December 2, 2025 • 39 mins
Mike Armstrong and Marc Fandetti break down how diversified the S&P 500 really is. OpenAI declares ‘Code Red’ as Google threatens AI lead. Washington must break its promise on Social Security. How sticky is US inflation? The end of the slop bowl era.
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Episode Transcript
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Speaker 1 (00:00):
The Financial Exchange is produced by Money Matters Radio and
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(00:20):
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(00:43):
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(01:06):
Armstrong and Mark Vandetti.
Speaker 2 (01:15):
Good morning, Welcome back to the Financial Exchange. Hope everybody's
having a nice snowy Tuesday out there, for those who
are north and west of the city of Boston and
staying safe and warm out there for our first first
major winter storm of the year. So good luck to
everybody this winter. We've got markets making a recovery from yesterday,
(01:37):
specifically crypto markets clawing back some of their gains from
the prior trading session.
Speaker 3 (01:43):
Well, there's not really a.
Speaker 2 (01:44):
Trading session for crypto, just kind of trades twenty four
hours a day, so that might not be relevant, but
equity markets clawing back as well. We had some stories
about the Federal Reserve upcoming meeting on December tenth and
the likelihood of a rate cut. Air also a fair
bit of just ajuda about crypto winter and whether or
(02:07):
not we are heading for another shakeout of amateur crypto
investors in that space. But I've been given a lot
of thought to concentration in the US stock market recently,
and mainly because I you know, my day job outside
of the Financial Exchange is to describe investment portfolios to
people and help them better understand what it is they're
(02:28):
doing currently and how it can be improved upon. And
when I describe to them, you know, their US stock exposure,
it's different than what I used to say, right like
ten years ago, it was, hey, this is this diversify.
If you're on the S and P five hundred, for example,
you owned this diversified thing where yeah, fifth of it
(02:49):
is tech exposure, but you know it's a bunch of
different industries, all of which are participating in profits.
Speaker 3 (02:55):
For the overall index.
Speaker 2 (02:58):
This year, about a third of the S and P
five hundreds gains are made up by alphabetan and video alone.
So important to frame all that that, Hey, when I
describe people to people like, hey, you know where did
your investment gains come from this year? Well, largely it
was from big tech companies. Furthermore, when I look at
the S and P five hundred today, nearly half of
(03:21):
it is comprised of the top ten companies in that index.
That's I think the most concentrated the index has ever been.
It's been around since what nineteen forty something, nineteen sixty something.
I know we muddled together data going back further than that,
But the S and P five and then.
Speaker 4 (03:36):
The invest the idea of an investable index fund dates
to like this seventies, but those will run as separate
accounts for banks, right, yeah, So in terms of investment on.
Speaker 2 (03:46):
The market index eighties nineties timeframe, maybe, yeah.
Speaker 4 (03:49):
When was the first, like in I should know this,
it was sometime in the eighties, but people had been
running S and P portfolios since A bunch of researchers
pointed out in the nineteen sixties that a market gap
weighted portfolio is efficient and that's all you really need.
Speaker 2 (04:03):
So I think the important thing for people to just
understand if let's say you're running your own money or
having somebody run it for you, and a major portion
of your exposure is the S and P five hundred, A,
you're a lot less diversified than you were a decade ago. B.
You're effectively making a bet on artificial intelligence right now.
(04:25):
Right Like, if you look at the majority of US
stock gains recently and the risks to that US DOC portfolio,
it is largely the exposure of what can artificial intelligence
do for these companies or on the other hand, what
can it detract from those companies' performance in the future.
And I think it's just I'm not saying that people
should be changing how they're doing it. But you know,
I keep hearing investment managers talk about diversification, and they're
(04:48):
kind of coming to this point where they're like, well,
crypto doesn't diversify as much as it used to. US
stocks are all one AI bet. I guess I can
go foreign and get some divers fied exposure, but if
I go to China, it's also an AI bet.
Speaker 3 (04:59):
And so so there's.
Speaker 2 (05:00):
Some acknowledgment here that Okay, Yeah, if you are investing
in stocks, especially US stocks, yeah, you're making a pretty
serious bet on that next dollar going into largely big
tech companies today.
Speaker 4 (05:14):
Yes, but if you're averaging in if you're a long
term investor with a horizon of I don't know, ten
years or more, that's a little arbitrary.
Speaker 5 (05:20):
But let's just purpose as of an example, say that.
Speaker 4 (05:24):
The complexion of the index could be as you pointed out,
it was different, it will be different, no, da I
suspect tech will not be a third of the index
as it is today in ten years, not because I
think I'm prescient or a profit, but because historically those
weights have been unstable as investors decide that companies in
different sectors for whatever reason, are worth more or less.
(05:47):
That's the beauty of a market cap weighted index. Funn
and I'll say again it comes out of theory theory
that everybody accepts who works in finance, and whether you
know it or not, if you're in finance, everything you.
Speaker 5 (05:59):
Do is based on this.
Speaker 4 (06:00):
As you start with a market cap weight that's a
fancy way of saying, you wait, companies in proportion to
the value of all their stock. You start with that portfolio,
and everybody can own a little slice of that. And
as it turns out under certain conditions and they're not
very stringent, that's an efficient way to invest. You start
with that. And again, this is the way all the
(06:21):
software and the portfolio construction models, whether you go to
Fidelity or Vanguard. I shouldn't start ticking off names because
I'm going to leave somebody off the list. But no
matter who you go to your local bank, they use
mot what's called modern portfolio theory, the name of the
whole body of thought that motivates this to start with,
and they start with a market cap weighted index. That's
why everybody's got to s and p five hundred or
(06:41):
Russell one thousand or Russell three thousand. You can market
cap waight just about any equity segment. That's why everybody
has that as the core of their portfolio.
Speaker 2 (06:51):
So the tag Alonge piece to this is one of
the clear beneficiaries and innovators in the artificial intelligence space.
Open ai, which is not publicly traded. You cannot go
invest in this in public indices. You can go invest
in companies that are somewhat related like Microsoft and Nvidia,
but to open ai is not investable in of itself.
It was also the first publicly available large language model
(07:14):
tool that was out there, with chat GPT CEO Sam
Altman declaring quote code read to improve chat GPT. This
is a follow on story to something we covered a
few weeks ago, which was Gemini owned by Google recently
released an updated version and came out to some pretty
big fanfare and people who are far more qualified to
test this stuff than I am did it ran a
(07:36):
bunch of tests and found it generally containing features and
usability that was a lot better or i shouldn't say
a lot better on the margins, better than what chat
GPT had most recently released and so Altman kind of
putting it out there as, Hey, this is a big
threat to our overall success. I'm going to start off
(07:56):
by saying that I have no means of measuring the
usability or accuracy of either of these tools. I'm relying
on outside experts to tell me which one is better.
What I am comfortable saying is that early indications seem
to be that every company that either creates artificial intelligence tools,
(08:18):
provides the energy or infrastructure for those companies to create
those tools, or uses any of those tools in their
businesses are being treated as winners from a stock perspective
Right now? Am I oversimplifying things there? That, with few exceptions,
most everyone who's playing in the AI space is being
treated from a stock perspective as though they are going
(08:38):
to win the AI race in some way.
