Driving alpha through dividends

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Subtitles are AI Generated

 

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Hello and welcome to Fidelity Connects, I'm Pamela Ritchie.

 

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Some of the major AI hyperscalers we've seen have been experiencing free

 

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cash flow decline as cap-back spending soars against a

 

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widening revenue gap. Of course, this is the AI story.

 

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And the surge in US treasury yields also has reduced market value

 

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for existing fixed rate bonds and caused broader ripple effects across

 

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commodities and credit markets.

 

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So can investors find stability in this period of market turbulence.

 

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Our guest here joining us today is known for swimming against the tide

 

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of glamour stocks.

 

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Instead she finds opportunities on attractively priced stocks in

 

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unexpected places. Joining us here today to discuss is portfolio

 

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manager Ramona Persaud. She's joining us from Boston.

 

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Hi, welcome Ramona. Nice to see you.

 

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Nice to see you too, Pamela. Thank you.

 

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Delighted to have you join us.

 

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There's a great article by, about you in the Globe and Mail over the weekend.

 

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I don't know if anyone else caught it, but I thought it was fabulous.

 

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Thank you.

 

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Let's dig into some of the things they talked about there and some others.

 

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Why don't we address the discussion of what rates

 

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and the story and direction of rates within the markets has

 

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been doing for a little while.

 

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But I wouldn't mind just getting your broad comments as someone who invests

 

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in stocks that are not necessarily all of the

 

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free flyers, but can be rate sensitive.

 

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What's your call on this rate story right now?

 

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Yes, thank you. That was a really good opening.

 

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All on the rate story. So we've been in a really narrow market, especially

 

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like narrowing even more in the last, certainly at the beginning of this

 

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year, say the last six months.

 

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And at the same time, we've got geopolitical issues that are keeping

 

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rates high, which is really impacting the U.S.

 

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Consumer. And that's almost almost a kind of fuel

 

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for the more hyper growth parts of the market, because if you can grow

 

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through ordinary challenges to the end consumer, you're going to get valued

 

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even more by the market. So that's a really interesting setup.

 

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It's made US affordability or certainly global affordability

 

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at the consumer level even more challenged.

 

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So, where that puts us is...

 

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Pretty interesting opportunities in the more cyclical ends of the market.

 

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So call it consumer discretionary, if you will.

 

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And also really interesting opportunities and the more stable ends

 

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of the market, because what the only thing that's worked is anything

 

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adjacent to hypergrowth.

 

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So I find that to be a pretty, a

 

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pretty fertile hunting ground, if you well, for just

 

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stock picking, even inside of my more conservative

 

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stealthy type strategies.

 

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Well, let's go into your conservative, stealthy type strategy.

 

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This is exactly the way you invest, which is discussed in the article.

 

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And I think a lot of people joining here know.

 

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But you're taking a look very much at the total return dividend strategy,

 

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the income of how that can ultimately be incorporated.

 

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And they're also known for helping us through downside moments in

 

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markets, making sure the protection is there.

 

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Just take us through sort of how you look at markets that are

 

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kind of off the charts in a lot of ways and how your process

 

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is taking you through that.

 

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Totally. So it's been such an interesting market because rightfully

 

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the market loves earnings growth and it has been like a

 

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beautifully growing earnings growth type market setup.

 

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And that earnings growth has been fueled by all the things that market

 

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participants love. So revenue growth we love and that

 

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generally, and then we love some good operating leverage.

 

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So you've had both revenue growth and operating leverage just boosting earnings

 

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growth. Everybody loves that.

 

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That has disproportionately come from AI or anything AI adjacent.

 

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And certainly in the last six months, it's been supply shortages

 

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against really strong AI driven demand in memory stocks.

 

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So very narrow market, very earnings growth driven.

 

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And when you measure it statistically, This level of

 

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earnings growth in the market if you look if your look-back period is

 

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75 to 100 years, this is 10th to 20th percentile

 

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level of earnings growth.

 

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Sorry, how many years back?

 

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75 to a 100 years. So depending on how you look at it.

 

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So call it like a lot of years, like almost a century back.

 

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So we have not had this kind of earnings

 

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growth.

 

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9080 to 90% of the time.

 

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Now, here's the thing, you can interpret that very differently.

