October 14, 2025 • 25 mins
High-quality stocks, measured by profitability, are trading at historically elevated levels, among the strongest in 25 years. In this episode of Inside Active, host David Cohne, mutual fund and active management analyst with Bloomberg Intelligence, and co-host Christopher Cain, US quantitative strategist at BI, speak with Sid Jain, deputy portfolio manager at GQG Partners, about the firm’s focus on durable earnings and forward-looking quality, its US Select Quality Equity Fund (GQEPX) and why today’s market — particularly in tech — could prove worse than the dot-com bubble. They also discuss the team’s approach, which blends quant guardrails, investigative research and price-momentum awareness to avoid value traps. The podcast was recorded on Oct. 6.
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Speaker 1 (00:13):
Welcome to Inside Active, a podcast about active managers that
goes beyond sound bites and headlines and looks deeper into
their processes, challenges and philosophies and security selection. I'm David Cohne,
i lead mutual fund and active Research at Bloomberg Intelligence. Today,
my cost is Christopher Kine, us quantitative strategist at Bloomberg Intelligence. Chris,
thank you for joining me today.
Speaker 2 (00:34):
Thank you so much for having me. David.
Speaker 1 (00:36):
So, you wrote interesting note last month on quality stocks
trading near their most expensive levels over the past twenty
five years. Is that still the case?
Speaker 2 (00:45):
Yes, it is still the case. I mean quality has
been certainly the most expensive factor from a historical perspective.
Now for a while. You know, our bi quality we
keep it pretty simple and we just consider profitability metrics
like r O E ro see as well as low leverage.
So you know, when you look at the top Quintown
on the Russell one thousand is trading over four and
(01:05):
a half time sales versus just over one time sales
for the lowest, lowest stock quality Quintal. So that's about
over three and a half times more expensive, which is
one of the most expensive readings we've seen. I will
say also, though, that you know, the profitability of these stocks,
of these high quality stocks are much elevated compared to history.
Obviously high profitability will you know, high quality will always
(01:28):
have higher profitability. But when you look at the spread
between the probitability of low and high quality right now,
it's very wide, So you would think there is some
fundamental support though the valuations are very stretched.
Speaker 1 (01:40):
Great, well, I'm sure today's guest has a great take
on valuations. And without further ado, i'd like to welcome
Sid Jane to the podcast. Sid is deputy portfolio manager
at GQG Partners. Sid, thank you for joining us today.
Speaker 3 (01:55):
Thanks for having me on. Guys.
Speaker 1 (01:58):
So I have to start with the research note your
firm recently published. You know, I couldn't I really think
that's the best way to start. So you put out
a note called dot com on Steroids. In the note,
you know, your firm says that today's market, you know,
could actually be worse than the dot com bubble, and
your firm argues that, you know, many of today's big
(02:20):
tech names represent backward looking quality, not forward with looking quality.
So you know, my question is, you know, what are
the clearest quantifiable metrics, say canaries in the coal mine,
that in your view, distinguished one from the other.
Speaker 2 (02:36):
Yeah.
Speaker 4 (02:37):
Absolutely, And I think to kick things off, it's important
to understand some of our history with the technology sector
where we're not perma bears by any means. We've been
actually quite bullish and constructive on the sector for better
part of our firm's history.
Speaker 3 (02:50):
Of the past decade.
Speaker 4 (02:52):
What has caused us to get nervous is this new
investment cycle that you're seeing. And if you study again history,
when you see major spikes in CAPEX and this is
on present level of investment you're seeing right now, that
usually tends put poorly for forward looking equity returns. And
(03:12):
so that's one metric where it's spiking CAPEX. And you've
seen this in the past, whether it's the railroad boom,
electricity boom, internet boom twenty five years ago. That gives
us pause, especially when there's really no clear evidence of
an ROI on the trillions of dollars investment that are
being debated today. The second thing that keeps us nervous
is just decelerating revenue growth. These companies, big tech companies
(03:36):
were growing twenty thirty percent like Clockwork pre COVID, whereas
now we believe the growth runaway is significantly less than
what existed before. I mean, digital ad penetration is now
running at seventy percent of over advertising. The metas Googles
of the world cannot go twenty thirty percent sustainably anymore.
I mean, same with Amazon's Microsoft. They're all slowing down structurally.
(04:00):
And so the combination of well of names, high multiples
and growth decelerating has problems been all over it. And
last thing I'll say is the accounting shenanigans. And this
is a little bit less quantifiable, but it was a
lot of press that I'm sure you guys have read about.
I mean, the circular vendor financing that you're seeing between
Nvidia and open Ai, or today's AMD deal that usually
(04:21):
comes at the very end of a cycle. So these
are some of the data points that causes to believe
that the best years are over for vast majority the
technology space. Part to be a large cap the AI winner,
so to speak.
Speaker 2 (04:35):
Interesting, very interesting. So you're talking about slowing growth, you know,
I was wondering, you know, quality of all the factors,
you know, tends to have the highest variance if you will,
of factor definitions, you know, because you know it's not
maybe as straightforward as a value or momentum. So do
you have explicit growth elements in your quality factor? I've
(04:58):
seen some quants do that, some not. Do you have
that component in your quality factor? Yeah?
Speaker 3 (05:04):
So growth, we like growing companies.
Speaker 4 (05:08):
We don't generally buy companies that are in secular decline.
But growth in and of itself is not what we're
looking for. That's the only variable that matters. And so
the way we think about investing is we want to
compound it roughly ten percent annually, and we get there
through a function of earnings per share growth plus dividend yield.
(05:31):
That combination gets you there. And so we're equally comfortable
owning software companies that get you to that tot re
turn predominantly from the growth side, as well as energy
companies where there's a much growth but you're getting a
massive buyback and dividend return, and we're equally comfortable flexing
both sides of that lever So it doesn't just have
to be.
