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Transcript

The Memory AI Trade · Trillions

• 0:06
  Speaker 1: Loking to train.
• 0:06
  Speaker 2: So I'm Joel Webber and I'm Eric Belchernas.
• 0:11
  Speaker 1: Eric AI trade has been a constant for about two
• 0:16
  Speaker 1: or three years now, but today we're going to talk
• 0:19
  Speaker 1: about a little corner of it that has become very interesting.
• 0:23
  Speaker 2: Yeah, it's almost like downstream from AI, these AI data
• 0:27
  Speaker 2: centers which they're building like crazy. This isn't news to anybody.
• 0:31
  Speaker 2: They need memory and high bandwidth memory in particular. And
• 0:35
  Speaker 2: there's like three companies that have almost the entire market
• 0:39
  Speaker 2: s k Heiniz, Samsung, and Micron. Two of them are
• 0:42
  Speaker 2: South Korea, one US. Now, there was a push though
• 0:47
  Speaker 2: all three of those thocks are up a ton, so
• 0:49
  Speaker 2: people were buying the South Korea ATF and we're seeing
• 0:52
  Speaker 2: an inordinate amount of flows into that ETF earlier in
• 0:55
  Speaker 2: the year and last year. But you don't get Micron
• 0:58
  Speaker 2: with that, but you still get too at pretty good way.
• 1:00
  Speaker 2: But you also get a lot of like other South korea'stocks,
• 1:02
  Speaker 2: so like you're going to get K pop stuff in there.
• 1:04
  Speaker 1: It's like a proxy, but not a one.
• 1:06
  Speaker 2: Then Roundhill saw this, which again heads up play and
• 1:09
  Speaker 2: they put out a memory ETF recently, very recently, and
• 1:13
  Speaker 2: it just blew up immediately. We're talking two hundred million
• 1:16
  Speaker 2: dollars of trading right off the bat. Now that's normal
• 1:19
  Speaker 2: for like the spot bitcoin ETF for or the first
• 1:21
  Speaker 2: ever like Ether ETF, that was pretty normal. But you
• 1:24
  Speaker 2: don't see that ever, especially for them ETF. Normally you're
• 1:28
  Speaker 2: lucky to trade two million, not two hundred million. I'm like,
• 1:31
  Speaker 2: what is going on here? So I figured out the
• 1:34
  Speaker 2: two South Korea companies aren't in ADR format yet, meaning
• 1:38
  Speaker 2: you can't really buy them in the US, so your
• 1:40
  Speaker 2: best way is to use the South Korea ETF, and
• 1:42
  Speaker 2: that doesn't have micron. So this has let's give you
• 1:44
  Speaker 2: all three in about a sixty five percent waiting and
• 1:48
  Speaker 2: people were like going crazy for it. They must have
• 1:51
  Speaker 2: let the market know. And it's at this point over
• 1:54
  Speaker 2: a billion dollars now to keep that, to put that
• 1:57
  Speaker 2: in perspective, the top four biggest the matic ETFs, it
• 2:01
  Speaker 2: took them all over one thousand days. In some three
• 2:04
  Speaker 2: thousand days, they hit a billion. So d Ram pulled
• 2:08
  Speaker 2: off in ten days. So again we have a massive
• 2:12
  Speaker 2: outlier smash hit in her hands. So I went and
• 2:16
  Speaker 2: worked with the Bloomberg intelligence analyst who's a specialist to
• 2:20
  Speaker 2: write a three Ways the Play note, which is one
• 2:22
  Speaker 2: of our new recurring notes, and we're here to talk
• 2:24
  Speaker 2: about it.
• 2:25
  Speaker 1: That ETF by Roundhill is called d ram and here
• 2:29
  Speaker 1: to speak with us about it is Jake Silverman, who's
• 2:33
  Speaker 1: a semi conductor analyst at Bloomberg Intelligence. He's going to
• 2:38
  Speaker 1: cover more than that as well, this time on trillions
• 2:45
  Speaker 1: the memory trade. Welcome to trillions.
• 2:48
  Speaker 3: Yeah, thanks for having me.