 

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If you're like If you're like a really optimistic, more of

 

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what we call a momentum-oriented investor, like that feels amazing because

 

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that's so exceptional.

 

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But if you're more like conservative,

 

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cautious, downside-oriented as I am, that

 

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just feels really scary.

 

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So it depends on who you ask, like whether that's an interesting statistic.

 

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Statistically as like a math-loving person.

 

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Statistically, the odds of that continuing are

 

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very low. So with that set up, and

 

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I give full credit to the market rewarding earnings growth as driven by

 

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revenues and operating leverage, but when you get to this level statistically,

 

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you can maybe argue that that's extreme.

 

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So some part of the market would say that's extremely, some part the market

 

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might even use the word exuberance.

 

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Um, so we're kind of in, you know, we're in like, there are lots of ways to

 

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argue for exuberance. And what I want to say very clearly is,

 

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um, exuberant doesn't mean that the underlying innovation, so it's usually

 

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innovation that drives like intense exuberants.

 

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Exuberance doesn't mean that underlying innovation is not real.

 

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But what we've seen time and time again, over certainly

 

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those hundred years that I've talked about, is you can have really significant

 

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and accelerating innovation.

 

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But often inside of this like tight complex

 

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system that's called a marketplace, you can easily

 

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outrun that in terms of exuberance.

 

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You can get ahead of yourself relative to the underlying pace of innovation.

 

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And it's very hard to measure, of course.

 

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It's hard to say if we're there. But when I look at sort of stats like this,

 

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what it causes me to think about is.

 

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Um every single time that you have exuberance

 

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fade in a setup like this what kinds of

 

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positioning will benefit you so i think of that as antique the word i've

 

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been using for that is anti-correlation what does anti- correlation

 

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look like for periods when exuberant fades even though the underlying

 

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innovation is perfectly legitimate those are those are the ways i'm about this

 

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market. So we even wrote We wrote a white paper on this idea

 

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of, I think we might have called it anti-correlation in the era of AI.

 

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At least that's how I envisioned the paper that we wrote.

 

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So we go through what I've just said here.

 

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So, to an extent, when AI

 

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becomes to the point where it's in everything,

 

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how do you make sure you can have an anti-correlation to that?

 

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Because it becomes almost a challenge, doesn't it?

 

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That's exactly right, really insightful question.

 

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And so exactly, what we essentially say and what we

 

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believe to be true today is that AI is now just not limited to

 

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the obvious players.

 

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Because it requires an infrastructure build out, it's sort of everywhere.

 

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So it's in utilities, it's certainly all over industrials.

 

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It's in financials, it's certainly in the alternative

 

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credit space and a lot of this capex,

 

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not a lot. At the margin, capex is getting funded by

 

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debt, so it's in financial, it is everywhere.

 

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So when it's so pervasive, what do you do, how do you get anti-correlation,

 

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and thankfully correlation is actually a quantitative term, so you can measure

 

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it. So, for instance, if you look at

 

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the stability part of the market, so call

 

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that the lowest beta parts of the markets, staples,

 

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some utilities, healthcare, the correlation

 

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of essentially the highest 20

 

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to 40% of stability, so you can sort of fractile it and

 

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get quintile, so the highest 20 to 40% of stability.

 

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If you correlate that to AI, so a basket of AI stocks, it's

 

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at trough levels. So it's that negative 60 to negative 80% correlation.

 

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So that's like, and if you chart that over time, it sort of like dramatic.

 

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So that, that's quite meaningful, especially relative to that other statistic

 

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I gave you of 10th to 20th percentile.

 

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So all of these things kind of argue for exuberance and then it can argue

 

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for anti-correlation positioning in those sectors, in healthcare,

 

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in staples, in boring stuff.

 

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In boring stuff that we need, regardless of whether there's been

 

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sort of updates. I mean, when you take a look at something like,

 

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so it will take financials, but it could, it could work anywhere where there

 

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are so many other areas where growth is happening that presumably

 

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the risk can be absorbed. The AI risk within each sector

 

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company can be offset with lots of other

 

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things that are going well and causing growth.

 

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Is that, just take us through that anti-correlation piece.

 

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So financials have some anti-correlation.

 

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I mean, of course, since the capex is at the

 

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margin funded by credit, by debt,

 

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financials are going to have more risk when

 

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we get into any kind of credit stress or distress.

