Speaker 1: Loking to train.
Speaker 2: So I'm Joel Webber and I'm Eric Belchernas.
Speaker 1: Eric AI trade has been a constant for about two
Speaker 1: or three years now, but today we're going to talk
Speaker 1: about a little corner of it that has become very interesting.
Speaker 2: Yeah, it's almost like downstream from AI, these AI data
Speaker 2: centers which they're building like crazy. This isn't news to anybody.
Speaker 2: They need memory and high bandwidth memory in particular. And
Speaker 2: there's like three companies that have almost the entire market
Speaker 2: s k Heiniz, Samsung, and Micron. Two of them are
Speaker 2: South Korea, one US. Now, there was a push though
Speaker 2: all three of those thocks are up a ton, so
Speaker 2: people were buying the South Korea ATF and we're seeing
Speaker 2: an inordinate amount of flows into that ETF earlier in
Speaker 2: the year and last year. But you don't get Micron
Speaker 2: with that, but you still get too at pretty good way.
Speaker 2: But you also get a lot of like other South korea'stocks,
Speaker 2: so like you're going to get K pop stuff in there.
Speaker 1: It's like a proxy, but not a one.
Speaker 2: Then Roundhill saw this, which again heads up play and
Speaker 2: they put out a memory ETF recently, very recently, and
Speaker 2: it just blew up immediately. We're talking two hundred million
Speaker 2: dollars of trading right off the bat. Now that's normal
Speaker 2: for like the spot bitcoin ETF for or the first
Speaker 2: ever like Ether ETF, that was pretty normal. But you
Speaker 2: don't see that ever, especially for them ETF. Normally you're
Speaker 2: lucky to trade two million, not two hundred million. I'm like,
Speaker 2: what is going on here? So I figured out the
Speaker 2: two South Korea companies aren't in ADR format yet, meaning
Speaker 2: you can't really buy them in the US, so your
Speaker 2: best way is to use the South Korea ETF, and
Speaker 2: that doesn't have micron. So this has let's give you
Speaker 2: all three in about a sixty five percent waiting and
Speaker 2: people were like going crazy for it. They must have
Speaker 2: let the market know. And it's at this point over
Speaker 2: a billion dollars now to keep that, to put that
Speaker 2: in perspective, the top four biggest the matic ETFs, it
Speaker 2: took them all over one thousand days. In some three
Speaker 2: thousand days, they hit a billion. So d Ram pulled
Speaker 2: off in ten days. So again we have a massive
Speaker 2: outlier smash hit in her hands. So I went and
Speaker 2: worked with the Bloomberg intelligence analyst who's a specialist to
Speaker 2: write a three Ways the Play note, which is one
Speaker 2: of our new recurring notes, and we're here to talk
Speaker 2: about it.
Speaker 1: That ETF by Roundhill is called d ram and here
Speaker 1: to speak with us about it is Jake Silverman, who's
Speaker 1: a semi conductor analyst at Bloomberg Intelligence. He's going to
Speaker 1: cover more than that as well, this time on trillions
Speaker 1: the memory trade. Welcome to trillions.
Speaker 3: Yeah, thanks for having me.
Speaker 1: Okay, So what Eric just laid out for us is
Speaker 1: a wildly successful ETF launch. It's been pretty interesting times
Speaker 1: in the semiconductor business. Why did it take so long
Speaker 1: for an ETF like this to come to market? Do
Speaker 1: you think?
Speaker 2: Yeah?
Speaker 3: Yeah, I think what Eric pointed out it was interesting
Speaker 3: is that the lack of ADRs, so the South Korean
Speaker 3: companies specifically in this case Samsung and s ke Heiniks
Speaker 3: really haven't had that ADR format before, and so I
Speaker 3: think there was just kind of folks are trying to
Speaker 3: understand the best way to play it, and so creating
Speaker 3: this ETF format was probably just sort of the key
Speaker 3: to unlock that. And so there have been a couple ETFs,
Speaker 3: as you pointed out, based on Korea, and you know,
Speaker 3: Korean stocks and et cetera. And so it is interesting
Speaker 3: now because there's such a memory up cycled, there's just
Speaker 3: such a renewed interest in memory.