Speaker 2 (05:50):
Growth awesome, thank you.
Speaker 1 (05:53):
So I know, I know you know with your firm,
you know it's a big approach with durable earnings rather
than you know, typical growth or value labels. How do you,
I guess, distinguish between durable earnings from just optimistic growth assumptions.
Speaker 4 (06:08):
So I think one area where we'd have maybe have
a bit of a differential view is truly appreciate long
term capital cycles. And this goes back to our founder
in Cio Rajiev having a thirty year track record investing
in developed markets, emerging markets, and everything in between. And
once you've seen enough cycle that forced you to appreciate
(06:30):
that everything experience goes through this. I mean, have you
wrote a white paper action on the semiconductor sector. I
think it was back in twenty seventeen House saying this
has become the new growth sector and we've got a
lot of pushback saying, how can you say that semic
corectors haven't.
Speaker 3 (06:43):
Grown in ages?
Speaker 4 (06:45):
And so you do see those and I think, for example,
if you look at today, we believe a lot of
the technology sectors are very late cycle. The growth is
slowing down, and the addressable market is just a lot
less than it used to be. Is on going from
twenty thirty percent revenue growth to ten percent, that's problematic
(07:05):
We're also very focused on the rate of change of growth.
So it's not just is it growing twenty percent a year,
but what direction is that heading? And that goes to
our definition of forward looking quality, is accelerating or decelerating,
and so that's a much bigger focus of our process.
So if you look at the energy space, we are
(07:27):
one of the few quality managers that made a large
pivot into energy back in twenty twenty one. Where people
have thought this was secular decline, our view was that's
the top of a cycle where you've seen most of
the industries underwater, not making much money, massive under investment,
and that will normalize. And that's how we think about
that in terms of the longer term cycle. That's a
(07:47):
big portion of how we deploy capital.
Speaker 1 (07:50):
So, you know, you mentioned, you know quality. Obviously, one
of the funds I really wanted to kind of focus
in is the gqg US Quality Value Fund ticker gq
ep X, And so you know, if you look at
the description, you know, invest in high quality companies with
attractively priced future growth products. How does this fund different
(08:11):
process or constraints from you know, your broader quality durable
earning philosophy.
Speaker 3 (08:17):
Yeah, sure. So there's.
Speaker 4 (08:20):
The investible The universe of names we choose from is
actually the exact same. So every name that we will
own on the value strategy has to meet our definition
of forward looking quality. So story that's improving has barriers
to enter, a strong cashoder, turner, equity and all of
that large chat focused. So that's the same. What is
(08:41):
different is where the returns are coming from. So, as
I mentioned, we go we want to get high single
digit load double edit total return with earnings, growth and
dividend yield. The growth strategy can go anywhere in between.
The value strategy will focus on the companies that pay
the yield. It's so usually the lower multiple names within
(09:05):
our investible universe, with a much greater focus on dividend yield.
So if you think from a scale of one to ten,
one being deep value, ten being super fast growth or
growth strategy will usually grow go anywhere between a three
to seven on that spectrum, the value strategy will be
(09:25):
between a three to five. Such a smaller subsector over
quality universe, and sometimes the strategy looked exactly the same
because the growth strategy can go everywhere in between.
Speaker 2 (09:36):
I would love to hear about You kind of alluded
to this a bit in your last answer, but you know,
I would love to hear about what's systematic, what's discretionary,
and how that process kind of weaves in together. You know,
I talked to a lot of clients that want to
do quant but maybe they don't want to do it
in a completely systematic way, right, they want to use
(09:58):
their own discretion. So is it like you have, you know,
a universe that's filtered for you quantitatively and then you
do more research on it, or how does that process work.
Speaker 3 (10:10):
It's a great question.
Speaker 4 (10:11):
At the end of the day, we will always be
a discretionary shop. We are fundamental Bondo stock managers, but
we believe heavily in using quant as almost like guardrails
on the process. So we have a team of quant
analysts and they help monitor things as factor exposures, what
factors are working, whatnot, doing historical back testing, making sure
(10:33):
we're not making any obvious mistakes. So, for example, one
thing we look at is what factor works in each country,
and it's not the same fact that it's work across
the world. So for example, if you look at China,
one factor that has proven pretty effective longer term is
divid and yield, and so our viob is let's maximize
the odds as much as we can and focus on
(10:55):
companies that have a yield versus purely growth. Now we
can buy growthy names, but the job is to just
improve the odds.
Speaker 3 (11:02):
As much as you can.
Speaker 4 (11:04):
As I mentioned the capex, we back to sectors that
are seeing significant CAPEX increases generally tend to underperform, and
so we monitor as those factors. But at the end
of the day, we are a bottom up shop. It's
another tool in our toolkit.
Speaker 2 (11:17):
Awesome, thank you so much. I would guess it's a similar,
you know answer, But as I kind of mentioned previously,
like quality definitely has the biggest variance of any quant factor,
and I've seen quants have wildly different definitions, and I
always ask, like, how do you weight the components of
(11:37):
your quality factor? Like, typically I see profitability as probably
the main thing, but obviously other things like margins and
stability of fundamentals and all this kind of stuff. So like,
is the waiting that you give to each of those
is that going to change kind of based on the
environment we're in, or do you have some kind of
structure in your mind of the weighting of the different components.
Speaker 4 (12:00):
So there's a couple of things that change. One is
the market environment also does matter. So for example, the
pre COVID era, we were much more focused on growth,
revenue growth. When it's a zero interest rate world where
you're struggling to get economic growth, earnings growth in most
major sectors, we are willing to pay a premium for
the fastest growing, best companies, whereas today it's a bit murkier.
(12:23):
It's a much higher interest rate world. You have to
be more valuation sensitive, and we do think there's a
lot of earnings risks from.
