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Watch these five AI signals this week · The Financial Exchange Show

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Speaker 1: donation today. This is the Financial Exchange with Chuck Zada
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Speaker 1: and Mark Fandetti.
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Speaker 2: Chuck Mark Tucker with you here and as we kick
1:14
Speaker 2: things off in video, has crossed the five trillion dollar
1:19
Speaker 2: market cap, Yes you heard that correctly, becoming the first
1:23
Speaker 2: company to have a five trillion dollar market cap in history.
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Speaker 2: And look, whether you think this is you know, the future,
1:33
Speaker 2: whether you think this is crazy, you gotta admit it's
1:36
Speaker 2: pretty impressive to get to that point. I mean, there's
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Speaker 2: plenty of companies out there. This is the only one
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Speaker 2: that's done it, and doing it in emphatic fashion as well.
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Speaker 2: After being up about five percent yesterday, up another three
1:47
Speaker 2: and a half today, was actually up about four and
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Speaker 2: a half at one point, and has pulled back a touch,
1:52
Speaker 2: but again at five point seven trillion dollars right now,
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Speaker 2: and uh again, it just continues to defy any of
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Speaker 2: the haters, you know when when you look at that's
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Speaker 2: the technical term that we use there taking a broader
2:11
Speaker 2: look at markets. Despite that, the S and P five
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Speaker 2: hundred only up a quarter percent. Uh so in Nvidia
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Speaker 2: today is quite literally carrying the whole market. If you
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Speaker 2: stripped it out, the SMP would basically be flat today.
2:24
Speaker 2: Dow Jones is up half a percent nasdak Can posite
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Speaker 2: up point six percent right now, so all three major
2:31
Speaker 2: US indices are in the green, though the Russell two
2:34
Speaker 2: thousand has taken a turn into very mild red territory
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Speaker 2: at the moment. Tenure US Treasury up six tenths of
2:42
Speaker 2: a basis point to three point nine to eight nine percent.
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Speaker 2: We've just been fluttering between like three nine seven and
2:48
Speaker 2: four h three for the last few days. Not much
2:51
Speaker 2: movement on that front. Dollar Index is up point one
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Speaker 2: two percent today to ninety eight fifty seven, and we've
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Speaker 2: we've got gold today rallying a little bit up thirty
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Speaker 2: nine to thirty and ounce to fourenty twenty two and
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Speaker 2: forty cents. And then when we take a look at oil,
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Speaker 2: West Texts Intermediate is currently up seventy three cents a
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Speaker 2: barrel to sixty dollars and eighty eight cents triple a
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Speaker 2: national average for gas prices, continuing to slide a little
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Speaker 2: bit as Midwest prices come back in line after a
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Speaker 2: refinery restarted there in the last couple of days. So
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Speaker 2: we're down another six tenths of a cent to three
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Speaker 2: zho three and eight tenths on the national average for
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Speaker 2: gas prices, mark couple different home a couple of different
3:40
Speaker 2: housing pieces to touch on. One here from this is
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Speaker 2: what is this Bloomberg home prices we post weakest gain
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Speaker 2: in more than two years, up just one and a
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Speaker 2: half percent year over year, and another one from market
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Speaker 2: Watch homebuilders are struggling and it's not just because new
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Speaker 2: houses aren't affordable. This all kind of fits into this
4:01
Speaker 2: idea that Connor Son's been pushing for the last couple
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Speaker 2: of weeks that I'm kind of on board with, which is, look,
4:07
Speaker 2: in order to buy a home, you need two things.
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Speaker 2: You need the ability to buy the home. That's the
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Speaker 2: affordability piece. The second one is you have to have
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Speaker 2: the belief that it's a good time to buy a home.
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Speaker 2: And that's the part that he's been arguing is is
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Speaker 2: now missing in large parts of the country because, as
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Speaker 2: an example, if you are in you know, different pockets
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Speaker 2: of Florida that Fort Myers Cape Coral area as an example,
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Speaker 2: where home prices have now fallen more than ten percent
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Speaker 2: from the peak a you're probably not wanting to list
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Speaker 2: your place because you're like, I'm not gonna get top
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Speaker 2: dollar for it, and I want to see how things
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Speaker 2: go b You're probably sitting there saying, well, prices are falling.
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Speaker 2: I'm gonna wait until I try to buy there, because
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Speaker 2: I see prices that keep coming down. And so his argument,
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Speaker 2: and the one that this kind of gets at, is,
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Speaker 2: look if affordability is still a problem in parts of
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Speaker 2: the country, but in others it's improved. But you're now
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Speaker 2: seeing you know, the rise of Hey, prices are falling,
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Speaker 2: so I don't want to buy it. Or I'm concerned about,
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Speaker 2: you know, potential layoffs in my industry, so I don't
5:07
Speaker 2: want to buy. Yeah, you've got you know, problems that
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Speaker 2: are really you know, continuing to see us just kind
5:13
Speaker 2: of floating around four million existing home sales on an
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Speaker 2: annualized basis with no real traction to move up, even
5:20
Speaker 2: though interest rates have come down about three quarters of
5:23
Speaker 2: a percent in the last couple months.
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Speaker 3: Hmmm, Yeah, that idea is kind of squishy. I don't
5:29
Speaker 3: know how to measure some of the figure centers.
5:32
Speaker 2: I don't think you can measure it.
