Speaker 1: Welcome to Inside Active, a podcast about active managers that
Speaker 1: goes beyond sound bites and headlines and looks deeper into
Speaker 1: their processes, challenges and philosophies and security selections. I'm David Cohne,
Speaker 1: i lead mutual fund and active research of Bloomberg Intelligence.
Speaker 1: Over the past decade, investing in technology has largely meant
Speaker 1: owning a small number of dominant companies. Passive strategies have
Speaker 1: made that easy but also highly concentrated. At the same time,
Speaker 1: we're entering a new phase of innovation driven by AI,
Speaker 1: where the next set of winners may look very different. Today,
Speaker 1: we're exploring what it means to actively invest technology in
Speaker 1: that environment to help us unpack that. I'm joined today
Speaker 1: by Dom Rizzo, a portfolio manager for the Troll Price
Speaker 1: Global Technology Fund tick our PRGTX and the trow Price
Speaker 1: Technology Etf tick your t Tech. Don thanks for joining
Speaker 1: me today.
Speaker 2: Thanks for having me. David really appreciate being here.
Speaker 1: So let's start with your process when you're invaluating a
Speaker 1: new investment. What does your research process actually look like
Speaker 1: from you know, first look to an actual position in
Speaker 1: the portfolio.
Speaker 2: At TIRO, we have so many great investors right, and
Speaker 2: I'm going to add TIRO for over a decade now,
Speaker 2: and I always say, you have to find a framework
Speaker 2: an investment process that really fits your personality. So when
Speaker 2: I talk to our young folks coming out of college,
Speaker 2: I always say, you know, t s Elliott's got this
Speaker 2: great line. Good author's borrow, great authors steal, and I've
Speaker 2: stolen so much of my framework from the great investors
Speaker 2: at TIROW, whether it's a David Eisweer or Justin Why
Speaker 2: or David Jeru, David Wallack, or our MidCap value PM.
Speaker 2: So I think you have to kind of come up
Speaker 2: with your framework and cobble it together through making mistakes
Speaker 2: and building it out. So kind of with that background,
Speaker 2: you know, over time at TRO, I've been really fortunate.
Speaker 2: I've covered hardware stocks, software stocks, payment stocks, small cap, MidCap,
Speaker 2: large cap, megacap us, Europe, Asia, and so I had
Speaker 2: to find a framework that kind of could do all geos,
Speaker 2: all regions, and all subsectors attack and that ended up
Speaker 2: being you know, looking for four things. Number one is
Speaker 2: what I call lynchpin technologies. These are the technologies that
Speaker 2: are mission critical to the success of their customers or
Speaker 2: make their users' lives dramatically better. The second, they have
Speaker 2: to be innovating in secular growth markets. What does that mean?
Speaker 2: That means taking share and fast growing and markets. I'm
Speaker 2: sure we're going to talk about AI today. Probably the
Speaker 2: biggest secular growth market that I see is AI chips.
Speaker 2: You know, we're going from forty five billion dollars at
Speaker 2: AI chip spending in twenty three to five hundred billion
Speaker 2: dollars at AI chip spending in twenty eight to you know,
Speaker 2: a trillion dollars by twenty thirty or potentially earlier. So
Speaker 2: you've got to be taking share in fast growing and markets. Third,
Speaker 2: and this is really important for kind of tactical trading,
Speaker 2: is I think stocks move when they have improving fundamentals,
Speaker 2: and so that's revenue that's accelerating, operating margins that are expanding,
Speaker 2: or free cash flow conversion that's improving. And then finally,
Speaker 2: you want to make sure you have a reasonable valuation.
Speaker 2: So in tech, I think the way you get burned
Speaker 2: is if you overpay and you can't compound from those
Speaker 2: very high valuations. And so I would say, you know,
Speaker 2: twenty twenty one software stocks is a great example of that.
Speaker 2: Or actually, if you get pulled into a value chap. Right,
Speaker 2: So if you get pulled into a value trap and
Speaker 2: it's broken and it looks cheap optically, but it's never
Speaker 2: going to change. So I just want to make sure
Speaker 2: that the valuation we're paying is reasonable and that we
Speaker 2: can compound there. So those four things lynch technologies innovating
Speaker 2: in secular growth markets with improving fundamentals have reasonable valuations,
Speaker 2: and I use that framework across both my strategies.
Speaker 1: So what would kill an idea of like valuations? You know,
Speaker 1: you might find like a potential company, but the valuations
Speaker 1: just don't look great, and that would kind of prevent
Speaker 1: you from jumping in.
Speaker 2: I think in the short term the thing that actually
Speaker 2: kills ideas the most is not having improving fundamentals. So
Speaker 2: finding a great company is actually relatively easy. We could
Speaker 2: just put it in chat GBT and say, oh, find
Speaker 2: me all the companies with like high returns on invested capital.
Speaker 2: So so, and finding companies that are expensive or cheap
Speaker 2: is actually relatively easy. You know, when you go into
Speaker 2: Bloomberg and you say, okay, what is the average historical
Speaker 2: pe for a STOC and what is it today? Right,
Speaker 2: it's not that difficult to figure out those things. I
Speaker 2: think the thing that's hard is having this insight on
Speaker 2: improving fundamentals, which anyone who's hurt Dave Eyes were at
Speaker 2: hero Speak knows that I completely copied that from him,
Speaker 2: going back to this point about stealing, and that's the
Speaker 2: hard part. You need. You need to be able to
Speaker 2: have this great insight about revenue that's inflecting and why
Speaker 2: and so so right now, I'll give you an example.