Speaker 1: Okay, so when we think about chips most of the time,
Speaker 1: especially with AI, we're thinking, like Nvidia, maybe the Google stuff.
Speaker 1: Memory is sort of old school. I kind of forgot
Speaker 1: about it, to be honest with you, Like, why is
Speaker 1: this taking off?
Speaker 3: Yeah? I would say memory is usually considered the boring
Speaker 3: aspect of semiconductors, but it's gotten a lot more exciting,
Speaker 3: and a lot of it is to do with high
Speaker 3: bandwidth memory. So basically, you take these typical dram dyes
Speaker 3: that you would get off of just any wafer that
Speaker 3: would come out of these fabs, and you stack them
Speaker 3: up and you use these things called through silicon via
Speaker 3: to connect them microbumps, and you put them on a
Speaker 3: logic dye that then connects over to the GPU. It's
Speaker 3: super complicated.
Speaker 1: It's way more interesting than can we get that in English.
Speaker 3: It's basically just stacking DRAMs that you're maximizing the amount
Speaker 3: of space you get on a GPU board, and so
Speaker 3: this way you get super high bandwidth that you can
Speaker 3: by maximize. I don't want to get too into the
Speaker 3: weeds with it, but it's basically maximizing the bandwidth based
Speaker 3: on a limited amount of space you have on a
Speaker 3: package for a GPU.
Speaker 2: In general, the idea is if people are building AI
Speaker 2: data centers and they want to store all this data,
Speaker 2: they clearly want to they need memory to do that,
Speaker 2: and they I want it to be in a small,
Speaker 2: smallest physical form possible. So there's just just this a
Speaker 2: demand and then be pressure to make it small. And
Speaker 2: so that's what's going on, is that right?
Speaker 1: Yeah.
Speaker 3: So one of the things that probably to keep in
Speaker 3: mind is when you think about some of these models
Speaker 3: like from open AI that come out and they have
Speaker 3: like trillion plus parameters, you have to store that memory.
Speaker 3: And then when you're actually interacting with a model. So
Speaker 3: let's see if you're on chat, GBT or claude or
Speaker 3: whatever and you're actually typing into it. So what it's
Speaker 3: doing is there's this thing called kb cash where it's
Speaker 3: actually storing the amount of data and then it's appending
Speaker 3: it over and over again. But what you want to
Speaker 3: do is so that the model is don't have to
Speaker 3: run through your entire context window every time you're typing
Speaker 3: and keep doing it over and over again, it'll store
Speaker 3: that data. So basically what happens is you need memory
Speaker 3: to interact with the model, and then when you're adding
Speaker 3: to the context for the model, it needs to interact
Speaker 3: with that as well. So basically, the more the larger
Speaker 3: these parameters are, the larger these context windows, the more
Speaker 3: memory you need.
Speaker 1: You're in equity analyst first and foremost. And we've got
Speaker 1: three companies here esk Heinex, Micron and Samsung. Distinguish them
Speaker 1: from each other or are they literally just plug and
Speaker 1: play versions of each other?
Speaker 3: They're very different one I would say Samsung is the
Speaker 3: most differentiated because they have various business units. So when
Speaker 3: you're buying Samsung, for example, you're not buying just memory,
Speaker 3: You're buying their smartphone business, You're buying their foundry business
Speaker 3: and the various other businesses that they have. Within that,
Speaker 3: esk Heinex and Micron are considered, or at least more
Speaker 3: so in the past, we're considered interchangeable. But the difference
Speaker 3: between Micron and eske Heinix is twofold. One. You have
Speaker 3: the capacity that eske Heinix has, that's a lot more
Speaker 3: than say Micron, and then the other aspect is that
Speaker 3: they've been the leader on a high band with memory
Speaker 3: for a while now, so when you compare it to
Speaker 3: micron A, Micron was playing catch up and has been
Speaker 3: gaining share, but sk Heinix has still had about double
Speaker 3: that share over the last I don't know, say twelve
Speaker 3: months or so roughly, So it's a question of technology leadership.
Speaker 3: Micron is still definitely in the mix. And then there's
Speaker 3: a capacity element which we can get into in a bit.
Speaker 2: Eric.
