June 7, 2025 • 46 mins
Warren Buffett himself called our economy "asset light" – and for good reason. Today's most valuable companies derive their worth not from factories or equipment, but from intellectual property, brand equity, human capital, and network effects. Yet traditional value investing metrics, developed in the industrial era of railroads and utilities, completely miss these crucial drivers of modern business value.
Kai Wu, founder and CIO of Sparkline Capital, takes us on a fascinating journey through the evolution of value investing and explains why it's due for a radical update. With 50-80% of US company balance sheet value now coming from intangible assets, investors relying solely on price-to-book ratios find themselves increasingly unable to identify true value in today's markets.
The problem extends beyond mere definition. Our accounting standards systematically distort company valuations by expensing rather than capitalizing R&D and other intangible investments. This creates the paradoxical situation where companies investing heavily in their future appear less profitable in the present – a disconnect that creates tremendous opportunity for investors willing to look deeper.
Sparkline's innovative approach leverages artificial intelligence and big data to analyze unstructured information sources, from patent filings to social media, quantifying what traditional financial statements miss. This methodology bridges the growing divide between growth and value investors, applying timeless valuation principles to the digital economy.
Wu shares a compelling case study of NVIDIA, which Sparkline owned when it traded at a seemingly astronomical P/E ratio of 100. After adjusting for NVIDIA's extraordinary intellectual property and innovative culture, their models showed the stock was actually undervalued – a perspective completely missed by traditional metrics.
For investors looking to apply these insights, Sparkline offers two ETFs: ITAN for US markets and DTAN for international developed markets. Both funds seek companies rich in intangible assets but trading at reasonable valuations – essentially value investing adapted for the digital age.
Want to dive deeper into Kai's research? Visit sparklinecapital.com to explore his published papers and learn more about investing in the intangible economy.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:00):
Was there some point in history where that definition
change, you think, kind of tookplace that made intangible
value more the proper way tothink about?
Speaker 2 (00:09):
value investing.
You know, fast forward to today, 100 years later, and it's
Google, apple, nvidia, companiesfor whom intangible assets, or
what matter, and physicalcapital, tangible capital is,
you know, not really relevantfor generating earnings, really
relevant for generating earnings.
And even Warren Buffett himself, who, of course you know is a
disciple of Ben Graham and adirect student of his, you know,
back in the day, has called theeconomy asset light and pointed
(00:35):
out the fact that, you know,companies today are no longer
like the exons of the world orGMs, where it's intellectual
property, brand, human capital,network effects that drive
earnings today.
Speaker 1 (00:43):
I love this graphic because you really kind of break
it down in terms of where thecompanies fit in.
Talk to me about turnover.
When it comes to this kind offramework meaning, do a lot of
companies tend to go out aftersome period of time, come in?
How does that look?
Speaker 2 (01:01):
Yeah, I mean there is certainly turnover.
It ends up being kind ofroughly the same as a more
traditional value strategy tothink like you know less than
you know less than over.
The holding period on averageis over a year for these names
and turnover can be driven bytwo things just mathematically.
So of course there could bechanges in the fundamentals.
So imagine you own a companyand there's these major scandals
(01:21):
and the culture starts to decayand employees start to leave.
That would be a negative changein fundamentals.
Speaker 1 (01:27):
So we're going to be talking about a lot of
interesting things here, Adifferent spin on investing,
focused primarily on theintangible value side of the
equation, which I'm personallyexcited to hear more about.
I've gotten to know Kai overthe last I don't know six, seven
, eight months.
Always strikes me as a verythoughtful individual in the
field, an entrepreneur which Icertainly respect as one myself,
(01:50):
and one that I think also a lotof you will enjoy hearing from.
And, with all that said, myname is Michael Gaya, publisher
of the Lead Lag Report.
This is a sponsoredconversation by Sparkline
Capital, Kai Wu's firm.
I got a couple of ETFs I'lltouch on.
But, Kai, introduce yourself tothe audience.
Who are you?
What's your background?
What have you done throughoutyour career?
What are you doing currently?
Speaker 2 (02:11):
Yeah, Hi, so I'm Kai.
I'm the founder and chiefinvestment officer of Sparkline
Capital, so my firm is aboutfive or six years old now.
We manage two ETFs.
One is called ITAN I-T calledITAN, focused on intangible
value in the US, and then asecond we launched last year
called DETAN the same concept,but in developed market
(02:33):
international space.
My background before that was Ico-founded a hedge fund in
Boston systematic fund.
We did volatility arbitrage andCTA trend following, and before
that I got my teeth at GMO, soJeremy Grantham's firm in Boston
.
That was just my first job outof college.
I studied economics at Harvardand did my thesis in financial
(02:56):
crises, so I've been doing a fewthings up until now.
But I think all these kind ofarcs converge in what we're
doing now and I'm happy to getinto it as we go along on this
conversation.
Speaker 1 (03:08):
I didn't know there was a way to study financial
crises in a formal setting.
I'm curious to hear more aboutthat.
Speaker 2 (03:14):
Yeah, so you know, basically I studied economics
and Harvard's, obviously aliberal arts school, so it's
pretty general.
I graduated in 2009, 2010.
So right around the aftermathof the globalances whether
external credit, asset price orcredit imbalances that could
(03:49):
potentially proceed and predict,with higher than unconditional
probability, a financial crisis.
And we did indeed find that tobe the case by looking at
historical data from Sweden toJapan to the US, and so that was
really interesting, kind of asa starting point, trying to get
more into the you know, moreinto the you know asset pricing
(04:11):
and evaluation side of things,because of course, my training
was more liberal arts.
And then, with a naturalhopping point, to go to GMO as
my first job out of college,where obviously Jeremy Grantham
is well known for his work inpredicting bubbles.
So that was a nice transitionjust across the river.
Speaker 1 (04:27):
So you had this really interesting career
progression hedge fund, gmo, andthen you had your own firm.
You got into theentrepreneurship game.
Let's talk about SparklineCapital First of all.
Why go that route?
I mean, it sounds like you wereat several kind of pedigree
firms.
Speaker 2 (04:43):
Yeah, look, I've always been driven in the
industry by kind of solving themarkets right.
The intellectual challenges oftrying to figure out how things
really work and, on the researchside, being in a boutique and
being able to kind of drive theresearch agenda myself has been
very rewarding, I think, doesfree us up at Sparkline toline
to conduct research on topicsthat may at the time not seem
(05:06):
obviously relevant or commercialbut will over a longer
timeframe prove themselves out.
And so talk about the researchagenda.
Basically, gmo, in addition totheir work on bubbles, has been
really well known and the wholewhole firm you know when I was
there was over over a hundredbillion dollars in assets was
(05:27):
built on the back of beingpioneers in quantitative
investing.
So you know, jeremy and hisco-founders were really early in
the seventies and eighties tobe using computers to to find
stocks that are undervaluedrelative to you know their
fundamentals like book value,and so they were pioneers of
what's now called factorinvesting or systematic value
(05:47):
investing, obviously notspecific to GMO, but just in
general.
The value factor has struggledthe past one to two decades as
technology stocks.
The Magnificent Seven havecontinued to do really well and
your classic value stocks thingslike banks and energy companies
, the kind of low price to booknames, have not really done
(06:09):
nearly as well.
So the question we have triedto answer at Sparkline is why is
it that value investing hasstruggled?
Is it the case that valuedoesn't matter anymore and it's
all just memes?
Or is the case that it's merelyjust a question of measurement,
that value principles stillapply, but we need to be
thoughtful about how to adaptthe definition of intrinsic
(06:31):
value to be more relevant to themodern day.
Speaker 1 (06:34):
All right.
So there's a lot of interestingdirection to go with, and I've
heard that argument that valueis.
It's not that value isunderperformed, it's just that
being defined incorrectly.
Was there some point in historywhere that definition change,
you think, kind of took placethat made intangible value more
the proper way to think aboutvalue investing?
Speaker 2 (06:53):
Yeah, that's a really good question.
I don't think it was any kindof discontinuous point in time,
but if you do kind of go back acentury right.
So value investing the fatherof value investing was Ben
Graham, so Graham and Dodd'ssecurity analysis investing the
father of value investing wasBen Graham, so Graham and Dodd's
security analysis, which is thekind of Bible of value, was
written in the 1930s when theeconomy was clearly very
industrial.
If you've read the book, whichis super long and many of the
(07:17):
examples may not be thatpertinent to today utilities,
railroads, those are kind of thehot and big stocks of the day.
Fast forward to today, a hundredyears later, and it's Google,
apple, nvidia, companies forwhom intangible assets or what
matter, and physical capital,tangible capital is not really
relevant for generating earnings.
And even Warren Buffett himself,who of course is a disciple of
(07:40):
Ben Grimm and a direct studentof his back in the day, has
called the economy asset lightand pointed out the fact that
companies today are no longerlike the exons of the world or
GMs, where it's intellectualproperty, brand, human capital,
network effects that driveearnings today.
You can also look at it from amacro standpoint.
If you look at the GDP data,intangible investments, from a
(08:02):
top-down standpoint, in thenational accounts, surpassed
tangible investment in the 90sand that gap has only widened
ever since.
So, whether you look bottoms upat the company level, top-down
at the national account level,it's pretty clear that
intangible assets are more andmore important.
My semi-estimate 50 to 80% ofthe balance sheet of US
companies are now intangible,and so, to the extent where more
(08:24):
traditional value approachesare focused on book value or
tangible equity, they're goingto miss out on a lot of these
really important drivers ofvalue, which also causes
distortions with respect to abias towards, say, asset-heavy
businesses which, as I mentionedearlier, have not performed as
well the past couple of decades.
Speaker 1 (08:43):
When you say intangible, I think digital
primarily, but let's talk aboutthe types of intangible assets.
Speaker 2 (08:49):
Yeah, yeah, so I touched upon them a second ago.
So at Sparklin we have aframework with four different
categories.
So the first one isintellectual property.
That's, you know, like patents,obviously would even trade
secrets, I would say software,any kind of like know-how, would
be in that category.
Second, brand equity.
That's pretty straightforward,think like Coca-Cola or LVMH.
The third category is humancapital.
(09:11):
You know, this is the having avery talented workforce, but
also having the culture be suchthat these people are all kind
of rowing in the same direction.
And finally, network effects.
Think like Facebook or GoogleSearch.
Right, having you know this isthe idea of increasing returns
to scale.