 

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Marginally, alternative forms of credit have been

 

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growing faster than the traditional banking system.

 

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So on a relative basis, in credit distress, it'll

 

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probably show up more in alternative credit.

 

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But look, it'll be everywhere. So you have to be careful about financials.

 

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Right now, however, given that we've got this high level, high and persistent

 

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level of inflation across the world from things like tariffs and

 

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geopolitical tension that's causing oil prices and that's filtering through to

 

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interest rates.

 

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What that means for obviously rate-sensitive financials is they

 

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are in a very good position to generate pretty

 

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strong cash flow from interest rates as long as you can keep credit

 

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at bay. So that's always the really difficult tension with financials.

 

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And in particular, European banks have

 

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this, they have this mismatched.

 

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Depending on what part of Europe, but a lot of European banks have this

 

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mismatched, what we call asset and liability match, so they really

 

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benefit when rates go up.

 

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So they are juiced to higher rates.

 

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So that's, you know, there's some anti-correlation in that versus

 

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AI because the drivers of that are not the same drivers

 

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of the AI build out.

 

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So within the strategies that you manage, the dividend

 

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part is a huge piece, some right in the fund name

 

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and some more in sort of a total return discussion.

 

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But the idea of getting dividends, getting cash income

 

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coming in, in a moment where if there's a risk that

 

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things deteriorate in markets, you always talk about

 

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that as being a cushion. This is just a new situation in markets perhaps for

 

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that also to be a cushion?

 

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Yeah. So a couple of things.

 

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If we can like entertain the idea of there being some exuberance

 

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in the market. And another example of that, I will tell you,

 

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is inside of the value in this, the big value index in

 

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the US, tech has gone from eight, nine percent to

 

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about 20 percent. So there are like all these ways to measure exuberant

 

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and A lot of that increase is

 

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AI-related, so there are no dividends in that.

 

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You're not going to take whatever free cash flow that you're generating, you're

 

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going to deploy that completely to the innovation as you should,

 

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to the extent you can get a return on it.

 

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So, because there are no dividends.

 

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Inside of that, you know, tech more than doubling in the index,

 

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the dividend availability in value indices is down.

 

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That also means that the valuation of the dividend stocks.

 

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Yeah, exactly. And it all kind of like mathematically makes sense.

 

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Because because of what's happened constitutionally to the index.

 

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So that's like pretty cool. I'm now at about two standard deviations.

 

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Cheap dividend yield inside of say the Russell 3000

 

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value. So and of course that comes back to the anti-correlation that I talked

 

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about. So staples and

 

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health care and parts of discretionary and certainly financials

 

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all these places where you can get pretty good dividend yield.

 

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So that's been really good hunting ground in certainly this year.

 

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So to take a departure to some of the other maybe

 

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glamorous stocks, I love that you're non-glamour and you're just such a

 

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glamorous person, but in any case, it's a great term for these stocks.

 

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Life is full of contrast.

 

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Yes, it is, isn't it?

 

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And we're richer for them in many cases.

 

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So tell us a bit about, you know, for instance,

 

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hyperscalers have gone a bit sideways for quite a long time.

 

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I mean, their valuations have come down.

 

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It's allowed rotations within the market.

 

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It has been exciting for other parts of the market because of that.

 

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What is it presented to you in terms of opportunities?

 

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Right. So it kind of moves around.

 

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You get these like, inside of this big AI innovation

 

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theme, it's there's this oscillation or I've almost thought of it like

 

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an accordion. So it kinda comes and goes or like a wave.

 

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And there are different parts of the theme that ride the wave at different

 

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times. So in the last six months has been memory stocks.

 

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The market has some concerns about the biggest cash, the biggest

 

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CapEx spenders.

 

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Particularly since we've seen the second derivative of free cash flow kind of

 

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go negative, right? So free cash flows declining at an accelerating rate

 

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Which is why they're tapping dead markets in a lot of cases, but yeah, it's

 

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interesting.

 

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Right. You've got to finance it somehow.

 

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So and one of the things that I always look at in sectors

 

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that are capital intensive.

 

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So we talked about this several years ago in energy, for instance, when CapEx

 

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to sales just starts to really peak.

 

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So in capital intensive sectors, when CapEX to sales is on the decline,

 

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that means typically as long as structurally, you know, you're not a broken

 

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business, typically you're starting to really accelerate your free cash flow.