• 2:49
  Speaker 1: Okay, So what Eric just laid out for us is
• 2:52
  Speaker 1: a wildly successful ETF launch. It's been pretty interesting times
• 2:57
  Speaker 1: in the semiconductor business. Why did it take so long
• 3:01
  Speaker 1: for an ETF like this to come to market? Do
• 3:03
  Speaker 1: you think?
• 3:04
  Speaker 2: Yeah?
• 3:05
  Speaker 3: Yeah, I think what Eric pointed out it was interesting
• 3:07
  Speaker 3: is that the lack of ADRs, so the South Korean
• 3:11
  Speaker 3: companies specifically in this case Samsung and s ke Heiniks
• 3:14
  Speaker 3: really haven't had that ADR format before, and so I
• 3:19
  Speaker 3: think there was just kind of folks are trying to
• 3:21
  Speaker 3: understand the best way to play it, and so creating
• 3:25
  Speaker 3: this ETF format was probably just sort of the key
• 3:29
  Speaker 3: to unlock that. And so there have been a couple ETFs,
• 3:32
  Speaker 3: as you pointed out, based on Korea, and you know,
• 3:35
  Speaker 3: Korean stocks and et cetera. And so it is interesting
• 3:39
  Speaker 3: now because there's such a memory up cycled, there's just
• 3:43
  Speaker 3: such a renewed interest in memory.
• 3:44
  Speaker 1: Okay, so when we think about chips most of the time,
• 3:47
  Speaker 1: especially with AI, we're thinking, like Nvidia, maybe the Google stuff.
• 3:52
  Speaker 1: Memory is sort of old school. I kind of forgot
• 3:55
  Speaker 1: about it, to be honest with you, Like, why is
• 3:57
  Speaker 1: this taking off?
• 3:58
  Speaker 3: Yeah? I would say memory is usually considered the boring
• 4:01
  Speaker 3: aspect of semiconductors, but it's gotten a lot more exciting,
• 4:05
  Speaker 3: and a lot of it is to do with high
• 4:06
  Speaker 3: bandwidth memory. So basically, you take these typical dram dyes
• 4:11
  Speaker 3: that you would get off of just any wafer that
• 4:13
  Speaker 3: would come out of these fabs, and you stack them
• 4:16
  Speaker 3: up and you use these things called through silicon via
• 4:18
  Speaker 3: to connect them microbumps, and you put them on a
• 4:21
  Speaker 3: logic dye that then connects over to the GPU. It's
• 4:25
  Speaker 3: super complicated.
• 4:26
  Speaker 1: It's way more interesting than can we get that in English.
• 4:30
  Speaker 3: It's basically just stacking DRAMs that you're maximizing the amount
• 4:33
  Speaker 3: of space you get on a GPU board, and so
• 4:36
  Speaker 3: this way you get super high bandwidth that you can
• 4:40
  Speaker 3: by maximize. I don't want to get too into the
• 4:42
  Speaker 3: weeds with it, but it's basically maximizing the bandwidth based
• 4:45
  Speaker 3: on a limited amount of space you have on a
• 4:48
  Speaker 3: package for a GPU.
• 4:50
  Speaker 2: In general, the idea is if people are building AI
• 4:53
  Speaker 2: data centers and they want to store all this data,
• 4:56
  Speaker 2: they clearly want to they need memory to do that,
• 4:59
  Speaker 2: and they I want it to be in a small,
• 5:01
  Speaker 2: smallest physical form possible. So there's just just this a
• 5:05
  Speaker 2: demand and then be pressure to make it small. And
• 5:07
  Speaker 2: so that's what's going on, is that right?
• 5:09
  Speaker 1: Yeah.
• 5:10
  Speaker 3: So one of the things that probably to keep in
• 5:11
  Speaker 3: mind is when you think about some of these models
• 5:14
  Speaker 3: like from open AI that come out and they have
• 5:15
  Speaker 3: like trillion plus parameters, you have to store that memory.