Whereas a network increases insize, it becomes more and more
(09:31):
valuable, you know, as afunction of the users.
So these are the kind of thefour main categories of
intangible assets that you know,we believe, encompass, you know
, most of intangible value today.
Speaker 1 (09:41):
So I think the challenge you could put me wrong
on this is how do you ascribe avaluation around each of those
categories, right?
It's like how do you considerif the market has priced in a
network effect as beingovervalued or undervalued?
So let's talk about that.
And then maybe also of the fourcategories.
Do we tend to see cyclesmeeting there sometimes when the
(10:03):
market favors brand equity overhuman capital?
You know, let's go through that.
Speaker 2 (10:08):
Yeah, no, that's a.
Those are both very goodquestions, so let's do the
second one first, because Ithink that is, you know, more
easily answered.
The answer is yes, absolutelyRight, like one of the
interesting story I could tellis that of Warren Buffett.
Going back to you know what Isaid earlier.
You know, when he first foundedBerkshire Hathaway, his
investments were primarilytraditional value stocks,
(10:30):
berkshire itself being in thatcategory, and over time he kind
of expanded what I call theinvestment moats to be more
intangible.
He met Charlie Munger.
He invested in Coca-Cola, wherebrand was very important and
human capital, the culture andthe management he would always
applaud.
And then, over time, obviouslythe biggest investment over the
past two decades has been Apple,which he valued for not just
(10:52):
its brand and management butalso the intellectual property
and the network effects.
So my thought would be networkeffects is kind of the most
recent one where, as the worldbecame more and more connected
by the internet and othertelecommunications technologies,
it's become more importantbecause of course the value of
network is a function of thenumber of people connected and
the world become bigger and moreand more connected over time.
(11:13):
You know, obviously,intellectual property and
technology that the capitalstock of the world has increased
in that aspect only morerecently, right Even going back
50 years.
Obviously technology was animportant element of what we do,
but less so and same withbrands.
So I'd say that there's thattime series element.
There's also a cross-sectionalelement.
(11:34):
One of the things that we did,as I mentioned, we launched an
international fund and we did alot of research to do that to
extend the intangible valueconcept from the US to non-US
countries, and one thing wefound was that in the US, the
intangible value concept fromthe US to non-US countries, and
one thing we found was that inthe US, the kind of primary
driver of value was intellectualproperty, which makes sense
since we had the best techcompanies.
But if you go to say Europe, ittends to be more brand equity
(11:55):
that drives the value of thesecompanies, which again makes
sense if you think of LVMH andmany of these kind of.
Speaker 1 (12:00):
And I thought the next thing is you were talking
about yeah, that makes totalsense.
Now, the moment you were sayingthat it's like, my mind
immediately went to brand as faras luxury right On Europe,
whereas in the US it is the IP.
Speaker 2 (12:12):
Yeah, exactly, and so yeah, and to answer your second
question, which is how do wemeasure it.
I think that's like you know,and I can go on for the next
hour about this if you want, butthat's where it's easier said
than done.
Nobody, from an intuitivestandpoint, would argue against
the idea that we should be, tothe extent we can, incorporating
intangible assets into ourmeasure of intrinsic value.
(12:34):
Of course that's the case.
Otherwise you're always goingto be underweight or short.
Nvidia and Google, apple, allthese great companies but how do
you actually do that?
It's easier said than done.
So the first thing we did to tryto attempt to measure this so
this is kind of sequential is wetried to basically correct for
accounting distortions thatpenalized intangible intensive
(12:55):
companies.
So not to get too technical,but basically when you do
physical capital expenditures,so physical CapEx, that CapEx is
capitalized, it becomes anasset on your balance sheet.
You build a factory with $100million.
It's a $100 million asset onyour balance sheet.
You depreciate that over time.
Now the inconsistency is thatan intangible company that was
(13:16):
trying to do the same thing, butdoing it on the intangible side
say doing research anddevelopment into a new drug or
engaging in a marketing andbranding campaign or investing
in training employees, that thisinvestment is not capitalized.
Instead, it's expensed, meaningthat these companies get a hit
to their bottom line in thatyear and they don't get to grow
an asset on their balance sheet,which is why I say Coca-Cola
(13:38):
has no book value.
And there is one more thing Ishould mention, which is that
acquired intangibles do show up,because if I acquire another
company, there's an item calledgoodwill that gets put on.
But this is a furtherdistortion in as much as it
penalizes companies that dohomegrown innovation, which is
many companies and arguably abetter way of building out a
(14:00):
company's IP.
So the first thing we did wassay what if we just treated
intangible investment like R&Dthe same way as we do physical
CapEx?
And you can do that.
And what you find is that ithelps a little bit and, in other
words, your portfolio as avalue investor is a little bit
less biased against technologystocks and healthcare and pharma
, life sciences and consumerbrands, but only a little bit
(14:21):
less.
And if you look at theperformance of the value factor
say Fama French, which is in adeep drawdown today relative to
its peak in, say, 2007, it's alittle bit less bad, but you're
still deep in the hole.
So, the point being that thiswas okay, but it was no panacea,
and if you think about why thatmight be the case, it just
comes down to the fact that justthink of this even more.
(14:42):
Basically, if you fact that,you know, just think of this
even more.
Basically, if you have twocompanies that are engaging in
R&D and one invents, you know,amazing, you know blockbuster
drug and the other one, you know, can't pass trials, well,
obviously, even if these twocompanies put the same amount of
value in, the output is verydifferent, and this is a feature
of intangible assets, thatthere's kind of this
non-linearity between input andoutput costs.
And so we decided a better way.
(15:02):
You know that the accountingmethodology was kind of a
non-starter that we can't lookat historical cost-based
analysis and we still have tolook at the output of this
investment, and that was kind ofthe next step that we went
forward to.
Speaker 1 (15:18):
How much does the importance of these different
intangible assets change,Meaning, is there a volatility
to brand equity?
Is there a volatility to IP?
I mean, I assume not, but Imean presumably there's an
aspect there.
Speaker 2 (15:34):
Yeah, I mean, it depends if you're asking at the
company level or, like at the,you know, at the sector level.
At the company level,definitely, you know, you have
examples of.
You know one thing I looked atwas like Amazon right, when they
first got set up in the late90s, they were just an online
bookstore, right, so they hadyou know good brand and you know
some IP, but you didn't reallyhave network effects.
But over time, as they expandedinto like the third-party
(15:56):
marketplace, into AWS and otheraspects like that, they their
kind of network effects grew andgrew and grew.
They obviously became huge andthey have this massive moat now
with their logistics anddistribution, and so that
changed through time.
Their brand arguably improvedand obviously they've had some
negative components as well.
(16:16):
So, again, these things aredynamic.
They do evolve through time,both at the overall level, as we
discussed, but also at thecompany level.
Speaker 1 (16:24):
We're going to get into the individual funds
themselves.
But OK, so you've got theframework.
Us international side of things.
Talk to me about people'sunderstanding of the concept.
All this makes a lot of sense,right, but I think people tend
to be talking their old ways ofanalyzing markets.
You find that it's hard to getpeople around the idea that
(16:44):
value is just not definedproperly, that this is a better
framework.
Speaker 2 (16:47):
Yeah.
So you know, maybe before Iyeah, so I think let's talk
about two things.
So first let me just go back towhat I was saying.
I want to kind of just finishthat thread there on how we
measure intangible value.
And so if accounting is not theway forward, like, what is the
path?
And you know, the insight we hadwas look, we actually live in
(17:07):
like the 21st century where wenow have access to what's called
big data, right, just massive.
Everyone.
You know there's hugeexponential growth in
information available tocompanies that may exist outside
of the 10K and 10Q.
This could range from anythingfrom trademarks to
user-generated data, socialmedia, right.
All this information now existsabout with potentially relevant
information on companies.
And so why aren't we using that?
Because that would seem like anatural place to look for
(17:30):
insights into companies andtangibles, and so we said that
that's an interesting place,let's start with that.
But then the barrier we ran intowas that this data is large and
unstructured.
So think about like an exampleof a patent.
Intuitively, if you wanted tomeasure, say, google's IP, you
would say, all right, let's readall the patents.
There's thousands, hundreds ofthousands of patents here, which
is obviously time consuming butin theory, doable.
(17:52):
The problem is you can't do itsystematically.
You can't just take a bunch ofpatent abstracts and throw them
through a linear regression.
Instead, you need better toolsto process the text.
So the first thing we did waswe said let's just use a simple
natural language processing tool, like just dictionary-based
approach.
So let's look for keywords,Because what we're trying to do
here is to distinguish fromlagging edge versus leading edge
(18:12):
patents.
So we can say let's just lookfor all patents that mention AI.
Right, that would be one simplehack and you can do.
You know more sophisticatedversions of that and that's, you
know, directionally helpfulbecause it'll help you
distinguish which.
You know which companies don'tjust have a lot of patents but
have really innovative ones.
But then over time, you know, westarted doing more
sophisticated techniques.
(18:33):
So around 2019, 2020, you know,I wrote a paper where I kind of
highlighted the potential largelanguage models which underpin
today's chat GPT as a way oftaking this unstructured data
and processing it into a youknow, a factor or to a single
score, and over time we used totrain our own models, you know,
from scratch, in-house and overtime.
Obviously, the providers, suchas the open AIs and anthropics
(18:57):
of the world have become so muchbetter and have invested so
much more resources into thesefoundational models.
Now we utilize those, which hasbeen a huge boon to what we do
right, because now a greater andgreater share of the insight in
these unstructured data setscan now be measured.
(19:20):
I think the final piece I shouldmention is when we convert this
into actual scores forcompanies.
We are value investors, sowe're not going to say, hey,
which company has the mostinnovative patents?
Because then you're just goingto get Google we care about.
You know which company has themost innovative patents relative
to market cap?
So it's more of a dividendyield or a earnings yield or, in
this case, a patent yield.
And we blend together all thesedifferent measures of
intangible assets from IP sideto brand, to human capital which
companies have the most talentrelative to the market cap,
(19:42):
which have the most brandmetrics and you come up with a
single composite score forvaluation.
So that's kind of our overallprocess, where we are using
large language models and AImerely as a tool not necessarily
predict the stock pricedirectly, but instead as a tool
to take the unstructuredinformation about companies that
are kind of hidden in all theseunstructured data sources and
(20:05):
to create factors around thefour pillars which we can then
bring into the creation of avalue factor.