5:33
Speaker 3: Yeah, he's just like he's a commentator. I'm sorry, I
5:35
Speaker 3: don't mean to diminish it, but he doesn't actually do research,
5:37
Speaker 3: or maybe he looks at spreadsheets or something. But he doesn't,
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Speaker 3: you know, publish peer reviewed stuff. So he throws out
5:42
Speaker 3: some stuff and maybe people remember in a week. Maybe
5:45
Speaker 3: they don't sound like I'm diminishing it, which I guess
5:47
Speaker 3: I am. I think you are because I think it's important. Well,
5:49
Speaker 3: when you do research, you got to put it out there.
5:50
Speaker 3: You gotta show me your data go. You gotta specify
5:53
Speaker 3: a model, you got to test it. You got to
5:54
Speaker 3: explain why you think it's the right specification. You've got
5:57
Speaker 3: to subject it to awful things that your peers will
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Speaker 3: say about this, stupid mistakes that you've made. It's a grueling,
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Speaker 3: difficult process, tough on one's ego, but it's how you
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Speaker 3: advance our understanding of things. These ideas are to me,
6:11
Speaker 3: things you talk about with your family over at Thanksgiving dinner.
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Speaker 3: It's tough to measure by. As far as I can tell,
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Speaker 3: he hasn't tested them, so I don't know what to
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Speaker 3: make of them. Is it a plausible story, Yeah, it's plausible.
6:21
Speaker 3: You and I could probably come up with several equally
6:23
Speaker 3: plausible stories, So forgive me. I just don't know what
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Speaker 3: to make of this squishy soft Maybe it's this, Maybe
6:30
Speaker 3: it's that, type stuff. Okay, prices, price growth is slow.
6:34
Speaker 3: That was inevitable. There's this divergence in year over year inventories.
6:38
Speaker 3: We learned last week from NAR. Some markets remain hot
6:42
Speaker 3: and tight on the coast southern California, some pockets of
6:46
Speaker 3: the East coast. Other markets Jacksonville, the Southwest appear to
6:51
Speaker 3: be sagging. That's maybe more typical normal, if you will,
6:55
Speaker 3: prior to the nationalization of the housing market that we
7:00
Speaker 3: saw on the in the two thousands. To me, it
7:02
Speaker 3: seems healthier for what it's worth. So that's squishy.
7:06
Speaker 2: I can't test that well.
7:07
Speaker 1: It is.
7:08
Speaker 2: Quite honestly, I think that a lot of there's a
7:13
Speaker 2: lot around housing that is squishy because I like it's
7:18
Speaker 2: it's something that There's two different things that I think
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Speaker 2: make it tough to make housing non squishy is each
7:25
Speaker 2: piece of real estate is unique. It's not you know, commoditized, right,
7:31
Speaker 2: it's you know, it's you're you're looking at again, there's
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Speaker 2: a reason why, Like if you talk to real estate
7:36
Speaker 2: investors or even just you know people own homes about Hey,
7:38
Speaker 2: why'd you buy this house? It's like, oh, I liked
7:40
Speaker 2: it because of X, Y and Z like it. It
7:43
Speaker 2: does have kind of that squish factor to it. It's
7:45
Speaker 2: you know, it's it's kind of this personal thing we have.
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Speaker 3: Some jobs are the same way, and there is search
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Speaker 3: in matching models and economics that overcome that. Maybe that's
7:54
Speaker 3: not doable in housing. I don't know, not my area.
7:57
Speaker 3: I probably probably sound stupid what I.
7:58
Speaker 2: Just said to a housing You can still like segmented
8:00
Speaker 2: in everything and we can learn things on that front.
8:03
Speaker 2: But the the other piece I think when we when
8:07
Speaker 2: we look at this is just trying to figure out look.
8:10
Speaker 2: Prices in parts of the country have come down over
8:14
Speaker 2: the last year, affordability has improved, mortgage rates have come
8:20
Speaker 2: down over the last year, and yet we're still not
8:24
Speaker 2: seeing more activity. So it's kind of the question that's
8:29
Speaker 2: that's being asked out there, is you got more inventory,
8:32
Speaker 2: prices are down and mortgage rates are down and they're
8:35
Speaker 2: still not moving. What is it in wage system that
8:40
Speaker 2: that that's the problem?
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Speaker 3: Wege growth slower in those markets? Do we know?
8:43
Speaker 2: Could be?
8:44
Speaker 3: But is anybody you know testing right?
8:46
Speaker 2: Could could be? And part of it, like we in
8:49
Speaker 2: specific markets like that, like you don't get that data
8:51
Speaker 2: in anywhere close to real time. You know you're going
8:54
Speaker 2: to be getting data a year or two after the fact. Yea,
8:59
Speaker 2: And so it's some thing where in the absence of
9:02
Speaker 2: that data, just because it's not produced in a timely fashion,
9:05
Speaker 2: and quite honestly, I don't think it's worth the cost
9:08
Speaker 2: to produce that data in a timely fashion. We're left saying, Okay,
9:13
Speaker 2: could it be this, could it be that? And we
9:14
Speaker 2: don't know, But there is something that's happening there.
9:18
Speaker 3: There's a divergence that cries out for an explanation. What
9:21
Speaker 3: is going on in Phoenix that inventories are up thirty
9:24
Speaker 3: excuse me, a year over year thirty percent? Is that right? Yeah? Yeah,
9:30
Speaker 3: So there's this big divergence. Some markets look healthy all
9:34
Speaker 3: against a Maryland, parts of the East Coast they appear healthy.
9:36
Speaker 3: Others Southwest markets that have in the past been boombustish,
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Speaker 3: they don't. They look more wobbly. Is it wages? Is
9:46
Speaker 3: it something else? I don't know? Is it well anyway,
9:49
Speaker 3: I obviously don't know.
