Episode Transcript
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Speaker 1 (00:02):
Bloomberg Audio Studios, Podcasts, Radio News. Welcome to Maren Talks Money,
the podcast in which people who know the markets explain
the markets.
Speaker 2 (00:21):
I'm Maren thumset Web.
Speaker 1 (00:23):
This week I'm speaking with Steve how quantitative researcher at Bloomberg.
Speaker 2 (00:27):
Now, Steve, thank you very much for joining us.
Speaker 3 (00:29):
Very good of you, very nice to you are to
speak with you marine, and thank you for the invitation.
Speaker 2 (00:35):
I wanted to talk to you this week because this week.
Speaker 1 (00:36):
Is macro week, right, everybody else is going to be
talking Trump, talking tariffs, talking inflation, all this kind of thing,
and so we're just going to leave that for everybody
else because, to be honest, no one really knows what's
going to happen with the tariffs. No one really knows
what the macro effects are going to be. There's a
lot written on and we are going to go a
little bit more micro and talk about things that directly
(00:59):
affect company that we can understand. So in particular, I
don't know innovation, how pressing power works, how analysts look
at companies, all those kind of things, so all the
areas that are specific to your work. So what we're
going to try and do is not mentioned tariffs once
in the whole forty minutes that we're going to speak.
Speaker 2 (01:20):
It's going to be like a challenge between us. Okay,
no mention of tariffs.
Speaker 4 (01:24):
Can we try? Yes?
Speaker 1 (01:26):
Okay, all right, everyone's going to let us know immediately
if we fail, of course. And so I want to
start by talking about the thing that, of course everyone
talked about last week, about innovation discovery, in particular about AI.
So everything that's happened over the last couple of years
with AI has really been the most extraordinary wave of
(01:48):
innovation and change. And then we had the news on
Deep Seek of course only hit the market last week.
Better of fact, WITH was out there several weeks before that,
and that represents massive change as well. So that's exciting.
But there's a lot else out there, right, It's not
just AI at the moment. We're in the middle of
an extraordinary wave of technological change. One of the most
(02:08):
interesting parts for you.
Speaker 3 (02:09):
So first of all, a little bit of background myself.
I'm a quiet researcher at Bloomberugh in disease and I
create systematic strategies where we use, you know, sort of
different signals that are trying to identify stocks systematically to
create investment strategies. And one of the recent wides we've
created is looking at innovation. How do you identify innovation
in the systematic fashion? And what we've found this turns
(02:31):
out that you can use R and D expenditures as
a signal. And this is not new, right, companies have
researchers have looked at R and D spending, you know,
for a long time and indeed identifies companies that are
exposed innovative. But what we have found is actually the
more indicative of research capability, innovative capability. It is not
(02:51):
so much the absolute amount of R and D spending,
but the persistence. Right when we screen for companies that
spend and persistently row, they're earned the expanditure year on
year for say three trailing years. Right, without doing just
so anything else, right, you autonomously pick up companies that
are actually exposed very innovative, and should get into details
(03:13):
as to how we actually show that they are indeed innovative,
because it's such a you know, sort of abstract thing.
And what's really remarkable is that if you say, screened
the US large MidCap companies, you know, by this metric
right and sort of market cap weave them with some
sort of camping and weights, so you get back exactly
(03:33):
the cues the Nasdaq Stock Exchange, which of course is
just happens to be everything that's listed on the NASTS
exchange and not you know, explicitly screening for innovation, which
we think thought it was very fascinating. And along the
way you also do pick up you know, of course
AI technology, but you also pick up things such as
pharmaceutical innovations. You know Eli Lilly, you know which invented
(03:55):
along with the noval nor disc. You know, the GP
one drugs, you know, the more weight loss want Wonder drug.
Speaker 1 (04:01):
So you look at companies and you can see trailing
R and D spend over over three years going up
and up and up, and that gives you some sense
that there's interesting innovations going on there, but of course
that doesn't help you choose between people who are using
their innovative abilities successfully with the product that will come
to market and those that are not. And it also
doesn't help you pick up the companies. So let's go
(04:23):
back to AI for example. Well, one of the things
that was much discussed last week was the fact that
so many companies are spending so much money, possibly on
the wrong thing. So it's not helping you distinguish between
good R and D and pointless R and D. And
particularly when you get, for example, to their bubble situation
where you get that massive capex spending over a series
(04:44):
of years, but you only get one winner.