Speaker 1: I'm not gonna ask Jake this because I think he knows.
Speaker 1: Do you know where Micron is based?
Speaker 2: I would guess like Seattle, No, you'll never guess, West Virginia, No, Mississippi,
Speaker 2: No Ohio, Missouri, no.
Speaker 1: Louisiana, all over the place. Idaho? Oh yeah, was that next?
Speaker 2: I mean the only thing I actually drove through Idaho
Speaker 2: once on a road trip, really cool, just long stretches
Speaker 2: of road built to spill is a famous indie rock
Speaker 2: band from Idaho. That's the only thing I think of
Speaker 2: in Potatoes, Potatoes and Micron.
Speaker 1: Like like that.
Speaker 2: Yeah, that is wild. Yes, I mean, look this industry, obviously,
Speaker 2: these companies have been around, but the AI demand you
Speaker 2: have here that it's seventy five billion dollars this memory industry,
Speaker 2: and you think it's going to double in only two
Speaker 2: two years to one hundred and thirty five billion. That's
Speaker 2: pretty wild.
Speaker 1: Is that bookcase or barecase?
Speaker 3: So I think in the past, I would have just
Speaker 3: talked about memory as an entire industry, and now it's
Speaker 3: like you have two product sets. You have high bandwidth memory,
Speaker 3: which is just completely outpacing I would say at least
Speaker 3: unit growth the thing that's gotten. So it's kind of
Speaker 3: important to understand. So because I was talking about the
Speaker 3: structure of high bandwidth memory, it actually requires three to
Speaker 3: four times the amount of space per wafer compared to
Speaker 3: the traditional products that we see that it's like you'd
Speaker 3: have in your smartphone or your laptop, anything like even
Speaker 3: traditional servers that go into like say the cloud or something.
Speaker 3: So what's happening is there's a limited amount of capacity.
Speaker 3: They're consistently continuously upgrading that amount of capacity. We don't
Speaker 3: have to get into the specifics of how they do that.
Speaker 3: But because you shift those wafers over to high bandwidth memory,
Speaker 3: you're taking away capacity from other products. And memory is
Speaker 3: very supply and demand driven way more commodity like than
Speaker 3: the rest of the semiconductor market. I mean, obviously GPUs
Speaker 3: are the least commodity like at this point, but memory
Speaker 3: is the most commodity like. So if you're taking off
Speaker 3: supply and demand keeps going up, pricing is going to
Speaker 3: increase at a fairly high rate, which we've already seen
Speaker 3: and this year alone is probably going to increase anywhere
Speaker 3: between one hundred and two hundred percent, if not more.
Speaker 3: That's just d ram Land is also similar.
Speaker 2: Well, when we hear all these big tech companies, some
Speaker 2: of the mag seven are spending all this cash, even
Speaker 2: taking out debt to spend cash on AI. This is
Speaker 2: where they're This is where they're spending it, right. It's
Speaker 2: not rocket science here. They got to they got to
Speaker 2: spend it on stuff.
Speaker 1: By the way, you said d RAM there, you were
Speaker 1: referring to the memory itself, not the ticker, but the ticker. Yes,
Speaker 1: we gotta talk about the ticker for a second. When
Speaker 1: you saw that ticker, d RAM, what did you think.
Speaker 3: I thought, this is the best name for an ETF
Speaker 3: for memory I could come up with.
Speaker 2: I honestly called it DRAM for a while, and then
Speaker 2: I got educated.
Speaker 1: Well, you're still still working on that, so Idaho and Drama.
Speaker 2: It's an ongoing education.
Speaker 1: So when you look at what this ETF holds, by
Speaker 1: the way, Eric, we've got those three companies. What else
Speaker 1: is in this sticker?
Speaker 2: Here are the rest of the holding. So those three
Speaker 2: stocks make up sixty seven, so two thirds of the portfolio.
Speaker 2: Then we got forgive me on my pronunciation. Okay again,
Speaker 2: I'm an ETF guy.
Speaker 1: Jake's gonna help you.
Speaker 2: Okay, Kyoksia, how's that pretty good?
Speaker 1: Good?