Speaker 2: We really like the CPU eco ecosystem names like a
Speaker 2: m D or Inteler ARM and that's because of an
Speaker 2: agentic world. CPUs become meaningfully more important to the orchestration
Speaker 2: layer and how how all these different ais work around
Speaker 2: an organization. Basically, the CPU increases barely materially in spending.
Speaker 2: So that's an insight that's going to result hopefully in
Speaker 2: revenue that's inflecting and and and that that's the thing
Speaker 2: that in the short term definitely either gets an idea
Speaker 2: into the strategies or kicks them out. Valuation is always
Speaker 2: something we consider. The one thing I always caution the
Speaker 2: team is that you could have really outsized outcomes in tech.
Speaker 2: And I'll give you an example. You know, when I
Speaker 2: did the anthropic round in the Global Tech Fund in
Speaker 2: in the summer, they were, you know, run raining roughly
Speaker 2: five billion dollars of ar R. No, no one in
Speaker 2: their right mind thought we would be close to twenty
Speaker 2: billion dollars of ARR by March, right, So, so you
Speaker 2: could have these outsized outcomes and then all of a sudden,
Speaker 2: the valuation is actually far more reasonable. So, yes, valuation matters,
Speaker 2: but make sure you have an imagination and try to
Speaker 2: have an insight into that improving fundamentals.
Speaker 1: So I just kind of want to do a follow
Speaker 1: up to that. You know, is it kind of you know,
Speaker 1: other specific you know, signals you're looking for for improving
Speaker 1: fundamentals you know overall, or is it kind of differ
Speaker 1: from company to company.
Speaker 2: A difference for company to company. Sometimes revenue growth is
Speaker 2: the thing that drives the stock. Sometimes it's order growth.
Speaker 2: Sometimes it's operating margins that you know, I'll give you
Speaker 2: a great example that we're debating right now internally is
Speaker 2: free cash flow. So if you look at the mag
Speaker 2: seven stocks, they're very cheap on PE and they're also
Speaker 2: very cheap on a peg ratio, so PE to growth. Right,
Speaker 2: So if you look at the mag seven versus the
Speaker 2: rest of the market. The max seven of PEG is far,
Speaker 2: far less than the mag seven of the whole the
Speaker 2: peg ratio of the whole market. But what's the issue
Speaker 2: with the mag seven. Of the seven of them, you know,
Speaker 2: six of them have increased in capital intensity, either through
Speaker 2: capex on their own balance sheet or you know, in
Speaker 2: the case of Apple, capacks on Google's balance sheet effectively,
Speaker 2: right because of their geminideal capital intensity is increasing for
Speaker 2: those companies, and then dollars are flowing into the semiconductor
Speaker 2: and semi capital equipment and you know, foundry ecosystem from
Speaker 2: the balance sheets of the most profitable companies in history.
Speaker 2: So a debate we're that's raging internally right now. Is
Speaker 2: it revenue acceleration that matter, is it operating margin expansion,
Speaker 2: or is it free cash flow conversion? Which of those
Speaker 2: three is actually going to drive those stocks today as
Speaker 2: we sit here on you know, March thirtieth, it appears
Speaker 2: free cash flow conversion is what the market's considering. But
Speaker 2: you know, let's see after earnings in April, Yeah, makes sense.
Speaker 1: I do want to take a quick step back and
Speaker 1: just think about technology companies as a whole what do
Speaker 1: you think would make a technology company enduring in a
Speaker 1: space it seems to change so quickly? Is it really
Speaker 1: you know their modes, you know their ability to adapt,
Speaker 1: you know, is it a leadership?
Speaker 2: This is where I came up with Lynchpin technology. And
Speaker 2: and you know, the one thing I don't love about
Speaker 2: the word enduring is it implies some level of durable growth.
Speaker 2: And I think the point that you're making, David, is
Speaker 2: that durable growth is actually very hard to come by
Speaker 2: in an age that's changing so rapidly because of AI.
Speaker 2: You know, five years ago, anyone who studies software would
Speaker 2: say that one of the most durable, enduring franchises in
Speaker 2: the world is the Microsoft Office Suite. Well, guess what
Speaker 2: if you spend most of your day in chat gybt
Speaker 2: or Claude, is the Microsoft Office Suite actually the most
Speaker 2: enduring piece of software in the world or is it
Speaker 2: potentially chatgybt or a claud that may aggregate all the
Speaker 2: data that sits below it, and Microsoft Office may just
Speaker 2: be a pipeline into your AI that's walking around with
Speaker 2: you all day. So it changes so rapidly, and so
Speaker 2: that's why I love this Lynchpin word. And I kind
Speaker 2: of came up with birth it by covering ASML. So
Speaker 2: I lived in London from twenty eighteen until twenty twenty
Speaker 2: three and I was our European tech analyst for part
Speaker 2: of that. And I love this concept that I really
Speaker 2: thought ASML was the most important company in the world, right,
Speaker 2: and I think we're actually kind of seeing it now.