Speaker 1 (20:12):
I love that.
The website sparklinecapitalcomfor ITAN factor.
I love that.
The website sparklinecapitalcomfor ITAN.
I love this graphic because youreally kind of break it down in
terms of where the companiesfit in.
Talk to me about turnover whenit comes to this kind of
framework meaning do a lot ofcompanies tend to go out after
some period of time, come in?
(20:33):
How does that look?
Speaker 2 (20:34):
Yeah, I mean there is certainly turnover.
It ends up being kind ofroughly the same as a more
traditional value strategy.
So think, like you know lessthan you know less than over.
The holding period on averageis over a year for these names
and turnover can be driven bytwo things just mathematically.
So of course there could bechanges in the fundamentals.
So imagine you own a companyand there's these major scandals
(20:54):
and the culture starts to decayand employees are to leave
Right, that would be a negativechange in fundamentals.
Or on the other side, you couldhave a company that you know
they start investing in, I don'tknow, ai, some kind of emerging
technology, early on and as we,as that trend starts to take
off, they really benefit on theIP side from that.
So fundamentals do change andthey do evolve through time, but
(21:16):
pretty slowly on average.
For example, company culturesgenerally are pretty sticky
through time.
The founders set the tone andhopefully the managers can carry
that torch moving forward whenyou see a lot more.
I think a lot more of theturnover actually gets driven by
the price side.
And this is the same, by theway, for like traditional value
price to book type strategieswhere you know prices are just a
(21:38):
lot more volatile thanfundamentals, and so what ends
up happening is you own a stockthat you like and then you know
prices, you know they run up andyou, you know, at some point
you say this stock is nowovervalued, we'll take our
profits and rotate and move on.
Or you find stocks that youthink are kind of interesting
but not quite at your thresholdPrecious fall, holding constant
(21:58):
fundamentals, and that's whenyou buy.
So a lot of turnover is drivenby precious, but even then, that
being said, going back to myinitial answer, the overall
turnover is pretty slow, alittle bit over a year on
average, but obviously thatchanges based on market
conditions.
Speaker 1 (22:12):
So I often use this line that what you own often
matters a lot less than how muchyou own of it.
All right, talk to me about howyou go about weighting with
this type of approach.
We know that very well-knownmarket gap weighting, weighting
some factor tilt, right.
But given that some of thisstuff you can argue is a little
(22:33):
bit squishy, right, how do youthink about weighting on this?
Speaker 2 (22:36):
Yeah, no, we've actually thought a lot about
this question when we designedthese funds.
So, as you point out, there'skind of two extremes you can use
.
On one end you can use fullmarket cap waiting.
On the other end you can useequal waiting.
So full market cap waiting hasthe advantage of tons of
liquidity, kinds of liquidityand, um, you know, in theory, to
(22:58):
the extent where clients,whether you like it or not,
measure you against the s&p,that will, you know, reduce the
amount of tracking error to thatum.
The downsides, of course, arethat now you're kind of
constrained with respect to yourbreadth, like you can't really
tilt that much on the, you know,on the smaller cap names, um
and um, and you also faceconcentration risk in as much as
if you, like some of the topcompanies, like you can only
hold so much, I mean, you'regoing to be massively overweight
(23:19):
, say the Mag7.
Equal weight has the oppositeproblem.
So equal weight you have themost breadth and you know is
kind of the most uniqueportfolio, the most active share
, but the downside, of course,being that a lot of that active
share is just driven by thissingle factor the size tilt
against S&P, and you know, andif it goes in your favor, you
look at the hero, and if it goesagainst you, you look at an
(23:40):
idiot.
And so that's not really thatfair.
And plus, it has lowerliquidity.
And so we tried to throw theneedle here, and what we ended
up doing was devising a kind ofhalfway between solution to
throw this needle, which isbasically the square root of
market cap.
So you can think of like achart where, like, you have the
market cap on the X axis andthen the Y axis is your position
.
It's a square root function, soit's like a concave function,
(24:01):
and the advantage of that isthat if a stock is, say, nine
times bigger than another stock,it only gets three times as
much weight.
So it does get more weight andthat helps increase the
liquidity and reduce thedependence over-dependence on
the size tilt, but it also stillleaves enough room to be making
pretty active decisions.
So we kind of settled on thatas a middle ground and, by the
(24:25):
way, this was something that Ididn't invent.
We did this at GMO and I'm suremany other coin shops also use
such a technique.
But going back to this overallquestion, so the portfolio is
built like this we effectivelyhave an investment universe,
going back to this overallquestion.
So the portfolio is built likethis we effectively have an
investment universe In the caseof the US fund, it's like the
top 1,000 US stocks and then inthe international universe it's
(24:46):
a universe of non-US stocks.
What we do is we have scoresfor each company, we line all
the stocks up for each company,we line all the stocks up, we
then, within our universe, takethe top 10% to 15%, depending on
the fund, and then that's yourportfolio.
We don't equal weight.
We then apply two tilts.
One is by the factor.
(25:07):
So obviously more intangiblevalue means more weight, and
then also more market cap meansmore weight, but only
proportionally to the squareroot, not the full market cap to
weight, but only proportionallythe square root, not the full
market cap to help create morediversification.
Speaker 1 (25:20):
All right, so a lot of interesting points here.
We talk about weighting fromthat perspective, which is
easier when it's a US-only fund.
Let's talk about DTAN, becausewhen you're dealing with
international investing, you nowhave to think about country
weightings as part of that.
Walk me through how that looks.
Is that just a function of sortof the output on the individual
names?
In terms of the intangibleassets?
How does the country allocationlook right now for DTM?
Speaker 2 (25:43):
Yeah, that's another good question.
So, as I mentioned before, likebefore I started Sparkline, you
know I was doing kind of morehedge fund style investing and
you know, when you go long shortand you're, you know, highly
levered on both sides, on bothsides risk management at the
factor level is very important.
So this is your bar, oractually only models, where you
can strain not just by countrybut you also can strain by
sectors or industries and youwant to be very, very tight
(26:05):
there to kind of remove anyunwanted exposures to various
risk factors that could createvolatility and hence create
problems, to the extent thatyou're highly levered In
long-only funds.
I've actually found that thatis kind of trying to be QQ'd.
You're kind ofover-concentrating the models by
attempting to do all the kindof sector neutralization and
(26:27):
style neutralization incountries, and so instead what
we've decided to do is to letthe weights go bottoms up.
It might be the case that at anypoint in time, the best
companies say all the humancapital and all the talent is
going into the tech sector.
Well, that's great, we shouldallow the fund to overweight
tech.
Or if all the talent happens tobe in, say, germany, that's
great, we should let the fundoverweight Germany.
(26:48):
So I think to a large extentyou don't want to mess with it
too much.
Obviously, if things are goingreally crazy, that's when you
might need some constraints.
But at least in our research,when we design the fund and also
positions, today that hasn'treally been the case, and so, to
answer your question, we letthe weights the country weights
and sector weights go bottoms up, just depending on what stocks
(27:11):
on an individual basis appearattractive on intangible value.
Speaker 1 (27:16):
I feel like we need to hit on currency to some level
here, because obviouslycurrency returns are a part of
total returns when you'reinvesting overseas.
But maybe a little bit morenuanced how does currency
volatility play into intangibleasset value?
Speaker 2 (27:33):
Honestly, we don't really include that as a
specific component of intangiblevalue.
We view stocks as realbusinesses and their
fundamentals are what they are.
And in the DTN fund we actuallydo not currency hedge, so we're
not hedging, we're not payingto hedge out the FX exposure.
So the stock prices will kindof move up and down also with
(27:57):
the dollar as it turns out.
You know, we do think thedollar remains expensive.
You know, whether I'mpurchasing per parity or any
other metric, you know, and whenwe launched the fund in
September we thought that couldbe a nice tailwind to have for
investors.
Speaker 1 (28:10):
you know, in the fund yeah, and obviously there's
been a lot of demand on theinternational side because
international has done a lotbetter than the US and that's
more of a traditional valuationcall right, I mean, as opposed
to intangible value.
But make the case for I thinkit's compelling when it comes to
the US, but make the case forintangible value as being a big
driver of that value discussionwhen it comes to international
too.
I think also part of this isalso around the idea that style
(28:35):
classifications in the US growthversus value, I'd argue, is
more driven because of tech.
In people's minds that's thequintessential growth sector
characteristic.
You don't have that in anythinginternational, which means I
think typically most would viewinternational markets anyway in
passive form as value.
Speaker 2 (28:54):
Yes, I want to answer that question in two parts.
So I wanted to pull on thatthread a little bit about the
value versus growth style thing.
And is it just tech?
So I actually wrote a separatepaper on this in 2019 where I
created I basically argue thattech is not a is a first
approximation of innovation, butobviously it's not sufficient,
right, because there'sinnovative tech companies and
non-innovative tech companies.
(29:15):
There are companies inindustrials that are very
innovative and others that arenot, right?
Amazon's a retailer, google's acommunications company, and so
I devised a factor called Icalled it disruption factor, so
innovation and then was able touse that as a way of kind of
saying you know what is theexposure of, say, a traditional
value portfolio or growthportfolio to that factor?
And indeed it is the case thattraditional value portfolios
(29:39):
tend to load on a shortinnovation factor, whereas
growth tends to load on a long,but it's not always 100%
correlated.
So I just wanted to make thatdistinction and I think that
actually flows nicely into whatis the point of these funds,
right?
So, whether in US or not in US,kind of the point of this fund
is to try to deal with thissituation we find ourselves in
now, where the investmentcommunity has become like super
(30:01):
bifurcated, where you have valueinvestors kind of your old
school guys who are kind ofholding onto these principles
but finding themselvesincreasingly, first of all, with
poor performance on a relativebasis, but also in stocks that
are kind of your old economynames financials, energy
materials, industrials,companies with much less dynamic
(30:22):
businesses and then you find,on the opposite side, your
growth investors who have donepretty well on the back of the
tech or innovation tailwindwe've seen in the past two
decades, but are increasinglyexposed to overvalued names,
because the world's kind ofcaught up to this idea that
tech's done better, right,people are pretty performance
chasing in general, and alsothere are these big swings right
(30:44):
, 2022 is not a good year forinvestors in technology stocks.
Interest rates were raised,there are other things that
happened, and a lot of thesecompanies that had pretty high
multiples to begin with ended upgetting smoked.
