December 10, 2025 • 32 mins
Earnings in 3Q beat expectations, but momentum is fading, suggesting a high earnings bar for 2026 and potentially more market volatility. In this episode of the Inside Active podcast, host David Cohne, mutual fund and active management analyst with Bloomberg Intelligence, and co-host Michael Casper, BI’s senior US equity strategist, speak with Justin White, portfolio manager of the T. Rowe Price All-Cap Opportunities Fund (PRWAX). They discuss White’s four-pillar investment process and how pattern recognition helps him identify durable growth or unrealistic expectations. They also explore what part of the market is overestimating long-term monopoly profits, where high valuations have become unattractive due to poor risk-reward and which areas could offer long-term outperformance through 2030. The podcast was recorded on Dec. 4.
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Speaker 1 (00:13):
Welcome to Inside Active, a podcast about active managers that
goes beyond soundbites and headlines and looks deeper into the processes, challenges,
and philosophies and security selection. I'm David Cone, I, lead
mutual fund and active research at Bloomberg Intelligence. Today, my
cost is Michael Casper, Senior US equity strategist at Bloomberg Intelligence. Mike,
thanks for joining me today.
Speaker 2 (00:34):
Thanks David.
Speaker 1 (00:36):
So this is actually our last episode of twenty twenty five,
and as we head into the year end and into
next year, I wanted to ask about a note you
put out earlier in the week. You know, basically on
what two three earnings are signaling for the market. Could
you give our audience kind of a brief overview of
what you're seeing.
Speaker 2 (00:55):
Yeah, so the third quarter was obviously a blowout quarter.
We doubled the preseason expectation for the S and P
five hundred, nearly doubled the preseason expectation for the Russell
two thousand revenue growth. And really what I'm seeing in
the earning stream is a lot of green signs, a
lot of green shoots. I think they're just a little
bit less bright than they were in the second quarter.
(01:17):
So what I'm talking about there is revision momentum, specifically
cyclical minus defensive earnings. We're hitting a peak on that,
but revision momentum also has peaked and is starting to
come down. What I mean by revision momentum is the
number of companies with hikes, number of companies with cuts
over the total number of companies that reported. And why
(01:40):
that's coming down a little bit is just, you know,
we had such dramatic cuts in the beginning of the
year as a result of Liberation Day and a result
of all the tariffs that were flowing through the system.
Consensus got it completely wrong for twenty twenty five kind
of yet again, they weren't necessarily great in twenty twenty
four either, but they got it completely wrong in twenty
(02:01):
twenty five and they really had to walk that back.
And much of that happened in the first and second
quarters as those results rolled in and they were better
than expected. Third quarter again better than expected, but it's
a little bit less robust than you know, a double
digit gain off a two percent expectation like we saw
in the second quarter, So that's a little bit less green.
Cyclical minus defensive earnings I mentioned before, we're hitting a
(02:24):
peak on that. Typically I look for that to peak
and wane to signal some volatility for the market. And
the earnings bar is very high going into twenty twenty six.
Whether we can hit that or not remains to be seen.
I will mention though that consensus has only overshot once
in the past four years, so quarters on the preseason
(02:46):
expectation for the S and P five hundred. So yeah,
the bar is a little bit high. Typically that means
a little bit more volatility, given you know, earnings are
already baked in, but that's yet to be seen in
twenty twenty six.
Speaker 1 (02:58):
Well, certainly be interesting to watch. Much Speaking of the markets,
I do want to introduce today's guest. Justin White, is
a portfolio manager of the US multicap growth equity strategy
at TROW Price, including the trow Price All Cap Opportunities
fund ticker PRWAX. Justin, thank you for joining us on
our last episode of the year.
Speaker 3 (03:18):
Thanks for having me.
Speaker 1 (03:20):
So let's start with your process. The four Pillars framework
is central to your process. How did this framework evolve
over time and do you ever feel like you have
to bend or adapt it? When the markets, you know, change.
Speaker 3 (03:33):
Sure, just to kind of get everybody on the same
page who might not be familiar with with my process.
Four pillars is the stock picking framework that drives my
decision making in the portfolio. And the way to think
about it is each pillar is an incremental reason for
a fundamental investor to want to own a stock. And
the idea is that if you can stack attractive attributes together,
(03:57):
you have a high probability of that stock up reforming
because there are lots of people who could be interested
in buying it for a lot of different logical reasons, right,
And so the four pillars I look for, but for
high quality businesses. Look for businesses that have potential for
positive estimate revisions. Businesses with fundamental acceleration and valuation is
(04:18):
the fourth pillar. So just how did I kind of
come up with this? So I joined TROW, you know,
seventeen years ago as a career switcher. Then didn't know
what I was doing, had to figure it out. So
I took that whole you know, Warren Buffett mental models
approach to heart, and the first year or two I
was in this in my seat as an analyst, I
just you know, tried to write down notes about lessons learned.
(04:42):
For example, in two thousand and nine, when a company
that was seeing negative revenue growth and the stock started working.
It kind of didn't understand why, but after talking to
other pms, they're like, oh, it's because revenue growth bottomed.
It went from negative twenty percent to negative sixteen percent
year over year. That's why it's working. Right. So anyway,
(05:03):
over two to three years, I collapsed to all these
mental models into the four pillars. I started using this
framework as an analyst in about the twenty eleven timeframe
and really haven't changed it at all during my tenure.
You know, each pillar has been approximately equal weighted, so
you know, save weight to quality and positive visions and
acceleration and valuation. The one thing I would mention is
(05:26):
that recently, as as market structure has changed, I've been
giving a little bit more weight to the quality pillar.
Speaker 1 (05:33):
Okay, so actually it was kind of goes right into
my next question is when you're looking at a company
using the four pillars. You know you mentioned it's you know,
equal weighted, but you know what happens when one looks
strong as you mentioned, you know, quality, you're really focusing
on when something else, like maybe valuation might not be
as strong. How do you balance that?
Speaker 3 (05:53):
Yeah, it's a good question. So the four pillars is
a body of evidence approach. Right, you look for stocks
that have enough pillars working for you strongly enough, and
not many pillars working against you. Right, You don't need
all four to be positive. So in fact, it's quite
rare to have all four working for you at the
(06:13):
same time. And when that happens, you make a big bet,
like in Nvidia end of twenty twenty two, like was
scored awesome on all four pillars, and kind of we
see what happened thereafter. But I'd say, like to kind
of answer the questions, you can get to four pillars,
get to yes in a number of different ways. Right. So,
if there's a really expensive stock like pal Andeer, where
(06:37):
the valuation is very difficult to justify, right, but it's
a super high quality business, high margin rapid growth estimates
have been coming up a lot, you know, the rate
of revenue growth they're seeing in dollar terms keeps accelerating.
You know, it's one where even though valuation is negative,
there's enough good stuff in other parts of the framework
(06:59):
that you can justify having a small overweight. You know,
you can also own lower quality stocks if they check
all the other boxes. Historically, financials don't sort to the
top of the pack in terms of business model quality.