 

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Which is great for stocks usually.

 

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In this case, in AI and AI-adjacent tech,

 

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CapEx sales is like off the charts peak.

 

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It's very peaky. So it's more peak than the late 1990s

 

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when we were investing for the internet. And the internet like is a real, it

 

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was a real thing. It continued. It's great.

 

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We still all benefit from it, but it got like really exuberant back then.

 

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So it back to like the 1960s level of CapEx to sales.

 

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And there's probably some variation around that depending on how you measure

 

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it, but it's pretty high.

 

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So that means you've got a problem with free cashflow.

 

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And so what you have to believe is that addressable markets

 

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for this innovation will keep deepening.

 

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So the existing addressable market can just go further and you can come up with

 

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new addressable markets.

 

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Those two things are probably true, but when you get kind of

 

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this level of exuberance, it's really about pacing.

 

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Can that happen as quickly as the market expects?

 

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And in fact, in every single sort of like...

 

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Accelerating innovation that is subject to exuberance, this is what you

 

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always have to believe. You always have believe that addressable markets can

 

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deepen and expand really fast because what you need is the revenue from

 

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that to overpower the cap expense.

 

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I kind of think that's the question the market's grappling with.

 

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For me, as a stability investor, I'm just like I have a

 

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lot of valuation just on my side while we wait for that question to be

 

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answered.

 

16:57.049 --> 17:01.820

When you speak to company leaders, which you at Fidelity often do,

 

17:01.820 --> 17:07.926

what is, I'm sure you put a version of that question to them.

 

17:07.926 --> 17:09.595

Do you get any direct answers?

 

17:09.595 --> 17:12.698

Are there a lot of, they also kind of need to wait and see.

 

17:12.698 --> 17:16.368

I mean, I think everyone is a little bit in a holding pattern there.

 

17:16.368 --> 17:19.338

I'm going to say something maybe controversial on average.

 

17:19.338 --> 17:22.174

So I think very statistically, as you can tell, like I don't really have

 

17:22.174 --> 17:26.245

absolutes. I think in terms of like continuums and odds along a

 

17:26.245 --> 17:30.282

continuum. So on average, company

 

17:30.282 --> 17:34.253

managements on average are pretty optimistic, and I

 

17:34.253 --> 17:36.088

think they have to be.

 

17:36.088 --> 17:39.525

You can't really get to the point where you're running a company, I think,

 

17:39.525 --> 17:43.829

without a certain amount of optimism, because you have to able to dream,

 

17:43.829 --> 17:46.432

but you need to to execute against the dream as well.

 

17:46.432 --> 17:51.070

So on average they're optimistic and on average, they will

 

17:51.070 --> 17:55.274

tend to communicate in a more optimistic

 

17:55.274 --> 17:59.278

manner. Now, over time, what I

 

17:59.278 --> 18:03.382

found is the really exceptional, so not average, but like highly above average,

 

18:03.382 --> 18:07.686

so you can, you know, but statistically like standard deviations higher

 

18:07.686 --> 18:11.924

type management teams, they can speak to their level

 

18:11.924 --> 18:16.095

of optimism while also grounding

 

18:16.095 --> 18:19.231

it in like in realistic risks.

 

18:19.231 --> 18:22.501

Those are those are the great conversations.

 

18:22.501 --> 18:27.172

So on average, the whole economy is really excited about AI and

 

18:27.172 --> 18:31.009

the incremental sort of or the average not incremental the average company that

 

18:31.009 --> 18:35.481

you talk to is really exciting to tell you about all

 

18:35.481 --> 18:39.318

the ways that AI is not going to kill their business and in fact what they're

 

18:39.318 --> 18:43.288

doing to get to get as adjacent to the AI value

 

18:43.288 --> 18:45.757

chain as they can.

 

18:45.757 --> 18:50.496

So when I hear this, actually I start to get a little bit nervous because

 

18:50.496 --> 18:55.868

it doesn't introduce enough realism about

 

18:55.868 --> 19:00.105

risks from the innovation to their business or

 

19:00.105 --> 19:04.243

about pace, the pace of innovation

 

19:04.243 --> 19:06.612

taking hold in their business. And I actually accept that.