9:51
Speaker 2: Let's take a quick break. When we return, we'll talk
9:55
Speaker 2: a little bit about the artificial intelligence industry and some
9:59
Speaker 2: key market signals coming up this week. We've also got
10:02
Speaker 2: trivia right after this.
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10:40
Speaker 4: Time for trivia here on the Financial Exchange. And in
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Speaker 4: Today, how many Halloween movies is Jamie Lee Curtison? Once again?
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Speaker 4: How many Halloween movies is Jamie Lee Curtis in be
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11:28
Speaker 2: Piece in Bloomberg Opinion titled watch these five AI signals
11:33
Speaker 2: closely this week in terms of you know, look, you
11:38
Speaker 2: got a bunch of corporate earnings specifically in that space.
11:41
Speaker 2: What are we seeing from them? Number one? Amazon Web Services?
11:46
Speaker 2: Are we seeing improvement there in their battle against Microsoft
11:51
Speaker 2: Azure and Google Cloud? That's going to be something to watch.
11:55
Speaker 2: Number two? How much is the demand crunch pushing up capex?
12:00
Speaker 2: So what are we seeing in terms of Hey, as
12:04
Speaker 2: companies battle for these chips and not just the chips,
12:08
Speaker 2: but all the other stuff that goes into building data centers.
12:11
Speaker 2: You know, think about cabling and cooling and all that stuff. Hey,
12:15
Speaker 2: is that pushing up the cost? And are we seeing
12:17
Speaker 2: you know, movement on that front? Another one for Apple.
12:22
Speaker 2: Apple has not been on the forefront of AI development
12:26
Speaker 2: to this point. I know they have their Apple Intelligence
12:29
Speaker 2: platform that has largely been panned. But are we seeing
12:35
Speaker 2: any you know, shift in spending in Apple's earnings as
12:40
Speaker 2: far as you know, consumer trends away from iPhone because
12:43
Speaker 2: of concerns about you know, lack of AI there to
12:46
Speaker 2: this point, we haven't seen that, but is it something
12:48
Speaker 2: that happens? Another one with Meta, Will Meta's advertising gains
12:53
Speaker 2: be enough of a distraction? The answer typically has been yes,
12:55
Speaker 2: because they they don't print money, They don't have the
12:59
Speaker 2: physic go money printer mark, but they are as close
13:03
Speaker 2: as you can get to printing money, you know, without
13:05
Speaker 2: having one of those things. And another one, Reddit, who
13:09
Speaker 2: also reports earnings this week. They are kind of in
13:14
Speaker 2: a battle of some of these AI companies that they're
13:16
Speaker 2: accusing of scraping their data illegally. And so what are
13:21
Speaker 2: we seeing with Reddit who has now struck deals with
13:25
Speaker 2: Google and open Ai? Are there more deals? How do
13:29
Speaker 2: they end up monetizing that? How much money is there
13:31
Speaker 2: for them? Just some interesting things to consider as we
13:34
Speaker 2: get these AI earnings this week.
13:36
Speaker 3: Yeah, for sure, term investors, traders, whatever you want to
13:39
Speaker 3: call them, these things are of interest longer term though.
13:43
Speaker 3: The big question hanging over the market now and that
13:45
Speaker 3: we'll be hanging over the market for a while, is
13:49
Speaker 3: is AI paying off? Is it increasing output per hour productivity?
13:55
Speaker 3: What we do with the tools that we A'm being
13:58
Speaker 3: a little fast and lost with term here, but more
14:00
Speaker 3: or less, what we do what a worker, any one
14:02
Speaker 3: of us does in an hour, measured in terms of
14:06
Speaker 3: whatever output. It is that we produce no evidence for
14:10
Speaker 3: that yet not surprising. You could argue that it's early,
14:13
Speaker 3: though some would say given the scale of the investments
14:16
Speaker 3: and the fact that they've been underway for several years
14:20
Speaker 3: and we as far as we know, there's no measurable benefit,
14:24
Speaker 3: though there's controversy around that as well. I guess what
14:28
Speaker 3: I'm trying to say is the proofs in the pudding,
14:30
Speaker 3: and the pudding is still cooking.
14:34
Speaker 2: Does one cook put? How do you make it?
14:36
Speaker 3: Don't you boil it?
14:37
Speaker 2: I have no, I'm not a pudding. It is believe heat.
14:41
Speaker 3: Heat is the reaction that you need. Yeah, yeah, cause
14:44
Speaker 3: the reaction.
14:44
Speaker 2: I just I don't understand pudding.
14:47
Speaker 3: No, we're not.
14:48
Speaker 2: I find it quite honestly. I want to talk about
14:52
Speaker 2: this piece from Barons because this is a it's not
14:57
Speaker 2: a fun one, but it's a really interesting one to
15:00
Speaker 2: look through big wayoffs look scary, why the job market
15:03
Speaker 2: is still holding up?
15:04
Speaker 3: Mark?
15:04
Speaker 2: What does this piece talk about and what are some
15:07
Speaker 2: of the key points in it?
15:08
Speaker 3: Well, to me, the point I was gonna make is
15:11
Speaker 3: that the eye bopping numbers. Amazon lays off fifty thirty
15:15
Speaker 3: thousand people, and there are examples, you could say just
15:19
Speaker 3: about every day. They're a drop in the bucket when
15:21
Speaker 3: it comes to the size of the labor force, about
15:23
Speaker 3: one hundred and seventy million people. When it comes to
15:26
Speaker 3: the number of people that quit their jobs every month,
15:28
Speaker 3: we talk about the Jolts survey. We haven't gotten that lately,
15:31
Speaker 3: but it's normally a monthly survey, and the most recent
15:34
Speaker 3: report three million people quit left their jobs voluntarily in August.
