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From one wild trading day to another · The Financial Exchange Show

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Speaker 1: Zada and Mike Armstrong.
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Speaker 2: We got Chuck, Mike and Ben with you today, and
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Speaker 2: yesterday was a day that quite honestly didn't really go
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Speaker 2: the way I expected it to.
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Speaker 1: Uh.
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Speaker 2: You had a big pop in the pre market session,
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Speaker 2: led by two factors. The first was in video being
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Speaker 2: up about five percent after reporting earnings, second being that
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Speaker 2: we got a jobs report that was better than expected
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Speaker 2: as well. And so the S and P five hundred
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Speaker 2: yesterday opened up one and a half percent and then
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Speaker 2: proceeded to rally an additional half percent or so. And
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Speaker 2: quite honestly, like I didn't know that, you know, I
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Speaker 2: thought there was a chance we'd be off to the
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Speaker 2: races and maybe end up, like, you know, two and
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Speaker 2: a half three percent. But I kind of figured, Okay,
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Speaker 2: even if you give some of this back, you know,
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Speaker 2: it's still gonna be a pretty solid day. In the end,
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Speaker 2: the S and P gave all of its gains back
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Speaker 2: and then gave back an additional one and a half
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Speaker 2: percent and finally ended up closing down over one hundred points.
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Speaker 2: And so what we ended up with, Mike was only
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Speaker 2: the fourth such instance, according to Luke Cowa of Sherwood News,
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Speaker 2: where the S and P opened at least one and
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Speaker 2: a half percent up and then closed at least one
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Speaker 2: and a half percent down. In the last thirty two years,
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Speaker 2: four times in thirty two years that has happened. You've
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Speaker 2: had bigger intra day swings, but you very rarely open
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Speaker 2: up so much, you know, above the previous close and
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Speaker 2: then closed down in this fashion. And so anyone who said, yeah,
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Speaker 2: I was expecting to see that, tell me how you
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Speaker 2: did on the other three days out of you know,
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Speaker 2: the last six thousand trading days that we've had, and
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Speaker 2: you know, maybe then we can talk.
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Speaker 3: Yeah, pretty unusual. The price action soft from in video
3:00
Speaker 3: was more significant. It started the day up, peaked up
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Speaker 3: five percent, finished the day down three percent. The Nasdaq
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Speaker 3: tech heavy NASDAC started up, peaked up two point six
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Speaker 3: percent before ending the day down two point two percent.
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Speaker 4: What I think made this.
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Speaker 3: One especially unique to Chuck was we were doing the
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Speaker 3: show live when it started to deteriorate. I don't know
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Speaker 3: exactly where the SMP was when we closed, but it
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Speaker 3: was negative. As we closed out the shoe show yesterday
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Speaker 3: at noon, and we were sitting there saying, Okay, this
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Speaker 3: is interesting. There's no breaking news story, there's no wild
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Speaker 3: change in the narrative. Overall, it's and Video reported earnings.
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Speaker 3: The earnings were better than we're anticipated, and as the
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Speaker 3: day went on, that story was just not enough to
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Speaker 3: shift the skepticism that you have been seeing about this
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Speaker 3: overall AI trade.
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Speaker 2: So let's dig in a little bit on this because
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Speaker 2: I think that there's an interesting thought that I've seen
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Speaker 2: bandied about the the deepest, darkest reaches of the Internet,
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Speaker 2: and I want to get your thoughts on it. So
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Speaker 2: on Wednesday, in additional and Videos earnings announcement, there was
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Speaker 2: another big AI announcement, which was that Alphabet, the parent
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Speaker 2: company of Google, came out and said, hey, here is
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Speaker 2: the latest version of our Gemini AI platform, Gemini three.
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Speaker 2: And a bunch of you know, really smart people around
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Speaker 2: the Internet who actually understand AI, took a look at it,
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Speaker 2: poked around, you know, ran it through some various different
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Speaker 2: benchmark testing and this and that, and pretty much unanimously said, yeah,
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Speaker 2: this is a huge step up from everything else that
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Speaker 2: is out there. We think this is better than what
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Speaker 2: open ai is putting out. We think it's better than
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Speaker 2: what Anthropic is putting out. We think it's it's the
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Speaker 2: cream of the crop and the best thing that we've seen.
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Speaker 2: And I don't know the exact time timing on this,
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Speaker 2: but at some point in you know, that twenty four
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Speaker 2: hour period. Google also disclosed that the training for the
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Speaker 2: model for Gemini three was not done on in Nvidia processors.
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Speaker 2: It was done on a different set that was developed
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Speaker 2: internally by Google. And the thought that I've seen bandied
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Speaker 2: about is, hey, if the latest and greatest AI model
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Speaker 2: that's out there is developed by Google, not by open ai,
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Speaker 2: and developed not using Nvidia chips, then given the fact
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Speaker 2: that for the last three years the center of focus
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Speaker 2: for that AI trade has been, hey, whatever open ai
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Speaker 2: is doing is where you want to be, and and
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Speaker 2: Vidia is the only way to power those kinds of
5:59
Speaker 2: models that that you know generate those results. Could Google
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Speaker 2: basically be putting a stake into the heart of those
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Speaker 2: two pillars of the AI trade. And maybe some of
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Speaker 2: that was what we saw investors realize over the course
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Speaker 2: of the day yesterday. Maybe, Like I'll put it out there,
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Speaker 2: I'm curious to get your thoughts, Mike.