• 5:19
  Speaker 3: And then when you're actually interacting with a model. So
• 5:22
  Speaker 3: let's see if you're on chat, GBT or claude or
• 5:25
  Speaker 3: whatever and you're actually typing into it. So what it's
• 5:28
  Speaker 3: doing is there's this thing called kb cash where it's
• 5:30
  Speaker 3: actually storing the amount of data and then it's appending
• 5:33
  Speaker 3: it over and over again. But what you want to
• 5:36
  Speaker 3: do is so that the model is don't have to
• 5:37
  Speaker 3: run through your entire context window every time you're typing
• 5:41
  Speaker 3: and keep doing it over and over again, it'll store
• 5:44
  Speaker 3: that data. So basically what happens is you need memory
• 5:47
  Speaker 3: to interact with the model, and then when you're adding
• 5:49
  Speaker 3: to the context for the model, it needs to interact
• 5:52
  Speaker 3: with that as well. So basically, the more the larger
• 5:55
  Speaker 3: these parameters are, the larger these context windows, the more
• 5:58
  Speaker 3: memory you need.
• 5:59
  Speaker 1: You're in equity analyst first and foremost. And we've got
• 6:01
  Speaker 1: three companies here esk Heinex, Micron and Samsung. Distinguish them
• 6:06
  Speaker 1: from each other or are they literally just plug and
• 6:09
  Speaker 1: play versions of each other?
• 6:10
  Speaker 3: They're very different one I would say Samsung is the
• 6:13
  Speaker 3: most differentiated because they have various business units. So when
• 6:16
  Speaker 3: you're buying Samsung, for example, you're not buying just memory,
• 6:20
  Speaker 3: You're buying their smartphone business, You're buying their foundry business
• 6:23
  Speaker 3: and the various other businesses that they have. Within that,
• 6:26
  Speaker 3: esk Heinex and Micron are considered, or at least more
• 6:30
  Speaker 3: so in the past, we're considered interchangeable. But the difference
• 6:33
  Speaker 3: between Micron and eske Heinix is twofold. One. You have
• 6:36
  Speaker 3: the capacity that eske Heinix has, that's a lot more
• 6:40
  Speaker 3: than say Micron, and then the other aspect is that
• 6:42
  Speaker 3: they've been the leader on a high band with memory
• 6:45
  Speaker 3: for a while now, so when you compare it to
• 6:47
  Speaker 3: micron A, Micron was playing catch up and has been
• 6:51
  Speaker 3: gaining share, but sk Heinix has still had about double
• 6:55
  Speaker 3: that share over the last I don't know, say twelve
• 6:58
  Speaker 3: months or so roughly, So it's a question of technology leadership.
• 7:02
  Speaker 3: Micron is still definitely in the mix. And then there's
• 7:04
  Speaker 3: a capacity element which we can get into in a bit.
• 7:08
  Speaker 2: Eric.
• 7:08
  Speaker 1: I'm not gonna ask Jake this because I think he knows.
• 7:10
  Speaker 1: Do you know where Micron is based?
• 7:11
  Speaker 2: I would guess like Seattle, No, you'll never guess, West Virginia, No, Mississippi,
• 7:17
  Speaker 2: No Ohio, Missouri, no.
• 7:22
  Speaker 1: Louisiana, all over the place. Idaho? Oh yeah, was that next?
• 7:27
  Speaker 2: I mean the only thing I actually drove through Idaho
• 7:30
  Speaker 2: once on a road trip, really cool, just long stretches
• 7:32
  Speaker 2: of road built to spill is a famous indie rock
• 7:36
  Speaker 2: band from Idaho. That's the only thing I think of
• 7:37
  Speaker 2: in Potatoes, Potatoes and Micron.
• 7:41
  Speaker 1: Like like that.
• 7:42
  Speaker 2: Yeah, that is wild. Yes, I mean, look this industry, obviously,
• 7:47
  Speaker 2: these companies have been around, but the AI demand you
• 7:52
  Speaker 2: have here that it's seventy five billion dollars this memory industry,
• 7:56
  Speaker 2: and you think it's going to double in only two
• 8:00
  Speaker 2: two years to one hundred and thirty five billion. That's
• 8:03
  Speaker 2: pretty wild.
• 8:04
  Speaker 1: Is that bookcase or barecase?