Speaker 3 (04:47):
Well, let's unpack that idea a lot of bits. So
first of all, let's get back to the idea of
for just simply screen for companies with persistent R and
D spending. You will think exactly like, how would I
be able to tell whether the company is just throwing
a bunch of money after bad right, you know, and
there's way one power building and the money is just
being set on fire. That indeed, that is possibility. And
(05:08):
what is surprising is it comes out when you screen
for companies that persistently spend the R and D instead
of just sort of you know, one.
Speaker 4 (05:16):
On and off.
Speaker 3 (05:17):
Uh, these tend to be companies that actually have the
ascertainability or knowledge about innovative success. And that has been
well documented in the academic literature that there is actually
persistence in skills, whether it's you know, sort of investing
skills or innovative skills, right, And it turns out without
explicity screening. So if you look at companies that persistently
(05:37):
spend R and D, they tend to be companies with
strong cash flows, internally generated cash flows, strong profitability, and high.
Speaker 4 (05:44):
And low leverage.
Speaker 3 (05:46):
And the reason is it turns out is because R
and D is a fundamentally opaque and asymmetric information activity. Right.
It is highly uncertain, it's extremely cost costly, So companies
are going to struggle to raise external financing, whether it's
debt or issue. You know, you should equity definance it.
So only companies that are confident in its own ability
(06:09):
to innovate to translate that innovatives that R and D
into valuable intensible capital that will produce cash flow streams
down the road, will actually do it in a persistent fashion.
And that's one thing. For example, you see when you
take a company, say R ETF for example, right, look
at the companies that are in the ETF. You know
they actually have very high percentage of R and D
(06:30):
expanditures as a share of net sales. Right, that's a
typical way people measure R and D. But if you
look at the companies that have persistent R and D
spending in that profolio is not very high because those
companies are not persistently profitable. So the R and D
spending is on and off. Right in one year they
spend a time and the next year run out of money,
they don't spend any And the companies that we do
pick up, you know, in our you know, methodology, then
(06:53):
is actually the persistence, right there is actually the embedded
quality screen. And I think that combine that with the
fact that if you're just doing a market cap waiting,
which you know sort of people do these days, you know,
sort of matter of factly because it's become the convention.
But you think about what it really means is that
there is a sense of expost market validation, right that
(07:14):
having spend all this money exposed you got you're getting
the market valuation because you've produced intensible capital that's actually
spinning out cash flows, and and and and and and
That's what's different about today's stock market compared to say
the bubble of two thousand, is that the bubble today
is in the quality stocks, right. The bubble today is
(07:36):
in the companies that are tremendously profitable, so much so
they seem to have escaped velocity, right, they don't. They
don't require credit, They don't require financing because they finance themselves.
Speaker 1 (07:47):
Okay, So we have this link between a company that
that has regular R and D spending and quality and
that that's that's the important part of the link. That
R and D spending as long as it's regular, inconsistent,
and rising, is also indicative of a high quality company.
Speaker 4 (08:05):
M h. Yeah.
Speaker 2 (08:05):
If we're buying those companies in the US at the moment,
we're really paying up for them.
Speaker 4 (08:10):
Aren't we quite right?
Speaker 3 (08:12):
Yeah, I mean, valuation has absolutely climbed over the last decade,
I think ten years ago, you know, or more, I guess.
So when Buffett started buying Apple that you know, tax
stocks were really cheap, right, and you know how many
years have we heard, you know, the sort of forecasts
of EXCA returns for US equities being lower than the
(08:35):
rest of the world and keeps being proven wrong. Is
because profitability keeps surprising to the upside, and along with it,
valuation paid for them because there was this you know,
desire for quality assets.
Speaker 1 (08:48):
And do you think that that rising and persistent R
and D is a thing that is driving earnings forward.
Speaker 2 (08:55):
Oh, just and justifies the valuations.
Speaker 3 (08:59):
Yeah, absolutely, thing we do in our white paper, which
your listeners can look up when they just search a
Bloomberok innovation factor and they'll find a blog.
Speaker 2 (09:08):
In the blog, we'll put a link in the show notes.
We don't have to search, no searching required. It will
be in the show notes.