Speaker 3 (12:29):
The higher revenue growth names. But that's number one.
Speaker 4 (12:31):
Number two, and this might be even more important, is
that we look at all the same factors that you
mentioned in profitability, margins, et cetera. But we are much
more focused on rate of change, the second derivative of
those factors. As you mentioned the beginning, some of these
quality companies today have very strong profits, strong returns today,
(12:52):
but the question is next five year do they mean revert,
which is what we think that will start happening. That's
much less attractive than a company or a sector that
is at the trophy of a cycle. Maybe improving take
energy a few years ago, utilities over the past twelve
to twenty four months, which you're much more positive on.
And so that rate of change is what I think
is differentiates us versus many other quality oriented fundamental managers
(13:15):
out there.
Speaker 2 (13:17):
Awesome. I guess my last question here is what about
other factors, Like we talked about value, we talked about quality,
like does price momentum matter at all, does low risk
matter at all, or any other factors that kind of
add into your process.
Speaker 4 (13:32):
So I think historically, if you go back, one of
the factors, and this is an output not an input,
is that we do tend to have a bit of
a momentum overlay on our strategies. And the reason for
that is a fundamental reason is we like to buy
improving stories, not getcheries. So that typically correlates with strong
price momentum as well, and so it's rare. We want
(13:53):
to be aware which sectors are seeing strong price momentum
and not and understanding what is a fundamental reason for that.
We don't have to buy based on just great price action,
but if a stock is clearly breaking down, we want
to know why because we focus on the largest companies
in the world. Is a hyper efficient market, and we
(14:13):
have deep respect for price section and that it has
been longer term guardrails to our process making sure we're
not a stock goes down twenty you buy it looks
cheap because another twenty buy it and the classic value
trapped territory. So price pomentum does matter to us.
Speaker 1 (14:29):
So your research process integrates not just traditional analysis, but
also incorporates, you know, journalists, domain experts, others. Can you
share an example of, you know where a non traditional
perspective may have shifted your investment view.
Speaker 4 (14:46):
Absolutely, and it's the non traditional team that truly has
some of the most differentiated views on our investment team.
Where these are folks who have previously worked as investigated journals, journalists.
There's the Wall Street journal or Barons or so Reuters,
and they approached the world very differently. They're not actually
(15:06):
allowed to talk to the investment team the traditional side.
They're working in a vacuum. They don't read seal side research.
They actually go on the ground and talk to people,
whether it's former employees, regulators and things of that sort.
And they've been a couple of examples where it's helped
avoid blow ups but also find incredibly attractive opportunities.
Speaker 3 (15:25):
So I'll give a few.
Speaker 4 (15:27):
One would have been the technology sector. Actually, back in
twenty twenty one, as I mentioned earlier, we made a
large pivot from IT tech to energy, which paid out
well in twenty twenty two. One of the interesting data
points we found was the non traditional team had been
talking to a lot of recruiters in Silicon Valley and
the feedback they started hearing by summer twenty twenty one,
(15:48):
where job offers were getting yanked. You're seeing reduced hiring
across the board. And that was surprising because at that
point you might remember, the technology companies were talking about growth,
very strong growth into perpetuity revenue, strong, business outlooks strong,
but quietly.
Speaker 3 (16:05):
They weren't hiring people anymore.
Speaker 4 (16:07):
And so when you see in disconnects like that, that
cast your attention. Now, that's not the only data point
we looked at, but that helped fit this mosaic that
maybe things aren't all hunky dory the way people thought
they were back in twenty twenty one. Another example would
be on the emerging market side. We did a lot
of work a few years ago on a coffee company
called luckin Coffee in China, which maybe I remember it
(16:29):
was a very hot IPO, supposed to be the next
star Books of China. Our non traditional team did a
lot of work and they were able to find core
filings that show the founder at a criminal track record,
obviously was not being talked about on the prospectus, and
we were able to avoid that company ended up becoming
a fraud a few years later. And so we've seen
(16:50):
it add a lot of value in terms of truly
differentiated insights versus what you read from Wall Street, the
echo chamber of Wall Street.
Speaker 2 (16:57):
That's interesting about Luck And I remember that IPO that
was a hot IPO. I didn't realize it was a fraud. Wow,
good good job avoiding that one. I would love to
hear about like stock waiting schemes, you know, is it
just like weight? Is there a discretion amount of waiting?
Is there like a quant process like a Marcowitz type situation?
(17:18):
How do you think about waiting your stocks?
Speaker 4 (17:22):
So we've the camp of hold all your eggs in
one basket and watch it closely. So typically the top
ten names can be roughly fifty percent of our strategy.
Top twenty seventy percent and the biggest name will be
ten percent for context, and so we do like to
run a concentrated strategy, and.
Speaker 3 (17:40):
The way we think about it is almost from.
Speaker 4 (17:42):
A credit perspective or a credit mindset, where it's not
about find the names that have the most raw upside,
it's find the names where it can lose.
Speaker 3 (17:52):
The least amount of money in.
Speaker 4 (17:54):
And so a name could have three hundred percent upside,
but if you're wrong, you lose fifty percent. That deserves
a spat on the portfolio. But we wouldn't make it
a ten percent position. So the quality of the business
plays a huge role in terms of how we size
these bets. The second thing is also we're focused on
very large liquid names because we do change our minds
a lot, and that's what's kept us in the game
(18:15):
over the long run. Where the beauty about the process
here is it's a super lean team, very fast decision making,
and so the moment we see the earnings deteriorate, we
can sell out a large position overnight. There's no investment committee,
there's no deck you have to put together, and so
that really is a risk management process is cutting back
losses when the markets move against you materially, earnings are deteriorating,
(18:38):
or there's a macro risk potentially looming. And I think
the historical context for that is when you think of
Ragie's early career, I mean, starting off in the nineties
as an em manager, you're forced to risk management is
deeply ingrained in the DNA, and so that's what still
plays a role. So there's not a stop loss mechanism
or anything like that, use of much faster, quick when
(19:01):
you see fundamentals even marginally deteriorate.