Because that's a big, thevaluation compression can be
pretty painful, and so whatwe're trying to do with these
products here is trying tobridge the gap between value and
(31:05):
growth, to create a strategythat say applies value,
investing these timelessprinciples, but also in a more
modern way with an acceptorexposure that includes
technology companies and canoperate successfully in sectors
other than the most traditionalones.
We find that price to bookratio still works if you apply
it in certain old economysectors.
(31:26):
It just doesn't work fortechnology companies.
You can't pick between Googleand Microsoft by using price to
book.
But intangible value does work,or we found it does work, at
least in the more modern sector.
So this is a way of takingvalue, investing and modernizing
it.
The other way we think aboutthis is on the growth side,
which is here's a way of owninginnovative companies, but with a
(31:46):
valuation discipline such thatif a stock goes up too much,
we'll sell it.
A great example that I talkedabout in my last investor letter
is NVIDIA.
So in ITN, our original fund,which is about four years old,
we actually owned NVIDIA atinception.
So this is 2021.
The P ratio of NVIDIA wasaround 100.
(32:07):
So a traditional value investorwould say this thing's super
expensive, there's no way I'mnot even touching it.
But then, once our modelsadjusted for intangibles, their
IP, their innovative culture,etc.
We actually found that thestock was not only cheap but
very cheap, went up a ton, atwhich point the model said, all
(32:40):
right, well, this is still agood stock, but it's just not
cheap anymore and so let'srotate out.
And we ended up going into someother more under the radar AI
plays.
But I think that illustratespretty nicely that this strategy
, while being kind of focused oninnovation and modern and
tangible intent of thebusinesses, is still a value
strategy and still cares a lotabout the price you're paying
for a lot of these assets.
Speaker 1 (32:58):
All that makes a kind of sense to me.
Those that are listening tothis you know that are intrigued
by the idea.
They're looking at the fundsand you know they might be used
to seeing some ETFs that trade.
You know hundreds of thousandsof volume shares traded daily
and they see the volume on ITANand DTAN.
Maybe they get a little bitconcerned about liquidity.
I want you to do some mythbusting around volume, liquidity
(33:23):
and how people should thinkabout smaller funds.
Speaker 2 (33:27):
Yeah, and look, what I'm going to say here is not
specific to what I'm doing.
It applies to any ETF, justbased on the way these things
are built.
So ETFs are just baskets.
They're baskets of stocks and,due to the arbitrage allowed by
CreateRedeem, they generallytrade very close to NAV.
And the way that works is, ifit trades at a premium, the
(33:49):
market makers will arbitragethat one way, or at a discount
the other way.
The capacity or liquidity of anETF is a function primarily of
the liquidity of the underlyingstocks.
So, for example, if I had asingle stock ETF where the only
holding was Apple, which issuper liquid, the ETF would
(34:10):
basically have the liquidity ofApple, more or less.
And so what you evaluate andthis is again not just specific
to me when you evaluate ETFsthat are, say, thinly traded or
kind of new or smaller ETFs,what you want to look at is what
are the actual underlyingholdings?
If you're holding micro-capemerging market stocks, then it
may actually not be that liquidand the spread, the bid-ask
(34:31):
spread, if you go on your screenshould be pretty wide to
reflect that.
If it's just trading mega-capUS stocks, it should be pretty
narrow.
In our case, itan, I think it'strading around 5 cents wide.
So currently I mean, and itholds Russell 1000, so top 1000
US stocks, so it's large and midcap names, so that's pretty
(34:54):
liquid.
Dtn is a bit wider.
It's a bit it holds non-USnames, which is a little bit
less good, but in both casesthese are kind of your large cap
stocks, like Amazon and Googleare kind of the top two current
holdings of ITAN.
So I think that liquiditygenerally has not been a concern
.
We've had investors put inamounts of money that are
(35:16):
significant percentages of thefund in a single day and have
had no issues with trading.
But of course, if that'ssomething you, if you're
interested in this concept, feelfree to reach out to me.
Or you know the trading team,you know Alpha Architect, who
does the operations for the fund, as you know, will obviously be
able to kind of help, you know,with any kind of specific
questions.
Speaker 1 (35:36):
So about how to think about this in terms of a
diversified portfolio, obviouslystill equities, obviously still
in a correlate to equities,maybe slightly less so, you know
, at least in kind of highervolatility junctures.
But how do you want to thinkabout pairing this against more
traditional passive investments?
Can this be a core?
Speaker 2 (35:55):
allocation.
So one of the things that wewere pretty deliberate to do is
to ensure that these stocks,that the ETFs, had sufficient
diversification.
So both ETFs have over 100names, right?
So it's not like you're.
Hey, you're buying a fund withthree stocks and therefore you
would, by definition, need tohave a handful of managers to
kind of diversify around that.
(36:16):
In our case, we hold enoughstocks that you know, even
though the active share can be,you know, pretty high relative
to, say, the S&P 500, you'repretty diversified across a lot
of names.
So you know that would helpwith the question around core
holdings.
I mean, there's look, there'sthree different ways I've found
that our clients use our funds.
So first is, you know, as youmentioned, as the first is, as
(36:37):
you mentioned, as a kind of wayof getting tracking error
against a passive index thatloads up on these intangible
value factors which we believeshould lead to outperformance.
A second way is as a valuesubstitute that will tend to
give you a bias towards your oldeconomy stocks, which you may
(37:01):
want to offset.
But you can offset it by justbuying, say, the QQQ, but then
you're just going growth.
So another way of doing thatwould be to instead add, say,
one of our funds which allowsyou to still be kind of
value-focused but just apply iton the intangible as opposed to
tangible side of the balancesheet.
And because our funds tend tobe more intangible, intensive,
tend to be more tech and grandfocused, you kind of balance out
(37:23):
some of the old versus neweconomy exposures and the final
way I've seen this be used is onthe growth side, where you have
folks who want to be exposed totechnology and growth and
innovation but also want a fundthat will be aware of the
valuation so that as things runup they'll kind of take profits
and prudently rotate into otherless overvalued assets.
(37:47):
Like we did a paper calledInvesting in AI Investing in AI
Navigating the Hype, and we dida study of the dot-com boom and
bust and one thing we found wasthat if you just buy the
internet stocks, you do reallywell and then you do really
poorly.
But if you're instead dynamicand you're kind of rotating
through based on valuations,kind of always rotating into the
cheapest internet stocks, youdo okay.
(38:08):
And that's kind of the ideahere, which is I find that you
know you don't need to kind ofworry about should I trade in
and out of this, based on, likeyou know, the valuations of, say
, the tech ETF or whatever, butit could just be something that
will smoothly, hopefully,navigate you through the various
valuation cycles.
Speaker 1 (38:29):
Any thought on how policy initiatives from the
Trump administration could maybeimpact the way intangible value
is valued?
I mean, I think aboutderegulation that may be
impacting the IP side.
I think about tariffs may beimpacting even the brand equity
side.
I mean, does that factor intoanything as you think about the
portfolio?
Speaker 2 (38:44):
Yeah, actually, the last paper I wrote, which came
out, I think, about a few weeksago in April, was called
Investing Amid Trade Wars, andit talked about the impact of
tariffs on global trade and onstocks more specifically.
One of the nice things aboutintangible assets is they can't
(39:05):
be tariffed.
So if you have a physical goodand it goes over on a ship to
customs, it's going to getinspected and potentially
tariffed, whereas an intangibleasset think like streaming music
or video, any kind of software,even services type thing cannot
be tariffed, right.
So that's actually makesintangible assets, I think at
(39:27):
least, a lot more robust when itcomes to the impact of this
tariff driven volatility, rightLike tariffs are on, tariffs are
off.
Tariffs are on, tariffs are off.
We don't know how things willplay out.
It's possible that we end upwith nothing, that that sticks,
but I think, regardless, we'regoing to end up.
I think, regardless, this hasbeen a shot across the bow.
Um, you know, companies andcountries are now, you know,
(39:49):
standing kind of more, more, uh,sanitized to the kind of, um,
geopolitical risks of supplychains going through various
countries and, as such, likethis is a factor that will
affect all companies, but Ithink those businesses that are
more intangible, intensive, havea bit of advantage just because
of the nature of intangibleassets.
(40:09):
And I think the second thingthat's really happened is and
this is partiallyunintentionally and partially
intentional on the part of theadministration is this kind of
like sell America theme right?
So we've seen over the pastyear past year to date, I guess
you know international stockshave rallied 15%, while US
stocks are basically flat.
So this huge gap has opened upin US versus non-US.
(40:31):
We've seen US bonds sell off,we've seen the US dollar sell
off, as capital is apparentlyfleeing the US into, you know,
other geographies.
And so I think what's happenedis a lot of US investors have
found themselves offsides tooverweight US stocks.
And that's a function of youlet your winners run.
So when US stocks do reallywell and they end up being 70%,
(40:53):
80%, maybe 100% of yourportfolio, you just kind of say
that's working.
But what's happened is, youknow, now it's the opposite case
, where the idiosyncraticpolitical risk is now in the US,
not as much abroad.
And so if you're an investorwho has, you know, 90 to 100% in
US stocks, right, maybe Ishould think about diversifying
internationally, maybe this Ican't tell you whether or not
(41:15):
this theme will continue movingforward, but it might.
And the problem here, thechallenge, is that the
international stock index is notthat good, right?
So I think about IFA or AcquiaxUS.
It's about 25% financials andthen 20% industrials, right, it
is very.
The kind of general stereotypeof non-US stocks as being less
(41:37):
dynamic, less innovative isactually true, at least at the
index level.
And so the key with DTAN whichis the you know find, where we
took the concept and put it intonon-US markets is that it only
invests in a subset of names andinvests in a subset that are
the most intangible, intensive,so they're kind of levered to
this growing intangible economy,this trend of growth.
(41:58):
It owns, as we discussed, morehealthcare, more brand-intensive
companies, even withinindustrials, the more innovative
technology names.
So it's a way, I think, ofdiversifying outside of the US
while still maintaining exposureto this intangible theme which
I think you know over the next,you know, 10, 20 years will only
(42:19):
become more and more pronouncedand important to the economy.
Speaker 1 (42:23):
And personally I think it makes the entire
concept makes a lot of sense andI've seen other papers outside
of viewers that have similararguments.
Speaking of those papers, wherecan people get access to those?
