:29:20.488]

That's interesting. There's so much

[00:29:21.789]

detail that go into, you know,

[00:29:23.424]

making those factors.

[00:29:25.293]

So congratulations for you and your

[00:29:26.527]

team. I mean, those products are

[00:29:27.795]

very successful and I believe that

[00:29:29.630]

we are at time.

[00:29:30.565]

So thank you, Bobby, for your time.

[00:29:32.133]

And to advisors who tuned in, thank

[00:29:34.202]

you for joining us this week on

[00:29:35.470]

Fidelity Connect.

[00:29:38.439]

the Fidelity Connects podcast.

[00:29:40.641]

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[00:30:13.307]

The views and opinions expressed on

[00:30:14.942]

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[00:30:46.841]

Thanks again. We'll see you next

[00:30:48.376]

time.