Speaker 2 (19:05):
That's so interesting. Yeah, you kind of mentioned like using
price momentum as a bit of a risk management to whenounce.
You kind of got ahead of me on my next question,
which was like about risk management. So basically, it's not
a systematic process. It's not a stop loss in the market.
You assess the market, you assess you know, your view
of earnings or the price momentum or something, and then
(19:27):
you can quickly make decision to pull the plug per se,
with no investment meetings or investment committees or anything like
that exactly.
Speaker 4 (19:36):
And in our first gut reaction, when a name moves
maturely against the frankly, is that we're wrong until proven otherwise.
Speaker 3 (19:44):
A lot of managers like.
Speaker 4 (19:46):
To view the in terms of a stall goes down
twenty percent, you should buy more and more attractively priced,
which is true in theory, but that also assumes that
the fundamentals haven't changed at all. The reality of large
gap investing today, it's so efficient that generally speaking, when
I stop gaps on twenty percent, don you something is
fundamentally changed, And it could be the other way around
(20:08):
as well. Sawcolls are twenty thirty percent large care well covered.
Something's happened, and you better understand why.
Speaker 2 (20:15):
I totally agree.
Speaker 1 (20:17):
So I want to go back to valuation just a
little bit. You know, if you have a situation where
there's a very high quality company but it's trading at
a less than ideal valuation, how do you look at it,
you know, you know, in terms of you know, waiting,
you know, risking the opportunity gets away, or kind of
(20:37):
going into it at what you may not consider an
ideal valuation.
Speaker 3 (20:42):
Yeah, So I think the a couple of things. One
is that we actually urge all the.
Speaker 4 (20:49):
Investment team members to look at valuation last when it
comes to the analysis. The reason for that is if
you start, let's say I tell you to look at
Into Surgical for example, it's a high quality robotics company.
This name trad is that generally fifty to seventy times
earning is always super expensive. If you start with valuation first,
(21:10):
it makes it, it doesn't. You need to first understand
the business, the long term growth runway, the barriers to entry,
and then you can value it. So it's a timing
thing we would urge everyone to do. Second is you
need to have conviction in the long term runway and
the barriers. And when we like to say that the
air gets very thin at the top of the mountain,
(21:31):
you can't have any misses.
Speaker 3 (21:32):
We're fine paying up and we paid.
Speaker 4 (21:35):
We've owned companies in the past trading at sixty seventy
times revenue in the past rarely, but it does happen.
You have to have conviction of the earning trajectory and
there's no room for error. You also have to have
conviction that the street is missing something. Where this is
a high multiple name that street expects to grow a
twenty percent a year, but you think it's a thirty
(21:55):
percent grower. That's extremely interesting. The vice versa is not
where stream expects thirty percent, you think it's will be
twenty percent. So again, the rate of change and the
disconnect versus market expectation matters a lot, especially when it's
such a high multiple name you have no room brearer.
Last thing I'll say is that there's an opportunity cost
element where there's a lot of big world out there,
(22:19):
what is what is the opportunity on Maybe there's another sector,
another company that's more interesting, that's more attractively valued, which
is why I said earlier where pre COVID we felt
much more comfortable paying up for growth because there weren't
a million options out there. Today, the investible universe, whether
it's from a country perspective, you look at emerging markets
(22:40):
or Europe, it's much broader than it's been for in
a very long time, and so we feel less the
need to chase high multiple names today.
Speaker 1 (22:49):
Okay, and we just got one more question, and this
kind of a second waiting question. You know, the US
equity Value fund is a US quality value fund, is
non diversified, so you know it's it's typically going to
be more concentrated than some of the more diversified funds.
How do you know, just look at position sizing in
(23:09):
terms of concentration and you know balancing risk reward trade
offs of fewer names.
Speaker 4 (23:17):
So our view is you have to make big bets.
That's the reason for active management. We do not believe
in Benchamarhaggey. We are completely benchmark agnostic, and you can
see by our tech positioning where it's gone from seventy
percent tech to zero, back to seventy and everything in between.
But the caveat is when you're making these big bets,
you do have to have a deep respect for price
(23:38):
action and selling quickly when the fundamentals are deteriorating. The
easiest way to blow up is you have a large position.
That's the fundamentals are getting worse and you don't cut
back risk immediately, which is why if you look at
our turnover, it's typically north of fifty percent, which is
quite high for a long only manager.
Speaker 3 (23:58):
And then that is part of the risk manage element.
Speaker 4 (24:01):
We also believe in macro in terms of a risk
off tool.
Speaker 3 (24:07):
We are a bottom up shop.
Speaker 4 (24:09):
We won't buy a name because of a good macro setup,
but if we feel there's a clear macro risk pending,
we'll cut back risk aggressively.
Speaker 3 (24:16):
And this goes back to again Rodger being an EA.
Speaker 4 (24:18):
Manager hard back in the thirties and in the nineties
and then so a class example would be back in
twenty twenty one twenty twenty two, where the mistake a
lot of quality managers missed made was not appreciating macro
where what is the impact of higher rates, higher inflation
on tech valuations. That was a fundamental issue that many
(24:39):
quality managers missed. But our view was the macro. Respect
for macros helped us preserve capital in bear markets. So
these are some of the things that play a role
in terms of how we size bets, how risk on
we are at any given moment and not that makes sense.
Speaker 1 (24:54):
Well, unfortunately we have to end here, but this is
a great conversation. Thank you so much said for.
Speaker 3 (24:59):
Joining us shoe the time. Guys, thanks again, thank you.