Speaker 4 (08:40):
If you claim your company has something to do with AI,
it will attach some ridiculous multiple to your stock price,
is the way I would put it.
Speaker 3 (08:47):
What I think we are. Yeah, you just just.
Speaker 4 (08:50):
Claim you're doing AI. That's good for one hundred percent
pop in your share price, or at least that has
been and I true have passed.
Speaker 5 (08:55):
By the way.
Speaker 4 (08:56):
This is true of the electronics revolution of late sixties
and the Internet graze among them.
Speaker 2 (09:00):
And I feel very comfortable saying that not every company
is going to be a winner in this space.
Speaker 5 (09:03):
Very comfortable. They say that, yeah, they.
Speaker 3 (09:05):
Can't be, And so what does this look like to me?
Speaker 2 (09:08):
Well, it's another version of the deep Seek story from
January of this year, where some unknown Chinese startup came
out there and said, oh wow, we were able to
create a pre darn good large language model with a
fraction of the cost of what chat jpt is doing.
Google didn't do it for a fraction of the cost.
They did it for quite a bit of money. But
the idea that a technology that's three years old can
(09:31):
already be substantially leap frogged by those with deep enough pockets.
I think further is that overall truism that we know,
which is not every company is going to be a winner.
Speaker 4 (09:41):
This is why you can't trust anybody on TV who's
talking about this space.
Speaker 5 (09:45):
They don't.
Speaker 4 (09:45):
They're mostly carnival barkers. They're promoters, they have skin in
the game. They don't try to get it themselves. If
you did get this, if you were a coder and
you understood just generally speaking, how these models work, and
I don't claim to, by the way, what I do
is a little.
Speaker 5 (09:59):
Bit of a s learning.
Speaker 2 (10:00):
But oh that's how I started the segment was I
have no means of testing which one's better.
Speaker 5 (10:04):
Yeah, I can't.
Speaker 4 (10:04):
Yeah, So I assume that anyone who's talking about this
is trying to sell me something, and unless they are
coders themselves, they don't know what they're talking about, and
so whatever they're saying is unreliable hype propaganda designed to
get me to buy whatever it is they're selling. All
I know is that historically speaking, the first movers in
(10:26):
some domains, the first movers because of so called network effects,
they become the winner that takes all. Google is an example, sure,
but they weren't the first mover. They were an early mover.
Their browser eventually displaced others. And if Gemini becomes too successful,
they're gonna want to break Gemini off of Google's browser.
Google's browser has well like sixty seventy percent I don't
(10:46):
even know off the top of my head more percent
of the market. They can't allow the same company that
owns the browser to capture the AI market too. They're
going to be breaking Google. If Gemini gets too successful,
they're gonna want to break it. Some anti trust person
who wants to put a notch in herb or his
belt is going to want to break Google. A Gemini
off of the browser. It'll happen if it becomes too dominant.
(11:08):
But network effects suggest that it could be. It's very
easy for me to And by network effects, I mean
we all use the qwe r t y keyboard because
early on a few people adopted it. I don't want
to be on a different standard. We all use Microsoft Word,
which wasn't, by the way, compatible with Apple Word. Early on,
you had to translate your file. Once it became usable
(11:30):
on any operating system, everybody got on word. That's network effects.
Think of it as think of it as a snowball effect.
Speaker 3 (11:38):
And by the way, this only answers like you know.
Speaker 2 (11:40):
This begins to answer one of the questions, which is
how difficult it is to create a successful model. The
probably more important question is does any business know how
to take that model?
Speaker 5 (11:50):
Doesn't want to be the fastest.
Speaker 4 (11:52):
It has to be capable of exploiting those network effects.
Attach it to your browser. Make Gemini easy for me
to use. Oh, it can see the Google page I'm
looking at. Can you put that end of day market
data in a table for me?
Speaker 5 (12:03):
Gemini?
Speaker 4 (12:04):
And it does it. It's looking at the page. I'm
that's the type of combination that's going to give it
a lethal advantage potentially over something I have to toggle
away to. And it also happens to be a little
bit clunky. I refer obviously to open AI. Sure, maybe
anthropics having similar issues. I don't know these well enough.
All I know is is a user Gemini is really
convenient for my kind of mundane Can you do this
(12:26):
really simple task for me?
Speaker 5 (12:27):
Type uses?
Speaker 2 (12:28):
Say a quick break when we come back, we're playing
a little bit of trivia here. Next on the Financial Exchange.
Speaker 1 (12:35):
Here the Financial Exchange every day from eleven to now
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This segment of The Financial Exchange is powered by circle
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for trivia here and the Financial Exchange, And on this day.
In two thou one, Enron filed for Chapter eleven bankruptcy
(14:03):
in the Southern District of New York. CEO Kenneth Lay
was heavily involved in Enron's accounting scandal that unraveled in
two thousand and one. Lay was indicted by a grand
jury and was found guilty of ten counts of securities
fraud at trival trial. So our trivia question today, how
many years did Kenneth Lay spend in prison? Once again,
(14:25):
how many years do Kenneth Lay spend in prison? Be
the third person today to text us at six one
seven three six two thirteen eighty five with the correct
answer along with the keyword trivia, and you win a
Financial Exchange Show T shirt.
Speaker 5 (14:41):
Once again.
Speaker 7 (14:41):
The third correct response to Texas to the number six
one seven three six two thirteen eighty five with the
correct answer in the keyword trivia, We'll win that T shirt.
See complete contest rules at Financial Exchange Show dot com.
Speaker 2 (14:56):
The editorial board for Bloomberg wrote a piece yesterday that
Washington must break its promise on Social Security and here's
what they lay out. Basically, the Trust Fund, as we
all know, is going bust by twenty thirty four because
elected lawmakers have chosen to ignore the issue. Any of
the fixes that could have been implemented a decade ago
(15:17):
that would have been relatively minor and you know, slowly
paced in are no longer doable because we waited until
nearly the depletion of the funds to deal with the problem,
and so now if you go and fix it, it's
going to have to be more significant. They lay out,
you know, a number of different solutions, from raising the
full retirement age from the currently sixty seven to sixty
(15:39):
nine and then indexing it for life expectancy. They propose
changing the inflation assumptions when it comes to cola adjustments,
which most retirees already find inadequate because it doesn't fully
account for the rising cost of healthcare. They talk about
increasing taxes on Social Security in order to fund the
(16:00):
trust fund better. But the point they make is a
good one, which is the solutions to actually fist fix
the existing the existing program would have to be substantial
because we've waited so long. But I go back to
what I think is the more likely scenario. Washington's gonna
have to break their promise one way or another. Either
they're gonna have to break their promises on Social Security
(16:23):
and rewrite the program, likely some combination of raising taxes
plus cutting benefits, either for current recipients, future recipients, or both,
or they're just gonna have to break their promise. When
it comes to what I view as a key job
of every elected official, which is maintaining some degree of
(16:43):
economic stability for our country's finances and spend the money
out of deficits. And in my opinion, if you're looking
for the much more likely solution in terms of how
lawmakers deal with the trust fund issue, they write a check.
They don't ever come up up with taxes to fund it,
and there is no compromise, there is no.