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Speaker 3: Yeah, I don't feel as though it made a huge
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Speaker 3: splash across all circles, but it is a big enough
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Speaker 3: announcement that if you're following this trade closely, you might
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Speaker 3: trade on that. It's reminiscent of the deep seek news
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Speaker 3: from what was.
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Speaker 4: That March of this year.
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Speaker 3: February Okay, so February of this year China, you know,
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Speaker 3: Chinese AI tool comes out claiming that it didn't really
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Speaker 3: use in video chips for training, gets tested by people,
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Speaker 3: it's you know, shown to be a pretty impressive large
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Speaker 3: language model. You know, sent some questions into the overall narrative. Ultimately,
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Speaker 3: I think, in part because the news was out of
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Speaker 3: China and in part because they were legitimate questions about
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Speaker 3: how they trained the thing. You know, that story kind
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Speaker 3: of died off in terms of where it went. But yeah, certainly,
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Speaker 3: I think if Google, if it holds true that this
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Speaker 3: new AI model is truly competitive, you know, more than
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Speaker 3: competitive then with chat JAPT and wasn't trained on in
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Speaker 3: video chips that is in newsworthy story and does question
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Speaker 3: in video I guess my point would be, it's not
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Speaker 3: as though we got some splashy headline about that at
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Speaker 3: eleven am that you and I can track down and say, oh, yeah,
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Speaker 3: this was the shift, this is when it.
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Speaker 2: Turned, which is why. I think a lot of times
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Speaker 2: what happens is markets move, and then people try to
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Speaker 2: ascribe meeting to the move after the fact, right, Like
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Speaker 2: was it just like every trading desk read this piece,
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Speaker 2: like the Morgan Stanley one read at eleven am, and
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Speaker 2: then Goldman read it at eleven oh five, and then
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Speaker 2: you know, Bank of America read it at eleven ten,
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Speaker 2: and it just kind of continued down. I don't know.
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Speaker 2: I do think those things do develop over time, and
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Speaker 2: what we are seeing, in my opinion, is the realization
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Speaker 2: of the idea, and this is over the last month
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Speaker 2: or two that hey, there's more than one way to
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Speaker 2: build an AI model, and where AI can go can
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Speaker 2: be dramatically different from where it's been the first few years.
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Speaker 2: Just look at how people are talking about this in
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Speaker 2: the last couple of days. Now it's like, oh, open
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Speaker 2: Aye's lost, you know, some of its leadership. That's a
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Speaker 2: thought that we haven't seen out in the public context
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Speaker 2: in the past three years.
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Speaker 4: Mike True.
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Speaker 3: The other piece of this in video earnings and just
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Speaker 3: the market reaction that I want to bring up.
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Speaker 4: You make a fair point.
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Speaker 3: I did not anticipate markets turning over midway through.
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Speaker 4: The day and going negative.
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Speaker 3: I don't think that anyone genuinely did. But we did
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Speaker 3: talk about going into this week, how in Video's earnings
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Speaker 3: did not really have the ability to genuinely.
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Speaker 4: Ship the narrative.
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Speaker 2: No, they couldn't.
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Speaker 3: They couldn't because they're the last to reports. So if
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Speaker 3: you are going to see a negative story about in
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Speaker 3: Video's earnings, it would have shown up in earnings from Meta, Microsoft, Alphabet, Amazon.
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Speaker 4: You would have expected it there.
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Speaker 3: And given the trajectory of spending that all those companies reported,
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Speaker 3: in Video's earnings had to be pretty decent. They didn't
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Speaker 3: need to beat their earnings estimates in the way that
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Speaker 3: they did. But even with that beat, that's not what
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Speaker 3: the shift in the AI narrative has been about. The
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Speaker 3: shift in the AI narrative has been these companies are
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Speaker 3: clearly going to continue to build out AI, but will
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Speaker 3: it ever pay for itself? And in Video can't answer
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Speaker 3: that question.
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Speaker 2: Right And specifically, if you're asking are we in an
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Speaker 2: AI bubble, then what you're actually saying is if the
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Speaker 2: answer to that question is yes, which I'm not saying
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Speaker 2: it is or isn't. But if you're answering, yes, we're
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Speaker 2: in an AI bubble. Then what you're telling me is
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Speaker 2: people are buying too many in vidio chips today. You're
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Speaker 2: not telling me people aren't buying enough of them, right,
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Speaker 2: You're telling me people are buying too many. The bubble
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Speaker 2: pops when they realize that they are buying too many.
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Speaker 2: But we don't know if that's what's going to end
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Speaker 2: up happening. It may it may not, and it still
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Speaker 2: is very uncertain at this point. What I can tell
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Speaker 2: you is that the market is starting to get worried
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Speaker 2: about these companies that may be buying too many. Specifically,
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Speaker 2: I got a point at Oracle, who is down another
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Speaker 2: five percent today.
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Speaker 4: Yeah.