Speaker 3 (09:14):
Perfect for you. So you can take a look at
the paper. And what we show is that if you
sort of you know, do an experiment where you go
back in history and identify companies that were persistently innovative
in biomasure right, having spent three consecutive years of growing
R and D, and look at that subsequent five year
(09:34):
sort of key fundamental performances, you will see that these
companies showed our strongest growth in revenue, net income free,
cash flow free cash for pressure and you know, just
along all the fundamental metrics, and that particularly accelerated over
the last ten years. And so, in other words, the
(09:59):
selection is not just based on valuation expansion. We actually
identified companies that produced intention by capital that translated into
our earnings and that is the reason why these companies
are being rewarded by the market and This is what
is really particularly reassuring is that this is a phenomenon
that we've documented across the globe. It's not just in
(10:20):
the US. It is in Europe as well, is in
Asia as well.
Speaker 1 (10:23):
Okay, interesting, but when we look at that, presumably, I'm well,
presumably you see the majority of the companies that fit
these fit these factors in the US. I mean, that's
where we all perceive the main innovation in listed markets
being let's put China to one side for a moment.
If we're looking at the US, the UK, Europe, et cetera.
It is in the US that we see that innovation
(10:45):
in the main and that's why we've seen that huge
valuation expansion there, which has been the main driver of
the US exceptionalism in the US outperformance since twenty fifteen
or so. It is the perception and possibly the reality
that all the innovation is in the US. That is
that the case, or are you actually seeing that persistence
of R and D spending in companies in say Europe
(11:06):
or the UK as well.
Speaker 4 (11:08):
Well?
Speaker 3 (11:09):
So you're absolutely right in that the bulk of the
dollar you know, activity, innovation activity probably takes place in
the US just because of the size of the market.
And also I think it was Jeff Bezos who recently
made it remark that observation that was really insightful is
because of the US risk capital markets that really finances
(11:31):
you know, innovative activities. But that being said, there is
less innovative activities, aren't the activity in Europe, But where
it does exist, markets actually rewarded those activities similarly as well. Right,
you saw this dramatic outperformance, and you see, you know,
market follows wherever the activity takes place. So whereas you
(11:54):
used to take place more in Germany, Switzerland, you know,
sort of in a farmer space, now micro it's more
northward towards US, you know, the Netherlands because of SML,
or because or Denmark because of a novel nor disc
and the associate you know, supply chain as well.
Speaker 1 (12:10):
Okay, so the innovation they you see in Europe is
very much in the farmer area.
Speaker 3 (12:14):
And and AI for that matter, ASML and their suppliers.
Speaker 2 (12:18):
Right, uh huh uh huh okay. And the UK can
you check us a bone here?
Speaker 3 (12:24):
Well, you know, actually interestingly, you know UK, I recently
noticed the company in my research on you know, we
will get you. Later on pressing power, I noticed that
there was a company called R E l X, and
I was very curious what it is because the stock
is absolutely ripping, and I realized it's actually a massive
AI beneficiary. Because it turns out there, I think you
(12:44):
may be familiar with the company, they own about half
the world's academic you know, publications, right, journals. And you
would have thought before AI that this was a dead
wood industry like who reads anymore? Led along academic journals,
but it turns out this is basically a vast of
extremely valuable data and AI. It's all about the training data.
(13:05):
Uh and and and they're definitely benefiting from it.
Speaker 2 (13:08):
Okay, that's interesting.
Speaker 3 (13:10):
Oh, I mean beyond that, of course, there is the
farmer angle and you know Astrosdenaga and so on. But yeah,
but that's more traditional.
Speaker 1 (13:16):
Okay, let's move on to talk about this pricing power subject.
But before we get there, how does one invest in
the companies that you've been talking about? Is there something
we can do to get access to these persistent R
and D spending quality companies across the board.
Speaker 3 (13:33):
So with respect to innovation, right you're talking about, Yeah,
we have a Bloomberg indices launched in the R and
D industries.
Speaker 4 (13:41):
So B R and D is the index.
Speaker 3 (13:43):
But then we also have a smaller set of companies
with a higher convication that's called be invent right, so
easy to remember, Monka. And on the back of that,
we have actually licensed the indices to ETF features. The
First Trust, for example, has licensed being then to create
an ETF with a ticket R and D in America.