• 8:07
  Speaker 3: So I think in the past, I would have just
• 8:10
  Speaker 3: talked about memory as an entire industry, and now it's
• 8:13
  Speaker 3: like you have two product sets. You have high bandwidth memory,
• 8:16
  Speaker 3: which is just completely outpacing I would say at least
• 8:19
  Speaker 3: unit growth the thing that's gotten. So it's kind of
• 8:21
  Speaker 3: important to understand. So because I was talking about the
• 8:24
  Speaker 3: structure of high bandwidth memory, it actually requires three to
• 8:27
  Speaker 3: four times the amount of space per wafer compared to
• 8:30
  Speaker 3: the traditional products that we see that it's like you'd
• 8:33
  Speaker 3: have in your smartphone or your laptop, anything like even
• 8:36
  Speaker 3: traditional servers that go into like say the cloud or something.
• 8:39
  Speaker 3: So what's happening is there's a limited amount of capacity.
• 8:42
  Speaker 3: They're consistently continuously upgrading that amount of capacity. We don't
• 8:47
  Speaker 3: have to get into the specifics of how they do that.
• 8:49
  Speaker 3: But because you shift those wafers over to high bandwidth memory,
• 8:53
  Speaker 3: you're taking away capacity from other products. And memory is
• 8:58
  Speaker 3: very supply and demand driven way more commodity like than
• 9:01
  Speaker 3: the rest of the semiconductor market. I mean, obviously GPUs
• 9:04
  Speaker 3: are the least commodity like at this point, but memory
• 9:08
  Speaker 3: is the most commodity like. So if you're taking off
• 9:11
  Speaker 3: supply and demand keeps going up, pricing is going to
• 9:15
  Speaker 3: increase at a fairly high rate, which we've already seen
• 9:18
  Speaker 3: and this year alone is probably going to increase anywhere
• 9:20
  Speaker 3: between one hundred and two hundred percent, if not more.
• 9:23
  Speaker 3: That's just d ram Land is also similar.
• 9:26
  Speaker 2: Well, when we hear all these big tech companies, some
• 9:29
  Speaker 2: of the mag seven are spending all this cash, even
• 9:32
  Speaker 2: taking out debt to spend cash on AI. This is
• 9:35
  Speaker 2: where they're This is where they're spending it, right. It's
• 9:37
  Speaker 2: not rocket science here. They got to they got to
• 9:40
  Speaker 2: spend it on stuff.
• 9:41
  Speaker 1: By the way, you said d RAM there, you were
• 9:44
  Speaker 1: referring to the memory itself, not the ticker, but the ticker. Yes,
• 9:48
  Speaker 1: we gotta talk about the ticker for a second. When
• 9:50
  Speaker 1: you saw that ticker, d RAM, what did you think.
• 9:52
  Speaker 3: I thought, this is the best name for an ETF
• 9:56
  Speaker 3: for memory I could come up with.
• 9:58
  Speaker 2: I honestly called it DRAM for a while, and then
• 10:00
  Speaker 2: I got educated.
• 10:02
  Speaker 1: Well, you're still still working on that, so Idaho and Drama.
• 10:08
  Speaker 2: It's an ongoing education.
• 10:21
  Speaker 1: So when you look at what this ETF holds, by
• 10:24
  Speaker 1: the way, Eric, we've got those three companies. What else
• 10:26
  Speaker 1: is in this sticker?
• 10:28
  Speaker 2: Here are the rest of the holding. So those three
• 10:30
  Speaker 2: stocks make up sixty seven, so two thirds of the portfolio.
• 10:34
  Speaker 2: Then we got forgive me on my pronunciation. Okay again,
• 10:38
  Speaker 2: I'm an ETF guy.
• 10:39
  Speaker 1: Jake's gonna help you.
• 10:40
  Speaker 2: Okay, Kyoksia, how's that pretty good?
• 10:44
  Speaker 1: Good?