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Speaker 2: Oracle, remember is the company that back in uh September,
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Speaker 2: it was it late August, hang on a wind pull
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Speaker 2: of the day, yep, September, they reported earnings and magically said, hey,
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Speaker 2: we've got another three hundred billion dollars in commitments for
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Speaker 2: cloud spending that's going to show up in the next,
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Speaker 2: you know, several years. And everyone was like, oh my goodness,
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Speaker 2: this is amazing. And Oracle stock popped like thirty plus
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Speaker 2: percent in a single day, and the stock before that
10:56
Speaker 2: was trading at about two hundred in let's see, it
10:59
Speaker 2: was like two hundred thirty five bucks to share. The
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Speaker 2: day of earnings, it went up to three hundred and
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Speaker 2: forty five. It sits here today at one hundred and
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Speaker 2: ninety nine. Yep, it is almost it's fifteen percent below
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Speaker 2: where it was the day before that announcement. And this
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Speaker 2: is the representation, in my opinion, of people saying, hey,
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Speaker 2: we're worried that you're spending too much money because Oracle
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Speaker 2: in particular is doing a ton of debt financing to
11:26
Speaker 2: do this. They don't have the cash flow, they don't
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Speaker 2: have the money that Meta and Google and Microsoft have
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Speaker 2: to just pour, you know, into these projects. And so
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Speaker 2: Oracle's financing it with a ton of debt, and the
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Speaker 2: market is looking at it, not just the equity, but
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Speaker 2: you take a look at what's going on with credit
11:41
Speaker 2: default swaps for Oracle and how their debts being priced,
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Speaker 2: and the market's looking at them saying, and we're not
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Speaker 2: sure that you're going to be able to generate enough
11:49
Speaker 2: revenue to cover all this chuck.
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Speaker 3: This is the for good reason, the only story that
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Speaker 3: anyone wants to write about today. When you see a
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Speaker 3: massive shift in markets like you did yesterday, it is noteworthy.
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Speaker 3: Where do we go with this next in terms of
12:04
Speaker 3: in terms of coverage, because there is a lot to
12:06
Speaker 3: unpeel here, and I know we need to take a break.
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Speaker 2: Yeah, why don't we. Let's see, let's dig into a
12:12
Speaker 2: little bit about the financing of this data center construction,
12:16
Speaker 2: because that, I think is where the adjecta is at
12:20
Speaker 2: the moment. So let's do a quick break and then
12:23
Speaker 2: get your pencils out unless you're driving, and we're gonna
12:27
Speaker 2: give you some stuff to scribble down about how debt
12:30
Speaker 2: finance markets work when it comes to building multi billion
12:35
Speaker 2: dollar data centers.
12:38
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13:45
Speaker 2: Mich Let's talk a little bit about what we are
13:47
Speaker 2: seeing in debt markets as it relates to artificial intelligence.
13:52
Speaker 2: Can you give some numbers surrounding, you know, kind of
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Speaker 2: what we've seen this year, in this quarter particularly.
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Speaker 3: Yeah, So, these companies that have been spending at least
14:03
Speaker 3: started by doing so out of cash flow, and they
14:08
Speaker 3: had the cash.
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Speaker 4: Flow to be able to do it.
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Speaker 3: But more recently, companies like Amazon, Alphabet, Microsoft, Meta, Oracle,
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Speaker 3: they've raised one hundred and eight billion dollars in debt
14:19
Speaker 3: combined in twenty twenty five. Just for some context, that's
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Speaker 3: more than three times the average over the previous nine
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Speaker 3: years in order to finance some of this. Now, on
14:31
Speaker 3: its surface, I don't really have a problem with Amazon
14:33
Speaker 3: borrowing that type of money, but it does, you know,
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Speaker 3: ultimately raise the question of when you talk about other
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Speaker 3: companies such as Oracle, if these projects don't pan out
14:45
Speaker 3: the way they are supposed to, what precisely does that
14:49
Speaker 3: look like. And then the other piece on this chuck
14:53
Speaker 3: that we haven't spent a lot of time on are
14:56
Speaker 3: the off balance sheet projects that these companies are also
14:59
Speaker 3: fine dancing without really taking out a boatload of debt
15:03
Speaker 3: on their balance sheet. For instance, the Hyperion project down
15:08
Speaker 3: in Louisiana, which utilizes a special purpose vehicle financing structure.
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Speaker 4: What does that mean.
15:14
Speaker 3: It means that the project is not actually owned by Meta.
15:21
Speaker 3: They financed all of it, but it is its own
15:25
Speaker 3: corporation that is effectively controlled by Meta, but they're financing
15:29
Speaker 3: all the debt that's been taken out is not on
15:31
Speaker 3: Meta's balance sheet because it's a special purpose vehicle. And
15:35
Speaker 3: you know, this is where some of the concerns about
15:37
Speaker 3: private credit come in. And so, yes, there's been a
15:40
Speaker 3: bunch of debt raised by a bunch of companies like
15:43
Speaker 3: these Big five, there's been a lot more debt raised
15:45
Speaker 3: by others, but then there's also a whole bunch of
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Speaker 3: kind of shadow debt as far as I'm concerned, that's
15:51
Speaker 3: funding some of these projects.