Speaker 1 (25:02):
And Chris, thanks again for being my host. Thank you,
and I want to thank our listeners. If you liked
the episode, please subscribe and leave a review. Also, if
you'd like to see more of our research, go to
bi fund go for fun research and b I S
t o X go for stock research on the Bloomberg
terminal until our next episode. This is David Cone with
(25:24):
Inside Active
Welcome to Inside Active, a podcast about active managers that
goes beyond sound bites and headlines and looks deeper into
their processes, challenges and philosophies and security selection. I'm David Cohne,
i lead mutual fund and active Research at Bloomberg Intelligence. Today,
my cost is Christopher Kine, us quantitative strategist at Bloomberg Intelligence. Chris,
thank you for joining me today.
Speaker 2 (00:34):
Thank you so much for having me. David.
Speaker 1 (00:36):
So, you wrote interesting note last month on quality stocks
trading near their most expensive levels over the past twenty
five years. Is that still the case?
Speaker 2 (00:45):
Yes, it is still the case. I mean quality has
been certainly the most expensive factor from a historical perspective.
Now for a while. You know, our bi quality we
keep it pretty simple and we just consider profitability metrics
like r O E ro see as well as low leverage.
So you know, when you look at the top Quintown
on the Russell one thousand is trading over four and
(01:05):
a half time sales versus just over one time sales
for the lowest, lowest stock quality Quintal. So that's about
over three and a half times more expensive, which is
one of the most expensive readings we've seen. I will
say also, though, that you know, the profitability of these stocks,
of these high quality stocks are much elevated compared to history.
Obviously high profitability will you know, high quality will always
(01:28):
have higher profitability. But when you look at the spread
between the probitability of low and high quality right now,
it's very wide, So you would think there is some
fundamental support though the valuations are very stretched.
Speaker 1 (01:40):
Great, well, I'm sure today's guest has a great take
on valuations. And without further ado, i'd like to welcome
Sid Jane to the podcast. Sid is deputy portfolio manager
at GQG Partners. Sid, thank you for joining us today.
Speaker 3 (01:55):
Thanks for having me on. Guys.
Speaker 1 (01:58):
So I have to start with the research note your
firm recently published. You know, I couldn't I really think
that's the best way to start. So you put out
a note called dot com on Steroids. In the note,
you know, your firm says that today's market, you know,
could actually be worse than the dot com bubble, and
your firm argues that, you know, many of today's big
(02:20):
tech names represent backward looking quality, not forward with looking quality.
So you know, my question is, you know, what are
the clearest quantifiable metrics, say canaries in the coal mine,
that in your view, distinguished one from the other.
Speaker 2 (02:36):
Yeah.
Speaker 4 (02:37):
Absolutely, And I think to kick things off, it's important
to understand some of our history with the technology sector
where we're not perma bears by any means. We've been
actually quite bullish and constructive on the sector for better
part of our firm's history.
Speaker 3 (02:50):
Of the past decade.
Speaker 4 (02:52):
What has caused us to get nervous is this new
investment cycle that you're seeing. And if you study again history,
when you see major spikes in CAPEX and this is
on present level of investment you're seeing right now, that
usually tends put poorly for forward looking equity returns. And
(03:12):
so that's one metric where it's spiking CAPEX. And you've
seen this in the past, whether it's the railroad boom,
electricity boom, internet boom twenty five years ago. That gives
us pause, especially when there's really no clear evidence of
an ROI on the trillions of dollars investment that are
being debated today. The second thing that keeps us nervous
is just decelerating revenue growth. These companies, big tech companies
(03:36):
were growing twenty thirty percent like Clockwork pre COVID, whereas
now we believe the growth runaway is significantly less than
what existed before. I mean, digital ad penetration is now
running at seventy percent of over advertising. The metas Googles
of the world cannot go twenty thirty percent sustainably anymore.
I mean, same with Amazon's Microsoft. They're all slowing down structurally.
(04:00):
And so the combination of well of names, high multiples
and growth decelerating has problems been all over it. And
last thing I'll say is the accounting shenanigans. And this
is a little bit less quantifiable, but it was a
lot of press that I'm sure you guys have read about.
I mean, the circular vendor financing that you're seeing between
Nvidia and open Ai, or today's AMD deal that usually
(04:21):
comes at the very end of a cycle. So these
are some of the data points that causes to believe
that the best years are over for vast majority the
technology space. Part to be a large cap the AI winner,
so to speak.
Speaker 2 (04:35):
Interesting, very interesting. So you're talking about slowing growth, you know,
I was wondering, you know, quality of all the factors,
you know, tends to have the highest variance if you will,
of factor definitions, you know, because you know it's not
maybe as straightforward as a value or momentum. So do
you have explicit growth elements in your quality factor? I've
(04:58):
seen some quants do that, some not. Do you have
that component in your quality factor? Yeah?
Speaker 3 (05:04):
So growth, we like growing companies.
Speaker 4 (05:08):
We don't generally buy companies that are in secular decline.
But growth in and of itself is not what we're
looking for. That's the only variable that matters. And so
the way we think about investing is we want to
compound it roughly ten percent annually, and we get there
through a function of earnings per share growth plus dividend yield.
(05:31):
That combination gets you there. And so we're equally comfortable
owning software companies that get you to that tot re
turn predominantly from the growth side, as well as energy
companies where there's a much growth but you're getting a
massive buyback and dividend return, and we're equally comfortable flexing
both sides of that lever So it doesn't just have
to be.
Speaker 2 (05:50):
Growth awesome, thank you.
Speaker 1 (05:53):
So I know, I know you know with your firm,
you know it's a big approach with durable earnings rather
than you know, typical growth or value labels. How do you,
I guess, distinguish between durable earnings from just optimistic growth assumptions.