Speaker 2: You know, chips are so important to not just AI
Speaker 2: build out but consumers, PC sparphones, defense, aerospace chips. Like
Speaker 2: people say right now is the new oil. But I
Speaker 2: find it funny because you know, the memory stocks Samsung, Heinex,
Speaker 2: and Micron are going to generate significantly more free casual
Speaker 2: than all the oil stocks put together. Right, But you
Speaker 2: know they're they're bigger than oil, bigger than us deal, right,
Speaker 2: bigger than oil. But uh, the the lynchpin of all that,
Speaker 2: in my opinion, is this EUV machine from ASML, which
Speaker 2: I consider the most important machine in the world. And
Speaker 2: we don't have to get into the details of it.
Speaker 2: So so I think finding this Finding companies that are
Speaker 2: mission critical to the success of their customers or make
Speaker 2: their users' lives dramatically better, results in more enduring outcomes.
Speaker 2: But like you said right now, part of the fun
Speaker 2: and where I think active can really add, you know,
Speaker 2: tremendous value is figuring out which lynchpin statuses are becoming
Speaker 2: more enduring and actually which lynchpin statuses are becoming less
Speaker 2: enduring and why something into indices frankly can't really do
Speaker 2: and I think active investors can.
Speaker 1: Okay, So if you have, you know, a company that
Speaker 1: you want to put in the portfolio, or you know,
Speaker 1: either the ETF or the mutual fund, how does that
Speaker 1: translate into position sizing? You know what earns kind of
Speaker 1: a larger position versus small and you know, does it
Speaker 1: differ between the two fun rappers, Well.
Speaker 2: The position sizing and portfolio construction is a bit different
Speaker 2: between the between the two rappers. And and since you
Speaker 2: kind of led me there, I'll just quickly go through that.
Speaker 2: If you think about the Global Technology Fund pr gt X,
Speaker 2: the right ETF competitors for people to think about is
Speaker 2: something like an I X and a v G T
Speaker 2: or an XLK the traditional information tech services ETFs. You know,
Speaker 2: between all those there's hundreds of billions of dollars for
Speaker 2: t T eq T tech. The right competitive set is
Speaker 2: QQQ right and you know, we could get into those
Speaker 2: details a bit. How does the name get into the portfolio?
Speaker 2: It's actually relatively simple. Does it fit my framework and
Speaker 2: is there huge alpha opportunities relative to risk? Right? And
Speaker 2: so that's how we do all of our bed sizing
Speaker 2: as well. Is you know, often you have companies that
Speaker 2: have stupendous upside and I'll give you an example, like
Speaker 2: the optical stocks, but they're very very high beta, so Lumentum, Siena, Towers, Demi,
Speaker 2: these names are have had you know, fabulous performance over
Speaker 2: the past nine months, but have come with very very
Speaker 2: high beta, and so naturally they were actually you know,
Speaker 2: small to middle size positions throughout this previous run that
Speaker 2: we've had also have a little bit of a shorter
Speaker 2: leash depending on that. So it's all risk adjusted alpha
Speaker 2: a risk adjusted performance, so it's all alpha potential that
Speaker 2: that that that really drives the position sizing. The other
Speaker 2: thing that I think about a lot is, you know
Speaker 2: your portfolio has stocks that are AI on, AI off,
Speaker 2: Semis on, Semis off, software on, software off, and you
Speaker 2: have to think about it in terms of overall construction.
Speaker 2: And I'll give you an example. Uh, Volunteer is probably
Speaker 2: My biggest mistake since I took over the strategy this
Speaker 2: either one I you know, I just I couldn't get
Speaker 2: around the valuation. But the acceller the fundamentals were accelerating
Speaker 2: so dramatically, and the way we were designing software was
Speaker 2: changing so rapidly. Now, the way I slept that night
Speaker 2: is I always thought to myself, Okay, well, palenteer will
Speaker 2: add to my AI exposure, and I already have a
Speaker 2: lot of AI exposure, so I don't need even more.
Speaker 2: So you have to always think about things in portfolio construction.
Speaker 2: But but you also have to go that and put
Speaker 2: it through the framework. So hopefully that gets me away
Speaker 2: to go. So I kind of want go back to
Speaker 2: valuation just a little bit. You know, how do you
Speaker 2: balance growth in valuation in a sector like this where
Speaker 2: narratives really dominate fundamentals And you know, I guess my
Speaker 2: bigger question is what does expensive actually mean in tech today? Well,
Speaker 2: it's really funny narratives versus fundamentals. The thing about narratives
Speaker 2: is so technology investing is reflexive because talent is elastic,
Speaker 2: it can move from company to company. Right. The beautiful
Speaker 2: thing about silicon values everyone lives there. And the bad
Speaker 2: thing if you're a company in Silicon Valley is everyone
Speaker 2: lives there, right, so everyone wants to go work for
Speaker 2: the winners. They want to go work for open AI
Speaker 2: or anthropic or data bricks right now because they know
Speaker 2: that that's a huge potential payoff for them. So narratives
Speaker 2: often become reality. And then you got to remember most
Speaker 2: of tech is not regulated, so things can change super rapidly,
Speaker 2: just fundamentally, right, and you could go from not being
Speaker 2: a growth asset to being growth asset. And then you
Speaker 2: finalize that with the fact that semiconductors, which are such
Speaker 2: a big portion of tech, maybe forty percent of the
Speaker 2: information technology services forty five percent of information technology services,
Speaker 2: are inherently cyclical. Right. You have periods of other ordering
Speaker 2: and under ordering. You have periods of lead time expansion
Speaker 2: and lead time contraction. You have periods where bookings growth
Speaker 2: is the thing that matters versus earnings. And so I'll
Speaker 2: kind of counting your question with a question, which is
Speaker 2: is Nvidia expensive at fifteen times street earnings? You know,
Speaker 2: I think the debate that's raging in the market right
Speaker 2: now is is that fifteen times earnings? Right? You know,
Speaker 2: are they really going to earn a double digit earnings
Speaker 2: number and is it going to grow from there? Or
Speaker 2: are we going to ask the cyclical pullback at a cruction.