I mean, some are better than others, right, But I've
been overweight banks and capital market stocks this year on
(07:20):
the view that the starting valuations were attractive. They're being deregulated,
which is going to be good for returns. Capital markets
activity was improving from a trough as a kind of
Trump cut a lot of red tape and allow more
activity to happen, and that basically is a set up
for higher returns and higher estimates. So I'd say that
(07:41):
it's a body of evidence approach, and it instills a
cell discipline as well, which is important to point out
because you know, when a stock checks a lot of
the boxes, I buy it, and when it doesn't check
a lot of the boxes, I sell it. This led
me to sell a lot of my tech exposure in
late twenty twenty one.
Speaker 1 (08:00):
Well, it makes sense. There's something else I wanted to
ask you about. Is you know I've read you describe
your research as pattern recognition, you know, basically looking at
how the world fits together and making sense of what's happening.
You kind of walk us through, you know, a recent
example of how how this you know, might have worked
for you and how that translated into an investment.
Speaker 3 (08:21):
Sure, so I'd begin by answering by saying that four
pillars is essentially how I describe my pattern recognition, right,
because it's a the each pillar kind of is a
reason for people who want to buy a stock, And
so that's kind of a pattern I observed over kind
of over time. But let me start with a historical
(08:41):
example to get to your question, and that a more
recent one, because the historical example I think is a
fun one. Right. So there's a company called Smile Direct Club,
which kind of you know, doesn't it's not not listed anymore,
and they had their IPO and it's basically an invisiline company,
you know, clear retainers. And the reason I passed on
(09:02):
the IPO was because I had studied Netflix's business model.
People like, what does Smile Direct Club have to do
with Netflix? Well, both their consumer products, but Netflix is
like easy to sign up, easy to cancel, the cost
is pretty low, the value is pretty high, Like it's
a low friction experience in contrast Smiled Rec Club. Right,
(09:25):
it's a considered purchase, high cost, high friction, Like you
have to go in the store, you have to keep
using the products you know reliably every day. So basically,
Smiled Rec Clubs the model had attributes that would argue
for a much shallower s curve of adoption than Netflix.
People just aren't going to penetrate the tam as quickly.
(09:46):
Yet when Smile Direct Club came public, they claim they'd
penetrate their market by ten points a year. Netflix, in
the sweet spot of its adoption curve only outed a
few percent of US households in any given year. Kind
of knew that SDC's numbers were unrealistic in I passed, right,
So that's that's one one way to get at it.
But more recently, I'd say, you know, Carvana is a
(10:08):
major bet in the fond. It's been a very positive contributor.
And the powder recognition here is that, you know, Carvana
is a business that a lot of people think is
you know, they're not sure how how high quality it
is or not. But when I look at it, I
see a business targeting a huge market with a first
mover advantage, with the material cost advantage very early in
(10:31):
the s curve. Right, they're one and a half percent
penetrated in their market, and powder recognition tells you that
when you have a company this kind of has a
really open ended runway and a competitive advantage that's going
to persist. You know, don't worry about the valuation, don't
worry about the quarterly estimates. The structural tailwinds are just
too strong and pursas for so long that valuation will
(10:52):
take care of itself. So so that's one that kind
of we've done it. We bought quite a quite a
bit earlier, and it's a it's it's been a performer
this year.
Speaker 1 (11:01):
Okay, great, And you know with your fund it's it's
an all cap, so you get a lot of flexibility
in what you can invest in. And so you've also
said before, you know, when I've looked at you know,
some of the things online, the il zigmore growth zagmar value,
you know, tilt up cap or down cap. How much
of that is tactical versus like long term in your view.
Speaker 3 (11:24):
It's a good question, and at the risk of sounding repetitive,
for one sentence, I make buy and sell decisions based
on the four pillars framework, and so when value stocks
score more strongly, I own more value stocks, right. I
think the spirit of the question is kind of getting
at what are my biases and as like, what kind
(11:44):
of investor am I know? Deep in my bones? And
I think the answer to that question is that I
have a growth bias.
Speaker 2 (11:52):
Uh.
Speaker 3 (11:53):
Most of the time my fund has had a growth
tilt versus the underlying benchmark. And the reason for that
is because one of my four pillars is the quality pillar,
and the highest quality stocks tend to outgrow the economy.
Lower quality stocks outgrow the economy less often. So value
(12:15):
stocks are often at a starting point at a disadvantage
because on average they score lower on one of the pillars.
You know, all else equal, I'd rather own Microsoft over
time than a brick and mortar retailer.
Speaker 2 (12:26):
Right.
Speaker 3 (12:26):
So I point out that in late twenty twenty one
and most of twenty twenty two I did not have
a growth tilt, and that is because growth stocks scored
really poorly then, especially tech stocks. The issue was that
we had peakish growth from the pandemic that was about
to decelerate. We had extremely high valuations, We had consensus
(12:48):
estimates that were not anticipating any deceleration and so looked
generally too high. And so you know, I went zero
eight Amazon went zero weight Meta With hindsight, this was
the right move. But the reason that I tiled down
the growth that and added to some value sector was
really because of the four pillars framework signaling that was
the right thing to do. Yeah, makes sense.
Speaker 1 (13:12):
And you know, one of the thing I know before
it might gets into some of the more market focused
topics is you know, you've also mentioned in your research
that you come across a lot of data and a
lot of it doesn't matter, and you're really focusing on
a couple of things. What are the one or you know,
maybe two data points state you think are really being
underappreciated by the market.
Speaker 3 (13:32):
Yeah, so when you say what's underappreciated by the market,
I do want to point out that that's a different
question than underappreciated by the media. So just because we
see headlines about AI bubble one week or it doesn't mean
the market's doing that or the prices reflect that they
believe that. So the market's generally brutally dispassionate and right
(13:55):
most of the time. But in terms of the prices,
we see out there.
Speaker 2 (13:59):
Now.
Speaker 3 (13:59):
I think they're are a couple things top of mind
that the market may be missing or getting wrong. I
don't know if I call these data points per se,
but but they're just a couple areas where I'm disagreeing
with the market. The first one is I think the
market is still too complacent about believing the depreciation schedules
for AI chips among the cloud platforms. Right. I personally
(14:22):
don't believe the GPUs have a six year useful life.
And if these companies are buying chips and advertising them
over six years but they only last four, then their
earnings quality is being overstated and returns are being overstated.
Oracle and core Weave are starting to snit this out
because they're kind of the tip of the spear, but personally,
(14:43):
I think there's still a ways to go. I mean,
if Oracles chips last four years instead of six, then
they're locking in a half trillion dollar backlog at value
destructive return levels, and that would be that would be
a problem if that's the case. One other thing I
kind of struggling to understand here is the markets enthusiasm
(15:03):
for the value potential of humanoid robots and autonomous driving.
And my hang up here is that, you know, like
Tesla has a market have of one and a half
trillion dollars, and the logic underlying it feels kind of lazy,
right as an industry structure issue. You know, suppose Tesla
(15:24):
figures out humanoid robots, do you think China is going
to figure it out too? Do you think China is
going to have a dozen manufacturers? Will they be selling
those robots below cost for a decade?