Speaker 2: Okay, Kia Holdings Japan, sand Disc, that's US another retro
Speaker 2: one Seagate, US Western Digital Retro, Nanya. Yeah, that's in Taiwan,
Speaker 2: Win Bond in Taiwan, and that's it. Those all the
Speaker 2: last ones I name probably collectively make up again to
Speaker 2: describe that portfolio.
Speaker 1: Jake.
Speaker 3: Yeah, So when you expand beyond eske Heinex, Samsung, Micron,
Speaker 3: you get into sort of more like nand specifics. So
Speaker 3: sand Disk and Kyoksa have a JV to do research
Speaker 3: and development and they share the same fabs together. But
Speaker 3: that's nand only. So the ticker for the ETF is
Speaker 3: d RAM. But within that you also have nand as well,
Speaker 3: because Micron, Samsung and Eskahannis make DIRAM and nand nand
Speaker 3: is more like storage. So if I if you bought it,
Speaker 3: buy an iPhone, you'll see like it'll have tiers of storage,
Speaker 3: for example, five hundred and twelve gigabytes, one terabyte that.
Speaker 1: Stuff that fills up with the gooey storage. Yeah yeah,
Speaker 1: I'm like, what's on my iPhone?
Speaker 3: It's like when I take too many pictures of my
Speaker 3: dog and now I need to back it up on
Speaker 3: the cloud. Yeah, and then I need more storage. So
Speaker 3: someone's got to buy that storage.
Speaker 1: Yeah yeah, Okay, So when you think about what we
Speaker 1: just rattled off, there, is there something that's missing or
Speaker 1: is this literally the perfect portfolio for this trade right now?
Speaker 3: It's pretty good. So non Ya Tech, for example, is
Speaker 3: pretty small. They are Taiwanese based, But there aren't that
Speaker 3: many pure play memory suppliers out there, and that's because
Speaker 3: memory has been historically tough industry, a lot of bankruptcy,
Speaker 3: a lot of consolidation. That's changed over the last two
Speaker 3: decades roughly as that's kind of stabilized, But there aren't
Speaker 3: that many players out there that exist today that simply
Speaker 3: just supply those products. Once you expand beyond that, you
Speaker 3: start to get into the suppliers of those businesses and
Speaker 3: those are a lot more diversified. So if you're looking
Speaker 3: for a specific way just to play memory, that's probably
Speaker 3: the best pure play opportunity that you're going to get
Speaker 3: that also has a little bit of diversification within there
Speaker 3: as well.
Speaker 1: You said that memory is like almost like a commodity, right,
Speaker 1: And if we think about how commodities trade, there are
Speaker 1: these fabulous booms and bus right, and like a commodity
Speaker 1: supercycle kind of means that everything's going up and then
Speaker 1: eventually the air comes comes out of the trade. Where
Speaker 1: are we in that supercycle commodity trade cycle?
Speaker 3: We're definitely a boom cycle. Where in that cycle is
Speaker 3: I think the million dollar question for every portfolio manager
Speaker 3: and retail investor out there, you know, the question is
Speaker 3: like are we in inning two? Are we in inning seven?
Speaker 3: Are we starting to approach the peak of the cycle?
Speaker 3: And that's where these stocks tend to You either tend
Speaker 3: to make a lot of money or you tend to
Speaker 3: get in a lot of trouble. There's no question right
Speaker 3: now that we're in an unprecedented upcycle like we've so
Speaker 3: we've done analysis where we kind of look at the
Speaker 3: length of these cycles and they typically last somewhere between
Speaker 3: I would say seven and ten quarters. We're well beyond
Speaker 3: that now based on the reporting and the guidance from
Speaker 3: these companies. So the question is, Okay, if we're beyond
Speaker 3: the sort of ten quarter roughly peak that we've seen
Speaker 3: in terms of that upcycle, can we go another ten quarters?
Speaker 3: The question is then becomes, okay, is AI demand enough
Speaker 3: to sustain that? And then if I'm if we are
Speaker 3: in a very commodity like industry, how to supply factor
Speaker 3: into this as well. Our base case has kind of
Speaker 3: been more like, okay, we think come maybe second half
Speaker 3: of twenty twenty seven, twenty twenty eight. There's a lot
Speaker 3: more of these green field fabs coming online. Historically, what
Speaker 3: you've seen is a lot of these fabs have unused space,
Speaker 3: and what you can do is you can install these
Speaker 3: tools and you can get additional capacity out of them.