Speaker 2: Now I know which side of the debate I end
Speaker 2: up on, which is very firmly in the side of
Speaker 2: not only are is the street earnings right? They may
Speaker 2: be actually be low, and I actually we're going to
Speaker 2: go higher from here in terms of earnings momentum. But
Speaker 2: the debate that's raging right now in the valuation is
Speaker 2: not whether fifteen times is expensive or not. Is that
Speaker 2: it's that is that the right number to be using
Speaker 2: for Nvidia? So that's one on software. Software is a
Speaker 2: little bit different. So software relative to SEMIS is at
Speaker 2: the cheapest level it's ever been historically today, right, I mean,
Speaker 2: there's never been a period you look at basically every
Speaker 2: metric EVY to sales, pe EVE to TROO free cash flow,
Speaker 2: which really matters in software because the stock based comp
Speaker 2: is so stupendously high. Software is cheap relative to SEMIS
Speaker 2: versus every single metric you can look at. Now, I
Speaker 2: think that software has got more terminal value risk that
Speaker 2: it's ever had at any other period too, because AI
Speaker 2: is becoming the aggregator of aggregators, could commoditize the name
Speaker 2: like a salesforce or a workday or an Adobe really
Speaker 2: really quickly, even potentially, like we said earlier, the Microsoft
Speaker 2: Office franchise, it's under threw. And so I think valuation
Speaker 2: manners and manners most and it's extremes again for dero listeners.
Speaker 2: Another Dave Ozer quote that I am blatantly stealing. And
Speaker 2: you have to have an imagination that can envision these
Speaker 2: different scenarios, have a cyclical framework, have an imagination and
Speaker 2: be able to do so. Yes, narratives do drive a
Speaker 2: lot of tech investing, but I'm actually not sure it's unjustified. Okay, no,
Speaker 2: fair enough.
Speaker 1: I've been actually writing a few different research notes just
Speaker 1: talking about large cap funds, you know, active lige cat
Speaker 1: funds kind of looking they're a lot more concentrated now,
Speaker 1: just because the indexes are more concentrated, and you know,
Speaker 1: obviously that's kind of big in tech. There's a lot
Speaker 1: of big names in tech that are kind of driving
Speaker 1: returns in each portfolio. How many names do you really
Speaker 1: think drive returns in a typical year?
Speaker 2: You know, it was a great question. So you know
Speaker 2: for listeners, Dave David prepped me with that question, and
Speaker 2: I went and I looked it up, so I can
Speaker 2: give you an exact number that it's ten roughly ten
Speaker 2: names drive the performance. It's a power law dynamic, whether
Speaker 2: it was twenty three, twenty four, twenty five. Ten names
Speaker 2: drive my relative performance and my underperformance. Now, what's a
Speaker 2: really interesting point you're raising is this concentration issue. So
Speaker 2: I'll give you t tech as an example. If you
Speaker 2: go buy the Russell one thousand growth index today, north
Speaker 2: of fifty percent of your funds are going into seven names,
Speaker 2: right Like if you just buy the rust of one thousand growth,
Speaker 2: I think the number off the top of my head's
Speaker 2: like fifty two percent. So you know, we went back.
Speaker 2: You know, I think you guys have had so many
Speaker 2: great conversations about passive versus active and why is active
Speaker 2: struggled historically in which active strategies have done well? And
Speaker 2: so number one, you have to believe, hey, I could
Speaker 2: generate alpha in these mags seven. I think it's completely possible,
Speaker 2: by the way, to generate alpha in the mag seven
Speaker 2: picking between those names. But that is a fundamental belief
Speaker 2: that you need to have Okay, So then I think
Speaker 2: a lot of people turn towards Nasdaq one hundred, right
Speaker 2: and QQQ. But that's still like forty two percent. You
Speaker 2: know these seven names, right, it's it's it's still forty
Speaker 2: two forty three. I forget the exact number off the
Speaker 2: top of my head. What I tell my clients is
Speaker 2: I want to look smell act like a tech fund.
Speaker 2: So I need to own enough max seven to keep up.
Speaker 2: You know, we don't want to own to have a
Speaker 2: situation where we don't own any in either strategy. And
Speaker 2: you know, obviously in the information tech strategy is more
Speaker 2: more infotech weighted, but like you have to have some
Speaker 2: strategy so you could do your asset allocation properly. I
Speaker 2: need to be able to pick between those seven names.
Speaker 2: But also I don't want my value to be derived
Speaker 2: from those seven names. So if you look at T tech,
Speaker 2: it's something in like the low to mid thirties is
Speaker 2: is MA seven. So that means seventy plus percent of
Speaker 2: the strategy is named outside of that. So you need
Speaker 2: to own enough to keep up. If you have a
Speaker 2: situation where an Apple or a Microsoft do really well,
Speaker 2: and those two stocks in particular have fabulous downside capture.