(14:05):
And we're also I personally think that this concept applies
equally well to Europe. And part of the reason why
I'm in London this week is to try to persuade
people that Europe ought to invest in the South and
or to invest in innovation, because you know, the race
is on and you know, by both necessity and reward,
(14:28):
I think this actually presents a very interesting alternative to
US innovation.
Speaker 1 (14:34):
Okay, so if and if that happens, we might actually
see the European markets pick up a little, which we
already are this year, right, we're already seeing great performance
from European markets relative to the US.
Speaker 4 (14:42):
Oh absolutely abslightly better.
Speaker 3 (14:44):
Yeah, yeah, German stocks are killing it, right, you know,
everyone's talking about Germany going into a procession. But the
decks keep hitting a what time highs and you know,
and I think that's part of the reason why we're
seeing this pivot of AI broaden out right away from
the first phase of pigs and shovels to more applications
(15:06):
software and you know, with you know AI, last week's
news about AI being much cheaper to implement a much
more you know, sort of energy efficient, that means that
everybody else can start getting into the game. And that's
why software you know is actually doing very well.
Speaker 1 (15:21):
And it's yet another reminder, isn't it, which apparently people
do continually need that markets are not economies. Economies are
not markets, and markets can move in completely different directions
to economies depending on on the starting valuations.
Speaker 4 (15:35):
Hmm absolutely mm.
Speaker 1 (15:38):
Okay, right, So let's go back to what you were
saying about pricing power. I mean, this is one of
the basics of investing is that analysts and investors always
say they're looking for companies with modes with monopoly power
or agobly power of some kind and with the ability
to control their own pricing. So you would think that
(15:58):
that would be the kind of thing that we're be
very much out there in the market and you wouldn't
be able to find any pricing anomalies in that area.
But I think you're going to tell me that I'm wrong.
Speaker 3 (16:09):
Well, we're going to go back to I think you know,
eventually we'll always go back to the quality paradox. But indeed,
we've been looking at these accounts of pricing power because
over the last few years, so we were looking at
this two three years ago, inflation was all the rage,
and you know, everyone's asking how do we actually capture
pricing power?
Speaker 4 (16:28):
Pricing power?
Speaker 3 (16:30):
So everyone has their own ideas and there's qualitative ways
of you know, capturing it, and people will throw alls
of company names out there and claim that those companies
have pricing power. I've seen claims of our Tesla Hast
pricing power, Apple is pricing power, But does it.
Speaker 4 (16:44):
Really how do we actually know?
Speaker 3 (16:46):
So we sort of did a bit of work and
found that it turns out it's not so much profitable
companies that have pricing power, because high profit margins can
be eroded into right if you don't have pricing power.
So either if you look at the case of Apple, right,
you know, the flagship iPhone price has actually not changed
very much all over the last few years, even though
(17:09):
I'm sure cost has gone up, you know, tremendously for them.
So how do we actually then sort of capture companies
that do have pricing powers, in my opinion, in our opinion,
you look at not the level, but the stability, in
other words, the standard deviation of gross margins over the
last five years.
Speaker 4 (17:28):
Right.
Speaker 3 (17:28):
So again there's a certain theme to how we sort
of look at to our you know, systematic strategies here.
And it turns out that the reason we focus on
gross margins because it's the least manipulated you know, accounting metric,
you know, because it's just the difference between the top
line and the subtracting the variable costs, including our wages.
So the things that are more sensitive to inflationary shocks. Now,
(17:52):
if you have a company that have pricing power, then
if there's cost push shock, they can pass on a
cost to customers, and if gross margins growing indicative of
a demand shock, then they can supply into it and
drive down the margin towards their target. So that's why
we've constructed a measure where we look at companies with
(18:14):
the most stable gross margins.
Speaker 1 (18:16):
Okay, and so if you're looking at companies like this,
you're going to expect them to be in relatively niche
areas like the company you were just disgusting being in
an academic academic journals. This marcher not in an area
that other people are going to break into in a hurry,
is it.
Speaker 4 (18:32):
Indeed?
Speaker 3 (18:33):
Yeah, That's one An interesting thing that emerges from our
systematic you know so of our screen is that you
look at the companies that come out of the screen,
they look incredibly either boring or you know, not really
one you recognize. For example, one company that keeps popping
up in the American version of the Oppresing Power Indux
is this company called Cadence Design Systems.
Speaker 4 (18:53):
Have you heard of it?
Speaker 2 (18:55):
Chugs familiar, But I don't think I can straight up there,
I have no So.