Speaker 2 (42:34):
Yeah, so just go to my website sparklinecapitalcom.
I publish all my research there.
Speaker 1 (42:39):
Perfect, and I obviously did learn more about
the funds sparklinecapitalcom.
Any final?
Speaker 2 (42:43):
thoughts here before we wrap up.
No, this has been a fundiscussion and I look forward to
answering any other questionsthat come up.
You can feel free to reach outto me directly online or just
send me an email.
I think my email's posted on mywebsite somewhere.
Speaker 1 (42:59):
I appreciate those that watched this live.
Again, this will be a podcastunder Lead Lag Live.
We're going to be doing thesemonthly, so you'll be hearing
more from Kai and we'll get intosome more nuances, especially
as it relates to the environment, and maybe some analysis on
individual positions across thetwo ETFs.
Hopefully, I'll see you all inthe next episode.
Thank you, kai, I appreciate it.
Was there some point in history where that definition
change, you think, kind of tookplace that made intangible
value more the proper way tothink about?
Speaker 2 (00:09):
value investing.
You know, fast forward to today, 100 years later, and it's
Google, apple, nvidia, companiesfor whom intangible assets, or
what matter, and physicalcapital, tangible capital is,
you know, not really relevantfor generating earnings, really
relevant for generating earnings.
And even Warren Buffett himself, who, of course you know is a
disciple of Ben Graham and adirect student of his, you know,
back in the day, has called theeconomy asset light and pointed
(00:35):
out the fact that, you know,companies today are no longer
like the exons of the world orGMs, where it's intellectual
property, brand, human capital,network effects that drive
earnings today.
Speaker 1 (00:43):
I love this graphic because you really kind of break
it down in terms of where thecompanies fit in.
Talk to me about turnover.
When it comes to this kind offramework meaning, do a lot of
companies tend to go out aftersome period of time, come in?
How does that look?
Speaker 2 (01:01):
Yeah, I mean there is certainly turnover.
It ends up being kind ofroughly the same as a more
traditional value strategy tothink like you know less than
you know less than over.
The holding period on averageis over a year for these names
and turnover can be driven bytwo things just mathematically.
So of course there could bechanges in the fundamentals.
So imagine you own a companyand there's these major scandals
(01:21):
and the culture starts to decayand employees start to leave.
That would be a negative changein fundamentals.
Speaker 1 (01:27):
So we're going to be talking about a lot of
interesting things here, Adifferent spin on investing,
focused primarily on theintangible value side of the
equation, which I'm personallyexcited to hear more about.
I've gotten to know Kai overthe last I don't know six, seven
, eight months.
Always strikes me as a verythoughtful individual in the
field, an entrepreneur which Icertainly respect as one myself,
(01:50):
and one that I think also a lotof you will enjoy hearing from.
And, with all that said, myname is Michael Gaya, publisher
of the Lead Lag Report.
This is a sponsoredconversation by Sparkline
Capital, Kai Wu's firm.
I got a couple of ETFs I'lltouch on.
But, Kai, introduce yourself tothe audience.
Who are you?
What's your background?
What have you done throughoutyour career?
What are you doing currently?
Speaker 2 (02:11):
Yeah, Hi, so I'm Kai.
I'm the founder and chiefinvestment officer of Sparkline
Capital, so my firm is aboutfive or six years old now.
We manage two ETFs.
One is called ITAN I-T calledITAN, focused on intangible
value in the US, and then asecond we launched last year
called DETAN the same concept,but in developed market
(02:33):
international space.
My background before that was Ico-founded a hedge fund in
Boston systematic fund.
We did volatility arbitrage andCTA trend following, and before
that I got my teeth at GMO, soJeremy Grantham's firm in Boston
.
That was just my first job outof college.
I studied economics at Harvardand did my thesis in financial
(02:56):
crises, so I've been doing a fewthings up until now.
But I think all these kind ofarcs converge in what we're
doing now and I'm happy to getinto it as we go along on this
conversation.
Speaker 1 (03:08):
I didn't know there was a way to study financial
crises in a formal setting.
I'm curious to hear more aboutthat.
Speaker 2 (03:14):
Yeah, so you know, basically I studied economics
and Harvard's, obviously aliberal arts school, so it's
pretty general.
I graduated in 2009, 2010.
So right around the aftermathof the globalances whether
external credit, asset price orcredit imbalances that could
(03:49):
potentially proceed and predict,with higher than unconditional
probability, a financial crisis.
And we did indeed find that tobe the case by looking at
historical data from Sweden toJapan to the US, and so that was
really interesting, kind of asa starting point, trying to get
more into the you know, moreinto the you know asset pricing
(04:11):
and evaluation side of things,because of course, my training
was more liberal arts.
And then, with a naturalhopping point, to go to GMO as
my first job out of college,where obviously Jeremy Grantham
is well known for his work inpredicting bubbles.
So that was a nice transitionjust across the river.
Speaker 1 (04:27):
So you had this really interesting career
progression hedge fund, gmo, andthen you had your own firm.
You got into theentrepreneurship game.
Let's talk about SparklineCapital First of all.
Why go that route?
I mean, it sounds like you wereat several kind of pedigree
firms.
Speaker 2 (04:43):
Yeah, look, I've always been driven in the
industry by kind of solving themarkets right.
The intellectual challenges oftrying to figure out how things
really work and, on the researchside, being in a boutique and
being able to kind of drive theresearch agenda myself has been
very rewarding, I think, doesfree us up at Sparkline toline
to conduct research on topicsthat may at the time not seem
(05:06):
obviously relevant or commercialbut will over a longer
timeframe prove themselves out.
And so talk about the researchagenda.
Basically, gmo, in addition totheir work on bubbles, has been
really well known and the wholewhole firm you know when I was
there was over over a hundredbillion dollars in assets was
(05:27):
built on the back of beingpioneers in quantitative
investing.
So you know, jeremy and hisco-founders were really early in
the seventies and eighties tobe using computers to to find
stocks that are undervaluedrelative to you know their
fundamentals like book value,and so they were pioneers of
what's now called factorinvesting or systematic value
(05:47):
investing, obviously notspecific to GMO, but just in
general.
The value factor has struggledthe past one to two decades as
technology stocks.
The Magnificent Seven havecontinued to do really well and
your classic value stocks thingslike banks and energy companies
, the kind of low price to booknames, have not really done
(06:09):
nearly as well.
So the question we have triedto answer at Sparkline is why is
it that value investing hasstruggled?
Is it the case that valuedoesn't matter anymore and it's
all just memes?
Or is the case that it's merelyjust a question of measurement,
that value principles stillapply, but we need to be
thoughtful about how to adaptthe definition of intrinsic
(06:31):
value to be more relevant to themodern day.
Speaker 1 (06:34):
All right.
So there's a lot of interestingdirection to go with, and I've
heard that argument that valueis.
It's not that value isunderperformed, it's just that
being defined incorrectly.
Was there some point in historywhere that definition change,
you think, kind of took placethat made intangible value more
the proper way to think aboutvalue investing?
Speaker 2 (06:53):
Yeah, that's a really good question.
I don't think it was any kindof discontinuous point in time,
but if you do kind of go back acentury right.
So value investing the fatherof value investing was Ben
Graham, so Graham and Dodd'ssecurity analysis investing the
father of value investing wasBen Graham, so Graham and Dodd's
security analysis, which is thekind of Bible of value, was
written in the 1930s when theeconomy was clearly very
industrial.
If you've read the book, whichis super long and many of the
(07:17):
examples may not be thatpertinent to today utilities,
railroads, those are kind of thehot and big stocks of the day.
Fast forward to today, a hundredyears later, and it's Google,
apple, nvidia, companies forwhom intangible assets or what
matter, and physical capital,tangible capital is not really
relevant for generating earnings.
And even Warren Buffett himself,who of course is a disciple of
(07:40):
Ben Grimm and a direct studentof his back in the day, has
called the economy asset lightand pointed out the fact that
companies today are no longerlike the exons of the world or
GMs, where it's intellectualproperty, brand, human capital,
network effects that driveearnings today.
You can also look at it from amacro standpoint.
If you look at the GDP data,intangible investments, from a
(08:02):
top-down standpoint, in thenational accounts, surpassed
tangible investment in the 90sand that gap has only widened
ever since.
So, whether you look bottoms upat the company level, top-down
at the national account level,it's pretty clear that
intangible assets are more andmore important.
My semi-estimate 50 to 80% ofthe balance sheet of US
companies are now intangible,and so, to the extent where more
(08:24):
traditional value approachesare focused on book value or
tangible equity, they're goingto miss out on a lot of these
really important drivers ofvalue, which also causes
distortions with respect to abias towards, say, asset-heavy
businesses which, as I mentionedearlier, have not performed as
well the past couple of decades.
Speaker 1 (08:43):
When you say intangible, I think digital
primarily, but let's talk aboutthe types of intangible assets.
Speaker 2 (08:49):
Yeah, yeah, so I touched upon them a second ago.
So at Sparklin we have aframework with four different
categories.
So the first one isintellectual property.
That's, you know, like patents,obviously would even trade
secrets, I would say software,any kind of like know-how, would
be in that category.
Second, brand equity.
That's pretty straightforward,think like Coca-Cola or LVMH.
The third category is humancapital.
(09:11):
You know, this is the having avery talented workforce, but
also having the culture be suchthat these people are all kind
of rowing in the same direction.
And finally, network effects.
Think like Facebook or GoogleSearch.
Right, having you know this isthe idea of increasing returns
to scale.
Whereas a network increases insize, it becomes more and more
(09:31):
valuable, you know, as afunction of the users.
So these are the kind of thefour main categories of
intangible assets that you know,we believe, encompass, you know
, most of intangible value today.
Speaker 1 (09:41):
So I think the challenge you could put me wrong
on this is how do you ascribe avaluation around each of those
categories, right?
It's like how do you considerif the market has priced in a
network effect as beingovervalued or undervalued?
So let's talk about that.
And then maybe also of the fourcategories.
Do we tend to see cyclesmeeting there sometimes when the
(10:03):
market favors brand equity overhuman capital?
You know, let's go through that.
Speaker 2 (10:08):
Yeah, no, that's a.
Those are both very goodquestions, so let's do the
second one first, because Ithink that is, you know, more
easily answered.
The answer is yes, absolutelyRight, like one of the
interesting story I could tellis that of Warren Buffett.