• 10:44
  Speaker 2: Okay, Kia Holdings Japan, sand Disc, that's US another retro
• 10:49
  Speaker 2: one Seagate, US Western Digital Retro, Nanya. Yeah, that's in Taiwan,
• 10:57
  Speaker 2: Win Bond in Taiwan, and that's it. Those all the
• 11:01
  Speaker 2: last ones I name probably collectively make up again to
• 11:04
  Speaker 2: describe that portfolio.
• 11:05
  Speaker 1: Jake.
• 11:06
  Speaker 3: Yeah, So when you expand beyond eske Heinex, Samsung, Micron,
• 11:10
  Speaker 3: you get into sort of more like nand specifics. So
• 11:12
  Speaker 3: sand Disk and Kyoksa have a JV to do research
• 11:16
  Speaker 3: and development and they share the same fabs together. But
• 11:20
  Speaker 3: that's nand only. So the ticker for the ETF is
• 11:23
  Speaker 3: d RAM. But within that you also have nand as well,
• 11:26
  Speaker 3: because Micron, Samsung and Eskahannis make DIRAM and nand nand
• 11:31
  Speaker 3: is more like storage. So if I if you bought it,
• 11:33
  Speaker 3: buy an iPhone, you'll see like it'll have tiers of storage,
• 11:37
  Speaker 3: for example, five hundred and twelve gigabytes, one terabyte that.
• 11:40
  Speaker 1: Stuff that fills up with the gooey storage. Yeah yeah,
• 11:43
  Speaker 1: I'm like, what's on my iPhone?
• 11:45
  Speaker 3: It's like when I take too many pictures of my
• 11:46
  Speaker 3: dog and now I need to back it up on
• 11:48
  Speaker 3: the cloud. Yeah, and then I need more storage. So
• 11:51
  Speaker 3: someone's got to buy that storage.
• 11:52
  Speaker 1: Yeah yeah, Okay, So when you think about what we
• 11:56
  Speaker 1: just rattled off, there, is there something that's missing or
• 11:59
  Speaker 1: is this literally the perfect portfolio for this trade right now?
• 12:02
  Speaker 3: It's pretty good. So non Ya Tech, for example, is
• 12:05
  Speaker 3: pretty small. They are Taiwanese based, But there aren't that
• 12:09
  Speaker 3: many pure play memory suppliers out there, and that's because
• 12:12
  Speaker 3: memory has been historically tough industry, a lot of bankruptcy,
• 12:16
  Speaker 3: a lot of consolidation. That's changed over the last two
• 12:19
  Speaker 3: decades roughly as that's kind of stabilized, But there aren't
• 12:23
  Speaker 3: that many players out there that exist today that simply
• 12:26
  Speaker 3: just supply those products. Once you expand beyond that, you
• 12:30
  Speaker 3: start to get into the suppliers of those businesses and
• 12:33
  Speaker 3: those are a lot more diversified. So if you're looking
• 12:36
  Speaker 3: for a specific way just to play memory, that's probably
• 12:39
  Speaker 3: the best pure play opportunity that you're going to get
• 12:41
  Speaker 3: that also has a little bit of diversification within there
• 12:44
  Speaker 3: as well.
• 12:44
  Speaker 1: You said that memory is like almost like a commodity, right,
• 12:48
  Speaker 1: And if we think about how commodities trade, there are
• 12:51
  Speaker 1: these fabulous booms and bus right, and like a commodity
• 12:55
  Speaker 1: supercycle kind of means that everything's going up and then
• 12:58
  Speaker 1: eventually the air comes comes out of the trade. Where
• 13:02
  Speaker 1: are we in that supercycle commodity trade cycle?
• 13:06
  Speaker 3: We're definitely a boom cycle. Where in that cycle is
• 13:10
  Speaker 3: I think the million dollar question for every portfolio manager
• 13:13
  Speaker 3: and retail investor out there, you know, the question is
• 13:15
  Speaker 3: like are we in inning two? Are we in inning seven?
• 13:18
  Speaker 3: Are we starting to approach the peak of the cycle?