 

19:06.612 --> 19:10.516

I've covered enough boom busty type businesses to understand that this is

 

19:10.516 --> 19:12.918

actually very human and normal.

 

19:12.918 --> 19:16.889

But when you just to go back to the idea of being sort of at

 

19:16.889 --> 19:21.827

peak and looking things looking a little bit peak-ish.

 

19:21.827 --> 19:25.898

Depends on who you ask. Depend on who you ask, but how do

 

19:25.898 --> 19:29.001

you deal with it or what do you look for in that moment?

 

19:29.001 --> 19:32.504

I guess what else do you Look for, for instance, is it is it a good

 

19:32.504 --> 19:34.740

opportunity?

 

19:34.740 --> 19:38.844

I think listening to each company talk about, and this is true in

 

19:38.844 --> 19:42.181

general, but certainly true now because we're in a hugely capital-intensive

 

19:42.181 --> 19:46.585

capital spending cycle, listening to companies talk about what

 

19:46.585 --> 19:50.556

they want to spend money on and the potential

 

19:50.556 --> 19:54.126

return on investment of that and how solid.

 

19:54.126 --> 19:58.096

How robust that thinking sounds relative to the

 

19:58.096 --> 20:01.500

free cash flow that they can generate and then their uses of free cash.

 

20:01.500 --> 20:04.336

That's what I'm always looking for. And that's certainly what I am looking for

 

20:04.336 --> 20:07.272

when I'm listening to companies talk about trying to get more and more adjacent

 

20:07.272 --> 20:09.141

to AI.

 

20:09.141 --> 20:14.446

There can be kind of like a desperation in this.

 

20:14.446 --> 20:18.717

There's a momentum psychology that takes over, because we're

 

20:18.717 --> 20:22.721

all kind of human, in terms of I cannot This is

 

20:22.721 --> 20:24.523

me speaking from the perspective of company.

 

20:24.523 --> 20:27.125

I cannot be late to this. I have to. It's like a trend, right?

 

20:27.125 --> 20:28.860

It's anything. It's fashion.

 

20:28.860 --> 20:31.463

I have be on trend.

 

20:31.463 --> 20:35.400

And when I perceive that kind of desperation, I start

 

20:35.400 --> 20:38.804

thinking really carefully about return about free cash flow.

 

20:38.804 --> 20:42.708

And if it just doesn't sound solid enough, robust enough, I get nervous.

 

20:42.708 --> 20:46.078

So it's hard to put that into like quantifiable terms.

 

20:46.078 --> 20:48.180

It's very gut.

 

20:48.180 --> 20:52.184

And here's the thing. In my world, the companies I invest in.

 

20:52.184 --> 20:56.288

Um they are not really often trying to be

 

20:56.288 --> 21:00.926

on trend they're the opposite of that so i'll give you some examples like

 

21:00.926 --> 21:04.830

um i'm looking for a lot of turnarounds because we're in a we're in a kind of

 

21:04.830 --> 21:07.966

precarious type marketplace we have a lotof exogenous risks we've got

 

21:07.966 --> 21:10.836

geopolitics is one of the biggest ones right now tariffs have been a huge

 

21:10.836 --> 21:14.906

exogenous risk now we've got like you know this this uh need

 

21:14.906 --> 21:19.444

to this on average people feeling this need to spend to not

 

21:19.444 --> 21:21.880

get left behind on AI.

 

21:21.880 --> 21:26.285

So I like companies that have so much that's wrong that

 

21:26.285 --> 21:29.488

they just need to like get back on track for the stock to work.

 

21:29.488 --> 21:33.892

They don't need to really be at the mercy of either one of these two things.

 

21:33.892 --> 21:38.096

Target is a good example of that. They have mis-executed

 

21:38.096 --> 21:42.167

so much at now like a sort of 13 to 15 times, somewhere

 

21:42.167 --> 21:44.002

in the teens, like a mid-teens multiple.

 

21:44.002 --> 21:47.306

They just have to figure out their execution at a good enough level.

 

21:47.306 --> 21:49.841

So I'm looking for like good enough.

 

21:49.841 --> 21:53.278

And good enough is often coming with pretty good valuations.