Speaker 3 (18:59):
Caidence Design system they design software for designing microchips.
Speaker 2 (19:03):
Uh huh that does that boring? Yeah?
Speaker 4 (19:06):
Right?
Speaker 3 (19:06):
So in other words, they are not the ones manufacturing
the chips. That's a highly cyclical sector, right. Uh, that
comes with bone and bars of demand of traditionally consumer electronics.
They design the software with which uh, these manifesture these
chip designers design chips. In other words, you know, you
would even if your business is down a lot at
(19:28):
a MD or wherever you are, you're not going to
conceive of canceling your subscription to the software with which
you do your work. Right, So that's really what gives
them the pressing power is that they are supplier in
the verified space with which there's maybe a handful of
companies and continuing consolidation. Uh So that and it doesn't
attract the attention of regulators because it's not the category
(19:51):
that people think of because it's not consumer facing or
very glamorous, right, And that's how the pressing power is
actually maintained.
Speaker 1 (19:59):
This when you speak about companies like this and in
the category we were discussing for R and D equality, etc.
It sounds to me like you're making the case for
active investment. You're saying this market is it is not
particularly efficient. There's all sorts of anomalies out there. There's
lots of places where investors can go to find companies
that other people aren't looking at. Are you making the
(20:22):
case here for a shift back towards active investment or
are you really making the case for factor specifical sector
specific ETFs.
Speaker 4 (20:33):
That's a great question.
Speaker 3 (20:34):
I mean, so I have a somewhat controversial perhaps view
on this whole active passive debate. I don't think of
it as being I mean, I think the better word
is discretionary versus systematic. Right, Like what I just described
to you, the methodology, whether it's looking at the stability
(20:54):
of growth margins or the persistent R and D growth,
that's not particularly passive. As much as you think about
the traditional benchmark of just buying everything on the stock
market simply market capt weighted, right, this requires a certain
I think particular set of rules and actually involves pretty
(21:16):
sizeable turnovers in your portfolios, you know, on every rebalanced date,
and depending on the signal you're looking at that the
channel can be did quite high. So I don't know
if that means it's not in that case active in
some sense. Right, It's just it's not discretionary, right. The
process is rules based and fully systematic, and that gives
(21:40):
you the consistency.
Speaker 2 (21:41):
Yeah, so rules based active investing.
Speaker 4 (21:45):
I guess you could say so.
Speaker 3 (21:46):
I mean, you know there are quant funds out there,
you know, and would you consider quant funds to be
active or passive?
Speaker 2 (21:52):
Ooh, rules based active?
Speaker 1 (21:58):
But it's still from what you're saying it sounds like
an argument for active ETFs rather than a traditional active fund.
Speaker 3 (22:06):
I do think there is opportunity to the extand that
investors want to, you know, uh, take take a different
view on things and try to you know, sort of
capture the changing trends in the market, because I mean,
let's be frank, it is incredibly difficult, if not outright impossible,
to outperformed the S and P five Well, I mean
(22:28):
the B five hundred. You know context we're here, and
you know we're talking about Bloomberg five hundred index. Uh
and you know, for the matter, you know, a systematic
you know, R and D index that we have created here.
Like if you just simply have that you know, benchmark view,
you know, that gives you essentially a core holding that's
really hard to outperform. But then if you want to
(22:48):
do some things along along that, if you have sort
of microviews or micro industrial views, that's how you can
express it. In our opinion, you know, you should do
it in a systematic fashion.
Speaker 1 (23:00):
Yeah, fair enough, fair enough, Okay, Well, let's look at
one more of the things that you've been writing about recently,
which is about turnaround companies and the way that analyst
ratings might give clues as to whether those turnarounds. Oh
you wrote on that middle of last year.
Speaker 4 (23:18):
Right I did.
Speaker 3 (23:18):
Yeah, So yeah, that's that's another interesting idea that we
were looking at. So here bloomber of indices, we tried
to leverage the various types of data you know on
the terminal that I think somewhat unique, and I think
one thing is what everyone looks at is analyst ratings
(23:39):
and less opinions you know about stocks.
Speaker 4 (23:42):
Of course, you.
Speaker 3 (23:43):
Know, a first order intuitive thing when we look at
is just to buy all the stocks that analysts are
recommending you to buy. And we were thinking, is there
maybe a slightly different you know, views or approach to it?