• 13:21
  Speaker 3: And that's where these stocks tend to You either tend
• 13:24
  Speaker 3: to make a lot of money or you tend to
• 13:25
  Speaker 3: get in a lot of trouble. There's no question right
• 13:28
  Speaker 3: now that we're in an unprecedented upcycle like we've so
• 13:31
  Speaker 3: we've done analysis where we kind of look at the
• 13:33
  Speaker 3: length of these cycles and they typically last somewhere between
• 13:36
  Speaker 3: I would say seven and ten quarters. We're well beyond
• 13:39
  Speaker 3: that now based on the reporting and the guidance from
• 13:42
  Speaker 3: these companies. So the question is, Okay, if we're beyond
• 13:45
  Speaker 3: the sort of ten quarter roughly peak that we've seen
• 13:48
  Speaker 3: in terms of that upcycle, can we go another ten quarters?
• 13:51
  Speaker 3: The question is then becomes, okay, is AI demand enough
• 13:55
  Speaker 3: to sustain that? And then if I'm if we are
• 13:58
  Speaker 3: in a very commodity like industry, how to supply factor
• 14:01
  Speaker 3: into this as well. Our base case has kind of
• 14:04
  Speaker 3: been more like, okay, we think come maybe second half
• 14:08
  Speaker 3: of twenty twenty seven, twenty twenty eight. There's a lot
• 14:11
  Speaker 3: more of these green field fabs coming online. Historically, what
• 14:15
  Speaker 3: you've seen is a lot of these fabs have unused space,
• 14:19
  Speaker 3: and what you can do is you can install these
• 14:20
  Speaker 3: tools and you can get additional capacity out of them.
• 14:23
  Speaker 3: But now these fabs are essentially full, and we can
• 14:26
  Speaker 3: get into the history if you want a little bit,
• 14:28
  Speaker 3: but basically these fabs filled up. They need to build
• 14:31
  Speaker 3: new fabs, but the lead time on fab construction is
• 14:34
  Speaker 3: at least two years, and that's if you do it
• 14:36
  Speaker 3: incredibly fast. So if you want to build it from
• 14:39
  Speaker 3: the ground, if I have dirt that's just sitting there
• 14:41
  Speaker 3: ready to go, if you've already leased that space the
• 14:44
  Speaker 3: green field, then you want to actually construct the fab
• 14:46
  Speaker 3: and you know, again they need to be absolutely perfect.
• 14:49
  Speaker 3: You can't even have particles of dust in these things,
• 14:52
  Speaker 3: so it requires a lot of really specific construction that's specialized,
• 14:57
  Speaker 3: and then you need to get these tools like, for example,
• 14:59
  Speaker 3: as mel Cell's EUV lithography machines. Those cost hundreds of
• 15:04
  Speaker 3: millions of dollars. You have to get those in install them,
• 15:06
  Speaker 3: and that's just one piece of equipment. So this is
• 15:09
  Speaker 3: incredibly complex and takes probably at least three years really
• 15:13
  Speaker 3: from just digging dirt actually getting these functioning, and then
• 15:17
  Speaker 3: that's the first wafer that comes out. So it's a
• 15:19
  Speaker 3: long lead.
• 15:19
  Speaker 1: Time and we're talking lot of greenfield coming online.
• 15:22
  Speaker 3: A lot of greenfield. So part of that is ske
• 15:25
  Speaker 3: Heinez has a fab coming online pretty soon. They probably
• 15:27
  Speaker 3: already just started getting wafers out. Micron is expanding in Boise,
• 15:31
  Speaker 3: They're also going to expand in New York. Samsung has
• 15:34
  Speaker 3: talked a little bit about it. But another underrated aspect
• 15:37
  Speaker 3: is probably China. So there's a couple of fabs. There
• 15:39
  Speaker 3: are a couple of companies that have fabs in China
• 15:42
  Speaker 3: YMTC for nand and then CXMT for DRAM. They have
• 15:46
  Speaker 3: been aggressively expanding their capacity and gaining market share over
• 15:50
  Speaker 3: the last five or so. Longer than five years or so,
• 15:53
  Speaker 3: and so basically does that start to impact the industry
• 15:57
  Speaker 3: come and say twenty twenty seven, twenty twenty eight, because
• 16:00
  Speaker 3: they don't have the market share yet that if they
• 16:02
  Speaker 3: doubled their capacity over the next year or so, could
• 16:05
  Speaker 3: that actually really drive negative pricing as opposed to not
• 16:09
  Speaker 3: just slowing down the price increases we've seen.