Speaker 3 (17:03):
Solution to it.
Speaker 2 (17:04):
It's just, oh, we've got the money, let's just write
a blank check for funding Social Security, even though the
program's completely bankrupt.
Speaker 4 (17:11):
I guess this was inevitable with increasing life expectancy. We
all know that the program was designed and implemented nearly
one hundred years ago when life expectancy basically didn't extend
much beyond retirement. So it was meant to be truly
a safety net. That's changed, and our expectations of it have.
Speaker 2 (17:32):
Changed, as have demographics as society. And that's what I'm
getting healthier life expectancy changes, but birth rates changed too,
and so like none of the formula works anymore, and
it's going to get worse probably before it gets better.
Speaker 4 (17:44):
It's a little tedious to have to talk about the
things that could be done to fix it, because obviously there's.
Speaker 3 (17:49):
No nobody would be happy about any of them.
Speaker 4 (17:51):
And I got to say again, for what it's worth,
I've never seen such bad fiscal and monetary policy at
the same time in my life, nor have I ever
and I'm not the oldest person in the world, but
at fifty three, I'm not the youngest. I've never read
about such bad and don't tell me well Andrew Jackson
veto the Second Bank of the United States, and that's
I'm not talking about the eighteen thirties. I'm talking about
the modern era. Hohmever, go ahead, no no good.
Speaker 2 (18:13):
If you are evaluating decisions about your social security, it
is a pretty important time to do so because of
this looming concern. Twenty thirty four is right around the corner,
and I know a lot of people are making fear
based decisions when it comes to social security. I'm here
to tell you that even in the face of this,
you can't make your decision on social security out of fear.
(18:34):
It is a critical part of many retirees future. And
if you have questions about it, about the strategies for
claiming social security and how it will affect your future.
Call eight hundred three nine three for zero zero one.
That's the number for the Armstrong Advisory Group. You can
book your free call at Armstrong Advisory dot com or
eight hundred three nine three for zero zero one.
Speaker 1 (18:54):
The proceeding was paid for by Armstrong Advisory Group, a
registered investment advisor. Nothing in the ad or in any
Armstrong guide to specific financial, legal, or tax advice. Consult
your own financial, tax into state planning advisors before making
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Speaker 3 (19:10):
Do you think I'm wrong about that?
Speaker 2 (19:11):
By the way, I seem to have these blinders on
where I just refuse to believe that lawmakers are actually
going to solve the problem when it comes.
Speaker 5 (19:19):
To social that's what I was talking about.
Speaker 2 (19:21):
Or we're just going to spend a whole bunch of money, right,
We're just gonna blow out deficits.
Speaker 4 (19:24):
It's not our nature to do something about a problem
the magnitude of which is uncertain years in advance, whether
it's climate change or this. Democracies don't lend and I
would defend them, but they don't lend themselves to proactively
years in advance. When the consequences of not doing anything
are uncertain, they don't lend themselves to imposing sacrifices today,
(19:46):
when the reward is uncertain, they just if.
Speaker 3 (19:48):
Your job is to get reelected, you wait until twenty
thirty three.
Speaker 5 (19:51):
Much easier to do nothing.
Speaker 3 (19:54):
Quick break full market update next with Wall Street Watch.
Speaker 1 (20:10):
Bringing the latest financial news straight to your radio. Every day.
It's the Financial Exchange 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 7 (20:29):
Oll markets are now flattening after initially seeing a tech
rally in early trading.
Speaker 1 (20:34):
Traders are also.
Speaker 7 (20:35):
Monitoring Bitcoin after its recent pullback. Today, Bitcoin is rebounding
and trading right around ninety thousand dollars at the moment.
The Dow is up two tenths of a percent or
ninety five points. SMP five hundred is completely flat, NASDAC
up only a tenth of percent after seeing a nice
(20:57):
rally in early trading. RUSSA two thousand is a tenth
of percent as well. Tenure treasure field is flat at
four point zero nine two percent, and crude oil off
about a half a percent, trading just above fifty nine
dollars a barrel. According to sever reports, Comcast, Netflix, and
Paramount all submitted second offers for Warner Brothers Discovery assets,
(21:19):
while Paramount and Comcasts have made improved offers. Netflix reportedly
submitted a primarily cash based offer. Netflix shares it down
about one percent, while Warners Warner stock is up about
one percent. Meanwhile, Apple is shaking up its AI leadership,
where the IFL maker landed a Microsoft executive after announcing
the retirement of its top AI leader. Apple shares up modestly. Elsewhere,
(21:44):
developer data platform Mango dB is seeing its stock serge
twenty three percent after posting solid third quarter results. The
company also hiked its full year guidance in a push
against rivals Google and Nvidia. AWS or Amazon Web Services
announced the public launch of its Trainium three custom AI chip,
(22:05):
which it says is four times as fast as its
previous generation of AI chips at Amazon stock is edging
higher and Boeing stock is soaring nearly eight percent after
it's CFO said at a UBS conference this morning that
the company expects deliveries for both its seven thirty seven
jets in seven eighty seven jets to be up next year.
(22:28):
I'm Tucker Silva and that is Wall Street Watch. And
in the previous segment, we asked you the trivia question
how many years did Kenneth Lay spend in prison? That
would be none. Kenneth Lay died three months before his
scheduled sentencing. Jason from Kingston, New Hampshire's our winner today
taking home a Financial Exchange Show T shirt. Congrats to Jason.
(22:50):
We play trivia every day here in the Financial Exchange
See complete contest rules at Financial Exchange Show dot com.
Speaker 2 (22:57):
Just one more thing that I was running across when
it came to that AI story. I finished one of
the last segments with the fact that we still don't
really understand how these tools are going to be monetized
properly and who's going to actually pay for them all,
which is somewhat concerning. But Amazon rolling out to exclusively
to their AWS customers. So let's say you are a
(23:19):
business that stores your data in Amazon's cloud. What they
are offering is the ability for those business customers to
go in and customize a generative AI model. What does
that mean so that in the midst of training this thing,
you let's say I'm going to take this to our
industry for ease of you. Now, let's let's use a
different industry. Let's say you are a marketing agency that
(23:44):
works specifically with small banks I don't know, and you
write campaigns and design campaigns for them. This offering would
allow you to basically take all of your content that
you have written over the years and feed it right
into a model so that that model is more customized
and designed to help you build campaigns for those small
(24:07):
banks as opposed to just building it all right in chat,
GPT or another large language model. They're charging one hundred
thousand bucks a year for that ability.
Speaker 5 (24:16):
See how it goes?
Speaker 3 (24:17):
I don't know.
Speaker 2 (24:17):
I mean, you don't think think about the previous employers
you've worked for, and granted they've been a lot larger
than a small marketing agency.
Speaker 4 (24:24):
But actually I've worked for mostly small companies. Okay, so
I've only had three, so it's like a ton.
Speaker 2 (24:28):
So you know, imagine you are one of those companies
and you have a whole bunch of analyst reports and
models that you've built on all sorts of sorts of
different analytics. You don't think it'd be useful to feed
that into an AI model and you know, building around.
Speaker 4 (24:41):
Using it today to do mundane stuff like here's some data,
put this in a spreadsheet and do this other cleanup
stuff for me, stuff that might take me fifteen or
twenty minutes. The engine can obviously do a lot faster.