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Speaker 2: And let's use Meta just as an example, because I
15:55
Speaker 2: think this represents, you know, kind of the Again, remember
15:58
Speaker 2: Meta reported earn and sold off pretty hard on them,
16:03
Speaker 2: and it's because what's going on with metas financials are
16:06
Speaker 2: different from what you're seeing with Microsoft and Amazon as
16:08
Speaker 2: an example. So Microsoft still has increasing year over year
16:13
Speaker 2: trailing twelve month free cash flow and earnings. Right now,
16:16
Speaker 2: there's there's nothing in Microsoft's financials that you look at
16:19
Speaker 2: and you're like ew. Meta, on the other hand, there's
16:23
Speaker 2: still nothing that you're like ew, like this is awful.
16:27
Speaker 2: But when we look at their free cash flow picture,
16:29
Speaker 2: just as an example, at the end of last year,
16:33
Speaker 2: trailing twelve month free cash flow was fifty four billion dollars,
16:37
Speaker 2: which is a lot of money. Today it's forty four
16:41
Speaker 2: billion dollars. It's a twenty percent decline in a span
16:43
Speaker 2: of nine months. And remember Metas committing to continue increasing
16:48
Speaker 2: capex next year at an even higher rate. So you
16:53
Speaker 2: look at this and you're like, okay, so metas capex
16:56
Speaker 2: Metas free cash flow is declined by twenty percent this year,
16:59
Speaker 2: and they're going to continue ramping up capex even if
17:02
Speaker 2: the debt doesn't hit their balance sheet. You're still going
17:04
Speaker 2: to see that spending coming out on you know, cash
17:08
Speaker 2: flow statements. And then when you get to the income statement,
17:11
Speaker 2: the depreciation eventually is going to hit as well. And
17:13
Speaker 2: this is before you even look at the fact that, hey,
17:16
Speaker 2: they're trailing twelvemonth net income went from seventy one billion
17:21
Speaker 2: dollars in Q two down to fifty eight billion in
17:25
Speaker 2: Q three. Now, some of that a decent chunk of
17:28
Speaker 2: it was because of a one time hit related to
17:30
Speaker 2: how they're realizing some tax things related to the new
17:34
Speaker 2: tax bill. But still you're basically seeing it flattening out
17:37
Speaker 2: in terms of net income if you exclude that charge,
17:40
Speaker 2: and that means that again, once that depreciation starts kicking in,
17:44
Speaker 2: it's going to start showing up there. And these are
17:47
Speaker 2: the concerns is that, hey, if you're really committing to
17:51
Speaker 2: spend the amount of money that you say you are
17:53
Speaker 2: committing to spend, at some point you have to start
17:57
Speaker 2: generating a return on that, because otherwise it's going to
18:01
Speaker 2: negatively impact these metrics as you go forward.
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Speaker 3: Yeah, that's been the focus over the last couple of
18:08
Speaker 3: weeks especially, it has been the questions about how long
18:13
Speaker 3: these chips last. The debts taken out over thirty year
18:16
Speaker 3: time periods, But if you need to replace these things
18:19
Speaker 3: every couple of years, which has been theorized, how does
18:22
Speaker 3: that really match up? And then again, probably just because
18:26
Speaker 3: I've been obsessed with the private credit side of all
18:28
Speaker 3: of this too, I keep seeing these stories of oh, yeah,
18:32
Speaker 3: and now Blue Owl is lending to this vehicle that's
18:35
Speaker 3: going to build out this AI data center, and oh,
18:38
Speaker 3: don't worry because it's got a you know, one of
18:41
Speaker 3: the tenants in there is alphabet, or one of the
18:43
Speaker 3: tenants is meta.
18:45
Speaker 4: And you look at it all and.
18:48
Speaker 3: You say, okay, yeah, the tenant is meta, but they
18:50
Speaker 3: don't actually own it or have any real liability if
18:53
Speaker 3: that thing doesn't pan out the way you want it to.
18:56
Speaker 4: I don't know.
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Speaker 3: All of it just seems very nected and interconnected, and
19:01
Speaker 3: you know, beyond even just the public book debt issuance
19:04
Speaker 3: that's happening.
19:04
Speaker 2: The other piece. This is all happening during a normal economy.
19:09
Speaker 2: What happens to these businesses if there is a recession, which,
19:13
Speaker 2: by the way, like there will be some at one
19:15
Speaker 2: at some point, like you, we're not just going to
19:17
Speaker 2: never have another recession ever again, I don't know when
19:21
Speaker 2: it may or may not be. But what happens to
19:23
Speaker 2: these businesses and their plans and their revenue if there's
19:27
Speaker 2: a recession at some point? Quick break when we come back,
19:30
Speaker 2: it's Wall Street Watch.
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19:59
Speaker 5: After yesterday day is wild ride, markets look like they
20:02
Speaker 5: might be taking us on another wild ride today. It
20:04
Speaker 5: is mixed out there. The Dow Jones is up over
20:07
Speaker 5: half a percent. The S and P five hundred is
20:10
Speaker 5: just barely clung to one tenth of a percent upright now,
20:13
Speaker 5: the Nasdaq has flipped it's now in the negative territory,
20:16
Speaker 5: down almost four tenths of a percent, and the VIX
20:19
Speaker 5: has flipped positive. It's up one point six three percent.