Speaker 4 (06:08):
So I think one area where we'd have maybe have
a bit of a differential view is truly appreciate long
term capital cycles. And this goes back to our founder
in Cio Rajiev having a thirty year track record investing
in developed markets, emerging markets, and everything in between. And
once you've seen enough cycle that forced you to appreciate
(06:30):
that everything experience goes through this. I mean, have you
wrote a white paper action on the semiconductor sector. I
think it was back in twenty seventeen House saying this
has become the new growth sector and we've got a
lot of pushback saying, how can you say that semic
corectors haven't.
Speaker 3 (06:43):
Grown in ages?
Speaker 4 (06:45):
And so you do see those and I think, for example,
if you look at today, we believe a lot of
the technology sectors are very late cycle. The growth is
slowing down, and the addressable market is just a lot
less than it used to be. Is on going from
twenty thirty percent revenue growth to ten percent, that's problematic
(07:05):
We're also very focused on the rate of change of growth.
So it's not just is it growing twenty percent a year,
but what direction is that heading? And that goes to
our definition of forward looking quality, is accelerating or decelerating,
and so that's a much bigger focus of our process.
So if you look at the energy space, we are
(07:27):
one of the few quality managers that made a large
pivot into energy back in twenty twenty one. Where people
have thought this was secular decline, our view was that's
the top of a cycle where you've seen most of
the industries underwater, not making much money, massive under investment,
and that will normalize. And that's how we think about
that in terms of the longer term cycle. That's a
(07:47):
big portion of how we deploy capital.
Speaker 1 (07:50):
So, you know, you mentioned, you know quality. Obviously, one
of the funds I really wanted to kind of focus
in is the gqg US Quality Value Fund ticker gq
ep X, And so you know, if you look at
the description, you know, invest in high quality companies with
attractively priced future growth products. How does this fund different
(08:11):
process or constraints from you know, your broader quality durable
earning philosophy.
Speaker 3 (08:17):
Yeah, sure. So there's.
Speaker 4 (08:20):
The investible The universe of names we choose from is
actually the exact same. So every name that we will
own on the value strategy has to meet our definition
of forward looking quality. So story that's improving has barriers
to enter, a strong cashoder, turner, equity and all of
that large chat focused. So that's the same. What is
(08:41):
different is where the returns are coming from. So, as
I mentioned, we go we want to get high single
digit load double edit total return with earnings, growth and
dividend yield. The growth strategy can go anywhere in between.
The value strategy will focus on the companies that pay
the yield. It's so usually the lower multiple names within
(09:05):
our investible universe, with a much greater focus on dividend yield.
So if you think from a scale of one to ten,
one being deep value, ten being super fast growth or
growth strategy will usually grow go anywhere between a three
to seven on that spectrum, the value strategy will be
(09:25):
between a three to five. Such a smaller subsector over
quality universe, and sometimes the strategy looked exactly the same
because the growth strategy can go everywhere in between.
Speaker 2 (09:36):
I would love to hear about You kind of alluded
to this a bit in your last answer, but you know,
I would love to hear about what's systematic, what's discretionary,
and how that process kind of weaves in together. You know,
I talked to a lot of clients that want to
do quant but maybe they don't want to do it
in a completely systematic way, right, they want to use
(09:58):
their own discretion. So is it like you have, you know,
a universe that's filtered for you quantitatively and then you
do more research on it, or how does that process work.
Speaker 3 (10:10):
It's a great question.
Speaker 4 (10:11):
At the end of the day, we will always be
a discretionary shop. We are fundamental Bondo stock managers, but
we believe heavily in using quant as almost like guardrails
on the process. So we have a team of quant
analysts and they help monitor things as factor exposures, what
factors are working, whatnot, doing historical back testing, making sure
(10:33):
we're not making any obvious mistakes. So, for example, one
thing we look at is what factor works in each country,
and it's not the same fact that it's work across
the world. So for example, if you look at China,
one factor that has proven pretty effective longer term is
divid and yield, and so our viob is let's maximize
the odds as much as we can and focus on
(10:55):
companies that have a yield versus purely growth. Now we
can buy growthy names, but the job is to just
improve the odds.
Speaker 3 (11:02):
As much as you can.
Speaker 4 (11:04):
As I mentioned the capex, we back to sectors that
are seeing significant CAPEX increases generally tend to underperform, and
so we monitor as those factors. But at the end
of the day, we are a bottom up shop. It's
another tool in our toolkit.
Speaker 2 (11:17):
Awesome, thank you so much. I would guess it's a similar,
you know answer, But as I kind of mentioned previously,
like quality definitely has the biggest variance of any quant factor,
and I've seen quants have wildly different definitions, and I
always ask, like, how do you weight the components of
(11:37):
your quality factor? Like, typically I see profitability as probably
the main thing, but obviously other things like margins and
stability of fundamentals and all this kind of stuff. So like,
is the waiting that you give to each of those
is that going to change kind of based on the
environment we're in, or do you have some kind of
structure in your mind of the weighting of the different components.
Speaker 4 (12:00):
So there's a couple of things that change. One is
the market environment also does matter. So for example, the
pre COVID era, we were much more focused on growth,
revenue growth. When it's a zero interest rate world where
you're struggling to get economic growth, earnings growth in most
major sectors, we are willing to pay a premium for
the fastest growing, best companies, whereas today it's a bit murkier.
(12:23):
It's a much higher interest rate world. You have to
be more valuation sensitive, and we do think there's a
lot of earnings risks from.
Speaker 3 (12:29):
The higher revenue growth names. But that's number one.
Speaker 4 (12:31):
Number two, and this might be even more important, is
that we look at all the same factors that you
mentioned in profitability, margins, et cetera. But we are much
more focused on rate of change, the second derivative of
those factors. As you mentioned the beginning, some of these
quality companies today have very strong profits, strong returns today,
(12:52):
but the question is next five year do they mean revert,
which is what we think that will start happening. That's
much less attractive than a company or a sector that
is at the trophy of a cycle. Maybe improving take
energy a few years ago, utilities over the past twelve
to twenty four months, which you're much more positive on.