Speaker 2: It's usually in down markets, right, and so if you
Speaker 2: don't own any that's you actually get really beat up
Speaker 2: on the downside. So you have to have some level
Speaker 2: of exposure to those names, be able to generate alpha
Speaker 2: between those names, and then be able to find names
Speaker 2: outside of those max seven that could drive differentiated performance.
Speaker 2: And in my case that's it ends up being like
Speaker 2: ten ten stocks a year that end up driving it. Okay.
Speaker 1: And so say you have a position that's doing really well,
Speaker 1: a big winner, how do you decide whether it'll let
Speaker 1: it run or trim it? So I guess it kind
Speaker 1: of gets more into like your cell discipline. So what
Speaker 1: are your flowers, don't you know? Don't cut your weeds,
Speaker 1: don't water your weeds right, and cut your flowers.
Speaker 2: So I just personally find my instinct is to let
Speaker 2: my winners run and to cut my losers. Which is
Speaker 2: really funny because anyone who reads The Intelligent Investor, which
Speaker 2: all great, you know, college students who want to be investors,
Speaker 2: is the first book they pick up. And it actually
Speaker 2: shouldn't be the first pick you should pick up. It
Speaker 2: should be like the tenth book you pick up, because
Speaker 2: it's actually quite dense. You want to get excited, you know,
Speaker 2: pick one up, Pick one up on Wall Street first.
Speaker 2: I'm telling you, whoever's listening, One Up on Wall Street
Speaker 2: should be the first book, and then go from there.
Speaker 2: So I find myself letting, letting my winners ride and
Speaker 2: cutting my losers. That being said, the framework saves me
Speaker 2: from myself at my natural inclination. So Lynchpin technologies innovating
Speaker 2: in secular growth markets with improving fundamentals have reasonable valuations.
Speaker 2: I can have a stock that I love more than
Speaker 2: anything has been executing fabulously on my investment thesis, and
Speaker 2: either the team, the risk guy or increasingly the AI
Speaker 2: I will tell me, hey, fundamentals are getting worse. So
Speaker 2: Albert Albert and risk will say, hey, Dom, I know
Speaker 2: you know, but you have a very large position and
Speaker 2: the fundamentals are getting worse. Here the team will say, hey,
Speaker 2: it's decelerating, doesn't make sense. Or increasingly AI and we
Speaker 2: can talk about AI and the investment process too. Fundamentals
Speaker 2: getting worse is the best reason to sell a stock,
Speaker 2: and you particularly want to do it when when when
Speaker 2: growth rates, in my opinion, are peaking. That being said,
Speaker 2: you want to let your winners run too, And and
Speaker 2: the question like with all great frameworks and all great rules, right.
Speaker 2: I used to have a teacher. I used to want
Speaker 2: to start my sentences with butt. And then you know,
Speaker 2: I read a book I think it was Roaldall and
Speaker 2: he started a bunch of sentences with the word butt.
Speaker 2: And she kept saying, you can't do that, you know,
Speaker 2: you have you have to have a comma. And then
Speaker 2: but da da da da, And I said, well what
Speaker 2: about him? And she she goes, well, he knew the
Speaker 2: rules so he could break them. And and it's kind
Speaker 2: of like that with brainworks too, like when when do
Speaker 2: you deviate slightly? Right? And and you know, when fundamentals
Speaker 2: are peaking, that's a great time to sell stocks.
Speaker 1: Historically, so you've been vocal about the limitations of passive
Speaker 1: tech investing. You know, it kind of alluded to it
Speaker 1: a little bit earlier. Where do you think index based
Speaker 1: strategies break down the most? Is it missing emerging winners
Speaker 1: or just kind of over concentrating incumbents.
Speaker 2: I want to start with actually saying passive is this
Speaker 2: wonderful invention, right, It's really cheap beta and it gave
Speaker 2: you know, individuals and investors access to exposures a very
Speaker 2: reasonable priceis and so I think the thing you have
Speaker 2: to do as an active investor is that, Okay, there's
Speaker 2: a price for cheap beta. Let's take QQQ that's eighteen
Speaker 2: basis points right, you know, VGT is nine in And
Speaker 2: then there's prices for different types of exposures, different tsted
Speaker 2: types of beta. IgM and IXN are in the forty
Speaker 2: something that range, right, So that's global beta and expanded
Speaker 2: technology beta is a little higher than just kind of
Speaker 2: cheap information technology beta or QQQ type beta. Right, So
Speaker 2: there's a price of beta, and then can you deliver
Speaker 2: something to your clients as an active investor. That's the
Speaker 2: price of beta whatever that is plus your alpha potential
Speaker 2: And I love what you guys always say, plus some
Speaker 2: hot sauce, right, like what is the hot sauce? And
Speaker 2: so that's how you have to get to fee construction
Speaker 2: and so overall for the average investor, just look at
Speaker 2: fees on a twenty five year basis, it's like fabulous.
Speaker 2: The fees have come down, right, and it's probably resulted
Speaker 2: in this barbelll effect in the industry where the larger
Speaker 2: have gotten larger, and there's large players, and then they're
Speaker 2: small niche, and then everything in the middle kind of struggles,
Speaker 2: kind of like what's happened in a lot of different industries.