But when you ask it to explore relationships, plot date, chart,
data used, it has no judgment.
Speaker 5 (24:58):
It may someday.
Speaker 2 (25:00):
That's my question is maybe by training it on Well,
that's actual work that you've done.
Speaker 4 (25:04):
That All models are trained on stuff that people have already.
By the way, training just means fit a model to data.
We say training, We give it data, find a relationship.
That's training a model.
Speaker 5 (25:16):
This is this.
Speaker 4 (25:16):
Stuff's been going on for a long for as long
as computer computing power has been available. It's AI is
just a different layer of complaining.
Speaker 3 (25:23):
Guess my point would be at one hundred thousand bucks. Yeah,
that's a.
Speaker 5 (25:27):
Large spend, like how much you spend a night. That's
a question.
Speaker 2 (25:31):
Yeah, I mean to me, one hundred thousand bucks for
a pretty small business to throw at training its own
large language model does not seem.
Speaker 5 (25:38):
Like never gonna happen.
Speaker 4 (25:38):
Now, Well, what's your ad spend. Now, if it's two
hundred o K, then maybe this makes sense. But I
want to see the proofs in the shooting show me
that this isn't just some homogenized PAP that every other
little bank gets. It can have a hard time proving
value added. I mean, if I can have somebody come in,
do a little song and dance for me, present some
you know, present some ad stuff on an easel, the
(26:01):
old fac I know it's not mad men, but you
know I expect to be wooed for my one hundred K.
Speaker 2 (26:08):
Yeah, I agree, but but I don't.
Speaker 3 (26:14):
I would want that.
Speaker 2 (26:15):
But I think there are plenty of bustesses that know
nothing about AI who are feeling behind the eight ball
because they don't have the expertise nor the money to
spend on developing their own internal tool like Goldman Sachs does.
Who say WHOA six figures? And I can customize my
own AI model and Amazon's gonna help me do it.
I think there'll be plenty of customers to pick.
Speaker 4 (26:32):
Okay, maybe maybe the chief marketing officer needs something to
add to burnish their year end stuff so they get
the bonus they will want, and so they come in
and say, well, okay, my big idea is we pay
Amazon another hundred k a year to do this. Yeah,
Ceo says, I don't want to deal with that. Sure,
let's give it a try.
Speaker 3 (26:44):
Yeah, yeah, maybe yeah.
Speaker 7 (26:46):
Uh.
Speaker 2 (26:47):
Mark Financial Times asks how sticky is you in US inflation?
We're gonna get some sense of this on Friday, as
inflation figures for September get published, which, again, if you're
the Federal Reserve trying to make interest rate decisions in December,
I don't know how useful September data is other than
to tell you that directionally inflation usually it kind of
goes in the same direction. But how do we answer
(27:09):
the question of how sticky US inflation is? Because well, ultimately,
in twenty twenty two we were getting readings of nine
percent on its night, and we've come way down from there.
Speaker 4 (27:18):
I think when they say how sticky is it, they
mean how we introduced the concept of correlation and the
for we talked about it.
Speaker 5 (27:23):
We didn't introduce it. Sure, we talked about.
Speaker 4 (27:24):
Correlation in the first hour. The way you measure you
persistence is how correlated is something with its most recent observation,
then it's next most reason. Then it's next most recent
fancy term word of the day. If you want to
impress your boss. Is it auto correlated? Self correlated? Is
it serially correlated? Is another way analysts might say that
inflation is persistent, it's highly auto correlated. I don't that's
(27:45):
not what they mean here, though, I don't think so.
Why did I just go off on that tangent? I
don't really know what they mean. I think yet lost.
Speaker 5 (27:52):
How hard is it going to be?
Speaker 4 (27:53):
Yeah, I don't know where I am, but what I'm talking.
Speaker 3 (27:55):
About I just blacked out what I'm aging and I'm confused.
Speaker 4 (28:00):
I think what they mean is how hard is it
going to be to get inflation down? And all modern
macro whole economy models assume that prices are there's some rigidity,
some stickiness, if you will, in prices. That's why they're
that's why monetary policy works. It's also why inflation is
(28:21):
uh is difficult to get down. So the short answer
to this is, well, prices are rigid, prices are sticky
on average, That's why you get inflation in everything. When
oil why the average rate of inflation goes up when
oil prices jumped, Because you might ask, well, if oil
prices or tariffs are only going up on certain things,
why don't they go down elsewhere? The modern macro answer
(28:43):
to that is, and I'll just be technical, say nominal rigidities.
Speaker 2 (28:47):
And to humanize this a little bit, and not that labor,
not that labor is the only piece of this. But
if your boss came to you and said, hey, you know,
prices have been moderating a little bit, so I need
to take your salary from ninety thousand to eighty eight
thousand dollars, you're not going to say, yes.
Speaker 5 (29:04):
Yeah, wages are rigid to wages.
Speaker 3 (29:06):
Are extremely rigid.
Speaker 2 (29:07):
That is a big portion of what contributes to overall
price levels. And nominally, yes, and so yeah, the idea
that prices they have the pace that there increases have
calmed down quite a bit. But the idea that it's
going to be some easy feat to get inflation from
three percent down to two percent is a big question
(29:31):
mark in my mind. And at this stage I'm not
entirely sure that it is an actual goal of those
who are going to lead the FED.
Speaker 4 (29:38):
We were getting there, but the Fed, the FED is
chickening out essentially, And I'm not saying I wouldn't do
the same thing, by the way, because it's well known
that I'm a coward. The Fed does not. Everybody's just nodding.
Speaker 5 (29:49):
Everybody in the office is yep, his whole family.
Speaker 4 (29:52):
He shaped me, he turns tail. The Fed stopped trying
to get inflation down. It's turned to fighting weakness in
the labor market. Because getting inflation to two percent would
require reducing demand. The Fed is doing the opposite right
now by easing monetary policy. It's goosing demand. To get
(30:13):
inflation down to two would require probably a recession, which,
by the way, is what everybody said in twenty twenty two.
We all acclaimed the immaculate disinflation, but we never really
got to two percent because getting finishing that last mile,
or whatever analogy you want to use, would have been
economically painful. Now it's too late.
Speaker 2 (30:33):
Let's take a quick break. As we head towards the
noon hour. Here, markets are wavering a little bit.
Speaker 3 (30:39):
We've got the S.
Speaker 2 (30:40):
Andp up now only a little bit more than a
tenth of a percent. We'll recap it for you and
play some stack roulette here.
Speaker 5 (30:45):
Next.
Speaker 1 (30:47):
Find daily interviews and full shows of the Financial Exchange
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(31:09):
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Speaker 7 (31:28):
This segment of The Financial Exchange is brought to you
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Speaker 3 (31:41):
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Speaker 2 (32:13):
There it is, Ah Tucker. Are you fed up with
spot me talking slop bowls?
Speaker 3 (32:23):
Also?
Speaker 2 (32:23):
When did we start calling Chipotle bowls slop bowls? Because
that seems.
Speaker 7 (32:28):
Chipotle That term come out maybe six months ago. Is
the first time we put it on.