In particular, can we think about the you know, companies
that the analysts are becoming more polish on And that
(24:05):
led us essentially to looking at this idea of looking
at analysts rating momentum but ignoring the ones that analysts
tell you to buy. So, you know, on the Bloomook terminal,
if you look up any stock and you type the
function A and R, you see a score going from
one to five, one being strong seale and five being
strong bys.
Speaker 4 (24:26):
If you just toss out the.
Speaker 3 (24:27):
Ones that have a rating of four and above in
other words, a buy or strong by and then you
look at the stocks whose consensus rating has improved the
most between the last six to twelve months, and you
buy those stocks. We found that that sets actually tended
to capture a set of companies that the way we
can think about summarizing them as being basically turn around companies,
(24:51):
companies that are sort of have fallen on hard times.
They were hated or not so much or not at
least not but love by analysts. But analysts are like
starting to change their minds on those stocks before converging
their consensus.
Speaker 4 (25:04):
If that makes sense.
Speaker 1 (25:05):
Yeah, So the general idea being that if you if
you're only looking at stocks that everyone already has a
buy on it, maybe.
Speaker 4 (25:11):
Too late indeed, so yes, so all the games are.
Speaker 1 (25:15):
In there, so you want to be looking for I mean, analysts,
they're going to be slightly late to things, aren't they
by definition, by the time everyone's caught hold of a story,
and so it's already underway.
Speaker 2 (25:25):
So it's it.
Speaker 1 (25:28):
Is it contrariant by something where people are beginning to
turn their minds. Yeah, because you've found you found the
bottom and you've found the catalyst, right.
Speaker 3 (25:36):
Yeah, I mean the way yeah, we think about is that, Yeah, analysts,
you know, over the long run, they're not wrong, they
can be late. By the time everybody comes to love
a stock, you know, and give it, you know, a
strong by rating, it tends to be that the price
has already reflected you know, that strong sentiment and good fundamentals.
(25:59):
So we are capturing here. You say, essentially that company
is just about turning around or from you know being
previously you know, having been in a bad fact of
fundamentals and that you know, sentiments to just about improving, right,
and that gives you that asymmetric risk award.
Speaker 1 (26:18):
So you've got an improvement score. Have you got any
examples in mind of companies that fit that mold right now?
Speaker 4 (26:24):
Yeah.
Speaker 3 (26:25):
So there's a few examples that we go into in
the white paper, which again we will.
Speaker 4 (26:30):
Linked to uh one way.
Speaker 3 (26:32):
Well, one of them is interesting recently is Oracle, Right.
Oracle you know was actually you know, having a hard
time until the whole AI thing you know, kicked off,
and you know, their consensus ratings were in the threes
and and then improving a bit. And then we you know,
the index sort of identify that company as say, you know,
(26:53):
essentially a company who's analysts are changing their minds on right,
And indeed, then we pick the stock and the stock
sort of goes of a lot because it catches this
AI you know, turn around and also generally I think
the sector having bottomed. So that's one example. And another
(27:14):
example we saw was actually Hershey's, right, Hershey's, uh, you
know in the chocolate you know industry, uh and.
Speaker 2 (27:25):
Terrible, terrible chocolate. Terrible chocolate.
Speaker 4 (27:28):
Was it? What's your chocolate choice? Milky?
Speaker 1 (27:32):
Well, they're very very dark chocolate and my kind of
lint eighty five person myself, so you know, Hershey's is inedible, inedible.
Speaker 3 (27:40):
Well, perhaps that's why that's carry on, that's why the
stock has fallen the hard times. And the stock did
fall on hart that much chocolate A yeah, so and
then you know it was getting hammered by the the
the chocolate commodity ripping and eating into their margins. And
then the stock, you know, was picked up because analyst
(28:02):
ratings finally started improving. Right from trailing six to twelve
month we take we'd take an average, and then we
saw basically the stock, you know, recovering. But then of course,
you know, and then maybe this is the point with
actively passive, is that because it's a fully passive, systematic
rules based you know, signal, you can pick up, we
pick up the stock, and then chocri rice, you know,
(28:23):
went down and shot up again, and the stock went
down again. So the index, the strategy didn't you know,
react to it as quickly, you know, as you would
if you were in a fully fully discretionary you know, strategy.
But but that's sort of the general idea.