Going back to you know what Isaid earlier.
You know, when he first foundedBerkshire Hathaway, his
investments were primarilytraditional value stocks,
(10:30):
berkshire itself being in thatcategory, and over time he kind
of expanded what I call theinvestment moats to be more
intangible.
He met Charlie Munger.
He invested in Coca-Cola, wherebrand was very important and
human capital, the culture andthe management he would always
applaud.
And then, over time, obviouslythe biggest investment over the
past two decades has been Apple,which he valued for not just
(10:52):
its brand and management butalso the intellectual property
and the network effects.
So my thought would be networkeffects is kind of the most
recent one where, as the worldbecame more and more connected
by the internet and othertelecommunications technologies,
it's become more importantbecause of course the value of
network is a function of thenumber of people connected and
the world become bigger and moreand more connected over time.
(11:13):
You know, obviously,intellectual property and
technology that the capitalstock of the world has increased
in that aspect only morerecently, right Even going back
50 years.
Obviously technology was animportant element of what we do,
but less so and same withbrands.
So I'd say that there's thattime series element.
There's also a cross-sectionalelement.
(11:34):
One of the things that we did,as I mentioned, we launched an
international fund and we did alot of research to do that to
extend the intangible valueconcept from the US to non-US
countries, and one thing wefound was that in the US, the
intangible value concept fromthe US to non-US countries, and
one thing we found was that inthe US, the kind of primary
driver of value was intellectualproperty, which makes sense
since we had the best techcompanies.
But if you go to say Europe, ittends to be more brand equity
(11:55):
that drives the value of thesecompanies, which again makes
sense if you think of LVMH andmany of these kind of.
Speaker 1 (12:00):
And I thought the next thing is you were talking
about yeah, that makes totalsense.
Now, the moment you were sayingthat it's like, my mind
immediately went to brand as faras luxury right On Europe,
whereas in the US it is the IP.
Speaker 2 (12:12):
Yeah, exactly, and so yeah, and to answer your second
question, which is how do wemeasure it.
I think that's like you know,and I can go on for the next
hour about this if you want, butthat's where it's easier said
than done.
Nobody, from an intuitivestandpoint, would argue against
the idea that we should be, tothe extent we can, incorporating
intangible assets into ourmeasure of intrinsic value.
(12:34):
Of course that's the case.
Otherwise you're always goingto be underweight or short.
Nvidia and Google, apple, allthese great companies but how do
you actually do that?
It's easier said than done.
So the first thing we did to tryto attempt to measure this so
this is kind of sequential is wetried to basically correct for
accounting distortions thatpenalized intangible intensive
(12:55):
companies.
So not to get too technical,but basically when you do
physical capital expenditures,so physical CapEx, that CapEx is
capitalized, it becomes anasset on your balance sheet.
You build a factory with $100million.
It's a $100 million asset onyour balance sheet.
You depreciate that over time.
Now the inconsistency is thatan intangible company that was
(13:16):
trying to do the same thing, butdoing it on the intangible side
say doing research anddevelopment into a new drug or
engaging in a marketing andbranding campaign or investing
in training employees, that thisinvestment is not capitalized.
Instead, it's expensed, meaningthat these companies get a hit
to their bottom line in thatyear and they don't get to grow
an asset on their balance sheet,which is why I say Coca-Cola
(13:38):
has no book value.
And there is one more thing Ishould mention, which is that
acquired intangibles do show up,because if I acquire another
company, there's an item calledgoodwill that gets put on.
But this is a furtherdistortion in as much as it
penalizes companies that dohomegrown innovation, which is
many companies and arguably abetter way of building out a
(14:00):
company's IP.
So the first thing we did wassay what if we just treated
intangible investment like R&Dthe same way as we do physical
CapEx?
And you can do that.
And what you find is that ithelps a little bit and, in other
words, your portfolio as avalue investor is a little bit
less biased against technologystocks and healthcare and pharma
, life sciences and consumerbrands, but only a little bit
(14:21):
less.
And if you look at theperformance of the value factor
say Fama French, which is in adeep drawdown today relative to
its peak in, say, 2007, it's alittle bit less bad, but you're
still deep in the hole.
So, the point being that thiswas okay, but it was no panacea,
and if you think about why thatmight be the case, it just
comes down to the fact that justthink of this even more.
(14:42):
Basically, if you fact that,you know, just think of this
even more.
Basically, if you have twocompanies that are engaging in
R&D and one invents, you know,amazing, you know blockbuster
drug and the other one, you know, can't pass trials, well,
obviously, even if these twocompanies put the same amount of
value in, the output is verydifferent, and this is a feature
of intangible assets, thatthere's kind of this
non-linearity between input andoutput costs.
And so we decided a better way.
(15:02):
You know that the accountingmethodology was kind of a
non-starter that we can't lookat historical cost-based
analysis and we still have tolook at the output of this
investment, and that was kind ofthe next step that we went
forward to.
Speaker 1 (15:18):
How much does the importance of these different
intangible assets change,Meaning, is there a volatility
to brand equity?
Is there a volatility to IP?
I mean, I assume not, but Imean presumably there's an
aspect there.
Speaker 2 (15:34):
Yeah, I mean, it depends if you're asking at the
company level or, like at the,you know, at the sector level.
At the company level,definitely, you know, you have
examples of.
You know one thing I looked atwas like Amazon right, when they
first got set up in the late90s, they were just an online
bookstore, right, so they hadyou know good brand and you know
some IP, but you didn't reallyhave network effects.
But over time, as they expandedinto like the third-party
(15:56):
marketplace, into AWS and otheraspects like that, they their
kind of network effects grew andgrew and grew.
They obviously became huge andthey have this massive moat now
with their logistics anddistribution, and so that
changed through time.
Their brand arguably improvedand obviously they've had some
negative components as well.
(16:16):
So, again, these things aredynamic.
They do evolve through time,both at the overall level, as we
discussed, but also at thecompany level.
Speaker 1 (16:24):
We're going to get into the individual funds
themselves.
But OK, so you've got theframework.
Us international side of things.
Talk to me about people'sunderstanding of the concept.
All this makes a lot of sense,right, but I think people tend
to be talking their old ways ofanalyzing markets.
You find that it's hard to getpeople around the idea that
(16:44):
value is just not definedproperly, that this is a better
framework.
Speaker 2 (16:47):
Yeah.
So you know, maybe before Iyeah, so I think let's talk
about two things.
So first let me just go back towhat I was saying.
I want to kind of just finishthat thread there on how we
measure intangible value.
And so if accounting is not theway forward, like, what is the
path?
And you know, the insight we hadwas look, we actually live in
(17:07):
like the 21st century where wenow have access to what's called
big data, right, just massive.
Everyone.
You know there's hugeexponential growth in
information available tocompanies that may exist outside
of the 10K and 10Q.
This could range from anythingfrom trademarks to
user-generated data, socialmedia, right.
All this information now existsabout with potentially relevant
information on companies.
And so why aren't we using that?
Because that would seem like anatural place to look for
(17:30):
insights into companies andtangibles, and so we said that
that's an interesting place,let's start with that.
But then the barrier we ran intowas that this data is large and
unstructured.
So think about like an exampleof a patent.
Intuitively, if you wanted tomeasure, say, google's IP, you
would say, all right, let's readall the patents.
There's thousands, hundreds ofthousands of patents here, which
is obviously time consuming butin theory, doable.
(17:52):
The problem is you can't do itsystematically.
You can't just take a bunch ofpatent abstracts and throw them
through a linear regression.
Instead, you need better toolsto process the text.
So the first thing we did waswe said let's just use a simple
natural language processing tool, like just dictionary-based
approach.
So let's look for keywords,Because what we're trying to do
here is to distinguish fromlagging edge versus leading edge
(18:12):
patents.
So we can say let's just lookfor all patents that mention AI.
Right, that would be one simplehack and you can do.
You know more sophisticatedversions of that and that's, you
know, directionally helpfulbecause it'll help you
distinguish which.
You know which companies don'tjust have a lot of patents but
have really innovative ones.
But then over time, you know, westarted doing more
sophisticated techniques.
(18:33):
So around 2019, 2020, you know,I wrote a paper where I kind of
highlighted the potential largelanguage models which underpin
today's chat GPT as a way oftaking this unstructured data
and processing it into a youknow, a factor or to a single
score, and over time we used totrain our own models, you know,
from scratch, in-house and overtime.
Obviously, the providers, suchas the open AIs and anthropics
(18:57):
of the world have become so muchbetter and have invested so
much more resources into thesefoundational models.
Now we utilize those, which hasbeen a huge boon to what we do
right, because now a greater andgreater share of the insight in
these unstructured data setscan now be measured.
(19:20):
I think the final piece I shouldmention is when we convert this
into actual scores forcompanies.
We are value investors, sowe're not going to say, hey,
which company has the mostinnovative patents?
Because then you're just goingto get Google we care about.
You know which company has themost innovative patents relative
to market cap?
So it's more of a dividendyield or a earnings yield or, in
this case, a patent yield.
And we blend together all thesedifferent measures of
intangible assets from IP sideto brand, to human capital which
companies have the most talentrelative to the market cap,
(19:42):
which have the most brandmetrics and you come up with a
single composite score forvaluation.
So that's kind of our overallprocess, where we are using
large language models and AImerely as a tool not necessarily
predict the stock pricedirectly, but instead as a tool
to take the unstructuredinformation about companies that
are kind of hidden in all theseunstructured data sources and
(20:05):
to create factors around thefour pillars which we can then
bring into the creation of avalue factor.
Speaker 1 (20:12):
I love that.
The website sparklinecapitalcomfor ITAN factor.
I love that.
The website sparklinecapitalcomfor ITAN.
I love this graphic because youreally kind of break it down in
terms of where the companiesfit in.
Talk to me about turnover whenit comes to this kind of
framework meaning do a lot ofcompanies tend to go out after
some period of time, come in?
(20:33):
How does that look?
Speaker 2 (20:34):
Yeah, I mean there is certainly turnover.
It ends up being kind ofroughly the same as a more
traditional value strategy.
So think, like you know lessthan you know less than over.
The holding period on averageis over a year for these names
and turnover can be driven bytwo things just mathematically.
So of course there could bechanges in the fundamentals.
So imagine you own a companyand there's these major scandals
(20:54):
and the culture starts to decayand employees are to leave
Right, that would be a negativechange in fundamentals.