Speaker 2 (32:34):
They never heard of a garbage plate. No, it's an
upstate New York thing when I was in college. Basically
just French fries, ground beef, cheese, like, basically whatever they
could find they're just toss into a garbage plate.
Speaker 3 (32:46):
And to answer her, that's a slop plate.
Speaker 2 (32:49):
I don't think that a Cova Mediterranean bowl is a
slop bowl. I think I think we're doing that that
branded disservice.
Speaker 7 (32:57):
I mean to answer your question, am I toired of
the said slop bowl? I would say no, because I
think it's the most customizable lunch out there. And I
still don't understand why I'm continuing to see these headlines
of diners pulling back because they're over the slop bowls.
I think it's more of a money thing than anything.
Speaker 2 (33:17):
Tucker, you're old man. You're not the target demo anymore. Right,
sixteen year olds here, I mean don't want slop bowls anymore.
Speaker 7 (33:24):
So what are they going to back to?
Speaker 2 (33:25):
Well again, I think if he stopped calling them slop bowls,
I think it would do a lot for the brand image.
Speaker 3 (33:33):
To me.
Speaker 2 (33:33):
I like you said, I think that this is a
cost issue. If I go to Chipotle, it's going to
be sixteen bucks. If I go to Cava, that new
Mediterranean startup chain. Yeah, you're talking, it's all in the
same about the same, yea. So maybe McDonald's needs to
put together a slop bowl and prove them all wrong.
Just a disgusting bowl field.
Speaker 7 (33:51):
I mean they've done the salad.
Speaker 2 (33:52):
Fried chicken chunks, you know, French fries, and whatever else
they've got, you know, big Max sauce.
Speaker 3 (33:59):
I think that I would work for them.
Speaker 4 (34:01):
Well, big Mac is a slop bowl between two slice.
Speaker 3 (34:04):
It's a sandwich.
Speaker 5 (34:05):
Mark, I love McDonald's.
Speaker 3 (34:06):
It's a sandwich. Yeah.
Speaker 2 (34:08):
So apparently some of these brands pulling back on some
of that stuff and focusing more on there. I mean,
you know, Chipotle was made famous by burritos. I think
that's largely what they still sell. But those those brands
that are focusing on just salad, you know, not just
sout what's the what's the sweet greens and others are
having a tough time attracting.
Speaker 3 (34:28):
Again. I go back to.
Speaker 2 (34:30):
These are all sixteen to twenty dollars lunches, and I
think people are just feeling like they should pinch some
pennies at this stage because they don't have enough money
to do a four to twenty dollars lunches.
Speaker 7 (34:41):
If I'm Chipotle, I'm coming out with like eight ninety
nine burrito, like a smaller one man that's available now.
Speaker 2 (34:50):
Yeah, I guess if you can be popular, if you
can do it without worsening your ingredients, then maybe that works.
But it's just a smaller brand nine dollars burrito. You're
gonna have to only after like ground beef.
Speaker 7 (35:01):
Just have a smaller, tour less yeah, and basic ingredients.
Speaker 5 (35:07):
That's a terrible idea.
Speaker 7 (35:08):
It's not a terrible idea, Michael. It's a great idea,
and they should do it.
Speaker 3 (35:12):
What do you got for us? Mark?
Speaker 4 (35:14):
Bringing things back to finance, I like talking about earlier
on not this close to lunch, though very distracting. Earlier on,
we were talking about the S and P as being
composed of of sectors information technology, financials.
Speaker 5 (35:29):
There are eleven of them.
Speaker 4 (35:31):
Information technology is the biggest, Like we said, thirty five
percent of the S and P. So if every dollar ahead, Mike.
Speaker 2 (35:37):
I just wanted to mention a confusing part of this.
The technology sector is comprised of a bunch of those
big names. Other sectors, though, are also comprised of what
we would consider to be big tech companies. The communication
services sector, for instance, is a big one, and you'd think, oh,
communication service, we're talking about AT and T. Well, yeah,
but we're mainly talking about alphabet We're mainly talking about
(35:59):
meta I think in the communications services sector, even though
largely we talk about them as though they're teching.
Speaker 4 (36:03):
But you made the point that when you put a
dollar in the S and P, thirty five cents is
going into more narrowly defined tech companies, and in turn,
twenty percent of every dollar currently this changes every day,
goes into Nvidia fifteen percent of every so six percent
of your nearly six percent.
Speaker 3 (36:22):
Twenty percent of the tech okay, twenty percent.
Speaker 4 (36:24):
Of techs on multiplying fractions here or proportions point two
times point three five, blah blah blah. That's how I
get to that number. And Nvidia, I'm rounding up.
Speaker 5 (36:34):
A little bit.
Speaker 4 (36:35):
Your point was, well, it's it's never been more dominated
by one sector and that sector has never been as
large as it is today.
Speaker 5 (36:44):
Did I get something wrong? You know you do? Okay, good? Good.
Speaker 4 (36:48):
My point is, on a daylight today, you're glad that
I'm not saying you shouldn't consider something other than a
market cap weighted index. That's a personal decision. I am
saying that the whole investment for fashion starts with market
cap weighted and then makes bets relative to that. But
on a daylight today, infotech is, with the exception of
one other sector, industrials, infotech is the only sector in
(37:11):
the green. So as distended as that part of the
S and P may seem, there are times plenty of times,
like the year to date period, for example, when it
can pull the whole index along. And why if your
objective is just to match the market, not necessarily to
beat it, so you don't consider yourself to be a
savvy active manager, for example, why it can be dangerous
(37:33):
to tilt away from market cap weights.
Speaker 2 (37:35):
Yeah, it most certainly can. I when I was trying
to pull up here, I'm going to see if I
can find it. Yeah, here we've I don't have the percentages, though,
what is it?
Speaker 3 (37:43):
What are you looking on that I was looking up?
Speaker 2 (37:45):
What are the what is the composition of the s
and P five hundred? So to your point, if I
invest a dollar, I believe something like not. No, I
want the company weights because I think if I invest
a dollars, something like nine cents is going into a video,
eight cents into Apple, and another seven into Microsoft or
something along those lines.
Speaker 3 (38:06):
And so yeah, you take a look at that.
Speaker 2 (38:08):
And so the top ten in Vidia, Apple, Microsoft, Amazon, Broadcom, Alphabet, Meta, Tesla, Berkshire.
I believe those ten are making up nearly fifty percent.
And you've got it. So between the top three, what
do we have.
Speaker 4 (38:22):
Having seven six is twenty three three three? Called that
thirty ten now doesn't quite get you. They're more like
thirty five.
Speaker 2 (38:30):
Yeah, but quite swesome. As we close out the show,
markets are still holding on too gains here, SMP up
one fifth of a percent, NASDAK up a half percent,
Dow Jones Industrial average up about a third of a percent.
We'll be back at it tomorrow. Folks, Stay tuned and
have a great rest of your day.
The Financial Exchange is produced by Money Matters Radio and
is hosted by employees of the Armstrong Advisory Group, a
registered investment advisor. All opinions expressed are solely those of
the hosts. Do not reflect the opinions of Armstrong Advisory
or anyone else. Investments can lose money. This program does
not offer any specific financial or investment advice. Please consult
your own financial, tax, and estate planning advisors before making
(00:20):
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this program do not endorse each other or their services.