Speaker 2 (28:37):
Okay, And is there an index for that as well?
Speaker 4 (28:40):
Oh?
Speaker 3 (28:40):
Yeah, so the indexes again very simple, B, A and R.
Is the index blone broke A N R okay?
Speaker 2 (28:47):
And is there a way to invest in that?
Speaker 4 (28:49):
Yeah?
Speaker 2 (28:50):
There is a for the ordinary investor, Yeah, there isn't.
Speaker 3 (28:53):
There is an ETF in America. That investor has licensed
the index and they ticklar upgrade up g.
Speaker 4 (29:01):
D uh that's upgrade.
Speaker 2 (29:04):
Very good.
Speaker 3 (29:07):
Actually, speaking of investment ways of investing, a Passion Pressing
Power index in America has also been been licensed. And
the ticker is p o.
Speaker 4 (29:17):
W A p w A.
Speaker 2 (29:19):
That's not too good. That's not too good.
Speaker 1 (29:21):
I'm always interested in the in these tickets and the
cleverness of some of them. You know, there's somebody out
there who does a great job on tickets, isn't it
who chooses those?
Speaker 4 (29:29):
Who chooses those?
Speaker 1 (29:30):
Maybe you knows that who worked when you when you
apply to have your ETF do you think of the
ticker and you ask them? Or is this someone clever
around the the the creators.
Speaker 3 (29:39):
You make, I think this typically comes from uh and yes,
someone creative on the as a manager issue side, you
know that, I think, Yeah, I like you marvel at
not just the tremendous creativity but the availability of some
of these tickets. You would have thought they'd been picked up.
But yes, like I was very pleasantly surprised that R
(30:02):
and D, you know, the ticker was actually available.
Speaker 4 (30:05):
But there you go.
Speaker 2 (30:07):
Mm hmm mmmmmm. Well interesting.
Speaker 1 (30:10):
And I suppose that this tells you about the relative
newness of the entirety of industry, doesn't it.
Speaker 3 (30:14):
Yeah, at least you know sort of. Well, I mean
in America it's not so new anymore. I mean, it's
all the rage. But but we're trying to see if
this become you know, the way in Europe as well.
Speaker 2 (30:27):
Yeah, so what are you working on at the moment, Steven.
Speaker 3 (30:30):
So right now, we're working on a couple of things.
One of them is we're trying to you know, think
about shareholder yield as a concept, you know, total shareholder return.
I'm writing a white paper on that topic. So I
don't know if you're familiar with the concept of shareholder yilding.
(30:50):
You know, there was you know, sort of not just
looking at dividends, but all forms in which companies can
return capital to shareholders, which includes buy back and debt reduction. Right. Uh,
this is not a particular new concept and it has
done well, but we have had given our own spin
as well at bloom Bloomberg Indices, where we not just
(31:14):
look at companies with strong total shareholder holder return, but
the companies that have the consistent historical fundamentals to be
ablity to afford those you know, strong total shareholder return.
In other words, we're looking at a long history of
free cash flow and capacity as a ship you know,
as a ratio to the total shareholder payout. That will
(31:37):
allow us to eliminate more false positives that you might
pick up, you know, if you just screened naively for
companies that happen to have very large total shareholder return.
Speaker 1 (31:48):
Okay, interesting, So that's the results of that would be
something for us to look out for, assuming we can't
see them quite yet.
Speaker 2 (31:55):
Thank you, Steven.
Speaker 1 (31:57):
Is it anything that you would like to tell our
listeners that we have not talked about yet, Any any
perfect little insights, any brilliant investment recommendations, anything we haven't
discussed that you feel they should know.