Speaker 2: I would actually argue that's just internet economics coming through
Speaker 2: the asset management industry. But that's a whole, a whole
Speaker 2: nother tangent. Right, So so what where do passive or
Speaker 2: rules based fail. In my opinion, Let's take NASDAQ one hundred.
Speaker 2: Because it's so successful for so long, I completely understand
Speaker 2: why people use it as its main, the main allocating vehicle.
Speaker 2: NASZAK one hundred is simply the hundred largest names on
Speaker 2: the Nasdaq ex financial services. Okay, so right there, you
Speaker 2: don't get fintech, right, You'll never have a winner like
Speaker 2: an audience or a coinbase or a robin inherently, right,
Speaker 2: you don't, you don't, you don't get fintech. Then you
Speaker 2: get twenty percent of NASDAQ one hundred that has nothing
Speaker 2: to do with technology and innovation, right. Costco, Marriott, Pepsi, Lindy,
Speaker 2: Walmart is moving from the New York Stock Exchange to
Speaker 2: the NASDAC. I think primarily to get into the queues, right,
Speaker 2: and and and get get a lower cost to capital.
Speaker 2: You know, I'm sure there's other reasons too, but inherently,
Speaker 2: there's hundreds of billions of dollars behind the Nasdaq one hundred,
Speaker 2: and you know, you get this lower cost to capital
Speaker 2: as a result, and then you know, there there's maximum concentration,
Speaker 2: and then things like international often get thrown out with
Speaker 2: the bathwater. And so I remember there are plenty of
Speaker 2: times where people say, why does it make sense to
Speaker 2: own any international and well, there's all these fabulous lynchpin companies,
Speaker 2: whether it's an ASML or TSMC, all around the world,
Speaker 2: and so so to only focus on the US market,
Speaker 2: you know, I think the US market is really amazing
Speaker 2: in so many ways, but I think there's these these
Speaker 2: great companies all around the world. So if I think
Speaker 2: about portfolio construction, how how these names are put in
Speaker 2: mag seven concentration, the big get bigger. Now, now a
Speaker 2: few of the indices have capped benchmarks, right, so inherently
Speaker 2: the big can't get too big. But but I think
Speaker 2: there's a lot of things that go go into the construction,
Speaker 2: and so I think it's actually incumbent on the active
Speaker 2: industry to say, okay, this is the price of the
Speaker 2: cheap beta whatever that is, whatever beta you're offering, what
Speaker 2: is your alpha potential on top and can you price accordingly?
Speaker 2: And then can you add any hot sauce, And like
Speaker 2: t EQ is a great example of potential hot sauce,
Speaker 2: we can add names that will never be in not never,
Speaker 2: but names that momentum. Is a fabulous example that we
Speaker 2: got really right over the past nine months or the
Speaker 2: six months or whatever it is, because you know, we
Speaker 2: had an insight on on optical. It's a very high
Speaker 2: beta name. It's a relatively small position, but that's a
Speaker 2: that's that's an interesting idea conceptually. And privates is another
Speaker 2: really interesting area where you can add a lot of
Speaker 2: value outside of finding names that are not in those
Speaker 2: traditional pack seven so open AI anthropic data bricks, all
Speaker 2: of which are in TTEQ. And I think I'm the
Speaker 2: only strategy ETF that owns open AI. But you know
Speaker 2: know better than me.
Speaker 1: So you know, I do want to get into privates
Speaker 1: and just a little bit, but I kind of want
Speaker 1: to just talk about AI in general, because you would
Speaker 1: you had compared AI to or AIS impact to electricity,
Speaker 1: and so I'm just curious where you think we are
Speaker 1: in that kind of adoption curve today or even you
Speaker 1: know what inning are we in?
Speaker 2: Yeah? So what do I mean by that? First? So,
Speaker 2: there's only three ways to grow an economy, right, There's capital, labor,
Speaker 2: and productivity. Broadly speaking, capital swishes back and forth depending
Speaker 2: on animal spirits. Labor is probably flat to down going forward,
Speaker 2: may maybe up slightly depending on the economy. And so
Speaker 2: basically all of economic growth will come from productivity. The
Speaker 2: last major productivity boom we saw in the US was
Speaker 2: the Internet, and that correlated with the Internet bubble, you know,
Speaker 2: quite strikingly. But there's also been railroads and electricity, and historically,
Speaker 2: if you look, productivity centered technologies come with speculative bubbles. Right,
Speaker 2: people get so excited because they're amazing. They're making your
Speaker 2: life so dramatically better. Productivity bubbles are not to be feared.
Speaker 2: They're to be navigated responsibly via framework and to try
Speaker 2: to capture upside in one downside for clients. Right, people
Speaker 2: hear bubble, they think bad thing. I hear bubble and
Speaker 2: I think, oh wow, off a generation opportunity. Right, that
Speaker 2: sounds really exciting in many ways. If you have a
Speaker 2: framework that can help you navigate it electricity at it
Speaker 2: roughly one percent a year to US GDP growth for
Speaker 2: thirty two years. I think AI is going to smash
Speaker 2: those numbers. And I think we've actually already saw it.