20:23
Speaker 5: Eli Lilly earlier this morning reached one trillion dollar market capitalization,
20:28
Speaker 5: the first healthcare company in the world to join the
20:30
Speaker 5: exclusive club dominated by tech's firms. The company's stock has
20:34
Speaker 5: climbed more than thirty six percent this year. The Indianapolis,
20:38
Speaker 5: Indiana based drugmaker stock has been riding the skyrocketing popularity
20:42
Speaker 5: of its weight loss injection zet bound and diabetes treatment
20:46
Speaker 5: Munjaro Eli Lilly is currently up over half a percent.
20:50
Speaker 5: Apparel retailer gap up over five percent after topping expectations
20:54
Speaker 5: for same store sales with five percent growth in the
20:56
Speaker 5: latest quarter thanks to its viral better in denhim cam
21:00
Speaker 5: paign with kats Eye excluding the pandemic. Same store sales
21:03
Speaker 5: growth was the fastest since its fiscal twenty seventeen holiday quarter.
21:08
Speaker 5: Cloud solutions provider Viva Systems is off by over eleven
21:12
Speaker 5: percent after saying it expects fewer top biopharmaceutical companies to
21:16
Speaker 5: select its vault CRM. Viva posted third quarter earnings of
21:20
Speaker 5: two dollars and four cents per share excluding one time items,
21:23
Speaker 5: on eight hundred and eleven point two million dollars in revenue,
21:27
Speaker 5: versus analyst estimate of a dollar ninety five per share
21:30
Speaker 5: on seven hundred.
21:31
Speaker 2: And ninety two point eight million in revenue.
21:33
Speaker 5: Ross Stores reported better than expected revenue of five point
21:36
Speaker 5: six billion, compared to contensus estimate of five point four
21:39
Speaker 5: to two billion, pushing its shares up over six percent.
21:43
Speaker 5: Ross also raised its fourth quarter earnings guidance, saying we
21:46
Speaker 5: now expect terror related costs to be negligible. I am
21:50
Speaker 5: Ben Kitchen and that was Wall Street Watch.
21:53
Speaker 2: I gotta say, Mike that Wall Street Watch was actually
21:55
Speaker 2: one of the first times that I've ever felt like
21:57
Speaker 2: really old.
22:01
Speaker 4: What made you feel really old?
22:03
Speaker 2: I had no Not only did I have no idea
22:05
Speaker 2: who Cat's eye is, sure, but when I actually when
22:10
Speaker 2: I read like an actual piece with that, I didn't
22:13
Speaker 2: even know that's how it was pronounced. I thought it
22:14
Speaker 2: was because it's spelled k A T s E y
22:17
Speaker 2: e with no spaces or apostrophes. I thought it was
22:21
Speaker 2: like kat's a ye.
22:23
Speaker 4: Yep. I can I can see how you get there,
22:26
Speaker 4: so I.
22:27
Speaker 5: Like, to be honest, it might be I just guessed.
22:29
Speaker 2: No, I'm reading the Wikipedia page right now. But uh,
22:33
Speaker 2: I again, this is when I'm I'm normally at least
22:37
Speaker 2: halfway like knowledgeable about things that people in their twenties
22:41
Speaker 2: are talking about this one. I had no idea so
22:47
Speaker 2: well pretty.
22:47
Speaker 4: Old once K pop demon Hunters started making its.
22:50
Speaker 2: Way through No that like that, I I get, I understand.
22:54
Speaker 2: I I like it's front and center in my mind.
22:56
Speaker 2: I'm I'm, I'm there. This I've I've just never heard
23:00
Speaker 2: heard of, even like cats Eye, I was. I thought
23:03
Speaker 2: Kat's Eye might have been a person at first, you know,
23:06
Speaker 2: kind of like Kesha, Or thought it.
23:08
Speaker 4: Was like a good luck charm, like a rabbit's.
23:10
Speaker 2: Foot right, or like is it another brand? You know,
23:15
Speaker 2: like I don't know, And now I find out that
23:18
Speaker 2: it is a group of six women that sing, So
23:22
Speaker 2: I guess.
23:22
Speaker 4: You know, we all learned something.
23:24
Speaker 2: I know, this is a great day that I learned
23:26
Speaker 2: something new. So it's wonder if you Ben, thank you.
23:29
Speaker 2: I appreciate that. Mike. Anything else on AI that we
23:33
Speaker 2: want to discuss now that the S and P is
23:36
Speaker 2: down another quarter percent?
23:40
Speaker 3: Look, I think yesterday's market move was an interesting point
23:44
Speaker 3: in this shift and confirmed some of my worst concerns
23:52
Speaker 3: about all this, which would be that, you know, even
23:54
Speaker 3: really robust arnings aren't gonna be enough to turn the
23:56
Speaker 3: tide on it a few interesting points that I don't
24:00
Speaker 3: think are hugely important to this current moment when it
24:03
Speaker 3: comes to AI.
24:06
Speaker 4: You know, one piece from the.
24:07
Speaker 3: Financial Times about you know, the entire AI piece right
24:11
Speaker 3: now is about large language models, and that's really what's matter,
24:14
Speaker 3: That's what's driven prices higher. What if that's actually not
24:19
Speaker 3: what AI and you know, what if the large language
24:22
Speaker 3: models not aren't ending up to be the winners in
24:25
Speaker 3: all this?