Armstrong and Money Matters Radio do not compensate each other
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Exchange with Mike Armstrong and Mark Vandetti. Your exclusive look
at business and financial news affecting your day, your city,
(00:43):
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heroes by visiting dav five K dot Boston and making
a donation today. Face is the Financial Exchange with Mike
(01:06):
Armstrong and Mark Vandetti.
Speaker 2 (01:15):
Good morning, Welcome back to the Financial Exchange. Hope everybody's
having a nice snowy Tuesday out there, for those who
are north and west of the city of Boston and
staying safe and warm out there for our first first
major winter storm of the year. So good luck to
everybody this winter. We've got markets making a recovery from yesterday,
(01:37):
specifically crypto markets clawing back some of their gains from
the prior trading session.
Speaker 3 (01:43):
Well, there's not really a.
Speaker 2 (01:44):
Trading session for crypto, just kind of trades twenty four
hours a day, so that might not be relevant, but
equity markets clawing back as well. We had some stories
about the Federal Reserve upcoming meeting on December tenth and
the likelihood of a rate cut. Air also a fair
bit of just ajuda about crypto winter and whether or
(02:07):
not we are heading for another shakeout of amateur crypto
investors in that space. But I've been given a lot
of thought to concentration in the US stock market recently,
and mainly because I you know, my day job outside
of the Financial Exchange is to describe investment portfolios to
people and help them better understand what it is they're
(02:28):
doing currently and how it can be improved upon. And
when I describe to them, you know, their US stock exposure,
it's different than what I used to say, right like
ten years ago, it was, hey, this is this diversify.
If you're on the S and P five hundred, for example,
you owned this diversified thing where yeah, fifth of it
(02:49):
is tech exposure, but you know it's a bunch of
different industries, all of which are participating in profits.
Speaker 3 (02:55):
For the overall index.
Speaker 2 (02:58):
This year, about a third of the S and P
five hundreds gains are made up by alphabetan and video alone.
So important to frame all that that, Hey, when I
describe people to people like, hey, you know where did
your investment gains come from this year? Well, largely it
was from big tech companies. Furthermore, when I look at
the S and P five hundred today, nearly half of
(03:21):
it is comprised of the top ten companies in that index.
That's I think the most concentrated the index has ever been.
It's been around since what nineteen forty something, nineteen sixty something.
I know we muddled together data going back further than that,
But the S and P five and then.
Speaker 4 (03:36):
The invest the idea of an investable index fund dates
to like this seventies, but those will run as separate
accounts for banks, right, yeah, So in terms of investment on.
Speaker 2 (03:46):
The market index eighties nineties timeframe, maybe, yeah.
Speaker 4 (03:49):
When was the first, like in I should know this,
it was sometime in the eighties, but people had been
running S and P portfolios since A bunch of researchers
pointed out in the nineteen sixties that a market gap
weighted portfolio is efficient and that's all you really need.
Speaker 2 (04:03):
So I think the important thing for people to just
understand if let's say you're running your own money or
having somebody run it for you, and a major portion
of your exposure is the S and P five hundred, A,
you're a lot less diversified than you were a decade ago. B.
You're effectively making a bet on artificial intelligence right now.
(04:25):
Right Like, if you look at the majority of US
stock gains recently and the risks to that US DOC portfolio,
it is largely the exposure of what can artificial intelligence
do for these companies or on the other hand, what
can it detract from those companies' performance in the future.
And I think it's just I'm not saying that people
should be changing how they're doing it. But you know,
I keep hearing investment managers talk about diversification, and they're
(04:48):
kind of coming to this point where they're like, well,
crypto doesn't diversify as much as it used to. US
stocks are all one AI bet. I guess I can
go foreign and get some divers fied exposure, but if
I go to China, it's also an AI bet.
Speaker 3 (04:59):
And so so there's.
Speaker 2 (05:00):
Some acknowledgment here that Okay, Yeah, if you are investing
in stocks, especially US stocks, yeah, you're making a pretty
serious bet on that next dollar going into largely big
tech companies today.
Speaker 4 (05:14):
Yes, but if you're averaging in if you're a long
term investor with a horizon of I don't know, ten
years or more, that's a little arbitrary.
Speaker 5 (05:20):
But let's just purpose as of an example, say that.
Speaker 4 (05:24):
The complexion of the index could be as you pointed out,
it was different, it will be different, no, da I
suspect tech will not be a third of the index
as it is today in ten years, not because I
think I'm prescient or a profit, but because historically those
weights have been unstable as investors decide that companies in
different sectors for whatever reason, are worth more or less.
(05:47):
That's the beauty of a market cap weighted index. Funn
and I'll say again it comes out of theory theory
that everybody accepts who works in finance, and whether you
know it or not, if you're in finance, everything you.
Speaker 5 (05:59):
Do is based on this.
Speaker 4 (06:00):
As you start with a market cap weight that's a
fancy way of saying, you wait, companies in proportion to
the value of all their stock. You start with that portfolio,
and everybody can own a little slice of that. And
as it turns out under certain conditions and they're not
very stringent, that's an efficient way to invest. You start
with that. And again, this is the way all the
(06:21):
software and the portfolio construction models, whether you go to
Fidelity or Vanguard. I shouldn't start ticking off names because
I'm going to leave somebody off the list. But no
matter who you go to your local bank, they use
mot what's called modern portfolio theory, the name of the
whole body of thought that motivates this to start with,
and they start with a market cap weighted index. That's
why everybody's got to s and p five hundred or
(06:41):
Russell one thousand or Russell three thousand. You can market
cap waight just about any equity segment. That's why everybody
has that as the core of their portfolio.
Speaker 2 (06:51):
So the tag Alonge piece to this is one of
the clear beneficiaries and innovators in the artificial intelligence space.
Open ai, which is not publicly traded. You cannot go
invest in this in public indices. You can go invest
in companies that are somewhat related like Microsoft and Nvidia,
but to open ai is not investable in of itself.
It was also the first publicly available large language model
(07:14):
tool that was out there, with chat GPT CEO Sam
Altman declaring quote code read to improve chat GPT. This
is a follow on story to something we covered a
few weeks ago, which was Gemini owned by Google recently
released an updated version and came out to some pretty
big fanfare and people who are far more qualified to
test this stuff than I am did it ran a
(07:36):
bunch of tests and found it generally containing features and
usability that was a lot better or i shouldn't say
a lot better on the margins, better than what chat
GPT had most recently released and so Altman kind of
putting it out there as, Hey, this is a big
threat to our overall success. I'm going to start off
(07:56):
by saying that I have no means of measuring the
usability or accuracy of either of these tools. I'm relying
on outside experts to tell me which one is better.
What I am comfortable saying is that early indications seem
to be that every company that either creates artificial intelligence tools,
(08:18):
provides the energy or infrastructure for those companies to create
those tools, or uses any of those tools in their
businesses are being treated as winners from a stock perspective
Right now? Am I oversimplifying things there? That, with few exceptions,
most everyone who's playing in the AI space is being
treated from a stock perspective as though they are going
(08:38):
to win the AI race in some way.