 

21:53.278 --> 21:57.049

Lowe's is similar. Lowe is at the mercy of a really weak housing market because

 

21:57.049 --> 22:01.486

of affordability. Is so poor in certainly in the u.s

 

22:01.486 --> 22:05.023

So Lowe's just has to like kind of take a little bit of share here and there

 

22:05.023 --> 22:08.994

which they can keep executing here And they're against a challenge

 

22:08.994 --> 22:13.198

backdrop which they because they are One of the winners in

 

22:13.198 --> 22:16.234

their space at like a 15 times valuation.

 

22:16.234 --> 22:20.339

That's a beautiful setup Metro the food retailer in

 

22:20.339 --> 22:23.408

Canada in Quebec They've had some execution challenges.

 

22:23.408 --> 22:26.011

They've got like labour challenges. They're also the mid teens multiple.

 

22:26.011 --> 22:29.348

They just have to like get to the other side of that.

 

22:29.348 --> 22:32.317

So you did a great really nice setup you did.

 

22:32.317 --> 22:36.355

A great shout-out for actually Quebec companies in in the article

 

22:36.355 --> 22:40.459

Yeah, and I mean they fit your style of investing quite

 

22:40.459 --> 22:42.994

well. I mean that that's one example of them Not all of them.

 

22:42.994 --> 22:47.032

Yeah, no, no But it was certainly part of the

 

22:47.032 --> 22:48.266

Canadian perspective

 

22:48.266 --> 22:50.602

Yeah, I mean CouchTard is another one.

 

22:50.602 --> 22:52.504

Couchtard is at a mid-teens multiple right now.

 

22:52.504 --> 22:56.041

You've got high oil prices, you've got an acquisition, there are all these like

 

22:56.041 --> 22:59.978

little sort of somewhat transitory things and the

 

22:59.978 --> 23:04.182

market, when the market gets so, I want to say fixated

 

23:04.182 --> 23:08.286

on one thing, which in this case has been everything AI, the rest of the

 

23:08.286 --> 23:12.424

market especially when you've got any kind of like, you

 

23:12.424 --> 23:17.062

know, any kind of wiggle that's negative, it gets, it gets de-weighted faster.

 

23:17.062 --> 23:20.999

At a sort of more accelerated pace and if you know the companies and you

 

23:20.999 --> 23:24.369

know what valuation you're waiting for it's it's a really nice setup.

 

23:24.369 --> 23:28.607

So I have all kinds of companies across the marketplace that's at like a 13

 

23:28.607 --> 23:32.677

to 15 times multiple 13 to like 17 let's call it.

 

23:32.677 --> 23:36.815

That's incredible for big high quality

 

23:36.815 --> 23:39.418

companies that are working through challenges.

 

23:39.418 --> 23:41.920

In North America?

 

23:41.920 --> 23:43.789

Across the world. Across the World. OK.

 

23:43.789 --> 23:47.626

Because in some places, that's a more reasonable valuation.

 

23:47.626 --> 23:50.862

Just let's go to some of the details of what you manage.

 

23:50.862 --> 23:53.832

You're very much a global manager.

 

23:53.832 --> 23:56.768

Tell us a little bit about the regional story right now.

 

23:56.768 --> 23:59.771

Diversification into the rest of the world has been a big theme over the course

 

23:59.771 --> 24:04.142

of the last couple of years, really. You've always been there, but what

 

24:04.142 --> 24:08.246

do you make of the importance of being sort of regionally diversified

 

24:08.246 --> 24:12.017

now as opposed to, I don't know, any other time?

 

24:12.017 --> 24:16.221

I love global investing, period, because it's the entire world

 

24:16.221 --> 24:20.292

and there's enough organic anti-correlation the

 

24:20.292 --> 24:22.227

bigger your universe gets, right?

 

24:22.227 --> 24:25.697

Makes sense? It's like a portfolio, the bigger the portfolios, I mean within

 

24:25.697 --> 24:27.566

limits, you get diversification benefits.

 

24:27.566 --> 24:31.937

So especially in this sort of more.

 

24:31.937 --> 24:36.041

Populist driven world where you don't have perhaps as much

 

24:36.041 --> 24:40.545

of a push for globalisation. So you just get like disconnects

 

24:40.545 --> 24:45.383

in various parts of the world, which means that you get you

 

24:45.383 --> 24:47.385

get more alpha.