Speaker 2 (15:34):
Right?
Speaker 3 (15:34):
And autonomy it's not going to be winner take all.
There's a lot of Chinese options, There's Weamo, et cetera.
And so so I feel like this idea that you know,
one company is going to have monopoly type profits and
we are confident that that's going to be true for
decades to come, I'm a little bit unsure about that.
Speaker 2 (15:55):
Do market valuations in general, and maybe particularly for tech,
do they concern you at all in terms of your portfolio?
Speaker 3 (16:03):
The short answer is absolutely, the valuation concerns me because
it's always less comfortable when you have to invest with
a lower margin of safety. But personally, I think that
stocks tend to follow earnings and will continue to cooperate
as long as earnings cooperate. And you know, I think
(16:24):
you mentioned at the start of the of the podcast
there's been some broadening out of earnings across the market,
including in small caps. So so you know, just because
the valuation is uncomfortable doesn't make that a good timing tool.
It just means there's more negative asymmetry if we have
have a market hiccop. So one argument in support of
(16:44):
the higher multiples, by the way, is that the mix
of stocks in the markets has changed over time. It
has become higher quality. Right, the megacap businesses are very
high quality businesses, so some degree of premium is warranted
versus his. But the areas that make me really uncomfortable
are stocks where you kind of know approximately what the
(17:07):
earnings growth is going to be and you just have
to pay too much for it. Right, So seeing Walmart
pushing forty times earnings, like, there's a lot of good
stuff happening at Walmart. But now, even if they do
grow earnings that at a rate a little better than
the street expects, couldn't that not go sideways for three years?
You know? I also think some of the more commoditized
(17:28):
AI data center component stocks going parabolic because they're in shortage,
like cables that connect one server to another, and there's
not enough of them, and so stocks are up tenfold
in a year. You know, a lot of these stocks
are beating numbers, but they make no sense on a
DCF basis, and so when fundamentals peak, in turn, a
lot of these are going to be down eighty ninety
(17:48):
percent from the peak. So I say that there are
areas that make me more uncomfortable and some areas where
I feel like it's more okay. But on balance, valuations
are pretty.
Speaker 2 (18:01):
And it seems that tech and maybe more specifically AI
companies are transitioning from an asset light to a capital
intensive model with all of this infrastructure build out that's
kind of necessary to support that theme. Does that change
how you value companies at all or change your or
change your view on growth companies?
Speaker 3 (18:19):
Yes, this is a super important question. The rising capital
intensity of the hyperscalar platforms makes it harder to make
big bets in them than before. And here's how I
frame it. So in the past financial metrics that say meta,
they all trended the same way. Right when revenue was growing,
(18:39):
ebit was growing, free cashal was growing they all trended
in the same direction, and now there's this divergence, right,
and get a setup where you're like, Okay, suppose Meta's
next quarter, Suppose they beat on revenue by quite a
bit but miss on ebit because they're investing so heavily
in AI and guide to no free cash on in
twenty twenty six. How does the stock process that? It
(19:02):
depends what people want to focus on, and that's it's
just harder to know. So essentially the degree of difficulty
has gotten harder. Oracle has robust earnings growth, accelerating revenue growth,
and burns a ton of cash. And that cash burns amplifying.
Like if you look at a chart graphing oracles free
cash flow against its share price over the last three years,
(19:25):
it's like a mirror image. It's fascinating. Right, The more
cash they burn, the more the stock goes parabolic up.
So I'm not trying to pick on Meta and Oracle,
but the point is just it's getting harder to score
these stocks cleanly on four pillars because it's harder to
score each pillar. Right, is Oracle getting is it accelerating? Well?
Revenues are, but free cash flow is the wrong way.
(19:47):
Is meta cheap? Well, it's twenty times earnings, but one
hundred times free cash flow right, And it's only twenty
times earnings if you trust the DNA assumptions on their chips.
So overall, this dynamic is causing you to rotate capital
to other names and other pockets at the market where
the setup feels cleaner. Not that I'm running, you know,
rapidly away from the mag seven, but on balance, the
(20:09):
incremental dollar of capital is going elsewhere.
Speaker 2 (20:12):
I'm a macro guy at heart, and it seems rates
are coming down. You know, the White House is influencing
the FED a little bit and might install their preferred
FED chair in twenty twenty six in fact, and then
they may even come down even faster. Does that concern
you that there might be a lasting shift from growth
style to value style.
Speaker 3 (20:31):
Yeah, so, I personally wouldn't make the connection that lower
rates necessarily means you buy value and sell growth. I mean,
if you took your business school textbook out and thought
about the concept of duration, theoretically, duration will argue for
the opposite. Right, lower rates should be more of a
(20:52):
tailwind for growth stocks than value stocks because more of
their values terminal value, which was more sensitive to changes
of discount rate. We kind of saw this with profitless
tech in twenty twenty and early twenty twenty one. So
I think the answer to the question about, you know,
value versus growth really comes down to company specific fundamentals.
I mean, if you force me to abstract and generalize
(21:15):
that the times that you want to overweight value are
either when growth stocks look particularly dangerous like they did
in late twenty twenty one and early twenty two, or
the economy's early cycle and broadening out because value stocks
have a heavier cyclical component to them. I point out
that even though we've seen some breadth in earnings, which
(21:38):
is encouraging, it's unclear how much magnitude of improvement there's
going to be in twenty six. It doesn't feel like
you're starting at a very depressed level with an imminent
massive acceleration coming. So I think that the case for
value stocks is more favorable now than it has been.
But my portfolio is still growth tilted because on four pillars,
(22:01):
I'm getting more bisignals and the growth cohorts.
Speaker 2 (22:04):
And how about small versus large caps? Small caps obviously
been an underperformer for some time, but the valuations are
looking really attractive at seventeen year lows. I've noted a
couple of days ago. But do you see any opportunities
emerging in smaller capitalizations in twenty twenty six?
Speaker 3 (22:22):
So there's the kind of question about next year versus
like a structural question. So let me just start by
talking about like structurally, I'm pretty bearish on small caps
because we're in a world where the stronger are getting stronger,
and AI amplifies this. Small caps have grown revenues more
(22:42):
slowly than large caps over the last twenty plus years
on balance their lower quality. Over the last twenty years,
there are were two periods where small caps had meaningful
outperformance that sustained for a full year. Right that was
two thousand and nine, and it was coming out of COVID,
And if you think about those two periods, right nine
(23:03):
and steps of COVID, the setup was like a bloodbath
starting point stocks down huge Russell two thousand basically didn't
have earnings. So I don't feel like we're at a
starting point like that now. So I would argue against
a huge outperformance of small caps versus large caps next year.
That said, small cap earnings didn't grow over the last
(23:26):
three years, and growth has bottomed and recently started improving
as he mentioned, which is encouraging. Valuations are cheap on
a relative basis, but on an absolute basis, I think
they're not that cheap personally, and so in small cap land,
I'm still just really trying to make idiosyncratic bets rather
than trying to make a sector call. Now we've made
(23:47):
good money in biotechs like Insmed, which is no longer
a small cap, or aero copper because we're structurally bullish
on copper, always looking for ideas. But right now there
aren't a ton that jump off the page at me.