15:40
Speaker 3: Companies hired five million people in that same month. Churn
15:44
Speaker 3: in the labor market turnover, however you want to characterize it,
15:48
Speaker 3: is enormous. And these layoff announcements though they and I
15:52
Speaker 3: certainly got to minimize them for people or families who
15:54
Speaker 3: are affected by them, but they're normal and really a
15:57
Speaker 3: drop in the bucket. The key, obviously is economic growth
16:02
Speaker 3: that will keep unemployment down overall. That's the measure you
16:05
Speaker 3: want to look at, not getting Oh, of course, if
16:07
Speaker 3: you're interested in the fortunes of a particular company or industry,
16:12
Speaker 3: these might be eye catching, but in the scheme of
16:16
Speaker 3: things they don't matter much.
16:17
Speaker 2: And Ernie Tedesky, who we've had on the show previously,
16:23
Speaker 2: mentioned something on this today where in kind of a
16:26
Speaker 2: related topic, you know, there's the idea of, hey, is
16:30
Speaker 2: the lack of hiring and is what we're seeing in
16:33
Speaker 2: the labor market now related to AI And he makes
16:38
Speaker 2: the point, No, he doesn't think it is. And the
16:42
Speaker 2: reason why is that there was such an over hiring
16:45
Speaker 2: that took place in the back half of twenty twenty
16:49
Speaker 2: really through the first half of twenty two that if
16:54
Speaker 2: you look at the trends in terms of the slowdown
16:56
Speaker 2: and hiring. Chat GPT was first rolled out in late
17:00
Speaker 2: twenty twenty two, very late, it was likeate December of
17:02
Speaker 2: twenty two. The slowdown in hiring started in mid twenty
17:07
Speaker 2: twenty one, a year and a half before chat GPT
17:11
Speaker 2: was rolled out, and it's basically continued since then at
17:14
Speaker 2: you know, kind of the same pace that slowdown. It's
17:16
Speaker 2: been the same slope that we've seen on that line.
17:20
Speaker 2: So he makes the point, Look, there's no inflection point
17:22
Speaker 2: where chat GPT was released and you suddenly saw hiring
17:25
Speaker 2: fall off a cliff or even you know more recently,
17:29
Speaker 2: you know, was there any shift. It's like kind of like, no,
17:31
Speaker 2: it's it's basically been this this trend that we're seeing there,
17:36
Speaker 2: and I've also seen kind of, in a related note,
17:39
Speaker 2: people talking about Look, if you think about this in
17:42
Speaker 2: terms of think about the labor market in terms of
17:46
Speaker 2: the housing market, which I know is weird, but housing
17:49
Speaker 2: we talked about last segment. Hey, you're not seeing people
17:53
Speaker 2: buying these prices even though you know, things are cheaper
17:58
Speaker 2: than they were a year ago, just because we're still
18:00
Speaker 2: not back to you know, twenty nineteen twenty eighteen levels
18:03
Speaker 2: of affordability relative to income. And think about companies and
18:08
Speaker 2: think about them in terms of purchasing labor. The labor
18:12
Speaker 2: that companies purchased back in twenty twenty one and twenty
18:17
Speaker 2: twenty two was really freaking expensive because it was an
18:21
Speaker 2: insanely competitive market. And so if you think about it
18:24
Speaker 2: from this perspective, companies can let go that surplus twenty
18:28
Speaker 2: one and twenty two labor right now that was priced
18:32
Speaker 2: really highly, and they either a could say, look, we
18:36
Speaker 2: don't need any additional labor right now, but even if
18:38
Speaker 2: we do, we can get additional labor more cheaply now
18:42
Speaker 2: on a you know, in terms of you know, kind
18:43
Speaker 2: of real terms, because hey, it's not as competitive as
18:47
Speaker 2: a job market right now. We can find better candidates
18:50
Speaker 2: for less cost today, and so some of what these
18:52
Speaker 2: companies might be doing, in particular, like Amazon, who went
18:55
Speaker 2: on a hiring spree during that time, I wonder how
18:59
Speaker 2: much of the layoff is concentrated in that vistage of
19:03
Speaker 2: people hired in twenty one and twenty two where they've
19:05
Speaker 2: got these crazy pay packages and Amazon's like, no, we
19:08
Speaker 2: can get rid of them. Let that position just sit
19:10
Speaker 2: for a year, then hire someone cheaper a year from now.
19:12
Speaker 3: Researchers will spend a lot of time trying to identify
19:15
Speaker 3: the specific reason for those these layoffs. They're interesting implications
19:20
Speaker 3: what the Fed's doing. Maybe we can talk about on
19:22
Speaker 3: the other Side's.
19:23
Speaker 2: Take a quick break. When we come back. We got
19:25
Speaker 2: Wall Street Watch, We've got trivia answer, and we're talking
19:28
Speaker 2: credit cockroaches when we return.
19:38
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19:48
Speaker 1: Time now for Wall Street Watch. A complete look at
19:51
Speaker 1: what's moving markets so far today right here on the
19:54
Speaker 1: Financial Exchange Radio Network.