Speaker 4 (08:40):
If you claim your company has something to do with AI,
it will attach some ridiculous multiple to your stock price,
is the way I would put it.
Speaker 3 (08:47):
What I think we are. Yeah, you just just.
Speaker 4 (08:50):
Claim you're doing AI. That's good for one hundred percent
pop in your share price, or at least that has
been and I true have passed.
Speaker 5 (08:55):
By the way.
Speaker 4 (08:56):
This is true of the electronics revolution of late sixties
and the Internet graze among them.
Speaker 2 (09:00):
And I feel very comfortable saying that not every company
is going to be a winner in this space.
Speaker 5 (09:03):
Very comfortable. They say that, yeah, they.
Speaker 3 (09:05):
Can't be, And so what does this look like to me?
Speaker 2 (09:08):
Well, it's another version of the deep Seek story from
January of this year, where some unknown Chinese startup came
out there and said, oh wow, we were able to
create a pre darn good large language model with a
fraction of the cost of what chat jpt is doing.
Google didn't do it for a fraction of the cost.
They did it for quite a bit of money. But
the idea that a technology that's three years old can
(09:31):
already be substantially leap frogged by those with deep enough pockets.
I think further is that overall truism that we know,
which is not every company is going to be a winner.
Speaker 4 (09:41):
This is why you can't trust anybody on TV who's
talking about this space.
Speaker 5 (09:45):
They don't.
Speaker 4 (09:45):
They're mostly carnival barkers. They're promoters, they have skin in
the game. They don't try to get it themselves. If
you did get this, if you were a coder and
you understood just generally speaking, how these models work, and
I don't claim to, by the way, what I do
is a little.
Speaker 5 (09:59):
Bit of a s learning.
Speaker 2 (10:00):
But oh that's how I started the segment was I
have no means of testing which one's better.
Speaker 5 (10:04):
Yeah, I can't.
Speaker 4 (10:04):
Yeah, So I assume that anyone who's talking about this
is trying to sell me something, and unless they are
coders themselves, they don't know what they're talking about, and
so whatever they're saying is unreliable hype propaganda designed to
get me to buy whatever it is they're selling. All
I know is that historically speaking, the first movers in
(10:26):
some domains, the first movers because of so called network effects,
they become the winner that takes all. Google is an example, sure,
but they weren't the first mover. They were an early mover.
Their browser eventually displaced others. And if Gemini becomes too successful,
they're gonna want to break Gemini off of Google's browser.
Google's browser has well like sixty seventy percent I don't
(10:46):
even know off the top of my head more percent
of the market. They can't allow the same company that
owns the browser to capture the AI market too. They're
going to be breaking Google. If Gemini gets too successful,
they're gonna want to break it. Some anti trust person
who wants to put a notch in herb or his
belt is going to want to break Google. A Gemini
off of the browser. It'll happen if it becomes too dominant.
(11:08):
But network effects suggest that it could be. It's very
easy for me to And by network effects, I mean
we all use the qwe r t y keyboard because
early on a few people adopted it. I don't want
to be on a different standard. We all use Microsoft Word,
which wasn't, by the way, compatible with Apple Word. Early on,
you had to translate your file. Once it became usable
(11:30):
on any operating system, everybody got on word. That's network effects.
Think of it as think of it as a snowball effect.
Speaker 3 (11:38):
And by the way, this only answers like you know.
Speaker 2 (11:40):
This begins to answer one of the questions, which is
how difficult it is to create a successful model. The
probably more important question is does any business know how
to take that model?
Speaker 5 (11:50):
Doesn't want to be the fastest.
Speaker 4 (11:52):
It has to be capable of exploiting those network effects.
Attach it to your browser. Make Gemini easy for me
to use. Oh, it can see the Google page I'm
looking at. Can you put that end of day market
data in a table for me?
Speaker 5 (12:03):
Gemini?
Speaker 4 (12:04):
And it does it. It's looking at the page. I'm
that's the type of combination that's going to give it
a lethal advantage potentially over something I have to toggle
away to. And it also happens to be a little
bit clunky. I refer obviously to open AI. Sure, maybe
anthropics having similar issues. I don't know these well enough.
All I know is is a user Gemini is really
convenient for my kind of mundane Can you do this
(12:26):
really simple task for me?
Speaker 5 (12:27):
Type uses?
Speaker 2 (12:28):
Say a quick break when we come back, we're playing
a little bit of trivia here. Next on the Financial Exchange.
Speaker 1 (12:35):
Here the Financial Exchange every day from eleven to now
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This segment of The Financial Exchange is powered by circle
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for trivia here and the Financial Exchange, And on this day.
In two thou one, Enron filed for Chapter eleven bankruptcy
(14:03):
in the Southern District of New York. CEO Kenneth Lay
was heavily involved in Enron's accounting scandal that unraveled in
two thousand and one. Lay was indicted by a grand
jury and was found guilty of ten counts of securities
fraud at trival trial. So our trivia question today, how
many years did Kenneth Lay spend in prison? Once again,
(14:25):
how many years do Kenneth Lay spend in prison? Be
the third person today to text us at six one
seven three six two thirteen eighty five with the correct
answer along with the keyword trivia, and you win a
Financial Exchange Show T shirt.
Speaker 5 (14:41):
Once again.
Speaker 7 (14:41):
The third correct response to Texas to the number six
one seven three six two thirteen eighty five with the
correct answer in the keyword trivia, We'll win that T shirt.
See complete contest rules at Financial Exchange Show dot com.
Speaker 2 (14:56):
The editorial board for Bloomberg wrote a piece yesterday that
Washington must break its promise on Social Security and here's
what they lay out. Basically, the Trust Fund, as we
all know, is going bust by twenty thirty four because
elected lawmakers have chosen to ignore the issue. Any of
the fixes that could have been implemented a decade ago
(15:17):
that would have been relatively minor and you know, slowly
paced in are no longer doable because we waited until
nearly the depletion of the funds to deal with the problem,
and so now if you go and fix it, it's
going to have to be more significant. They lay out,
you know, a number of different solutions, from raising the
full retirement age from the currently sixty seven to sixty
(15:39):
nine and then indexing it for life expectancy. They propose
changing the inflation assumptions when it comes to cola adjustments,
which most retirees already find inadequate because it doesn't fully
account for the rising cost of healthcare. They talk about
increasing taxes on Social Security in order to fund the
(16:00):
trust fund better. But the point they make is a
good one, which is the solutions to actually fist fix
the existing the existing program would have to be substantial
because we've waited so long. But I go back to
what I think is the more likely scenario. Washington's gonna
have to break their promise one way or another. Either
they're gonna have to break their promises on Social Security
(16:23):
and rewrite the program, likely some combination of raising taxes
plus cutting benefits, either for current recipients, future recipients, or both,
or they're just gonna have to break their promise. When
it comes to what I view as a key job
of every elected official, which is maintaining some degree of
(16:43):
economic stability for our country's finances and spend the money
out of deficits. And in my opinion, if you're looking
for the much more likely solution in terms of how
lawmakers deal with the trust fund issue, they write a check.
They don't ever come up up with taxes to fund it,
and there is no compromise, there is no.