 

24:47.385 --> 24:51.323

So for instance, this European banks thing where they have I

 

24:51.323 --> 24:54.359

mean, it's not a very high quality thing to do where they they have

 

24:54.359 --> 24:57.062

intentionally like sort of taken this asset liability mismatch.

 

24:57.062 --> 25:02.300

That's actually pretty good for them versus, say, the US banks.

 

25:02.300 --> 25:06.304

In there's some consumer discretionary turnarounds in

 

25:06.304 --> 25:08.974

Europe, like Adidas is a turn around, Burberry is a turnaround.

 

25:08.974 --> 25:13.678

So there's an interesting like stock specific names.

 

25:13.678 --> 25:17.649

Compass is a caterer in London that does catering all

 

25:17.649 --> 25:20.318

over the world. Really high quality business, sometimes it gets dislocated.

 

25:20.318 --> 25:23.588

So I can find pockets of opportunities.

 

25:23.588 --> 25:27.592

In lots of different parts of the world if I look closely enough and having

 

25:27.592 --> 25:31.563

now done it maybe like 20 years there's just there's

 

25:31.563 --> 25:32.964

there's so much.

 

25:32.964 --> 25:38.003

Okay. And that represents, you know, a way to make sure in

 

25:38.003 --> 25:41.940

the inevitability of some market movements around

 

25:41.940 --> 25:45.944

this AI story, you just are able to provide

 

25:45.944 --> 25:49.247

the ballast. I mean, I think that's sort of what everyone needs to kind of hear

 

25:49.247 --> 25:53.218

from your style, that if they're invested in lots of

 

25:53.218 --> 25:57.822

growthy type names, what this provides.

 

25:57.822 --> 26:01.560

Which is, I'm using the word anti-correlation, which is kind of a strong term,

 

26:01.560 --> 26:03.228

but it's really diversification.

 

26:03.228 --> 26:07.365

So if there's, it's diversification,

 

26:07.365 --> 26:11.903

especially against high momentum, narrow markets that

 

26:11.903 --> 26:15.307

are prone to becoming exuberant.

 

26:15.307 --> 26:17.842

And I really like to do it in a smooth way.

 

26:17.842 --> 26:21.646

So it's the diversification with a smoothness to the ride because it's that

 

26:21.646 --> 26:26.084

smoothness that is the primary determinant of investor trust.

 

26:26.084 --> 26:30.288

And so when you do get the inevitable shaking of that exuberance,

 

26:30.288 --> 26:34.459

trust gets shaken. And if you've already earned trust, people stay on.

 

26:34.459 --> 26:38.396

And so they then are able to capture more of the

 

26:38.396 --> 26:41.900

full return of the fund that you are investing for them.

 

26:41.900 --> 26:46.371

There's a great question coming in that you've

 

26:46.371 --> 26:48.073

touched on earlier, but I'll put this to you.

 

26:48.073 --> 26:52.143

Are you thinking about how companies integrate AI when you analyse how they

 

26:52.143 --> 26:56.214

fit into your allocation strategy and sort of, yeah, how they're putting it

 

26:56.214 --> 26:58.350

to work?

 

26:58.350 --> 27:03.088

Absolutely. I mean, there will be, there is and there will be a

 

27:03.088 --> 27:04.889

lot of dislocation in companies.

 

27:04.889 --> 27:08.827

If you look at operating costs,

 

27:08.827 --> 27:13.765

so what we call SG&A, selling general and administrative costs,

 

27:13.765 --> 27:16.801

which is different from, say, raw materials.

 

27:16.801 --> 27:19.337

So this is kind of the cost to operate your business.

 

27:19.337 --> 27:23.508

As a percentage of sales, that has been on a structural decline,

 

27:23.508 --> 27:27.679

which has been globalisation driven, but that decline has accelerated.

 

27:27.679 --> 27:32.050

And I think that is the argument is that is

 

27:32.050 --> 27:36.154

one impact of AI, because you can just get so much more productivity

 

27:36.154 --> 27:40.325

and efficiency in your operations.

 

27:40.325 --> 27:44.562

But this is tricky for employment, and it's tricky for

 

27:44.562 --> 27:47.332

various parts of the value chain across the economy.

 

27:47.332 --> 27:51.036

So it remains to kind of like shake out how this will look.

 

27:51.036 --> 27:54.606

So when we do meet with companies, we are listening carefully.