But they might not perform in twenty twenty six. I
just don't think it'll be shocked in awe if they do.
Speaker 1 (24:05):
So if we go into actual sectors or even themes,
are there any of that? You think the market's underestimating
any type of structural change, and you know or are there,
you know, any mistriced opportunities you're looking for?
Speaker 3 (24:21):
Yeah, So a couple things I think the market might
be underestimating. First is that as people focus so much
of their energy on the AI trade, the market is
starting to kind of ignore and just push to the
side a number of high quality open ended winners that
are pretty early in their s curves, and I see
(24:43):
some opportunities in kind of a number of those. I'll
just mention a couple quickly, like See Limited is the
Southeast Asian e comm gaming payments company, extremely well managed company.
You know on street numbers, it trains it sixteen times
free flow on twenty twenty seven. It's like a thirty
percent EBIT dot compounder, and the stocks lost a third
(25:05):
of its value because people are like nervous about a
very minor investment cycle for the next couple of quarters.
And I just see that and think, you know, if
you put that in a box for three years, and
it's like, I don't know, twelve times twenty twenty eight
free cash li like you're going to outperform the market,
like by a lot as long as the numbers come
in approximately how we think. Door Dash is another one
(25:26):
where it's probably sixteen times free cashlo on twenty twenty eight.
You know, in three years, you know, the multiples can
be a lot higher on that twenty twenty eight number.
So I feel like there's opportunity those types of stocks
that are just kind of not as not as front
and center as ASAI takes mind share. One other thing
I think the market's underestimating is the structural supply shortage
(25:49):
we have in copper.
Speaker 2 (25:51):
Right.
Speaker 3 (25:51):
So in my fund, I own Southern copper and Arrow copper.
And the insight here is that it's just getting harder
to get minds permitted, proof moved open in more parts
of the world right in emerging markets. It's a structural issue.
It's like a Nimby issue that's metastasized around the world.
And copper's required in so many things that has no substitutes.
(26:12):
It's rapid price in elastic. I think copper has the
potential be well above ten dollars a pound by the
end of the decade. So those are two that I'd
point to.
Speaker 2 (26:23):
We've already covered the public market bubble or air quote
bubble in depth pretty much, but does a possible private
credit equity private equity bubble concern you at all in
public markets?
Speaker 3 (26:40):
So I think that if there's carnage in private credit
at some point, that it will be largely a contained event.
It'll hit some of the alts, but it's not going
to really impact the overall economy in a big way,
it would be my view, because it's you know, it's
(27:01):
the you know you have you know, people have invested
in private equity funds and they might take a hickey
on some some some bad loans being written off, but
that's not like a bank losing capital and having to
you know, get help or get get bailed out. So
I think that they're the hiccups we've seen in private
credit uh well publicized issues in the last couple of months.
(27:25):
It feels like it's more one off than structural right now,
Like there's there's you know, there's some fraud uh and
and some bad behavior, but you know, overall, we don't
really have a have a reason to be that that
concerned about uh the activity. I mean, you know, high
yield bomb spreads have been quite well behaved this year.
(27:45):
They're still pretty tight equity markets at the highs. It
just feels like there were a couple of cockroaches. And
I hear Jamie Diamond when he says, when you see
you know one, then there's you know a lot more
of them. But I think that people are kind of
like looking for thus ignore that like this is the
top and I just don't feel like that's I'm not
kind of on board with that. And I think that
(28:06):
if there is a problem, it's not going to bring
down the economy with it. Like if the ai cat
X bubble unlines, that could bring down the economy, but
I don't think private credit souring would would would would fantastasize.
Speaker 1 (28:19):
So I got one more question for you. If we
look out a few years into the future, what are
a couple areas of the market that could you know,
meaningfully outperform or underperform through say twenty thirty And you
know what would be the secular forces that really underpin that.
Speaker 3 (28:38):
So so yeah, look, I like the question because it
does force you to take a longer term perspective. And
so if we're talking about, you know, themes through twenty
thirty and beyond, I just want to be clear by
saying I could be right over that timeframe, but look
terribly wrong for six or twelve months first, right, So
one one area I think could really underperform between now
(29:00):
twenty thirty is semiconductor sector, and for three reasons right.
One is just the risk that we have an overbuilding
ai CatEx that unwines I'm not trying to call the
top in AI CatEx, but I do think there's a
real risk that we're overbuilding capacity now and into twenty
twenty six, and this could become more obvious in twenty
seven and twenty eight. I also think industry structure in
(29:24):
many parts of the semiconductor complex is getting less favorable.
Speaker 1 (29:29):
Right.
Speaker 3 (29:29):
Analog semiconductors have more competition than China. GPU market structure
is still essentially just in Vidia today, but there's more
challenge coming from Google's TPU, from A and D, and
against this backdrop, you know, valuations are quite elevated, right.
It's like the socks is at twenty eight times forward
earnings if earnings grow twenty five percent next year, and
(29:51):
the historical average is seventeen times, So you know, it's
not like a near term call. Like it still looks
constructive in the near term, but I think over the
course of several years that it could be quite dangerous
in terms of areas that could outperform. I think that
the market's ignoring a number of high quality, cash generative,
(30:14):
asset light, durable growth businesses, and I think that the
the insight I would or the hypothesis I would throw
out there is that for a lot of these companies
that are lagging, there's a bearish narrative that you know
there there's there's a there's a problem looming, that there's
a disruption coming. And in many cases I don't believe
these narratives, right, And so as these durable compounders just
(30:38):
keep putting up numbers and keep doing what they're doing,
fell out perform as you know, people start to dismiss
some of the bearish narratives and the stocks just compound
with their earnings growth. So two specific examples there, I'd
point to Booking dot Com right trading at fifteen times
free cashrow. Next year, it grows free cashual mid teens
(30:58):
a year ish. The market thinks it's an AI loser.
I actually think it's an AI winner. I think they
have a huge cost out opportunity as they automate more
of their processes. Because they're the merchant of record, it's
hard to disintermediate them. And also point only Visa. Visa's
trading at point eight times the markets free cashual multiple. Right,
(31:18):
this is a mid teen's earnings grower with no capital intensity.
And there's always a concern that visa is going to
get disrupted by by stable coins or pick your reason,
but it just hasn't happened. And so I feel like
that those cohort of stocks over the next several years
could do really well because they've just kind of traded
down to low multiples on things I don't believe are correct,
(31:41):
and they're growing twice the market.
Speaker 1 (31:44):
So great. Unfortunately we need to end here, but I
really enjoy this. Justin thank you so much for joining us.
Speaker 3 (31:52):
Thank you David, thank you Michael In Mike.
Speaker 1 (31:55):
I'd also like to thank you for being my cost
for our year end episode.
Speaker 2 (31:59):
Thank you both.
Speaker 1 (32:00):
And I also want to thank our listeners for joining
us on this ride over the past year and a half.