And so that rate of change is what I think
is differentiates us versus many other quality oriented fundamental managers
(13:15):
out there.
Speaker 2 (13:17):
Awesome. I guess my last question here is what about
other factors, Like we talked about value, we talked about quality,
like does price momentum matter at all, does low risk
matter at all, or any other factors that kind of
add into your process.
Speaker 4 (13:32):
So I think historically, if you go back, one of
the factors, and this is an output not an input,
is that we do tend to have a bit of
a momentum overlay on our strategies. And the reason for
that is a fundamental reason is we like to buy
improving stories, not getcheries. So that typically correlates with strong
price momentum as well, and so it's rare. We want
(13:53):
to be aware which sectors are seeing strong price momentum
and not and understanding what is a fundamental reason for that.
We don't have to buy based on just great price action,
but if a stock is clearly breaking down, we want
to know why because we focus on the largest companies
in the world. Is a hyper efficient market, and we
(14:13):
have deep respect for price section and that it has
been longer term guardrails to our process making sure we're
not a stock goes down twenty you buy it looks
cheap because another twenty buy it and the classic value
trapped territory. So price pomentum does matter to us.
Speaker 1 (14:29):
So your research process integrates not just traditional analysis, but
also incorporates, you know, journalists, domain experts, others. Can you
share an example of, you know where a non traditional
perspective may have shifted your investment view.
Speaker 4 (14:46):
Absolutely, and it's the non traditional team that truly has
some of the most differentiated views on our investment team.
Where these are folks who have previously worked as investigated journals, journalists.
There's the Wall Street journal or Barons or so Reuters,
and they approached the world very differently. They're not actually
(15:06):
allowed to talk to the investment team the traditional side.
They're working in a vacuum. They don't read seal side research.
They actually go on the ground and talk to people,
whether it's former employees, regulators and things of that sort.
And they've been a couple of examples where it's helped
avoid blow ups but also find incredibly attractive opportunities.
Speaker 3 (15:25):
So I'll give a few.
Speaker 4 (15:27):
One would have been the technology sector. Actually, back in
twenty twenty one, as I mentioned earlier, we made a
large pivot from IT tech to energy, which paid out
well in twenty twenty two. One of the interesting data
points we found was the non traditional team had been
talking to a lot of recruiters in Silicon Valley and
the feedback they started hearing by summer twenty twenty one,
(15:48):
where job offers were getting yanked. You're seeing reduced hiring
across the board. And that was surprising because at that
point you might remember, the technology companies were talking about growth,
very strong growth into perpetuity revenue, strong, business outlooks strong,
but quietly.
Speaker 3 (16:05):
They weren't hiring people anymore.
Speaker 4 (16:07):
And so when you see in disconnects like that, that
cast your attention. Now, that's not the only data point
we looked at, but that helped fit this mosaic that
maybe things aren't all hunky dory the way people thought
they were back in twenty twenty one. Another example would
be on the emerging market side. We did a lot
of work a few years ago on a coffee company
called luckin Coffee in China, which maybe I remember it
(16:29):
was a very hot IPO, supposed to be the next
star Books of China. Our non traditional team did a
lot of work and they were able to find core
filings that show the founder at a criminal track record,
obviously was not being talked about on the prospectus, and
we were able to avoid that company ended up becoming
a fraud a few years later. And so we've seen
(16:50):
it add a lot of value in terms of truly
differentiated insights versus what you read from Wall Street, the
echo chamber of Wall Street.
Speaker 2 (16:57):
That's interesting about Luck And I remember that IPO that
was a hot IPO. I didn't realize it was a fraud. Wow,
good good job avoiding that one. I would love to
hear about like stock waiting schemes, you know, is it
just like weight? Is there a discretion amount of waiting?
Is there like a quant process like a Marcowitz type situation?
(17:18):
How do you think about waiting your stocks?
Speaker 4 (17:22):
So we've the camp of hold all your eggs in
one basket and watch it closely. So typically the top
ten names can be roughly fifty percent of our strategy.
Top twenty seventy percent and the biggest name will be
ten percent for context, and so we do like to
run a concentrated strategy, and.
Speaker 3 (17:40):
The way we think about it is almost from.
Speaker 4 (17:42):
A credit perspective or a credit mindset, where it's not
about find the names that have the most raw upside,
it's find the names where it can lose.
Speaker 3 (17:52):
The least amount of money in.
Speaker 4 (17:54):
And so a name could have three hundred percent upside,
but if you're wrong, you lose fifty percent. That deserves
a spat on the portfolio. But we wouldn't make it
a ten percent position. So the quality of the business
plays a huge role in terms of how we size
these bets. The second thing is also we're focused on
very large liquid names because we do change our minds
a lot, and that's what's kept us in the game
(18:15):
over the long run. Where the beauty about the process
here is it's a super lean team, very fast decision making,
and so the moment we see the earnings deteriorate, we
can sell out a large position overnight. There's no investment committee,
there's no deck you have to put together, and so
that really is a risk management process is cutting back
losses when the markets move against you materially, earnings are deteriorating,
(18:38):
or there's a macro risk potentially looming. And I think
the historical context for that is when you think of
Ragie's early career, I mean, starting off in the nineties
as an em manager, you're forced to risk management is
deeply ingrained in the DNA, and so that's what still
plays a role. So there's not a stop loss mechanism
or anything like that, use of much faster, quick when
(19:01):
you see fundamentals even marginally deteriorate.
Speaker 2 (19:05):
That's so interesting. Yeah, you kind of mentioned like using
price momentum as a bit of a risk management to whenounce.