24:25
Speaker 4: What if it's something else. What if it's drug.
24:27
Speaker 3: Creation from AI or using AI to you know, properly
24:30
Speaker 3: set up robotics, or something entirely new. And then the
24:34
Speaker 3: other piece that Mohammad Alarian wrote about the.
24:36
Speaker 4: Bubble right now is.
24:39
Speaker 3: Kind of I think it's worth reading because it reiterates
24:42
Speaker 3: a few of my points about all this is there
24:46
Speaker 3: will absolutely, at least in my opinion, there will absolutely
24:50
Speaker 3: be some massive winners because of this innovation around artificial intelligence.
24:55
Speaker 4: Yes, the problem is that.
24:59
Speaker 3: Everyone's being true as a winner right now, and that
25:03
Speaker 3: or at least as a few weeks ago, they were
25:04
Speaker 3: all being treated as winner. Now now that were a
25:06
Speaker 3: close stock has come way back down. Maybe they're not,
25:09
Speaker 3: But a few weeks ago they were all being treated
25:11
Speaker 3: as winners, And what we know from every market cycle
25:14
Speaker 3: previously is that not every company ends up being a
25:18
Speaker 3: winner when it comes to any new innovative technology.
25:22
Speaker 4: Yeah.
25:22
Speaker 2: I think that we've talked about this a little bit before,
25:26
Speaker 2: but look, everyone being priced as a winner is a
25:28
Speaker 2: problem because not everyone wins when new technology is created.
25:32
Speaker 2: But think about like all of not all of it,
25:35
Speaker 2: but think about some of the other technology bubbles that
25:38
Speaker 2: we've seen. You can have a bubble that exists, have
25:43
Speaker 2: a bubble that pops and creates a bunch of losers,
25:46
Speaker 2: but still changes the world for the better through increased productivity.
25:50
Speaker 2: This happened with railroads, this happened with radio, it happened
25:55
Speaker 2: with the automobile, It happened with airplanes, it happened with
25:59
Speaker 2: the Internet. And in each of those cases, yes, there
26:02
Speaker 2: was way too much money poured in to those businesses,
26:06
Speaker 2: chasing returns in the short term, and you had huge
26:09
Speaker 2: bankruptcies that came out of them. But Michael, last time
26:13
Speaker 2: I checked, we are broadcasting on radio. Correct, we are?
26:16
Speaker 4: Yeah?
26:16
Speaker 2: And did you drive to work today?
26:19
Speaker 4: Yeah?
26:20
Speaker 2: And again, these these innovations can change the world and
26:25
Speaker 2: still create all kinds of malinvestment. While the initial excitement
26:30
Speaker 2: is going on, and I think that it's important to
26:33
Speaker 2: realize that that can happen. And the piece to be
26:39
Speaker 2: careful of is, Hey, the people that even today, like
26:43
Speaker 2: I still meet with people today who are sixty seventy
26:48
Speaker 2: years old, and you know, they cut their teeth working
26:50
Speaker 2: in the tech bubble, and they'll tell you, yeah, I
26:53
Speaker 2: had all of my money in company stock because it
26:55
Speaker 2: seemed like the party would never end, and then it
26:57
Speaker 2: ended yep, and that's the.
27:00
Speaker 3: Kind million one night, and then overnight I was worth
27:03
Speaker 3: two on twentieth of that.
27:05
Speaker 2: Yeah, it's like that. Those are the things that you
27:08
Speaker 2: have to you know, be cognizant of in terms of
27:12
Speaker 2: not getting too greedy and understanding the mechanics of these things.
27:18
Speaker 2: But I do think that you can look at this
27:21
Speaker 2: and say, we're gonna all be using more artificial intelligence
27:24
Speaker 2: five years from now than we are today. We don't
27:27
Speaker 2: know exactly what format that's going to be in. At
27:31
Speaker 2: that point, there still is probably going to be a
27:34
Speaker 2: huge shakeout because the numbers that are being spent are
27:36
Speaker 2: just astronomical, and we still may come away better off
27:41
Speaker 2: when we look back twenty years from now, despite this
27:45
Speaker 2: maybe being bubblicious, and this.
27:49
Speaker 3: Type of bubble that we get here in the United States,
27:51
Speaker 3: which again you know, may not be unique to this
27:54
Speaker 3: moment in time, does lead to one good thing, which
27:59
Speaker 3: is his Workly, it's left behind a whole bunch of
28:02
Speaker 3: really usable infrastructure, and you just don't necessarily get that
28:06
Speaker 3: in economies that don't have I guess the type of
28:13
Speaker 3: free markets and free, free, free ish capitalism that we
28:17
Speaker 3: have in the United States. You can't exactly call it
28:19
Speaker 3: full free market capitalism here, but you know, compare it
28:23
Speaker 3: for a moment to the central planning of the Chinese government,
28:26
Speaker 3: and there's a reason they are, you know, several years
28:30
Speaker 3: behind us on this AI trade.