• 16:12
  Speaker 2: One interesting thing about this trade drool is that if
• 16:15
  Speaker 2: you look at the other ETFs, you know, we look
• 16:17
  Speaker 2: at these three companies. Obviously, DRAAM has sixty seven percenters
• 16:21
  Speaker 2: of the three companies, and EWY has forty eight percent,
• 16:26
  Speaker 2: but no Micron, but it's heavy, and there are other two,
• 16:28
  Speaker 2: but then there's a huge drop off even the AI ETFs.
• 16:31
  Speaker 2: There's one AIS that has all three but only eighteen
• 16:34
  Speaker 2: percent total waiting. But here's what really shocked me, the
• 16:37
  Speaker 2: semiconductor one like SMH which everybody uses, it only has
• 16:41
  Speaker 2: micron and it's only at like a five percent waiting,
• 16:43
  Speaker 2: so you miss a lot. And then here's why I
• 16:46
  Speaker 2: really wanted to write about this theme and really give
• 16:48
  Speaker 2: it attention, is that Spy has almost nothing like you
• 16:52
  Speaker 2: own none of this trade and Spy and as big
• 16:55
  Speaker 2: of a fan as I am of the Voo and
• 16:56
  Speaker 2: should trade, the one thing that I would argue that
• 16:59
  Speaker 2: you don't get with a voo and Chill is in
• 17:02
  Speaker 2: these trends. Eventually, if this grows and grows and grows,
• 17:05
  Speaker 2: Micron will be a bigger part of Spy, no doubt,
• 17:07
  Speaker 2: and you'll get at part of it. But you if
• 17:10
  Speaker 2: you want to front run that, yeah, you can get
• 17:12
  Speaker 2: these these runs that are earlier than when they're fully
• 17:15
  Speaker 2: grown adults. This is why theming ETFs exists, in my opinion.
• 17:20
  Speaker 2: So I think that's part of what we did. The
• 17:21
  Speaker 2: other thing we looked at DROEL was, you know, Jake
• 17:25
  Speaker 2: just talked about these memory companies are like under the
• 17:28
  Speaker 2: gun to build all this stuff. Well they need stuff too,
• 17:31
  Speaker 2: So we looked at semiconductor equipment makers and that's a
• 17:36
  Speaker 2: whole other thing. That's a whole nother trade. Now there
• 17:38
  Speaker 2: is no semiconducting equipment ETF yet, so we try to
• 17:41
  Speaker 2: look for one of those before we go over the
• 17:43
  Speaker 2: ETF that we chose for this. Do you want to
• 17:45
  Speaker 2: talk about that supply chain?
• 17:48
  Speaker 1: Yeah?
• 17:48
  Speaker 3: Yeah, So I mentioned ASML before, so they're one of
• 17:51
  Speaker 3: the keys. Now, in the past, DRAM hadn't utilized as
• 17:54
  Speaker 3: much EUV, so some of these older technology nodes that
• 17:58
  Speaker 3: were used for these DRAM waves didn't require EUV. That's changing,
• 18:02
  Speaker 3: so you need more EUV tools per fab. But then
• 18:05
  Speaker 3: expanding beyond that, LAM Research has really been one of
• 18:08
  Speaker 3: the leaders in different deposition and etch machines that specific
• 18:12
  Speaker 3: tools that specifically get used for these tabs. And then
• 18:14
  Speaker 3: you have applied materials and then you have a very
• 18:16
  Speaker 3: long tail of equipment companies that are In addition to that,
• 18:20
  Speaker 3: you have KLA. I couldn't name them all right here,
• 18:24
  Speaker 3: I would bore everybody, But the point is you have
• 18:26
  Speaker 3: all these players. And the thing about them though, to
• 18:29
  Speaker 3: keep in mind, memory tends to be a smaller percentage
• 18:32
  Speaker 3: of their overall revenue, so their biggest customers are almost
• 18:36
  Speaker 3: always TSMC. Then on top of that, you'll have company
• 18:40
  Speaker 3: like Intel, and you'll have Samsung. And again, if you're
• 18:43
  Speaker 3: talking about Samsung, a lot of that is for their
• 18:45
  Speaker 3: foundry for logics and not memory, and Intel they don't
• 18:49
  Speaker 3: make memory anymore, so if you're selling to Intel, you're
• 18:52
  Speaker 3: not getting memory exposure via that revenue. So again, and
• 18:56
  Speaker 3: there's a long tail also fabs that have smaller markets
• 19:00
  Speaker 3: like global foundaries for example, or tower semiconductor some of
• 19:04
  Speaker 3: the others that you're just not going to be selling into.