You kind of got ahead of me on my next question,
which was like about risk management. So basically, it's not
a systematic process. It's not a stop loss in the market.
You assess the market, you assess you know, your view
of earnings or the price momentum or something, and then
(19:27):
you can quickly make decision to pull the plug per se,
with no investment meetings or investment committees or anything like
that exactly.
Speaker 4 (19:36):
And in our first gut reaction, when a name moves
maturely against the frankly, is that we're wrong until proven otherwise.
Speaker 3 (19:44):
A lot of managers like.
Speaker 4 (19:46):
To view the in terms of a stall goes down
twenty percent, you should buy more and more attractively priced,
which is true in theory, but that also assumes that
the fundamentals haven't changed at all. The reality of large
gap investing today, it's so efficient that generally speaking, when
I stop gaps on twenty percent, don you something is
fundamentally changed, And it could be the other way around
(20:08):
as well. Sawcolls are twenty thirty percent large care well covered.
Something's happened, and you better understand why.
Speaker 2 (20:15):
I totally agree.
Speaker 1 (20:17):
So I want to go back to valuation just a
little bit. You know, if you have a situation where
there's a very high quality company but it's trading at
a less than ideal valuation, how do you look at it,
you know, you know, in terms of you know, waiting,
you know, risking the opportunity gets away, or kind of
(20:37):
going into it at what you may not consider an
ideal valuation.
Speaker 3 (20:42):
Yeah, So I think the a couple of things. One
is that we actually urge all the.
Speaker 4 (20:49):
Investment team members to look at valuation last when it
comes to the analysis. The reason for that is if
you start, let's say I tell you to look at
Into Surgical for example, it's a high quality robotics company.
This name trad is that generally fifty to seventy times
earning is always super expensive. If you start with valuation first,
(21:10):
it makes it, it doesn't. You need to first understand
the business, the long term growth runway, the barriers to entry,
and then you can value it. So it's a timing
thing we would urge everyone to do. Second is you
need to have conviction in the long term runway and
the barriers. And when we like to say that the
air gets very thin at the top of the mountain,
(21:31):
you can't have any misses.
Speaker 3 (21:32):
We're fine paying up and we paid.
Speaker 4 (21:35):
We've owned companies in the past trading at sixty seventy
times revenue in the past rarely, but it does happen.
You have to have conviction of the earning trajectory and
there's no room for error. You also have to have
conviction that the street is missing something. Where this is
a high multiple name that street expects to grow a
twenty percent a year, but you think it's a thirty
(21:55):
percent grower. That's extremely interesting. The vice versa is not
where stream expects thirty percent, you think it's will be
twenty percent. So again, the rate of change and the
disconnect versus market expectation matters a lot, especially when it's
such a high multiple name you have no room brearer.
Last thing I'll say is that there's an opportunity cost
element where there's a lot of big world out there,
(22:19):
what is what is the opportunity on Maybe there's another sector,
another company that's more interesting, that's more attractively valued, which
is why I said earlier where pre COVID we felt
much more comfortable paying up for growth because there weren't
a million options out there. Today, the investible universe, whether
it's from a country perspective, you look at emerging markets
(22:40):
or Europe, it's much broader than it's been for in
a very long time, and so we feel less the
need to chase high multiple names today.
Speaker 1 (22:49):
Okay, and we just got one more question, and this
kind of a second waiting question. You know, the US
equity Value fund is a US quality value fund, is
non diversified, so you know it's it's typically going to
be more concentrated than some of the more diversified funds.
How do you know, just look at position sizing in
(23:09):
terms of concentration and you know balancing risk reward trade
offs of fewer names.
Speaker 4 (23:17):
So our view is you have to make big bets.
That's the reason for active management. We do not believe
in Benchamarhaggey. We are completely benchmark agnostic, and you can
see by our tech positioning where it's gone from seventy
percent tech to zero, back to seventy and everything in between.
But the caveat is when you're making these big bets,
you do have to have a deep respect for price
(23:38):
action and selling quickly when the fundamentals are deteriorating. The
easiest way to blow up is you have a large position.
That's the fundamentals are getting worse and you don't cut
back risk immediately, which is why if you look at
our turnover, it's typically north of fifty percent, which is
quite high for a long only manager.
Speaker 3 (23:58):
And then that is part of the risk manage element.
Speaker 4 (24:01):
We also believe in macro in terms of a risk
off tool.
Speaker 3 (24:07):
We are a bottom up shop.
Speaker 4 (24:09):
We won't buy a name because of a good macro setup,
but if we feel there's a clear macro risk pending,
we'll cut back risk aggressively.
Speaker 3 (24:16):
And this goes back to again Rodger being an EA.
Speaker 4 (24:18):
Manager hard back in the thirties and in the nineties
and then so a class example would be back in
twenty twenty one twenty twenty two, where the mistake a
lot of quality managers missed made was not appreciating macro
where what is the impact of higher rates, higher inflation
on tech valuations. That was a fundamental issue that many
(24:39):
quality managers missed. But our view was the macro. Respect
for macros helped us preserve capital in bear markets. So
these are some of the things that play a role
in terms of how we size bets, how risk on
we are at any given moment and not that makes sense.
Speaker 1 (24:54):
Well, unfortunately we have to end here, but this is
a great conversation. Thank you so much said for.
Speaker 3 (24:59):
Joining us shoe the time. Guys, thanks again, thank you.
Speaker 1 (25:02):
And Chris, thanks again for being my host. Thank you,
and I want to thank our listeners. If you liked
the episode, please subscribe and leave a review. Also, if
you'd like to see more of our research, go to
bi fund go for fun research and b I S
t o X go for stock research on the Bloomberg
terminal until our next episode. This is David Cone with
(25:24):
Inside Active
Host
Gina Martin Adams
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