Speaker 3: But now these fabs are essentially full, and we can
Speaker 3: get into the history if you want a little bit,
Speaker 3: but basically these fabs filled up. They need to build
Speaker 3: new fabs, but the lead time on fab construction is
Speaker 3: at least two years, and that's if you do it
Speaker 3: incredibly fast. So if you want to build it from
Speaker 3: the ground, if I have dirt that's just sitting there
Speaker 3: ready to go, if you've already leased that space the
Speaker 3: green field, then you want to actually construct the fab
Speaker 3: and you know, again they need to be absolutely perfect.
Speaker 3: You can't even have particles of dust in these things,
Speaker 3: so it requires a lot of really specific construction that's specialized,
Speaker 3: and then you need to get these tools like, for example,
Speaker 3: as mel Cell's EUV lithography machines. Those cost hundreds of
Speaker 3: millions of dollars. You have to get those in install them,
Speaker 3: and that's just one piece of equipment. So this is
Speaker 3: incredibly complex and takes probably at least three years really
Speaker 3: from just digging dirt actually getting these functioning, and then
Speaker 3: that's the first wafer that comes out. So it's a
Speaker 3: long lead.
Speaker 1: Time and we're talking lot of greenfield coming online.
Speaker 3: A lot of greenfield. So part of that is ske
Speaker 3: Heinez has a fab coming online pretty soon. They probably
Speaker 3: already just started getting wafers out. Micron is expanding in Boise,
Speaker 3: They're also going to expand in New York. Samsung has
Speaker 3: talked a little bit about it. But another underrated aspect
Speaker 3: is probably China. So there's a couple of fabs. There
Speaker 3: are a couple of companies that have fabs in China
Speaker 3: YMTC for nand and then CXMT for DRAM. They have
Speaker 3: been aggressively expanding their capacity and gaining market share over
Speaker 3: the last five or so. Longer than five years or so,
Speaker 3: and so basically does that start to impact the industry
Speaker 3: come and say twenty twenty seven, twenty twenty eight, because
Speaker 3: they don't have the market share yet that if they
Speaker 3: doubled their capacity over the next year or so, could
Speaker 3: that actually really drive negative pricing as opposed to not
Speaker 3: just slowing down the price increases we've seen.
Speaker 2: One interesting thing about this trade drool is that if
Speaker 2: you look at the other ETFs, you know, we look
Speaker 2: at these three companies. Obviously, DRAAM has sixty seven percenters
Speaker 2: of the three companies, and EWY has forty eight percent,
Speaker 2: but no Micron, but it's heavy, and there are other two,
Speaker 2: but then there's a huge drop off even the AI ETFs.
Speaker 2: There's one AIS that has all three but only eighteen
Speaker 2: percent total waiting. But here's what really shocked me, the
Speaker 2: semiconductor one like SMH which everybody uses, it only has
Speaker 2: micron and it's only at like a five percent waiting,
Speaker 2: so you miss a lot. And then here's why I
Speaker 2: really wanted to write about this theme and really give
Speaker 2: it attention, is that Spy has almost nothing like you
Speaker 2: own none of this trade and Spy and as big
Speaker 2: of a fan as I am of the Voo and
Speaker 2: should trade, the one thing that I would argue that
Speaker 2: you don't get with a voo and Chill is in
Speaker 2: these trends. Eventually, if this grows and grows and grows,
Speaker 2: Micron will be a bigger part of Spy, no doubt,
Speaker 2: and you'll get at part of it. But you if
Speaker 2: you want to front run that, yeah, you can get
Speaker 2: these these runs that are earlier than when they're fully
Speaker 2: grown adults. This is why theming ETFs exists, in my opinion.
Speaker 2: So I think that's part of what we did. The
Speaker 2: other thing we looked at DROEL was, you know, Jake
Speaker 2: just talked about these memory companies are like under the
Speaker 2: gun to build all this stuff. Well they need stuff too,
Speaker 2: So we looked at semiconductor equipment makers and that's a
Speaker 2: whole other thing. That's a whole nother trade. Now there
Speaker 2: is no semiconducting equipment ETF yet, so we try to
Speaker 2: look for one of those before we go over the
Speaker 2: ETF that we chose for this. Do you want to
Speaker 2: talk about that supply chain?
