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