 

27:54.606 --> 27:58.576

For how they are using AI both productively, but also how it's

 

27:58.576 --> 28:02.714

challenging them. Frankly, however, I think it's very early

 

28:02.714 --> 28:06.651

to say. So what I'm always looking for is because the market

 

28:06.651 --> 28:09.888

is a relative organism.

 

28:09.888 --> 28:13.124

It's a continuum. So it's one part of the continuum versus the other and how

 

28:13.124 --> 28:14.726

the continuum is moving.

 

28:14.726 --> 28:15.293

It's a dance.

 

28:15.293 --> 28:18.830

I look for, it's a dance is another way to put it.

 

28:18.830 --> 28:23.468

It's a choreography. I look

 

28:23.468 --> 28:25.236

very simply relative valuation.

 

28:25.236 --> 28:29.407

So what I'm referring to today is the relative valuation of

 

28:29.407 --> 28:32.977

stability or we can call it anti-correlation or we call it diversification

 

28:32.977 --> 28:37.649

versus the glamour. And that relative valuation is very wide.

 

28:37.649 --> 28:41.820

If you chart it on a time series, it's beautiful, it's up here.

 

28:41.820 --> 28:44.355

It's probably at least one, if not two standard.

 

28:44.355 --> 28:47.692

I haven't z-scored it, but it's probably between one and two standard

 

28:47.692 --> 28:50.762

deviations. And that's when it gets really interesting.

 

28:50.762 --> 28:55.867

So to me, it's a good setup for continuing to buy really boring,

 

28:55.867 --> 28:59.804

high dividend paying companies

 

28:59.804 --> 29:04.542

that have a lot of scepticism in them or that have just been forgotten.

 

29:04.542 --> 29:07.145

Boring is beautiful.

 

29:07.145 --> 29:10.181

Yeah, I mean you need patience.

 

29:10.181 --> 29:14.252

It's unlikely it happens tomorrow, so you have to be able to wait, which is why

 

29:14.252 --> 29:18.623

an allocated portfolio really makes a lot of sense.

 

29:18.623 --> 29:23.828

You have various allocations to different types of strategies.

 

29:23.828 --> 29:27.198

If you had just one message that you'd like to leave with investors over the

 

29:27.198 --> 29:30.101

course of going into the end of this year, which has been kind of a wild year

 

29:30.101 --> 29:34.906

and there are midterms in there, but just as sort of an investment message,

 

29:34.906 --> 29:35.840

what would you say?

 

29:35.840 --> 29:38.843

You know, my message is around trust.

 

29:38.843 --> 29:42.881

I've been trying to, I've always had this belief about investor trust, but

 

29:42.881 --> 29:45.583

I've been trying be more explicit about it.

 

29:45.583 --> 29:49.988

The reason I care so much, I have so much risk sensitivity is because

 

29:49.988 --> 29:54.325

when, it's like riding in a car, if you will,

 

29:54.325 --> 29:58.429

when the road gets really choppy, if I have earned your

 

29:58.429 --> 30:02.467

trust to navigate that road, in such a

 

30:02.467 --> 30:05.403

way that I give you a little bit more smoothness than if I have not earned your

 

30:05.403 --> 30:09.374

trust, you will stay in the vehicle with me through the choppiness and

 

30:09.374 --> 30:12.644

to the other side where it gets smoother. And so my goal is to earn enough of

 

30:12.644 --> 30:15.046

your trust so that you stay with me.

 

30:15.046 --> 30:18.149

Because if you stay me, we realise like really good returns on the other as

 

30:18.149 --> 30:22.086

well. So smoothness of ride is really important

 

30:22.086 --> 30:25.990

to me because it's a big, it's to me the biggest determinant of trust and trust

 

30:25.990 --> 30:30.328

is how I get you the full return over a market cycle.

 

30:30.328 --> 30:34.399

Amazing. Ramona Persaud, thank you so much for joining us and sharing your

 

30:34.399 --> 30:38.369

wisdom and your thoughts on this fascinating market, but definitely

 

30:38.369 --> 30:40.271

needs your perspective to navigate it.

 

30:40.271 --> 30:43.174

Thanks for joining us. Thank you.

 

30:43.174 --> 30:45.243

Thanks for watching or listening to

 

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