28:32
Speaker 2: Maybe we think we don't know. Yeah, let's take a
28:37
Speaker 2: quick break here, and when we return, let's talk a
28:41
Speaker 2: little bit about what we are seeing from Amazon in
28:44
Speaker 2: terms of their layoffs. War notices are starting to come
28:47
Speaker 2: out in different states where employees are impacted. Who are
28:51
Speaker 2: they laying off and where are those layoffs happening? We'll
28:54
Speaker 2: tell you after this.
28:56
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29:26
Speaker 5: This segment of the Financial Exchange is powered by Circle
29:29
Speaker 5: circle K Convenience Stores. Circle K is now the official
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Speaker 5: of Circle K. Thank you veterans for all you've done.
29:41
Speaker 2: Mike Pce and CNBC talking about where the Amazon layoffs
29:44
Speaker 2: are starting to show up. What are we seeing? There?
29:47
Speaker 3: So a few states in which they have filed the
29:51
Speaker 3: mandatory layoff announcements. It's indicating that in places like Washington,
29:57
Speaker 3: New York, New Jersey, and California, forty percent of the
30:01
Speaker 3: jobs in those states were engineering job cuts. I don't
30:06
Speaker 3: know that I find this immensely surprising, but yeah, effectively,
30:10
Speaker 3: Amazon announced fourteen thousand layoffs that will be coming.
30:16
Speaker 4: In those states.
30:17
Speaker 3: They've actually filed the specifics and that's what you're finding.
30:20
Speaker 3: But to me, when I read through this a little
30:22
Speaker 3: bit more, it was kind of logical. They are laying
30:27
Speaker 3: off in some of the higher expensive areas of their business,
30:31
Speaker 3: such as a product that I wasn't even aware of,
30:34
Speaker 3: lens that allows people to kind of, I think, somehow,
30:38
Speaker 3: you know, shop with some sort of vision of what
30:42
Speaker 3: it looks like in your room, as well as some
30:45
Speaker 3: gaming sides of the business that were pretty highly intensive
30:48
Speaker 3: and high capital and so a lot of those are
30:51
Speaker 3: engineering jobs in that space. And look, every company has
30:55
Speaker 3: been out there looking to find ways that they can
30:57
Speaker 3: cut some of the higher expenses in order to focus
30:59
Speaker 3: on the only thing that investors have cared about, which
31:03
Speaker 3: is artificial intelligence and how to put more resources into it.
31:06
Speaker 4: Did it read any differently to you?
31:09
Speaker 2: No? Not really.
31:10
Speaker 3: Yeah, I mean fourteen thousand job cuts. I don't mean
31:14
Speaker 3: to minimize it, but it clearly hasn't been enough to
31:18
Speaker 3: move the needle on the overall employment situation. Yes, I
31:22
Speaker 3: understand why people are concerned about the labor market given
31:25
Speaker 3: the just quantity of all of these announced job cuts
31:29
Speaker 3: across major companies, but as we saw yesterday with the
31:32
Speaker 3: jobs report, it has not been enough to move the
31:35
Speaker 3: needle at least through September, and even with the most
31:38
Speaker 3: recent data we're getting on weekly jobless claims in the aggregate,
31:41
Speaker 3: these concerns about firings are not really moving the needle
31:45
Speaker 3: at all.
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Speaker 5: Visit USVII dot com and book your trip today. That's
32:45
Speaker 5: visit USVII dot com. Mike, we got a piece in
32:50
Speaker 5: the New York Times. Is a global housing bubble about
32:53
Speaker 5: to burst?
32:55
Speaker 4: What?
32:55
Speaker 3: A piece of clickbait which first begs the question, raises it,
33:00
Speaker 3: but begs it, is there a global housing bubble? Well,
33:04
Speaker 3: so they write this article. Somebody wrote the title of
33:07
Speaker 3: the article to get you to click on it.
33:09
Speaker 2: They then go on to say, no, We're not.
33:11
Speaker 4: In a housing bubble. It's not about to burst. So
33:16
Speaker 4: it seems misleading at.
33:17
Speaker 3: Best, and let's just move only deceptive at worse.
33:21
Speaker 2: Let's just move on.
33:22
Speaker 4: Because they literally did this.
33:24
Speaker 3: They asked, is a global housing bubble about to burst?
33:26
Speaker 3: Try and get you to click on this piece or
33:28
Speaker 3: pick up that newspaper, and then in about one thousand
33:32
Speaker 3: words tell you no. But there's a few cities that
33:35
Speaker 3: might be a little bit.
33:36
Speaker 2: Overvalued, right, Like, I will look at this part because
33:38
Speaker 2: it's kind of interesting. They basically analyze ubs analyzes the
33:43
Speaker 2: Global real Estate Bubble Index, which gosh, wish I could
33:47
Speaker 2: sit on like that committee, you know, and talk about that.
33:51
Speaker 2: More so, they looked at twenty one major international cities
33:55
Speaker 2: so again, this is not looking at where most people
33:59
Speaker 2: even live. It's basically just like the really expensive, crowded,
34:04
Speaker 2: you know, biggest cities out there, and it says, hey,
34:06
Speaker 2: here are the ones that are low risk Hong Kong,
34:09
Speaker 2: San Francisco, London, New York, Paris, Milan, and Sal Paulo. Okay,
34:14
Speaker 2: like there are some pretty big cities. If they're not
34:15
Speaker 2: going through something, then it doesn't seem that anything can happen.