Or on the other side, you couldhave a company that you know
they start investing in, I don'tknow, ai, some kind of emerging
technology, early on and as we,as that trend starts to take
off, they really benefit on theIP side from that.
So fundamentals do change andthey do evolve through time, but
(21:16):
pretty slowly on average.
For example, company culturesgenerally are pretty sticky
through time.
The founders set the tone andhopefully the managers can carry
that torch moving forward whenyou see a lot more.
I think a lot more of theturnover actually gets driven by
the price side.
And this is the same, by theway, for like traditional value
price to book type strategieswhere you know prices are just a
(21:38):
lot more volatile thanfundamentals, and so what ends
up happening is you own a stockthat you like and then you know
prices, you know they run up andyou, you know, at some point
you say this stock is nowovervalued, we'll take our
profits and rotate and move on.
Or you find stocks that youthink are kind of interesting
but not quite at your thresholdPrecious fall, holding constant
(21:58):
fundamentals, and that's whenyou buy.
So a lot of turnover is drivenby precious, but even then, that
being said, going back to myinitial answer, the overall
turnover is pretty slow, alittle bit over a year on
average, but obviously thatchanges based on market
conditions.
Speaker 1 (22:12):
So I often use this line that what you own often
matters a lot less than how muchyou own of it.
All right, talk to me about howyou go about weighting with
this type of approach.
We know that very well-knownmarket gap weighting, weighting
some factor tilt, right.
But given that some of thisstuff you can argue is a little
(22:33):
bit squishy, right, how do youthink about weighting on this?
Speaker 2 (22:36):
Yeah, no, we've actually thought a lot about
this question when we designedthese funds.
So, as you point out, there'skind of two extremes you can use
.
On one end you can use fullmarket cap waiting.
On the other end you can useequal waiting.
So full market cap waiting hasthe advantage of tons of
liquidity, kinds of liquidityand, um, you know, in theory, to
(22:58):
the extent where clients,whether you like it or not,
measure you against the s&p,that will, you know, reduce the
amount of tracking error to thatum.
The downsides, of course, arethat now you're kind of
constrained with respect to yourbreadth, like you can't really
tilt that much on the, you know,on the smaller cap names, um
and um, and you also faceconcentration risk in as much as
if you, like some of the topcompanies, like you can only
hold so much, I mean, you'regoing to be massively overweight
(23:19):
, say the Mag7.
Equal weight has the oppositeproblem.
So equal weight you have themost breadth and you know is
kind of the most uniqueportfolio, the most active share
, but the downside, of course,being that a lot of that active
share is just driven by thissingle factor the size tilt
against S&P, and you know, andif it goes in your favor, you
look at the hero, and if it goesagainst you, you look at an
(23:40):
idiot.
And so that's not really thatfair.
And plus, it has lowerliquidity.
And so we tried to throw theneedle here, and what we ended
up doing was devising a kind ofhalfway between solution to
throw this needle, which isbasically the square root of
market cap.
So you can think of like achart where, like, you have the
market cap on the X axis andthen the Y axis is your position
.
It's a square root function, soit's like a concave function,
(24:01):
and the advantage of that isthat if a stock is, say, nine
times bigger than another stock,it only gets three times as
much weight.
So it does get more weight andthat helps increase the
liquidity and reduce thedependence over-dependence on
the size tilt, but it also stillleaves enough room to be making
pretty active decisions.
So we kind of settled on thatas a middle ground and, by the
(24:25):
way, this was something that Ididn't invent.
We did this at GMO and I'm suremany other coin shops also use
such a technique.
But going back to this overallquestion, so the portfolio is
built like this we effectivelyhave an investment universe,
going back to this overallquestion.
So the portfolio is built likethis we effectively have an
investment universe In the caseof the US fund, it's like the
top 1,000 US stocks and then inthe international universe it's
(24:46):
a universe of non-US stocks.
What we do is we have scoresfor each company, we line all
the stocks up for each company,we line all the stocks up, we
then, within our universe, takethe top 10% to 15%, depending on
the fund, and then that's yourportfolio.
We don't equal weight.
We then apply two tilts.
One is by the factor.
(25:07):
So obviously more intangiblevalue means more weight, and
then also more market cap meansmore weight, but only
proportionally to the squareroot, not the full market cap to
weight, but only proportionallythe square root, not the full
market cap to help create morediversification.
Speaker 1 (25:20):
All right, so a lot of interesting points here.
We talk about weighting fromthat perspective, which is
easier when it's a US-only fund.
Let's talk about DTAN, becausewhen you're dealing with
international investing, you nowhave to think about country
weightings as part of that.
Walk me through how that looks.
Is that just a function of sortof the output on the individual
names?
In terms of the intangibleassets?
How does the country allocationlook right now for DTM?
Speaker 2 (25:43):
Yeah, that's another good question.
So, as I mentioned before, likebefore I started Sparkline, you
know I was doing kind of morehedge fund style investing and
you know, when you go long shortand you're, you know, highly
levered on both sides, on bothsides risk management at the
factor level is very important.
So this is your bar, oractually only models, where you
can strain not just by countrybut you also can strain by
sectors or industries and youwant to be very, very tight
(26:05):
there to kind of remove anyunwanted exposures to various
risk factors that could createvolatility and hence create
problems, to the extent thatyou're highly levered In
long-only funds.
I've actually found that thatis kind of trying to be QQ'd.
You're kind ofover-concentrating the models by
attempting to do all the kindof sector neutralization and
(26:27):
style neutralization incountries, and so instead what
we've decided to do is to letthe weights go bottoms up.
It might be the case that at anypoint in time, the best
companies say all the humancapital and all the talent is
going into the tech sector.
Well, that's great, we shouldallow the fund to overweight
tech.
Or if all the talent happens tobe in, say, germany, that's
great, we should let the fundoverweight Germany.
(26:48):
So I think to a large extentyou don't want to mess with it
too much.
Obviously, if things are goingreally crazy, that's when you
might need some constraints.
But at least in our research,when we design the fund and also
positions, today that hasn'treally been the case, and so, to
answer your question, we letthe weights the country weights
and sector weights go bottoms up, just depending on what stocks
(27:11):
on an individual basis appearattractive on intangible value.
Speaker 1 (27:16):
I feel like we need to hit on currency to some level
here, because obviouslycurrency returns are a part of
total returns when you'reinvesting overseas.
But maybe a little bit morenuanced how does currency
volatility play into intangibleasset value?
Speaker 2 (27:33):
Honestly, we don't really include that as a
specific component of intangiblevalue.
We view stocks as realbusinesses and their
fundamentals are what they are.
And in the DTN fund we actuallydo not currency hedge, so we're
not hedging, we're not payingto hedge out the FX exposure.
So the stock prices will kindof move up and down also with
(27:57):
the dollar as it turns out.
You know, we do think thedollar remains expensive.
You know, whether I'mpurchasing per parity or any
other metric, you know, and whenwe launched the fund in
September we thought that couldbe a nice tailwind to have for
investors.
Speaker 1 (28:10):
you know, in the fund yeah, and obviously there's
been a lot of demand on theinternational side because
international has done a lotbetter than the US and that's
more of a traditional valuationcall right, I mean, as opposed
to intangible value.
But make the case for I thinkit's compelling when it comes to
the US, but make the case forintangible value as being a big
driver of that value discussionwhen it comes to international
too.
I think also part of this isalso around the idea that style
(28:35):
classifications in the US growthversus value, I'd argue, is
more driven because of tech.
In people's minds that's thequintessential growth sector
characteristic.
You don't have that in anythinginternational, which means I
think typically most would viewinternational markets anyway in
passive form as value.
Speaker 2 (28:54):
Yes, I want to answer that question in two parts.
So I wanted to pull on thatthread a little bit about the
value versus growth style thing.
And is it just tech?
So I actually wrote a separatepaper on this in 2019 where I
created I basically argue thattech is not a is a first
approximation of innovation, butobviously it's not sufficient,
right, because there'sinnovative tech companies and
non-innovative tech companies.
(29:15):
There are companies inindustrials that are very
innovative and others that arenot, right?
Amazon's a retailer, google's acommunications company, and so
I devised a factor called Icalled it disruption factor, so
innovation and then was able touse that as a way of kind of
saying you know what is theexposure of, say, a traditional
value portfolio or growthportfolio to that factor?
And indeed it is the case thattraditional value portfolios
(29:39):
tend to load on a shortinnovation factor, whereas
growth tends to load on a long,but it's not always 100%
correlated.
So I just wanted to make thatdistinction and I think that
actually flows nicely into whatis the point of these funds,
right?
So, whether in US or not in US,kind of the point of this fund
is to try to deal with thissituation we find ourselves in
now, where the investmentcommunity has become like super
(30:01):
bifurcated, where you have valueinvestors kind of your old
school guys who are kind ofholding onto these principles
but finding themselvesincreasingly, first of all, with
poor performance on a relativebasis, but also in stocks that
are kind of your old economynames financials, energy
materials, industrials,companies with much less dynamic
(30:22):
businesses and then you find,on the opposite side, your
growth investors who have donepretty well on the back of the
tech or innovation tailwindwe've seen in the past two
decades, but are increasinglyexposed to overvalued names,
because the world's kind ofcaught up to this idea that
tech's done better, right,people are pretty performance
chasing in general, and alsothere are these big swings right
(30:44):
, 2022 is not a good year forinvestors in technology stocks.
Interest rates were raised,there are other things that
happened, and a lot of thesecompanies that had pretty high
multiples to begin with ended upgetting smoked.
Because that's a big, thevaluation compression can be
pretty painful, and so whatwe're trying to do with these
products here is trying tobridge the gap between value and
(31:05):
growth, to create a strategythat say applies value,
investing these timelessprinciples, but also in a more
modern way with an acceptorexposure that includes
technology companies and canoperate successfully in sectors
other than the most traditionalones.
We find that price to bookratio still works if you apply
it in certain old economysectors.
(31:26):
It just doesn't work fortechnology companies.
You can't pick between Googleand Microsoft by using price to
book.
But intangible value does work,or we found it does work, at
least in the more modern sector.
So this is a way of takingvalue, investing and modernizing
it.
The other way we think aboutthis is on the growth side,
which is here's a way of owninginnovative companies, but with a
(31:46):
valuation discipline such thatif a stock goes up too much,
we'll sell it.