We'll be back in January with more episodes. In the meantime,
wishing you happy holidays and a great start to the
new year. Also, if you liked the episode, please subscribe
and leave a review. And if you'd like to see
more of our research on the terminal, go to bi fund,
Go for fun research in Bisto x N go for
(32:23):
Equity Research. Until our next episode. This is David Cohne
with Inside Active
Welcome to Inside Active, a podcast about active managers that
goes beyond soundbites and headlines and looks deeper into the processes, challenges,
and philosophies and security selection. I'm David Cone, I, lead
mutual fund and active research at Bloomberg Intelligence. Today, my
cost is Michael Casper, Senior US equity strategist at Bloomberg Intelligence. Mike,
thanks for joining me today.
Speaker 2 (00:34):
Thanks David.
Speaker 1 (00:36):
So this is actually our last episode of twenty twenty five,
and as we head into the year end and into
next year, I wanted to ask about a note you
put out earlier in the week. You know, basically on
what two three earnings are signaling for the market. Could
you give our audience kind of a brief overview of
what you're seeing.
Speaker 2 (00:55):
Yeah, so the third quarter was obviously a blowout quarter.
We doubled the preseason expectation for the S and P
five hundred, nearly doubled the preseason expectation for the Russell
two thousand revenue growth. And really what I'm seeing in
the earning stream is a lot of green signs, a
lot of green shoots. I think they're just a little
bit less bright than they were in the second quarter.
(01:17):
So what I'm talking about there is revision momentum, specifically
cyclical minus defensive earnings. We're hitting a peak on that,
but revision momentum also has peaked and is starting to
come down. What I mean by revision momentum is the
number of companies with hikes, number of companies with cuts
over the total number of companies that reported. And why
(01:40):
that's coming down a little bit is just, you know,
we had such dramatic cuts in the beginning of the
year as a result of Liberation Day and a result
of all the tariffs that were flowing through the system.
Consensus got it completely wrong for twenty twenty five kind
of yet again, they weren't necessarily great in twenty twenty
four either, but they got it completely wrong in twenty
(02:01):
twenty five and they really had to walk that back.
And much of that happened in the first and second
quarters as those results rolled in and they were better
than expected. Third quarter again better than expected, but it's
a little bit less robust than you know, a double
digit gain off a two percent expectation like we saw
in the second quarter, So that's a little bit less green.
Cyclical minus defensive earnings I mentioned before, we're hitting a
(02:24):
peak on that. Typically I look for that to peak
and wane to signal some volatility for the market. And
the earnings bar is very high going into twenty twenty six.
Whether we can hit that or not remains to be seen.
I will mention though that consensus has only overshot once
in the past four years, so quarters on the preseason
(02:46):
expectation for the S and P five hundred. So yeah,
the bar is a little bit high. Typically that means
a little bit more volatility, given you know, earnings are
already baked in, but that's yet to be seen in
twenty twenty six.
Speaker 1 (02:58):
Well, certainly be interesting to watch. Much Speaking of the markets,
I do want to introduce today's guest. Justin White, is
a portfolio manager of the US multicap growth equity strategy
at TROW Price, including the trow Price All Cap Opportunities
fund ticker PRWAX. Justin, thank you for joining us on
our last episode of the year.
Speaker 3 (03:18):
Thanks for having me.
Speaker 1 (03:20):
So let's start with your process. The four Pillars framework
is central to your process. How did this framework evolve
over time and do you ever feel like you have
to bend or adapt it? When the markets, you know, change.
Speaker 3 (03:33):
Sure, just to kind of get everybody on the same
page who might not be familiar with with my process.
Four pillars is the stock picking framework that drives my
decision making in the portfolio. And the way to think
about it is each pillar is an incremental reason for
a fundamental investor to want to own a stock. And
the idea is that if you can stack attractive attributes together,
(03:57):
you have a high probability of that stock up reforming
because there are lots of people who could be interested
in buying it for a lot of different logical reasons, right,
And so the four pillars I look for, but for
high quality businesses. Look for businesses that have potential for
positive estimate revisions. Businesses with fundamental acceleration and valuation is
(04:18):
the fourth pillar. So just how did I kind of
come up with this? So I joined TROW, you know,
seventeen years ago as a career switcher. Then didn't know
what I was doing, had to figure it out. So
I took that whole you know, Warren Buffett mental models
approach to heart, and the first year or two I
was in this in my seat as an analyst, I
just you know, tried to write down notes about lessons learned.
(04:42):
For example, in two thousand and nine, when a company
that was seeing negative revenue growth and the stock started working.
It kind of didn't understand why, but after talking to
other pms, they're like, oh, it's because revenue growth bottomed.
It went from negative twenty percent to negative sixteen percent
year over year. That's why it's working. Right. So anyway,
(05:03):
over two to three years, I collapsed to all these
mental models into the four pillars. I started using this
framework as an analyst in about the twenty eleven timeframe
and really haven't changed it at all during my tenure.
You know, each pillar has been approximately equal weighted, so
you know, save weight to quality and positive visions and
acceleration and valuation. The one thing I would mention is
(05:26):
that recently, as as market structure has changed, I've been
giving a little bit more weight to the quality pillar.
Speaker 1 (05:33):
Okay, so actually it was kind of goes right into
my next question is when you're looking at a company
using the four pillars. You know you mentioned it's you know,
equal weighted, but you know what happens when one looks
strong as you mentioned, you know, quality, you're really focusing
on when something else, like maybe valuation might not be
as strong. How do you balance that?
Speaker 3 (05:53):
Yeah, it's a good question. So the four pillars is
a body of evidence approach. Right, you look for stocks
that have enough pillars working for you strongly enough, and
not many pillars working against you. Right, You don't need
all four to be positive. So in fact, it's quite
rare to have all four working for you at the
(06:13):
same time. And when that happens, you make a big bet,
like in Nvidia end of twenty twenty two, like was
scored awesome on all four pillars, and kind of we
see what happened thereafter. But I'd say, like to kind
of answer the questions, you can get to four pillars,
get to yes in a number of different ways. Right. So,
if there's a really expensive stock like pal Andeer, where
(06:37):
the valuation is very difficult to justify, right, but it's
a super high quality business, high margin rapid growth estimates
have been coming up a lot, you know, the rate
of revenue growth they're seeing in dollar terms keeps accelerating.
You know, it's one where even though valuation is negative,
there's enough good stuff in other parts of the framework
(06:59):
that you can justify having a small overweight. You know,
you can also own lower quality stocks if they check
all the other boxes. Historically, financials don't sort to the
top of the pack in terms of business model quality.
I mean, some are better than others, right, But I've
been overweight banks and capital market stocks this year on
(07:20):
the view that the starting valuations were attractive. They're being deregulated,
which is going to be good for returns. Capital markets
activity was improving from a trough as a kind of
Trump cut a lot of red tape and allow more
activity to happen, and that basically is a set up
for higher returns and higher estimates. So I'd say that
(07:41):
it's a body of evidence approach, and it instills a
cell discipline as well, which is important to point out
because you know, when a stock checks a lot of
the boxes, I buy it, and when it doesn't check
a lot of the boxes, I sell it. This led
me to sell a lot of my tech exposure in
late twenty twenty one.