• 19:08
  Speaker 3: So I think the exposure from these semiconductor capital equipment
• 19:13
  Speaker 3: companies has been probably growing for memory, but also declining
• 19:17
  Speaker 3: from China. So there's a couple of different moving pieces
• 19:20
  Speaker 3: to keep in mind.
• 19:21
  Speaker 2: The ETF we found for this one's roll was the
• 19:22
  Speaker 2: Pacer Blue Star Engineering the Future ETF good name, but
• 19:29
  Speaker 2: doesn't really have a ton of assets, only five million
• 19:32
  Speaker 2: charges forty nine basis points. But all the firms that
• 19:34
  Speaker 2: Jake just mentioned are in the top like ten holdings
• 19:36
  Speaker 2: of this one. And I've been doing this a long
• 19:39
  Speaker 2: time and sometimes when you find an analyst who's like,
• 19:43
  Speaker 2: here's like these interesting stocks that are probably the most relevant,
• 19:47
  Speaker 2: you have to go digging, and a lot of times
• 19:48
  Speaker 2: you do find these these like new ones or ones
• 19:50
  Speaker 2: that were overlooked in favor of the big popular one.
• 19:53
  Speaker 2: So this is part of why we try to get
• 19:57
  Speaker 2: people to explore the toolbox more fully and something we
• 19:59
  Speaker 2: sh do more often his analysts, which is unearthed some
• 20:01
  Speaker 2: of these really you know, cool, what's interesting there.
• 20:03
  Speaker 1: Is like this one ETF becomes like this new sensation
• 20:07
  Speaker 1: and then it makes you realize, don't look at the
• 20:09
  Speaker 1: sun directly, look off to the side slightly, and that
• 20:13
  Speaker 1: helps you see the rest of the eCos totally.
• 20:15
  Speaker 2: And you know, honestly, if I went to talk to
• 20:16
  Speaker 2: this issuer or the at least the index maker, they'd
• 20:19
  Speaker 2: be like, oh, yeah, we've known this for three years, dude,
• 20:20
  Speaker 2: you know, welcome to the club. Like that's how many
• 20:22
  Speaker 2: things are going on. And some of these ETF fishers
• 20:25
  Speaker 2: are honestly really on the bleeding edge. But the four
• 20:27
  Speaker 2: of them come out a day, so you just miss
• 20:29
  Speaker 2: them and it's just tough to keep up with all this.
• 20:31
  Speaker 2: But man, it's it's wild.
• 20:33
  Speaker 1: What's the ticker for that? B U l D be
• 20:36
  Speaker 1: you wealthy?
• 20:37
  Speaker 2: There we go and I can give you the performance
• 20:39
  Speaker 2: since it came out. It's not that old. It's up
• 20:41
  Speaker 2: sixty four percent since launching four years ago.
• 20:44
  Speaker 1: Okay, not bad, Jake, thanks so much for joining us
• 20:46
  Speaker 1: in Trillions.
• 20:47
  Speaker 3: Thank you, Thank you for having me here.
• 20:57
  Speaker 1: Thanks for listening to trillions and telling them Next time.
• 21:00
  Speaker 1: You can find us on the Bloomberg Terminal, Bloomberg dot com,
• 21:03
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• 21:06
  Speaker 2: You want to listen.
• 21:07
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• 21:10
  Speaker 1: Trillions is produced by Magnus Hendrickson and Kishav Pundia. Bye.