19:56
Speaker 4: FED meeting days upon us and markets are extending GA
20:00
Speaker 4: from their fresh record highs FED Chairman Jerome Powell will
20:03
Speaker 4: hold a press conference at two thirty this afternoon after
20:06
Speaker 4: the expected quarter point rate cut, however, and Nvidia is
20:10
Speaker 4: the big story on the day, where the chip and
20:12
Speaker 4: ai giant has officially crossed five trillion dollars in market cap,
20:17
Speaker 4: the first company to do so if Video shares are
20:20
Speaker 4: up four percent right now for markets, Dow is up
20:24
Speaker 4: about a half a percent, or two hundred and nineteen points,
20:27
Speaker 4: SMP five hundreds up two tents one percent or fourteen points,
20:30
Speaker 4: NASDAC up just over half a percent or one hundred
20:34
Speaker 4: and twenty five points, or Russell two thousand now actually
20:38
Speaker 4: up by six tenths of one percent. Ten year treasure
20:42
Speaker 4: yield is up one basis point at three point nine
20:46
Speaker 4: to nine three percent, and crude oil is up just
20:50
Speaker 4: over one percent higher, trading just below sixty one dollars
20:54
Speaker 4: a barrel. Boeing posted mixed quarterly results. While it's revenue
20:58
Speaker 4: beat estimates, the aerospace company logged a steeper loss than anticipated.
21:04
Speaker 4: Boeing also said it at increased seven thirty seven production
21:07
Speaker 4: to thirty eight airplanes a month. Boeing shares down by
21:11
Speaker 4: over four percent. Meanwhile, shares and Caterpillars surging thirteen percent
21:15
Speaker 4: after the maker of construction machinery beat third quarter forecasts. Elsewhere,
21:20
Speaker 4: Five Serve shares are tanking forty two percent after the
21:24
Speaker 4: financial services tech company reported a significant third quarter earnings
21:28
Speaker 4: and revenue miss Mandale's cut his twenty twenty five guidance,
21:32
Speaker 4: where the snack maker cited high cocoa prices and transportation costs,
21:37
Speaker 4: and also noted Americans were buying fewer snacks. That stock
21:40
Speaker 4: is retreating about three percent. According to CNBC, General Motors
21:45
Speaker 4: laid off roughly seventeen hundred workers across its manufacturing sites
21:49
Speaker 4: in Michigan and Ohio, citing a slowdown in the electric
21:53
Speaker 4: vehicle market. GM stock is flat, and after today's closing bell,
21:58
Speaker 4: the kickoff to big tech earnings begins, where Alphabet, Meta,
22:03
Speaker 4: and Microsoft will all report their quarterly results. I'm Tucker
22:07
Speaker 4: Silva and that is Wall Street Watch. And in the
22:09
Speaker 4: previous segment, we asked the trivia question how many Halloween
22:12
Speaker 4: movies is Jamie Lee Curtis in? That would be seven.
22:16
Speaker 4: Nancy from Newberry, New Hampshire is our winner today, taking
22:19
Speaker 4: home a Financial Exchange Show T shirt congrat congrats to Nancy,
22:23
Speaker 4: and we played trivia every day here in the Financial Exchange.
22:26
Speaker 4: See complete contest rules at Financial Exchange Show dot com.
22:30
Speaker 2: Mark, do you have any credit cockroaches at home?
22:33
Speaker 3: I don't think I have. I don't think I've ever
22:35
Speaker 3: seen a cockroach.
22:36
Speaker 2: I haven't, Tucker you.
22:38
Speaker 3: I think hotels, lots. Not like size of your thumbs.
22:41
Speaker 4: I've seen like a smaller one, but like not like
22:44
Speaker 4: the ones you've seen, like men in black or something
22:47
Speaker 4: like the giant guys.
22:48
Speaker 3: What's the biggest one you've ever seen?
22:50
Speaker 2: I've ever seen one.
22:51
Speaker 3: Okay, size of your thumb, I've never saw tell in
22:52
Speaker 3: New York City. Once trapped it under a glass, left
22:55
Speaker 3: it for housekeeping. I'm sorry, how big was it? Size
22:59
Speaker 3: of you? I'm including the antenna and all of the paraphernalia. Yeah,
23:03
Speaker 3: and I think he was packing something too. May have
23:05
Speaker 3: been a may have been a glock, I'm not sure.
23:07
Speaker 3: So he was pretty well equipped. Yeah, he was pretty
23:10
Speaker 3: well equipped. But I trapped him under a glass, and
23:12
Speaker 3: I felt proud that I was able to do it.
23:14
Speaker 3: They are the size of that thing. I'm sort of
23:17
Speaker 3: a suburban slash rural a this country boy, so it
23:20
Speaker 3: was horrifying anyway, you know what people have experienced.
23:23
Speaker 2: Honestly, it wouldn't be that impressive to me, like having
23:26
Speaker 2: experienced the rats of Somerville back when I was living there.
23:30
Speaker 3: Never I've never experienced.
23:31
Speaker 2: You'd you'd be walking home at like, you know, eight
23:33
Speaker 2: thirty nine at night, it's dark out, and you come
23:35
Speaker 2: to you know, your your door, and you're like, oh,
23:38
Speaker 2: like there's a dog on the porch and you're like,
23:40
Speaker 2: wait a minute, fine dog, that's like a foot long
23:43
Speaker 2: rat that's just hanging out on the porch waiting for you,
23:46
Speaker 2: waiting for you to get home. In any case, Credit
23:48
Speaker 2: cock roaches. So Jamie Diamond kind of brought this into
23:52
Speaker 2: the mainstream a couple of weeks ago when he said, look,
23:55
Speaker 2: you know, in reference to some of these uh privately
23:58
Speaker 2: held you know, loone that we're blowing up. Hey, usually
24:01
Speaker 2: when you see you know, one cockits, there's usually others
24:04
Speaker 2: that are out there. And I think that when we
24:09
Speaker 2: look at the the story on this, I think, once again,
24:14
Speaker 2: this this is one that just because Credit has now
24:17
Speaker 2: performed okay for the last couple of weeks, doesn't mean
24:21
Speaker 2: all clear. And I'm not saying like I don't know
24:23
Speaker 2: where this is going to go. Anyone who can conclusively
24:26
Speaker 2: tell you right now that they know exactly how this
24:30
Speaker 2: is going to play out is lying to you, because
24:33
Speaker 2: if they do know, they're not telling because they work
24:35
Speaker 2: for you know, Apollo or Blackstone or whoever. They're trying
24:40
Speaker 2: to clean up their books and figure out, like are
24:42
Speaker 2: we exploring, what are we doing?