Speaker 1 (08:00):
Well, it makes sense. There's something else I wanted to
ask you about. Is you know I've read you describe
your research as pattern recognition, you know, basically looking at
how the world fits together and making sense of what's happening.
You kind of walk us through, you know, a recent
example of how how this you know, might have worked
for you and how that translated into an investment.
Speaker 3 (08:21):
Sure, so I'd begin by answering by saying that four
pillars is essentially how I describe my pattern recognition, right,
because it's a the each pillar kind of is a
reason for people who want to buy a stock, And
so that's kind of a pattern I observed over kind
of over time. But let me start with a historical
(08:41):
example to get to your question, and that a more
recent one, because the historical example I think is a
fun one. Right. So there's a company called Smile Direct Club,
which kind of you know, doesn't it's not not listed anymore,
and they had their IPO and it's basically an invisiline company,
you know, clear retainers. And the reason I passed on
(09:02):
the IPO was because I had studied Netflix's business model.
People like, what does Smile Direct Club have to do
with Netflix? Well, both their consumer products, but Netflix is
like easy to sign up, easy to cancel, the cost
is pretty low, the value is pretty high, Like it's
a low friction experience in contrast Smiled Rec Club. Right,
(09:25):
it's a considered purchase, high cost, high friction, Like you
have to go in the store, you have to keep
using the products you know reliably every day. So basically,
Smiled Rec Clubs the model had attributes that would argue
for a much shallower s curve of adoption than Netflix.
People just aren't going to penetrate the tam as quickly.
(09:46):
Yet when Smile Direct Club came public, they claim they'd
penetrate their market by ten points a year. Netflix, in
the sweet spot of its adoption curve only outed a
few percent of US households in any given year. Kind
of knew that SDC's numbers were unrealistic in I passed, right,
So that's that's one one way to get at it.
But more recently, I'd say, you know, Carvana is a
(10:08):
major bet in the fond. It's been a very positive contributor.
And the powder recognition here is that, you know, Carvana
is a business that a lot of people think is
you know, they're not sure how how high quality it
is or not. But when I look at it, I
see a business targeting a huge market with a first
mover advantage, with the material cost advantage very early in
(10:31):
the s curve. Right, they're one and a half percent
penetrated in their market, and powder recognition tells you that
when you have a company this kind of has a
really open ended runway and a competitive advantage that's going
to persist. You know, don't worry about the valuation, don't
worry about the quarterly estimates. The structural tailwinds are just
too strong and pursas for so long that valuation will
(10:52):
take care of itself. So so that's one that kind
of we've done it. We bought quite a quite a
bit earlier, and it's a it's it's been a performer
this year.
Speaker 1 (11:01):
Okay, great, And you know with your fund it's it's
an all cap, so you get a lot of flexibility
in what you can invest in. And so you've also
said before, you know, when I've looked at you know,
some of the things online, the il zigmore growth zagmar value,
you know, tilt up cap or down cap. How much
of that is tactical versus like long term in your view.
Speaker 3 (11:24):
It's a good question, and at the risk of sounding repetitive,
for one sentence, I make buy and sell decisions based
on the four pillars framework, and so when value stocks
score more strongly, I own more value stocks, right. I
think the spirit of the question is kind of getting
at what are my biases and as like, what kind
(11:44):
of investor am I know? Deep in my bones? And
I think the answer to that question is that I
have a growth bias.
Speaker 2 (11:52):
Uh.
Speaker 3 (11:53):
Most of the time my fund has had a growth
tilt versus the underlying benchmark. And the reason for that
is because one of my four pillars is the quality pillar,
and the highest quality stocks tend to outgrow the economy.
Lower quality stocks outgrow the economy less often. So value
(12:15):
stocks are often at a starting point at a disadvantage
because on average they score lower on one of the pillars.
You know, all else equal, I'd rather own Microsoft over
time than a brick and mortar retailer.
Speaker 2 (12:26):
Right.
Speaker 3 (12:26):
So I point out that in late twenty twenty one
and most of twenty twenty two I did not have
a growth tilt, and that is because growth stocks scored
really poorly then, especially tech stocks. The issue was that
we had peakish growth from the pandemic that was about
to decelerate. We had extremely high valuations, We had consensus
(12:48):
estimates that were not anticipating any deceleration and so looked
generally too high. And so you know, I went zero
eight Amazon went zero weight Meta With hindsight, this was
the right move. But the reason that I tiled down
the growth that and added to some value sector was
really because of the four pillars framework signaling that was
the right thing to do. Yeah, makes sense.
Speaker 1 (13:12):
And you know, one of the thing I know before
it might gets into some of the more market focused
topics is you know, you've also mentioned in your research
that you come across a lot of data and a
lot of it doesn't matter, and you're really focusing on
a couple of things. What are the one or you know,
maybe two data points state you think are really being
underappreciated by the market.
Speaker 3 (13:32):
Yeah, so when you say what's underappreciated by the market,
I do want to point out that that's a different
question than underappreciated by the media. So just because we
see headlines about AI bubble one week or it doesn't mean
the market's doing that or the prices reflect that they
believe that. So the market's generally brutally dispassionate and right
(13:55):
most of the time. But in terms of the prices,
we see out there.
Speaker 2 (13:59):
Now.
Speaker 3 (13:59):
I think they're are a couple things top of mind
that the market may be missing or getting wrong. I
don't know if I call these data points per se,
but but they're just a couple areas where I'm disagreeing
with the market. The first one is I think the
market is still too complacent about believing the depreciation schedules
for AI chips among the cloud platforms. Right. I personally
(14:22):
don't believe the GPUs have a six year useful life.
And if these companies are buying chips and advertising them
over six years but they only last four, then their
earnings quality is being overstated and returns are being overstated.
Oracle and core Weave are starting to snit this out
because they're kind of the tip of the spear, but personally,
(14:43):
I think there's still a ways to go. I mean,
if Oracles chips last four years instead of six, then
they're locking in a half trillion dollar backlog at value
destructive return levels, and that would be that would be
a problem if that's the case. One other thing I
kind of struggling to understand here is the markets enthusiasm
(15:03):
for the value potential of humanoid robots and autonomous driving.
And my hang up here is that, you know, like
Tesla has a market have of one and a half
trillion dollars, and the logic underlying it feels kind of lazy,
right as an industry structure issue. You know, suppose Tesla
(15:24):
figures out humanoid robots, do you think China is going
to figure it out too? Do you think China is
going to have a dozen manufacturers? Will they be selling
those robots below cost for a decade?
Speaker 2 (15:34):
Right?
Speaker 3 (15:34):
And autonomy it's not going to be winner take all.
There's a lot of Chinese options, There's Weamo, et cetera.
And so so I feel like this idea that you know,
one company is going to have monopoly type profits and
we are confident that that's going to be true for
decades to come, I'm a little bit unsure about that.