Speaker 2: You know, in Q three we add incredible productivity numbers
Speaker 2: almost five percent. Now numbers change quarter to quarter, whatever,
Speaker 2: But I think AI is going to unleash this massive
Speaker 2: productivity cycle in the US, which is what we needed,
Speaker 2: and that is going to result in you know, very
Speaker 2: rapid GDP growth, potentially a speculati bubble. So I think
Speaker 2: when I look at the stocks today, we've seen major
Speaker 2: moves in many of these names, but they've all been
Speaker 2: earning streeven. So Nvidia is far cheaper today on a
Speaker 2: pe basis that it was in December of twenty two
Speaker 2: because the earnings growth has been so much bigger than
Speaker 2: the stock performance. And so the question is is that
Speaker 2: growth durable and we're going to see continued growth through
Speaker 2: the twenty thirties or not. Is the return on invested
Speaker 2: capital for the hyperscalers and the AI labs enough to
Speaker 2: justify the spend. I think in many ways, this scaling
Speaker 2: law which is driving a lot of this cap ax
Speaker 2: may be a law of physics though, but basically, if
Speaker 2: you spend more money, you get more intelligence. You know.
Speaker 2: The exact equation, I think depends on where you're at
Speaker 2: the curve. But but but basically, you spend more money,
Speaker 2: you get more intelligence. I think that may be a
Speaker 2: law of physics that we discovered. The question remains, if
Speaker 2: we spend more money, do we get more revenue? And
Speaker 2: so far I would argue the answers yes, right, Like
Speaker 2: Google Search grew seventeen percent year over year last quarter,
Speaker 2: Meta guide it to a thirty percent guide. We've seen
Speaker 2: open Ai go to you know, you know, well north
Speaker 2: of twenty billion dollars. A urr anthropic just behind it. Like,
Speaker 2: I think the answers yes, that we're getting the revenue
Speaker 2: to justify the spend. But inherently, in the situations you're
Speaker 2: pulling forward now, going back to reflexivity, inherently the spend
Speaker 2: of the hyperscalers will be based on two things. One
Speaker 2: competitive market dynamics. Right, does is Microsoft worried about the
Speaker 2: office suite? Yes or no? If they are, they're going
Speaker 2: to spend more money. If they're not gonna, they're gonna
Speaker 2: spend less money. And number two geopolitics and exoger to shocks.
Speaker 2: So my gut what ends all this and why I
Speaker 2: can't say we're an inning three, four, five six wherever?
Speaker 2: I mean? My gut is we're inning for or so,
Speaker 2: But but I don't know for sure. And the reason
Speaker 2: my mind could change, you know tomorrow, even though you
Speaker 2: know you always want to leave the ability to change
Speaker 2: your mind open is exogedive shocks could change the outcome.
Speaker 2: And so if you see major spikes and energy prices
Speaker 2: that result on major consumer pressure that result in revenue
Speaker 2: declines at the hyperscalers, something you want to be cognizant of.
Speaker 2: If you result in major oil prices as a result
Speaker 2: of geopolitics that make the ROI C less compelling to
Speaker 2: go invest in the data centers, that's something you want
Speaker 2: to be aware of. But risk aware doesn't doesn't mean
Speaker 2: take no risk. And I personally that the AI Bowl
Speaker 2: case is much bigger than those bear cases, but of
Speaker 2: course we're thinking about those at any given point.
Speaker 1: Okay, So I kind of want to do want to
Speaker 1: get into private companies just because it's such a big
Speaker 1: topic right now. How do you evaluate private companies alongside
Speaker 1: your public securities. You know, what does the underwriting of
Speaker 1: private investment look like as part of your process?
Speaker 2: Yeah? First off, I'm so lucky to be a Trow
Speaker 2: price for this, right. T Row has been doing privates
Speaker 2: for decades now through the work of many portfolio managers
Speaker 2: before me, We've built a strong reputation and crossover investing
Speaker 2: and I think as good partners in both the public
Speaker 2: and in the private markets. So inherently, I think that
Speaker 2: we're just in a very good position competitively when it
Speaker 2: comes to winning deals, and we have an amazing private
Speaker 2: steam that's the versus most of our deals, although some
Speaker 2: deal sources can be organic as well. The reality of
Speaker 2: private investing is that the tails are much wider, and
Speaker 2: it's that power law on steroids. You know, if ten
Speaker 2: names drive my performance in my strategy, even less names
Speaker 2: will drive you know, the performance on on on the
Speaker 2: on the privates. That being said, I think there's this
Speaker 2: new area of the private market which looks very similar
Speaker 2: to public market investing to me, and it's these names
Speaker 2: like open Ai, Anthropic Data Bricks. I mean these companies.
Speaker 2: You know, Sarah fryar At at open Ai was a
Speaker 2: public company CFO. Right, she was the CFO block and
Speaker 2: she's I mean she she is, you know, so so
Speaker 2: great for that organization in my opinion, And and I
Speaker 2: don't feel that different when I talk to open AI
Speaker 2: than I do to any of my public companies. And
Speaker 2: I would argue, actually that my framework stays exactly the same.
Speaker 2: Where I'm looking for lynchpin technologies, innovating in secular growth
Speaker 2: markets with improving fundamentals, have reasonable valuations. I want to
Speaker 2: catch these companies right before that takeoff, and don't want
Speaker 2: to make sure I pay a reasonable valuation for them
Speaker 2: in the context of where they can be in three years.