34:20
Speaker 2: Moderate risk Toronto, Sydney, Australia, Madrid. Why do they have
34:25
Speaker 2: to say Sydney Australia. They don't give us a country
34:28
Speaker 2: for any of the other ones in here. What other
34:30
Speaker 2: Sydney is there?
34:32
Speaker 1: Uh?
34:32
Speaker 4: Yeah?
34:32
Speaker 3: Likewise, they do give a country for South Paulo, and
34:35
Speaker 3: I am not familiar with any other South Paulo.
34:37
Speaker 2: Oh you don't know about Sal Paulo, Georgia.
34:40
Speaker 4: Yeah, no, it doesn't seem like the one they were
34:42
Speaker 4: talking about.
34:42
Speaker 2: Madrid, Frankfurt, Vancouver, Munich, Singapore. Okay, fine, elevated risk LA
34:48
Speaker 2: do buy Amsterdam and Geneva and high risk Miami, Tokyo
34:51
Speaker 2: and Zurich. What does one do with this? Not buy
34:56
Speaker 2: the property? I was going to never buy in Zurich.
34:58
Speaker 3: Anyways, I'm not sure, and I also don't know how
35:02
Speaker 3: you write this. I understand why you exclude mainland Chinese cities.
35:07
Speaker 3: You're not going to get a whole lot of pricing
35:09
Speaker 3: data on what's going on in those Chinese cities, But
35:12
Speaker 3: how are you writing this article and not factoring in
35:16
Speaker 3: cities like Mumbai, Mexico City. Yeah, other hugely populous cities
35:25
Speaker 3: that aren't seemingly on this list for some reason.
35:29
Speaker 2: I'll give you a hint. It's because they're not wealthy.
35:34
Speaker 3: Now there are South Paulo. I mean South Paula is
35:37
Speaker 3: actually fairly wealthy. So maybe that's it.
35:38
Speaker 2: Maybe that's you know, it's like it's just like you
35:41
Speaker 2: look at what is present. I'm just looking at like
35:44
Speaker 2: how they are trying to measure this, and number one,
35:47
Speaker 2: they need to They're looking at cities where real estate
35:49
Speaker 2: prices are up by more than twenty five percent in
35:51
Speaker 2: the last five years. I'm guessing that excludes most of
35:53
Speaker 2: China to begin with, because China real estate has been
35:55
Speaker 2: garbage for a while. Now, okay, other ones. They are
36:01
Speaker 2: looking at cities that are big for investment. I'm guessing
36:07
Speaker 2: that Mexico City and Mumbai probably don't have a whole
36:11
Speaker 2: lot of investors pouring money into real estate there. I
36:16
Speaker 2: don't know, but like just a guess beyond that, it
36:20
Speaker 2: really feels kind of arbitrary, like they just looked at
36:22
Speaker 2: and they're like, well, these cities aren't rich enough, so
36:25
Speaker 2: we're not going to put them in.
36:27
Speaker 3: But like New York Times, if you're going to just
36:29
Speaker 3: choose a cherry picking article about specific cities and you
36:33
Speaker 3: write the title, are we in a real estate bubblin
36:35
Speaker 3: is about to crash? You could have done a better
36:37
Speaker 3: job cherry picking.
36:39
Speaker 2: It's true, Like you could have made it sound worse.
36:43
Speaker 3: Right, Like, just choose a bunch of cities in Louisiana, California, Texas,
36:48
Speaker 3: and Florida and you can paint an easy picture of
36:51
Speaker 3: why this real estate market is a bubblin's about to crash.
36:54
Speaker 4: Instead, they just yeah, this is a bad piece.
36:58
Speaker 2: Yeah it's not great.
37:02
Speaker 3: I don't want to thank you for calling it to
37:03
Speaker 3: our attention, Ben, because we like finding pieces that are
37:07
Speaker 3: next to useless and talking about them.
37:09
Speaker 2: Well, again, the good news is this obviously is going
37:12
Speaker 2: to make it into our festivus stock.
37:14
Speaker 4: Yeah, that's true.
37:15
Speaker 2: You know, it's it's a pretty good candidate when when
37:20
Speaker 2: you know, the whole assumption of the title is swiftly,
37:24
Speaker 2: you know, put down pretty quickly into the piece that
37:27
Speaker 2: it doesn't even exist to begin with. So that's kind
37:30
Speaker 2: of nice. Let's see, do we want to cover anything
37:33
Speaker 2: else on real estate? No, anything on refinancing. It happens sometimes, but.
37:40
Speaker 3: One interesting note, it's seemingly happening faster than in previous cycles.
37:46
Speaker 3: Maybe that's just because we got really super used to
37:48
Speaker 3: four percent interest rates, but seemingly people are refinancing out
37:53
Speaker 3: of their existing mortgages faster than they would have in
37:56
Speaker 3: previous cycles.
37:58
Speaker 2: Okay, so there's that.
37:59
Speaker 4: There you go.
38:00
Speaker 2: Let's take a quick break. We still got a second
38:02
Speaker 2: hour coming up in a little bit, so make sure
38:04
Speaker 2: you stick around as we wrap up the week.