Speaker 1: Yeah?
Speaker 3: Yeah, So I mentioned ASML before, so they're one of
Speaker 3: the keys. Now, in the past, DRAM hadn't utilized as
Speaker 3: much EUV, so some of these older technology nodes that
Speaker 3: were used for these DRAM waves didn't require EUV. That's changing,
Speaker 3: so you need more EUV tools per fab. But then
Speaker 3: expanding beyond that, LAM Research has really been one of
Speaker 3: the leaders in different deposition and etch machines that specific
Speaker 3: tools that specifically get used for these tabs. And then
Speaker 3: you have applied materials and then you have a very
Speaker 3: long tail of equipment companies that are In addition to that,
Speaker 3: you have KLA. I couldn't name them all right here,
Speaker 3: I would bore everybody, But the point is you have
Speaker 3: all these players. And the thing about them though, to
Speaker 3: keep in mind, memory tends to be a smaller percentage
Speaker 3: of their overall revenue, so their biggest customers are almost
Speaker 3: always TSMC. Then on top of that, you'll have company
Speaker 3: like Intel, and you'll have Samsung. And again, if you're
Speaker 3: talking about Samsung, a lot of that is for their
Speaker 3: foundry for logics and not memory, and Intel they don't
Speaker 3: make memory anymore, so if you're selling to Intel, you're
Speaker 3: not getting memory exposure via that revenue. So again, and
Speaker 3: there's a long tail also fabs that have smaller markets
Speaker 3: like global foundaries for example, or tower semiconductor some of
Speaker 3: the others that you're just not going to be selling into.
Speaker 3: So I think the exposure from these semiconductor capital equipment
Speaker 3: companies has been probably growing for memory, but also declining
Speaker 3: from China. So there's a couple of different moving pieces
Speaker 3: to keep in mind.
Speaker 2: The ETF we found for this one's roll was the
Speaker 2: Pacer Blue Star Engineering the Future ETF good name, but
Speaker 2: doesn't really have a ton of assets, only five million
Speaker 2: charges forty nine basis points. But all the firms that
Speaker 2: Jake just mentioned are in the top like ten holdings
Speaker 2: of this one. And I've been doing this a long
Speaker 2: time and sometimes when you find an analyst who's like,
Speaker 2: here's like these interesting stocks that are probably the most relevant,
Speaker 2: you have to go digging, and a lot of times
Speaker 2: you do find these these like new ones or ones
Speaker 2: that were overlooked in favor of the big popular one.
Speaker 2: So this is part of why we try to get
Speaker 2: people to explore the toolbox more fully and something we
Speaker 2: sh do more often his analysts, which is unearthed some
Speaker 2: of these really you know, cool, what's interesting there.
Speaker 1: Is like this one ETF becomes like this new sensation
Speaker 1: and then it makes you realize, don't look at the
Speaker 1: sun directly, look off to the side slightly, and that
Speaker 1: helps you see the rest of the eCos totally.
Speaker 2: And you know, honestly, if I went to talk to
Speaker 2: this issuer or the at least the index maker, they'd
Speaker 2: be like, oh, yeah, we've known this for three years, dude,
Speaker 2: you know, welcome to the club. Like that's how many
Speaker 2: things are going on. And some of these ETF fishers
Speaker 2: are honestly really on the bleeding edge. But the four
Speaker 2: of them come out a day, so you just miss
Speaker 2: them and it's just tough to keep up with all this.
Speaker 2: But man, it's it's wild.
Speaker 1: What's the ticker for that? B U l D be
Speaker 1: you wealthy?
Speaker 2: There we go and I can give you the performance
Speaker 2: since it came out. It's not that old. It's up
Speaker 2: sixty four percent since launching four years ago.
Speaker 1: Okay, not bad, Jake, thanks so much for joining us
Speaker 1: in Trillions.
Speaker 3: Thank you, Thank you for having me here.
Speaker 1: Thanks for listening to trillions and telling them Next time.
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