A great example that I talkedabout in my last investor letter
is NVIDIA.
So in ITN, our original fund,which is about four years old,
we actually owned NVIDIA atinception.
So this is 2021.
The P ratio of NVIDIA wasaround 100.
(32:07):
So a traditional value investorwould say this thing's super
expensive, there's no way I'mnot even touching it.
But then, once our modelsadjusted for intangibles, their
IP, their innovative culture,etc.
We actually found that thestock was not only cheap but
very cheap, went up a ton, atwhich point the model said, all
(32:40):
right, well, this is still agood stock, but it's just not
cheap anymore and so let'srotate out.
And we ended up going into someother more under the radar AI
plays.
But I think that illustratespretty nicely that this strategy
, while being kind of focused oninnovation and modern and
tangible intent of thebusinesses, is still a value
strategy and still cares a lotabout the price you're paying
for a lot of these assets.
Speaker 1 (32:58):
All that makes a kind of sense to me.
Those that are listening tothis you know that are intrigued
by the idea.
They're looking at the fundsand you know they might be used
to seeing some ETFs that trade.
You know hundreds of thousandsof volume shares traded daily
and they see the volume on ITANand DTAN.
Maybe they get a little bitconcerned about liquidity.
I want you to do some mythbusting around volume, liquidity
(33:23):
and how people should thinkabout smaller funds.
Speaker 2 (33:27):
Yeah, and look, what I'm going to say here is not
specific to what I'm doing.
It applies to any ETF, justbased on the way these things
are built.
So ETFs are just baskets.
They're baskets of stocks and,due to the arbitrage allowed by
CreateRedeem, they generallytrade very close to NAV.
And the way that works is, ifit trades at a premium, the
(33:49):
market makers will arbitragethat one way, or at a discount
the other way.
The capacity or liquidity of anETF is a function primarily of
the liquidity of the underlyingstocks.
So, for example, if I had asingle stock ETF where the only
holding was Apple, which issuper liquid, the ETF would
(34:10):
basically have the liquidity ofApple, more or less.
And so what you evaluate andthis is again not just specific
to me when you evaluate ETFsthat are, say, thinly traded or
kind of new or smaller ETFs,what you want to look at is what
are the actual underlyingholdings?
If you're holding micro-capemerging market stocks, then it
may actually not be that liquidand the spread, the bid-ask
(34:31):
spread, if you go on your screenshould be pretty wide to
reflect that.
If it's just trading mega-capUS stocks, it should be pretty
narrow.
In our case, itan, I think it'strading around 5 cents wide.
So currently I mean, and itholds Russell 1000, so top 1000
US stocks, so it's large and midcap names, so that's pretty
(34:54):
liquid.
Dtn is a bit wider.
It's a bit it holds non-USnames, which is a little bit
less good, but in both casesthese are kind of your large cap
stocks, like Amazon and Googleare kind of the top two current
holdings of ITAN.
So I think that liquiditygenerally has not been a concern
.
We've had investors put inamounts of money that are
(35:16):
significant percentages of thefund in a single day and have
had no issues with trading.
But of course, if that'ssomething you, if you're
interested in this concept, feelfree to reach out to me.
Or you know the trading team,you know Alpha Architect, who
does the operations for the fund, as you know, will obviously be
able to kind of help, you know,with any kind of specific
questions.
Speaker 1 (35:36):
So about how to think about this in terms of a
diversified portfolio, obviouslystill equities, obviously still
in a correlate to equities,maybe slightly less so, you know
, at least in kind of highervolatility junctures.
But how do you want to thinkabout pairing this against more
traditional passive investments?
Can this be a core?
Speaker 2 (35:55):
allocation.
So one of the things that wewere pretty deliberate to do is
to ensure that these stocks,that the ETFs, had sufficient
diversification.
So both ETFs have over 100names, right?
So it's not like you're.
Hey, you're buying a fund withthree stocks and therefore you
would, by definition, need tohave a handful of managers to
kind of diversify around that.
(36:16):
In our case, we hold enoughstocks that you know, even
though the active share can be,you know, pretty high relative
to, say, the S&P 500, you'repretty diversified across a lot
of names.
So you know that would helpwith the question around core
holdings.
I mean, there's look, there'sthree different ways I've found
that our clients use our funds.
So first is, you know, as youmentioned, as the first is, as
(36:37):
you mentioned, as a kind of wayof getting tracking error
against a passive index thatloads up on these intangible
value factors which we believeshould lead to outperformance.
A second way is as a valuesubstitute that will tend to
give you a bias towards your oldeconomy stocks, which you may
(37:01):
want to offset.
But you can offset it by justbuying, say, the QQQ, but then
you're just going growth.
So another way of doing thatwould be to instead add, say,
one of our funds which allowsyou to still be kind of
value-focused but just apply iton the intangible as opposed to
tangible side of the balancesheet.
And because our funds tend tobe more intangible, intensive,
tend to be more tech and grandfocused, you kind of balance out
(37:23):
some of the old versus neweconomy exposures and the final
way I've seen this be used is onthe growth side, where you have
folks who want to be exposed totechnology and growth and
innovation but also want a fundthat will be aware of the
valuation so that as things runup they'll kind of take profits
and prudently rotate into otherless overvalued assets.
(37:47):
Like we did a paper calledInvesting in AI Investing in AI
Navigating the Hype, and we dida study of the dot-com boom and
bust and one thing we found wasthat if you just buy the
internet stocks, you do reallywell and then you do really
poorly.
But if you're instead dynamicand you're kind of rotating
through based on valuations,kind of always rotating into the
cheapest internet stocks, youdo okay.
(38:08):
And that's kind of the ideahere, which is I find that you
know you don't need to kind ofworry about should I trade in
and out of this, based on, likeyou know, the valuations of, say
, the tech ETF or whatever, butit could just be something that
will smoothly, hopefully,navigate you through the various
valuation cycles.
Speaker 1 (38:29):
Any thought on how policy initiatives from the
Trump administration could maybeimpact the way intangible value
is valued?
I mean, I think aboutderegulation that may be
impacting the IP side.
I think about tariffs may beimpacting even the brand equity
side.
I mean, does that factor intoanything as you think about the
portfolio?
Speaker 2 (38:44):
Yeah, actually, the last paper I wrote, which came
out, I think, about a few weeksago in April, was called
Investing Amid Trade Wars, andit talked about the impact of
tariffs on global trade and onstocks more specifically.
One of the nice things aboutintangible assets is they can't
(39:05):
be tariffed.
So if you have a physical goodand it goes over on a ship to
customs, it's going to getinspected and potentially
tariffed, whereas an intangibleasset think like streaming music
or video, any kind of software,even services type thing cannot
be tariffed, right.
So that's actually makesintangible assets, I think at
(39:27):
least, a lot more robust when itcomes to the impact of this
tariff driven volatility, rightLike tariffs are on, tariffs are
off.
Tariffs are on, tariffs are off.
We don't know how things willplay out.
It's possible that we end upwith nothing, that that sticks,
but I think, regardless, we'regoing to end up.
I think, regardless, this hasbeen a shot across the bow.
Um, you know, companies andcountries are now, you know,
(39:49):
standing kind of more, more, uh,sanitized to the kind of, um,
geopolitical risks of supplychains going through various
countries and, as such, likethis is a factor that will
affect all companies, but Ithink those businesses that are
more intangible, intensive, havea bit of advantage just because
of the nature of intangibleassets.
(40:09):
And I think the second thingthat's really happened is and
this is partiallyunintentionally and partially
intentional on the part of theadministration is this kind of
like sell America theme right?
So we've seen over the pastyear past year to date, I guess
you know international stockshave rallied 15%, while US
stocks are basically flat.
So this huge gap has opened upin US versus non-US.
(40:31):
We've seen US bonds sell off,we've seen the US dollar sell
off, as capital is apparentlyfleeing the US into, you know,
other geographies.
And so I think what's happenedis a lot of US investors have
found themselves offsides tooverweight US stocks.
And that's a function of youlet your winners run.
So when US stocks do reallywell and they end up being 70%,
(40:53):
80%, maybe 100% of yourportfolio, you just kind of say
that's working.
But what's happened is, youknow, now it's the opposite case
, where the idiosyncraticpolitical risk is now in the US,
not as much abroad.
And so if you're an investorwho has, you know, 90 to 100% in
US stocks, right, maybe Ishould think about diversifying
internationally, maybe this Ican't tell you whether or not
(41:15):
this theme will continue movingforward, but it might.
And the problem here, thechallenge, is that the
international stock index is notthat good, right?
So I think about IFA or AcquiaxUS.
It's about 25% financials andthen 20% industrials, right, it
is very.
The kind of general stereotypeof non-US stocks as being less
(41:37):
dynamic, less innovative isactually true, at least at the
index level.
And so the key with DTAN whichis the you know find, where we
took the concept and put it intonon-US markets is that it only
invests in a subset of names andinvests in a subset that are
the most intangible, intensive,so they're kind of levered to
this growing intangible economy,this trend of growth.
(41:58):
It owns, as we discussed, morehealthcare, more brand-intensive
companies, even withinindustrials, the more innovative
technology names.
So it's a way, I think, ofdiversifying outside of the US
while still maintaining exposureto this intangible theme which
I think you know over the next,you know, 10, 20 years will only
(42:19):
become more and more pronouncedand important to the economy.
Speaker 1 (42:23):
And personally I think it makes the entire
concept makes a lot of sense andI've seen other papers outside
of viewers that have similararguments.
Speaking of those papers, wherecan people get access to those?
Speaker 2 (42:34):
Yeah, so just go to my website sparklinecapitalcom.
I publish all my research there.
Speaker 1 (42:39):
Perfect, and I obviously did learn more about
the funds sparklinecapitalcom.
Any final?
Speaker 2 (42:43):
thoughts here before we wrap up.
No, this has been a fundiscussion and I look forward to
answering any other questionsthat come up.
You can feel free to reach outto me directly online or just
send me an email.
I think my email's posted on mywebsite somewhere.
Speaker 1 (42:59):
I appreciate those that watched this live.
Again, this will be a podcastunder Lead Lag Live.
We're going to be doing thesemonthly, so you'll be hearing
more from Kai and we'll get intosome more nuances, especially
as it relates to the environment, and maybe some analysis on
individual positions across thetwo ETFs.
Hopefully, I'll see you all inthe next episode.
Thank you, kai, I appreciate it.
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