Speaker 3 (32:10):
One subject we are looking more active now is the
idea of more macro aware investments because I think we've
exited the age of moderation, you know, the monitor policy,
which used to be the only showing in town. I
think I taken a back seat, and we are now
(32:32):
seeing more and more of these thematic trends, you know,
a macro volatility. So I think during this period it's
important to be more tactical. And one thing we are
looking at increasingly is how do we identify sort of robust,
simple signals that will allow us to essentially pivot between
(32:58):
different views. Not so much market timing, because now we
know it's nearly impossible, but can we find ways in
which that allows us to stay risk one and not
miss the upside? While key junctures, you know, avoid the
big mistakes. So one signal I've found in all of
my micro research, it turns out that you know, there
(33:21):
is if you look at the change in CPI right, yeah,
year inflation, that turns out to be an extremely robust
and powerful projector of uh, you know, sort of as
a performance. And what I'm talking about, for example, is
if you look at today's inflation in Let's say I
don't know what what's was the inflation in K today? Actually,
because I normally follow the US, let's say it's two percent,
(33:45):
some two point two percent. Let's just pick up a number, right,
and if it was say four point four percent a
year ago, right, inflation would have gone down over the
last twelve month. That is actually a very powerful risk
on signal because what follows from falling inflation is you
tend to get all the good things right Stronger economic growth,
(34:05):
stronger job market, higher earnings per share, higher productivity, higher
customer confidence, and lower bond yields. All of these things
tend to be good for assets. Now, if you flip
the picture and you say, over the last traillion twelve months,
if inflation had gone up, right, if let's say it
was two point five percent and now it's going back
to three point two percent. You get the opposite of
(34:25):
all of those things previously. So how do we take
advantage of this? So we created a index that is
called dynamic equity duration where we essentially calculated the implied
cash flow distribution of stocks, and if inflation has been
coming down, would buy stocks whose cash flows are further
out right, they tend to be growth stocks, risk on stocks. Right,
(34:48):
our inflation has been going up, then we do the opposite.
We lean towards companies whose cash flows are more near term.
And that I think that we have shown to be
actually a very interesting way to allow investors to remain
risk on, ignoring all of the noise, right, you know,
whatever you may be what this deep seek where there
(35:11):
is terriffs.
Speaker 2 (35:13):
Whoa, we nearly got to the end. We were so close.
Speaker 4 (35:20):
Well I couldn't resist.
Speaker 3 (35:21):
But anyway, but the point is that you know you've
had all this well I think retail investors called fut right,
all these sort of news that will give you a
terrifying narrative. But if you just look at the trailing
half months inflation and remain risk going in terms of
equity duration, you would have actually done really well and
(35:41):
avoided you know, the disares of Tony Hunty too, right
when you know that we had an evaluation compression.
Speaker 1 (35:47):
Yeah, okay, interesting, So that's the signal that everyone can watch.
One last question, Davin, is there anything that you are
reading at the moment that you are finding very interesting?
Speaker 3 (35:57):
Yes, this is actually great question. And I'm reading this
little white paper, a slash book called Situational Awareness, which
I recommend to all of your listeners. Uh. This is
a researcher who used to work at open AI and
he has written this long essay or slash or you
(36:19):
know book talking about the path forward on AI. And
there is a one sentence in that intro that really
sort of you know, made me curious. He says, everyone
is now talking about AI, but few have the faintest
glimmer about what is about to hit them. Nvidia analysts
(36:41):
still think twenty twenty four maybe close to the peak.
Mainstream pundits are stuck on the idea of just predicting
the next word. But they actually they think everything is
going to be hype and business as usual. But actually
we're going to look at another Internet scale technology change.
And I think what he talks about in that essay
is going to be very illuminating for people who won't
(37:03):
understand the implications of all these different news that comes along.
That we are actually proceeding exactly according to script in
terms of what the scaling law would have predicted. So
what happened last Monday should not be surprising to you know,
people at all if they actually, you know, read this
little book.
Speaker 1 (37:22):
So anyway, okay, well we will put the link to
that in the show notes as well. I found that
mildly terrifying, so I will I've got some long claim
flights this way, I will make sure that I read
it then. Steve, thank you so much for joining us today.
Speaker 2 (37:37):
We really appreciate it. That was fascinating.
Speaker 3 (37:39):
Thank you very much for the conversation, Marie.
Speaker 2 (37:47):
Thanks for listening to this week's Marryn Talks Money.
Speaker 1 (37:49):
If you like us, share, rate, review, and subscribe wherever
you listen to podcasts, and keep sending your questions or
comments to Marryn Money at Bloomberg dot net. You can
also follow me and John on Twitter or ex I'm
at marins w and.
Speaker 2 (38:00):
John is at john Underscore Staffic.
Speaker 1 (38:02):
You can follow Steve on at Steve hoe F that
is s t e v e h o u F.
This episode was hosted by me Maren Sunset Web the
shows produced by Someuersadi and Moses and sound designed by
Blake Maples.
Speaker 2 (38:15):
Special thanks to Steve Howe