Speaker 2: And I need to make sure that I have an
Speaker 2: appropriate imagination to do so. But that's incumbent on the
Speaker 2: team and me to really stress different case scenarios. So
Speaker 2: I actually think the space between public market decision making
Speaker 2: and private market decision making is actually very similar in
Speaker 2: that late stage, you know, eighteen to twenty four months
Speaker 2: before becoming public, and I think that's exactly where where
Speaker 2: where we can build you know, I think a lot
Speaker 2: about where can we build differentiated business models. I think
Speaker 2: that's exactly where we can build a differentiated business as well.
Speaker 1: You did touch upon valuation. How do you think about
Speaker 1: valuation for privates when there's no daily price discovery.
Speaker 2: But there is obviously, you know, traditional valuation metrics that
Speaker 2: you apply, whether it's eaveny to sales, you know, pe
Speaker 2: over a long enough time rise in or price to
Speaker 2: pre cash flow. I find this element. I mean, I
Speaker 2: think people I'm a public markets guy. I will always
Speaker 2: be a public markets guy. I think people underestimate the
Speaker 2: intelligence of the public markets. I think I think the
Speaker 2: public markets are something to be respected, and there's a
Speaker 2: lot of noise, but often there's a signal in the
Speaker 2: noise of day to day price fluctuations, and so inherently
Speaker 2: you don't have that on the private side. But of
Speaker 2: course we consider you know, traditional valuation metrics in all
Speaker 2: of our our private investments, just like we do on
Speaker 2: our public investments. You have to have more imagination on
Speaker 2: the private side. You definitely need to have more imagination. Again,
Speaker 2: right when I did and propic I have five billion
Speaker 2: dollars AR and the Global Tech Fund. Nope, I don't
Speaker 2: think anyone thought it would be be you know, pushing
Speaker 2: twenty No just on privates. Just one more thing. I
Speaker 2: think some of these companies are so special. I mean,
Speaker 2: I just really quickly want to talk about open AI
Speaker 2: and and what a special asset that is. You know,
Speaker 2: here we have a company, whatever the numbers, is a
Speaker 2: you know, roughly a billion users, right, with a product
Speaker 2: that knows you so intimately. Right, chat GBT knows everything
Speaker 2: about me. And you know, if you ask Jack, GBT
Speaker 2: tell me everything about me. It gets get really it
Speaker 2: gets really close. It gets to my views as a father, right,
Speaker 2: it would get to how I think about investing, how
Speaker 2: I think about life, how I think about compounding. I mean,
Speaker 2: it would it would really paint you a picture of
Speaker 2: Don Rizzo. This concept that they're not going to build
Speaker 2: the most profitable ADS business and history is is really
Speaker 2: silly to me. Of course they are, and they're going
Speaker 2: to do it in an appropriate, thoughtful manner and take
Speaker 2: the time to do it in a way that's user
Speaker 2: friendly and doesn't require you know, everybody in the world
Speaker 2: spending twenty dollars a month on consumer subscriptions or two
Speaker 2: hundred dollars a month on consumer subscriptions, which frankly not
Speaker 2: everyone can do. Right. We know that for a fact,
Speaker 2: there's a price where it doesn't make sense for most
Speaker 2: people to pay the subscription. And so if you could
Speaker 2: build a thoughtful advertising business that's very down funnel, right.
Speaker 2: You plan a whole vocation to Italy, you understand where
Speaker 2: you want to go, what you want to do, and
Speaker 2: at the very bottom of it says, okay, do you
Speaker 2: want to here, hey, booking Expedia, let's go bit on this,
Speaker 2: just like in google'search. You know, I don't know if
Speaker 2: that's exactly how it's going to play out over time,
Speaker 2: but but I think there's a clear path there and
Speaker 2: then agents are really going to take off here in
Speaker 2: the next you know, twenty five months. Say, you know,
Speaker 2: I think this open claw innovation that we saw it.
Speaker 2: You know, Jensen had this quote at GtC where he
Speaker 2: said open Claw was the iPhone of tokens. And sometimes,
Speaker 2: you know, there's this old Kobe Bryant commercial where where
Speaker 2: Kanye West says, what are you talking about? Kobe? What
Speaker 2: does that mean? And when you hear Jensen sometimes to talk,
Speaker 2: he says something and you say, what does that mean? Jensen?
Speaker 2: Open claw is the iPhone of tokens. Okay, what let's
Speaker 2: dissect it piece by piece and rationalized open Claw this
Speaker 2: amazing open source technology that allows a gentic workloads to
Speaker 2: take place on the consumer side or the enterprise was
Speaker 2: easy enough that it was like the iPhone and it's
Speaker 2: going to result in massive token consumption. Oh, I got
Speaker 2: it right. Well, guests who open a I just hired.
Speaker 2: They just hired the the designer and developer of open Claw,
Speaker 2: and so I think that they're going to really build
Speaker 2: this magical agentic experience over time that will spend but
Speaker 2: it's the consumer and the enterprise.
Speaker 1: Well, it'll definitely be exciting to watch. Fortunately we do
Speaker 1: need to end here though, but this is a lot
Speaker 1: of fun. I really appreciate you coming on, Dom. I
Speaker 1: appreciate it definitely. Thanks David talksin. I'd also want to
Speaker 1: thank our listeners. If you like the episode, please share it,
Speaker 1: subscribe and leave a review. And if you'd like to
Speaker 1: see more of our research on the terminal, go to
Speaker 1: bifund go for fun and active research Until our next episode.
Speaker 2: This is David Cone with Inside Active