24:43
Speaker 3: What's going to blow up next? That they can buy insurance?
24:45
Speaker 2: Yes, the people who do know aren't talking, and the
24:48
Speaker 2: people who don't know, why would they like?
24:50
Speaker 3: These are very sophisticated investors.
24:52
Speaker 2: Correct, So I think that when you look at this,
24:55
Speaker 2: I do think this is going to be binary. It's
24:58
Speaker 2: either going to be something where six month from now
25:00
Speaker 2: we look back at this and say, hey, this was
25:03
Speaker 2: kind of like Silicon Valley Bank where you had a
25:05
Speaker 2: few blow ups. Maybe there were a couple, you know,
25:08
Speaker 2: companies that had to be acquired in order to manage this,
25:12
Speaker 2: but ultimately it led to nothing. It wasn't a systemic issue.
25:15
Speaker 3: Late cycle reaching for yield is a hallmark of the
25:20
Speaker 3: credit cycle to be a little redundant there. So All
25:23
Speaker 3: Diamond's not psychic. He's not saying he knows he just
25:25
Speaker 3: knows things are frothy. When things get frothy, analysts get sloppy.
25:30
Speaker 3: They bring increasingly dodgy deals to their managers and they
25:34
Speaker 3: stretch the case a little bit, and the managers say, well,
25:37
Speaker 3: I think we've got clients who would buy this. Let's
25:41
Speaker 3: work on syndicating it or selling it directly. It's inherent
25:45
Speaker 3: to late cycle dynamics. You might call it the interaction
25:49
Speaker 3: between people that need money and people that lend money.
25:52
Speaker 3: The ladder get the ladder are emboldened by frothy financial conditions,
25:59
Speaker 3: the lenders get sloppier. Diamond seeing this over again over again, right.
26:04
Speaker 2: So one possibility is, hey, you've got a few of
26:07
Speaker 2: these that pop up. You know, we already went through
26:09
Speaker 2: first brands, we went through Tricolor. There's been a couple
26:11
Speaker 2: more now that are you know, in the process. But
26:15
Speaker 2: ultimately it doesn't become a systemic issue just because it's
26:17
Speaker 2: not big enough and widespread enough for that to be
26:21
Speaker 2: a problem. And if that's the case, we'll know in
26:24
Speaker 2: the next six to nine months. The other path that
26:27
Speaker 2: this can follow is, hey, these are the canaries and
26:30
Speaker 2: the coal mine. You know, these are the subprime funds
26:34
Speaker 2: that blew up in April of seven that eventually led
26:38
Speaker 2: to the entire financial crisis in fall of eight. I
26:43
Speaker 2: have no idea which path we are going to take.
26:46
Speaker 2: The private credit market is substantial now. I mean we're
26:50
Speaker 2: talking the estimates that I've seen alre anywhere from like
26:53
Speaker 2: two to five trillion dollars in assets here. To put
26:57
Speaker 2: this in perspective of the US mortgage market today is
26:59
Speaker 2: about twelve trillion dollars. So it's anywhere from like fifteen
27:03
Speaker 2: to forty percent the size, and no one really knows,
27:07
Speaker 2: partly because the private markets, like there is no public
27:12
Speaker 2: accounting of how much is out there. Like you can't
27:14
Speaker 2: look at this like you do with the bond market
27:16
Speaker 2: and be like, here are all the bonds traded publicly,
27:18
Speaker 2: here's how much is outstanding. We know how much debt
27:20
Speaker 2: is there, Here's how big the US stock market is.
27:23
Speaker 2: Because you can run the numbers, you don't know how
27:26
Speaker 2: big this is, and you don't know how widespread problems are.
27:30
Speaker 2: And it's just gonna take some time for this to
27:32
Speaker 2: play out. So I think it's something that's worth monitoring absolutely,
27:37
Speaker 2: because this stuff can go bad quickly. You know, it
27:43
Speaker 2: can happen rather fast in this area. But it's also
27:48
Speaker 2: something where hey, you might be sitting here six to
27:51
Speaker 2: nine months now and you're like, oh, yeah, I remember
27:53
Speaker 2: those concerns about private credit. Wasn't that quaint? I don't
27:56
Speaker 2: know where we're going yet, But something continues to say
28:00
Speaker 2: think out there. And the other thing that you're seeing
28:03
Speaker 2: in a lot of these it's an awful lot of
28:06
Speaker 2: fraud that's showing up in these companies that are going
28:08
Speaker 2: belly up, and that is not reassuring to me in
28:11
Speaker 2: any way, shape or form.
28:12
Speaker 3: Well, somebody missed it. An analyst missed it, their manager,
28:15
Speaker 3: meaning they saw what they wanted to see. Yes, and
28:18
Speaker 3: no analyst sees the full picture. And by that I
28:21
Speaker 3: mean companies show you when you're doing due diligence on
28:24
Speaker 3: a loan, they show you what they want you to see.