Speaker 2 (15:55):
Do market valuations in general, and maybe particularly for tech,
do they concern you at all in terms of your portfolio?
Speaker 3 (16:03):
The short answer is absolutely, the valuation concerns me because
it's always less comfortable when you have to invest with
a lower margin of safety. But personally, I think that
stocks tend to follow earnings and will continue to cooperate
as long as earnings cooperate. And you know, I think
(16:24):
you mentioned at the start of the of the podcast
there's been some broadening out of earnings across the market,
including in small caps. So so you know, just because
the valuation is uncomfortable doesn't make that a good timing tool.
It just means there's more negative asymmetry if we have
have a market hiccop. So one argument in support of
(16:44):
the higher multiples, by the way, is that the mix
of stocks in the markets has changed over time. It
has become higher quality. Right, the megacap businesses are very
high quality businesses, so some degree of premium is warranted
versus his. But the areas that make me really uncomfortable
are stocks where you kind of know approximately what the
(17:07):
earnings growth is going to be and you just have
to pay too much for it. Right, So seeing Walmart
pushing forty times earnings, like, there's a lot of good
stuff happening at Walmart. But now, even if they do
grow earnings that at a rate a little better than
the street expects, couldn't that not go sideways for three years?
You know? I also think some of the more commoditized
(17:28):
AI data center component stocks going parabolic because they're in shortage,
like cables that connect one server to another, and there's
not enough of them, and so stocks are up tenfold
in a year. You know, a lot of these stocks
are beating numbers, but they make no sense on a
DCF basis, and so when fundamentals peak, in turn, a
lot of these are going to be down eighty ninety
(17:48):
percent from the peak. So I say that there are
areas that make me more uncomfortable and some areas where
I feel like it's more okay. But on balance, valuations
are pretty.
Speaker 2 (18:01):
And it seems that tech and maybe more specifically AI
companies are transitioning from an asset light to a capital
intensive model with all of this infrastructure build out that's
kind of necessary to support that theme. Does that change
how you value companies at all or change your or
change your view on growth companies?
Speaker 3 (18:19):
Yes, this is a super important question. The rising capital
intensity of the hyperscalar platforms makes it harder to make
big bets in them than before. And here's how I
frame it. So in the past financial metrics that say meta,
they all trended the same way. Right when revenue was growing,
(18:39):
ebit was growing, free cashal was growing they all trended
in the same direction, and now there's this divergence, right,
and get a setup where you're like, Okay, suppose Meta's
next quarter, Suppose they beat on revenue by quite a
bit but miss on ebit because they're investing so heavily
in AI and guide to no free cash on in
twenty twenty six. How does the stock process that? It
(19:02):
depends what people want to focus on, and that's it's
just harder to know. So essentially the degree of difficulty
has gotten harder. Oracle has robust earnings growth, accelerating revenue growth,
and burns a ton of cash. And that cash burns amplifying.
Like if you look at a chart graphing oracles free
cash flow against its share price over the last three years,
(19:25):
it's like a mirror image. It's fascinating. Right, The more
cash they burn, the more the stock goes parabolic up.
So I'm not trying to pick on Meta and Oracle,
but the point is just it's getting harder to score
these stocks cleanly on four pillars because it's harder to
score each pillar. Right, is Oracle getting is it accelerating? Well?
Revenues are, but free cash flow is the wrong way.
(19:47):
Is meta cheap? Well, it's twenty times earnings, but one
hundred times free cash flow right, And it's only twenty
times earnings if you trust the DNA assumptions on their chips.
So overall, this dynamic is causing you to rotate capital
to other names and other pockets at the market where
the setup feels cleaner. Not that I'm running, you know,
rapidly away from the mag seven, but on balance, the
(20:09):
incremental dollar of capital is going elsewhere.
Speaker 2 (20:12):
I'm a macro guy at heart, and it seems rates
are coming down. You know, the White House is influencing
the FED a little bit and might install their preferred
FED chair in twenty twenty six in fact, and then
they may even come down even faster. Does that concern
you that there might be a lasting shift from growth
style to value style.
Speaker 3 (20:31):
Yeah, so, I personally wouldn't make the connection that lower
rates necessarily means you buy value and sell growth. I mean,
if you took your business school textbook out and thought
about the concept of duration, theoretically, duration will argue for
the opposite. Right, lower rates should be more of a
(20:52):
tailwind for growth stocks than value stocks because more of
their values terminal value, which was more sensitive to changes
of discount rate. We kind of saw this with profitless
tech in twenty twenty and early twenty twenty one. So
I think the answer to the question about, you know,
value versus growth really comes down to company specific fundamentals.
I mean, if you force me to abstract and generalize
(21:15):
that the times that you want to overweight value are
either when growth stocks look particularly dangerous like they did
in late twenty twenty one and early twenty two, or
the economy's early cycle and broadening out because value stocks
have a heavier cyclical component to them. I point out
that even though we've seen some breadth in earnings, which
(21:38):
is encouraging, it's unclear how much magnitude of improvement there's
going to be in twenty six. It doesn't feel like
you're starting at a very depressed level with an imminent
massive acceleration coming. So I think that the case for
value stocks is more favorable now than it has been.
But my portfolio is still growth tilted because on four pillars,
(22:01):
I'm getting more bisignals and the growth cohorts.
Speaker 2 (22:04):
And how about small versus large caps? Small caps obviously
been an underperformer for some time, but the valuations are
looking really attractive at seventeen year lows. I've noted a
couple of days ago. But do you see any opportunities
emerging in smaller capitalizations in twenty twenty six?
Speaker 3 (22:22):
So there's the kind of question about next year versus
like a structural question. So let me just start by
talking about like structurally, I'm pretty bearish on small caps
because we're in a world where the stronger are getting stronger,
and AI amplifies this. Small caps have grown revenues more
(22:42):
slowly than large caps over the last twenty plus years
on balance their lower quality. Over the last twenty years,
there are were two periods where small caps had meaningful
outperformance that sustained for a full year. Right that was
two thousand and nine, and it was coming out of COVID,
And if you think about those two periods, right nine
(23:03):
and steps of COVID, the setup was like a bloodbath
starting point stocks down huge Russell two thousand basically didn't
have earnings. So I don't feel like we're at a
starting point like that now. So I would argue against
a huge outperformance of small caps versus large caps next year.
That said, small cap earnings didn't grow over the last
(23:26):
three years, and growth has bottomed and recently started improving
as he mentioned, which is encouraging. Valuations are cheap on
a relative basis, but on an absolute basis, I think
they're not that cheap personally, and so in small cap land,
I'm still just really trying to make idiosyncratic bets rather
than trying to make a sector call. Now we've made
(23:47):
good money in biotechs like Insmed, which is no longer
a small cap, or aero copper because we're structurally bullish
on copper, always looking for ideas. But right now there
aren't a ton that jump off the page at me.
But they might not perform in twenty twenty six. I
just don't think it'll be shocked in awe if they do.
Speaker 1 (24:05):
So if we go into actual sectors or even themes,
are there any of that? You think the market's underestimating
any type of structural change, and you know or are there,
you know, any mistriced opportunities you're looking for?