28:26
Speaker 3: You can go on site, which you should. Indeed, better
28:29
Speaker 3: managers do go on site, kick the tires, talk to management,
28:33
Speaker 3: talk to look at their track record, but you never
28:36
Speaker 3: really see the full picture. But to me, it always
28:40
Speaker 3: comes down to taking two to tango, the analyst to
28:43
Speaker 3: the manager, the investment manager who buys, who lends the money. Effectively,
28:46
Speaker 3: they want to be fooled. They kind of want to
28:48
Speaker 3: believe that these high returns with a triple A rating
28:51
Speaker 3: or possible, and of course the guy on the other side,
28:54
Speaker 3: maybe they want to believe that their collateral is worth
28:56
Speaker 3: a lot more than they represent. Now, the double counting
28:58
Speaker 3: of collateral is a different store. Unless you don't know
29:01
Speaker 3: how to use a spreadsheet, that's pretty clearly fraudwadll you
29:03
Speaker 3: shouldn'tay clearly.
29:04
Speaker 2: Probably, yeah, probably. Let's take a quick break here. When
29:11
Speaker 2: we return, we'll do a little bit of stack rough.
29:13
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30:20
Speaker 2: Mark what you got for stack roulette?
30:22
Speaker 3: Did you know that Oracles loaded up on or issued
30:25
Speaker 3: about sixty billion dollars in debt in just the last
30:28
Speaker 3: couple of months. That makes yes. I think the sex
30:31
Speaker 3: you and Mike or you and Paul have talked about this.
30:34
Speaker 3: A corollary to that, or a related story is that
30:37
Speaker 3: bigs of the big sophisticated investors that we were talking
30:39
Speaker 3: about in the last segment, who are able to buy
30:43
Speaker 3: insurance or protection or just make a bet on somebody defaulting,
30:47
Speaker 3: they are now piling into so called credit default swaps,
30:51
Speaker 3: which is a way to either buy insurance or to
30:53
Speaker 3: speculate that somebody will not be able to repay their loan.
30:57
Speaker 3: The CDs is we don't see them. They're not publicly traded.
31:01
Speaker 3: But interest in Oracle cds's is increasing, i'll to say
31:05
Speaker 3: rapidly according to Bloomberg, though they don't quantify it because
31:08
Speaker 3: it's tough to get a handle on it for reasons
31:10
Speaker 3: that you mentioned in the previous segment. These vehicles like
31:13
Speaker 3: private credit though this Oracle issues their bonds publicly, but
31:18
Speaker 3: the insurance against them is private. Interest is picking up.
31:21
Speaker 3: So this is another to me symptom of late stage
31:23
Speaker 3: froth of financial conditions that are too easy. Amazing that
31:27
Speaker 3: the FED is loosening in the face of these obvious
31:31
Speaker 3: signs of speculative froth. But here we have yet yet
31:36
Speaker 3: another one. I hope they know more about the labor market,
31:39
Speaker 3: the FED, I mean, than we do.
31:41
Speaker 2: And quite honestly, when it comes to these companies that
31:44
Speaker 2: are building data centers, the entire question is going to
31:49
Speaker 2: be when the depreciation starts to really hit, can you
31:55
Speaker 2: find the revenue in order to actually cover it on
31:59
Speaker 2: your statement? Like it are you going to have basically
32:03
Speaker 2: like the gross revenue that can end up getting you
32:06
Speaker 2: to you know, the net income that's needed to cover it.
32:10
Speaker 2: That's that's where the meat is because ultimately, like I
32:14
Speaker 2: keep having to come back to this, the amount of
32:16
Speaker 2: construction that's taken place to this point is a drop
32:19
Speaker 2: in the bucket compared to what's projected for the next
32:21
Speaker 2: five years. And when you start having five hundred billion
32:26
Speaker 2: dollars in data center construction coming through that you need
32:29
Speaker 2: to depreciate over probably like an eight to twelve year period,
32:34
Speaker 2: maybe a little shorter than that, depending on you know,
32:36
Speaker 2: how much of the spend goes into chips that you
32:40
Speaker 2: know basically have a useful life of only a few years.
32:43
Speaker 2: You will agat and you say, okay, how are these
32:45
Speaker 2: companies going to figure out how to deal with you know,
32:49
Speaker 2: sixty billion dollars of depreciating hitting from next year's vintage,
32:52
Speaker 2: another sixty from the year after, and pretty soon you
32:55
Speaker 2: got like one hundred and eighty two hundred billion dollars
32:58
Speaker 2: of depreciate, a depreciation that's hitting your income statement, and
33:01
Speaker 2: you're like, okay, like, we got to figure out some
33:05
Speaker 2: way to deal with this. Are you gonna have the
33:08
Speaker 2: five hundred billion dollars in sequential revenue in order to cover.
33:12
Speaker 3: That and make the investments that are required to keep
33:14
Speaker 3: these right?
33:14
Speaker 2: Like I don't know. Yeah, I'd like that is a
33:19
Speaker 2: you basically have to get to. I think you know,
33:22
Speaker 2: I think you have Okay, Quite honestly, I suspect that
33:26
Speaker 2: unless we're actually talking about replacing twenty to forty percent
33:31
Speaker 2: of the workforce with AI for either you know, LMS
33:35
Speaker 2: for white collar jobs and robots for blue collar jobs,
33:39
Speaker 2: unless that is feasible by twenty thirty, it doesn't pay
33:45
Speaker 2: for itself.
33:46
Speaker 3: Where's the investment gonna come from? We we already don't
33:49
Speaker 3: save enough. We talked about this in the first hour.
33:50
Speaker 3: That has trade deficit implications because it's the flip side
33:53
Speaker 3: of foreign investment coming in. Where's the If it's gonna
33:56
Speaker 3: come from abroad, the trade deficit blows out.
33:58
Speaker 2: And the other piece is okay, if if you start
34:02
Speaker 2: seeing companies increasingly relying on AI and robots as their
34:05
Speaker 2: workforce and trimming their workforce further, our economy is seventy
34:09
Speaker 2: percent consumer spending. How does that work if you have
34:12
Speaker 2: a smaller and smaller pool of people actually working. What
34:14
Speaker 2: needs to change in order for that to you know,
34:16
Speaker 2: remain functional. I like, there's a lot of potential problems
34:22
Speaker 2: as you get out there. We're not really the market's
34:26
Speaker 2: not worried about those right now. That's fine. Doesn't have
34:28
Speaker 2: to worry about.
34:29
Speaker 3: What's worse, what's scarier prospect in your mind, AI doesn't
34:32
Speaker 3: fulfill its promise, or it does does.
34:36
Speaker 2: If it doesn't, we've gone through boombus cycles before. This
34:39
Speaker 2: one would be large. But there's a path to figuring
34:42
Speaker 2: out how to deal with that. Like here, here's the
34:46
Speaker 2: interesting thought experiment. You've got one hundred and sixty million
34:48
Speaker 2: people working in the US right now at this very
34:51
Speaker 2: point in time. Maybe not right now because some of
34:53
Speaker 2: them are you know, night shift, but you got one
34:56
Speaker 2: hundred and sixty million people that are working in the
34:58
Speaker 2: United States today. If five years from now you only
35:04
Speaker 2: have one hundred and thirty million jobs because AI has
35:08
Speaker 2: taken thirty million of them. Well, that thirty million people,
35:12
Speaker 2: let's say that they you know, they work, and they
35:15
Speaker 2: have got you know, kind of just median income in general.
35:17
Speaker 2: Let's say let's call it like seventy thousand a year
35:19
Speaker 2: times thirty million people. Uh, that is two point one
35:24
Speaker 2: trillion dollars in income that is no longer being earned. Well,
35:29
Speaker 2: if that's not being earned, then how much money do
35:32
Speaker 2: the companies that laid them off, have to spend on AI.
35:35
Speaker 2: And if they're further cutting spending, then how much more
35:38
Speaker 2: has to happen in terms of cuts? And do you
35:39
Speaker 2: get to this spiral where eventually you just say okay,
35:43
Speaker 2: like this is the thing now where people like aren't
35:47
Speaker 2: working in most of these places. Like if AI can
35:50
Speaker 2: actually do all of the stuff that its proponents say
35:52
Speaker 2: it can, how do you make the economics of society work?
35:56
Speaker 2: Because we are not set up for this in any way.
35:59
Speaker 3: Some people are screaming at the radio saying what about electricity,
36:01
Speaker 3: what about steam? What about the IT revolution?
36:04
Speaker 1: No?
36:04
Speaker 3: I know, I oh yeah, But it could work out
36:06
Speaker 3: that AI favors capital over labor and that these that
36:11
Speaker 3: people don't shift seamlessly between sectors. It could. I don't
36:15
Speaker 3: think the odds are on that.
36:15
Speaker 2: But here's the other scenario that I think we have
36:18
Speaker 2: to be aware of as a possibility. What if we
36:20
Speaker 2: get both? What if you get and this, by the way,
36:24
Speaker 2: is what happened with you will get all these major inventions,
36:26
Speaker 2: whether it's the railroad, electricity, radio flight, what if you
36:32
Speaker 2: get Hey, this transforms how business is done. But we
36:38
Speaker 2: also spent way too much building this out like the
36:40
Speaker 2: example that I love to give, it's likely like railroads
36:42
Speaker 2: and radio are right there, where, Hey, we spent so
36:46
Speaker 2: much money in the eighteen hundreds building railroads, and think
36:50
Speaker 2: of all the railroads that went bust in the eighteen
36:52
Speaker 2: hundreds because there still wasn't the demand to fill all
36:55
Speaker 2: those but they still transform society.
36:56
Speaker 3: It was a depression every three years.
36:58
Speaker 2: Radio is the same thing. You had this explosion of
37:01
Speaker 2: commerce that could take place because of radio that previously
37:04
Speaker 2: couldn't happen, and yet you still saw the radio sector
37:09
Speaker 2: decimated in the nineteen twenties and thirties because of overinvestment
37:12
Speaker 2: in it. What if you get the same thing with AI,
37:16
Speaker 2: where yeah, it's this transformational product, but we still put
37:20
Speaker 2: way too much money into you know, building the back
37:22
Speaker 2: end of it, and it turns out that you know,
37:25
Speaker 2: that ends up being a loss as well. Like it
37:28
Speaker 2: could be both, because most great technological changes are they
37:33
Speaker 2: change the world, but we also think that they're going
37:35
Speaker 2: to do so much. You know that we spend so
37:37
Speaker 2: much money, We put so much money into them an
37:39
Speaker 2: investment and it just can't work out. So it could
37:43
Speaker 2: be both. You could have AI change the world and
37:46
Speaker 2: do all these crazy things and we could still be
37:49
Speaker 2: investing way too much into it.
37:51
Speaker 3: Well, yeah, most of us have experienced that within our
37:53
Speaker 3: lifetimes with the sure Internet.
37:54
Speaker 2: Sure, So with that in mind, let's take a break
37:59
Speaker 2: for the rest of the day. Tomorrow, we got all
38:01
Speaker 2: the earnings from this afternoon to recap Microsoft Meta and Alphabet.
38:06
Speaker 2: We've got a FED meeting we're gonna be recapping, and
38:09
Speaker 2: we're previewing tomorrow's big earnings of Apple and Amazon. Pack
38:13
Speaker 2: show tomorrow. Make sure you tune in