Speaker 3 (24:21):
Yeah, So a couple things I think the market might
be underestimating. First is that as people focus so much
of their energy on the AI trade, the market is
starting to kind of ignore and just push to the
side a number of high quality open ended winners that
are pretty early in their s curves, and I see
(24:43):
some opportunities in kind of a number of those. I'll
just mention a couple quickly, like See Limited is the
Southeast Asian e comm gaming payments company, extremely well managed company.
You know on street numbers, it trains it sixteen times
free flow on twenty twenty seven. It's like a thirty
percent EBIT dot compounder, and the stocks lost a third
(25:05):
of its value because people are like nervous about a
very minor investment cycle for the next couple of quarters.
And I just see that and think, you know, if
you put that in a box for three years, and
it's like, I don't know, twelve times twenty twenty eight
free cash li like you're going to outperform the market,
like by a lot as long as the numbers come
in approximately how we think. Door Dash is another one
(25:26):
where it's probably sixteen times free cashlo on twenty twenty eight.
You know, in three years, you know, the multiples can
be a lot higher on that twenty twenty eight number.
So I feel like there's opportunity those types of stocks
that are just kind of not as not as front
and center as ASAI takes mind share. One other thing
I think the market's underestimating is the structural supply shortage
(25:49):
we have in copper.
Speaker 2 (25:51):
Right.
Speaker 3 (25:51):
So in my fund, I own Southern copper and Arrow copper.
And the insight here is that it's just getting harder
to get minds permitted, proof moved open in more parts
of the world right in emerging markets. It's a structural issue.
It's like a Nimby issue that's metastasized around the world.
And copper's required in so many things that has no substitutes.
(26:12):
It's rapid price in elastic. I think copper has the
potential be well above ten dollars a pound by the
end of the decade. So those are two that I'd
point to.
Speaker 2 (26:23):
We've already covered the public market bubble or air quote
bubble in depth pretty much, but does a possible private
credit equity private equity bubble concern you at all in
public markets?
Speaker 3 (26:40):
So I think that if there's carnage in private credit
at some point, that it will be largely a contained event.
It'll hit some of the alts, but it's not going
to really impact the overall economy in a big way,
it would be my view, because it's you know, it's
(27:01):
the you know you have you know, people have invested
in private equity funds and they might take a hickey
on some some some bad loans being written off, but
that's not like a bank losing capital and having to
you know, get help or get get bailed out. So
I think that they're the hiccups we've seen in private
credit uh well publicized issues in the last couple of months.
(27:25):
It feels like it's more one off than structural right now,
Like there's there's you know, there's some fraud uh and
and some bad behavior, but you know, overall, we don't
really have a have a reason to be that that
concerned about uh the activity. I mean, you know, high
yield bomb spreads have been quite well behaved this year.
(27:45):
They're still pretty tight equity markets at the highs. It
just feels like there were a couple of cockroaches. And
I hear Jamie Diamond when he says, when you see
you know one, then there's you know a lot more
of them. But I think that people are kind of
like looking for thus ignore that like this is the
top and I just don't feel like that's I'm not
kind of on board with that. And I think that
(28:06):
if there is a problem, it's not going to bring
down the economy with it. Like if the ai cat
X bubble unlines, that could bring down the economy, but
I don't think private credit souring would would would would fantastasize.
Speaker 1 (28:19):
So I got one more question for you. If we
look out a few years into the future, what are
a couple areas of the market that could you know,
meaningfully outperform or underperform through say twenty thirty And you
know what would be the secular forces that really underpin that.
Speaker 3 (28:38):
So so yeah, look, I like the question because it
does force you to take a longer term perspective. And
so if we're talking about, you know, themes through twenty
thirty and beyond, I just want to be clear by
saying I could be right over that timeframe, but look
terribly wrong for six or twelve months first, right, So
one one area I think could really underperform between now
(29:00):
twenty thirty is semiconductor sector, and for three reasons right.
One is just the risk that we have an overbuilding
ai CatEx that unwines I'm not trying to call the
top in AI CatEx, but I do think there's a
real risk that we're overbuilding capacity now and into twenty
twenty six, and this could become more obvious in twenty
seven and twenty eight. I also think industry structure in
(29:24):
many parts of the semiconductor complex is getting less favorable.
Speaker 1 (29:29):
Right.
Speaker 3 (29:29):
Analog semiconductors have more competition than China. GPU market structure
is still essentially just in Vidia today, but there's more
challenge coming from Google's TPU, from A and D, and
against this backdrop, you know, valuations are quite elevated, right.
It's like the socks is at twenty eight times forward
earnings if earnings grow twenty five percent next year, and
(29:51):
the historical average is seventeen times, So you know, it's
not like a near term call. Like it still looks
constructive in the near term, but I think over the
course of several years that it could be quite dangerous
in terms of areas that could outperform. I think that
the market's ignoring a number of high quality, cash generative,
(30:14):
asset light, durable growth businesses, and I think that the
the insight I would or the hypothesis I would throw
out there is that for a lot of these companies
that are lagging, there's a bearish narrative that you know
there there's there's a there's a problem looming, that there's
a disruption coming. And in many cases I don't believe
these narratives, right, And so as these durable compounders just
(30:38):
keep putting up numbers and keep doing what they're doing,
fell out perform as you know, people start to dismiss
some of the bearish narratives and the stocks just compound
with their earnings growth. So two specific examples there, I'd
point to Booking dot Com right trading at fifteen times
free cashrow. Next year, it grows free cashual mid teens
(30:58):
a year ish. The market thinks it's an AI loser.
I actually think it's an AI winner. I think they
have a huge cost out opportunity as they automate more
of their processes. Because they're the merchant of record, it's
hard to disintermediate them. And also point only Visa. Visa's
trading at point eight times the markets free cashual multiple. Right,
(31:18):
this is a mid teen's earnings grower with no capital intensity.
And there's always a concern that visa is going to
get disrupted by by stable coins or pick your reason,
but it just hasn't happened. And so I feel like
that those cohort of stocks over the next several years
could do really well because they've just kind of traded
down to low multiples on things I don't believe are correct,
(31:41):
and they're growing twice the market.
Speaker 1 (31:44):
So great. Unfortunately we need to end here, but I
really enjoy this. Justin thank you so much for joining us.
Speaker 3 (31:52):
Thank you David, thank you Michael In Mike.
Speaker 1 (31:55):
I'd also like to thank you for being my cost
for our year end episode.
Speaker 2 (31:59):
Thank you both.
Speaker 1 (32:00):
And I also want to thank our listeners for joining
us on this ride over the past year and a half.
We'll be back in January with more episodes. In the meantime,
wishing you happy holidays and a great start to the
new year. Also, if you liked the episode, please subscribe
and leave a review. And if you'd like to see
more of our research on the terminal, go to bi fund,
Go for fun research in Bisto x N go for
(32:23):
Equity Research. Until our next episode. This is David Cohne
with Inside Active
Host
Gina Martin Adams
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