Speaker 3 (17:03):
Solution to it.
Speaker 2 (17:04):
It's just, oh, we've got the money, let's just write
a blank check for funding Social Security, even though the
program's completely bankrupt.
Speaker 4 (17:11):
I guess this was inevitable with increasing life expectancy. We
all know that the program was designed and implemented nearly
one hundred years ago when life expectancy basically didn't extend
much beyond retirement. So it was meant to be truly
a safety net. That's changed, and our expectations of it have.
Speaker 2 (17:32):
Changed, as have demographics as society. And that's what I'm
getting healthier life expectancy changes, but birth rates changed too,
and so like none of the formula works anymore, and
it's going to get worse probably before it gets better.
Speaker 4 (17:44):
It's a little tedious to have to talk about the
things that could be done to fix it, because obviously there's.
Speaker 3 (17:49):
No nobody would be happy about any of them.
Speaker 4 (17:51):
And I got to say again, for what it's worth,
I've never seen such bad fiscal and monetary policy at
the same time in my life, nor have I ever
and I'm not the oldest person in the world, but
at fifty three, I'm not the youngest. I've never read
about such bad and don't tell me well Andrew Jackson
veto the Second Bank of the United States, and that's
I'm not talking about the eighteen thirties. I'm talking about
the modern era. Hohmever, go ahead, no no good.
Speaker 2 (18:13):
If you are evaluating decisions about your social security, it
is a pretty important time to do so because of
this looming concern. Twenty thirty four is right around the corner,
and I know a lot of people are making fear
based decisions when it comes to social security. I'm here
to tell you that even in the face of this,
you can't make your decision on social security out of fear.
(18:34):
It is a critical part of many retirees future. And
if you have questions about it, about the strategies for
claiming social security and how it will affect your future.
Call eight hundred three nine three for zero zero one.
That's the number for the Armstrong Advisory Group. You can
book your free call at Armstrong Advisory dot com or
eight hundred three nine three for zero zero one.
Speaker 1 (18:54):
The proceeding was paid for by Armstrong Advisory Group, a
registered investment advisor. Nothing in the ad or in any
Armstrong guide to specific financial, legal, or tax advice. Consult
your own financial, tax into state planning advisors before making
any investment decisions. Armstrong may contact you to offer investment
advisory services.
Speaker 3 (19:10):
Do you think I'm wrong about that?
Speaker 2 (19:11):
By the way, I seem to have these blinders on
where I just refuse to believe that lawmakers are actually
going to solve the problem when it comes.
Speaker 5 (19:19):
To social that's what I was talking about.
Speaker 2 (19:21):
Or we're just going to spend a whole bunch of money, right,
We're just gonna blow out deficits.
Speaker 4 (19:24):
It's not our nature to do something about a problem
the magnitude of which is uncertain years in advance, whether
it's climate change or this. Democracies don't lend and I
would defend them, but they don't lend themselves to proactively
years in advance. When the consequences of not doing anything
are uncertain, they don't lend themselves to imposing sacrifices today,
(19:46):
when the reward is uncertain, they just if.
Speaker 3 (19:48):
Your job is to get reelected, you wait until twenty
thirty three.
Speaker 5 (19:51):
Much easier to do nothing.
Speaker 3 (19:54):
Quick break full market update next with Wall Street Watch.
Speaker 1 (20:10):
Bringing the latest financial news straight to your radio. Every day.
It's the Financial Exchange 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 7 (20:29):
Oll markets are now flattening after initially seeing a tech
rally in early trading.
Speaker 1 (20:34):
Traders are also.
Speaker 7 (20:35):
Monitoring Bitcoin after its recent pullback. Today, Bitcoin is rebounding
and trading right around ninety thousand dollars at the moment.
The Dow is up two tenths of a percent or
ninety five points. SMP five hundred is completely flat, NASDAC
up only a tenth of percent after seeing a nice
(20:57):
rally in early trading. RUSSA two thousand is a tenth
of percent as well. Tenure treasure field is flat at
four point zero nine two percent, and crude oil off
about a half a percent, trading just above fifty nine
dollars a barrel. According to sever reports, Comcast, Netflix, and
Paramount all submitted second offers for Warner Brothers Discovery assets,
(21:19):
while Paramount and Comcasts have made improved offers. Netflix reportedly
submitted a primarily cash based offer. Netflix shares it down
about one percent, while Warners Warner stock is up about
one percent. Meanwhile, Apple is shaking up its AI leadership,
where the IFL maker landed a Microsoft executive after announcing
the retirement of its top AI leader. Apple shares up modestly. Elsewhere,
(21:44):
developer data platform Mango dB is seeing its stock serge
twenty three percent after posting solid third quarter results. The
company also hiked its full year guidance in a push
against rivals Google and Nvidia. AWS or Amazon Web Services
announced the public launch of its Trainium three custom AI chip,
(22:05):
which it says is four times as fast as its
previous generation of AI chips at Amazon stock is edging
higher and Boeing stock is soaring nearly eight percent after
it's CFO said at a UBS conference this morning that
the company expects deliveries for both its seven thirty seven
jets in seven eighty seven jets to be up next year.
(22:28):
I'm Tucker Silva and that is Wall Street Watch. And
in the previous segment, we asked you the trivia question
how many years did Kenneth Lay spend in prison? That
would be none. Kenneth Lay died three months before his
scheduled sentencing. Jason from Kingston, New Hampshire's our winner today
taking home a Financial Exchange Show T shirt. Congrats to Jason.
(22:50):
We play trivia every day here in the Financial Exchange
See complete contest rules at Financial Exchange Show dot com.
Speaker 2 (22:57):
Just one more thing that I was running across when
it came to that AI story. I finished one of
the last segments with the fact that we still don't
really understand how these tools are going to be monetized
properly and who's going to actually pay for them all,
which is somewhat concerning. But Amazon rolling out to exclusively
to their AWS customers. So let's say you are a
(23:19):
business that stores your data in Amazon's cloud. What they
are offering is the ability for those business customers to
go in and customize a generative AI model. What does
that mean so that in the midst of training this thing,
you let's say I'm going to take this to our
industry for ease of you. Now, let's let's use a
different industry. Let's say you are a marketing agency that
(23:44):
works specifically with small banks I don't know, and you
write campaigns and design campaigns for them. This offering would
allow you to basically take all of your content that
you have written over the years and feed it right
into a model so that that model is more customized
and designed to help you build campaigns for those small
(24:07):
banks as opposed to just building it all right in chat,
GPT or another large language model. They're charging one hundred
thousand bucks a year for that ability.
Speaker 5 (24:16):
See how it goes?
Speaker 3 (24:17):
I don't know.
Speaker 2 (24:17):
I mean, you don't think think about the previous employers
you've worked for, and granted they've been a lot larger
than a small marketing agency.
Speaker 4 (24:24):
But actually I've worked for mostly small companies. Okay, so
I've only had three, so it's like a ton.
Speaker 2 (24:28):
So you know, imagine you are one of those companies
and you have a whole bunch of analyst reports and
models that you've built on all sorts of sorts of
different analytics. You don't think it'd be useful to feed
that into an AI model and you know, building around.
Speaker 4 (24:41):
Using it today to do mundane stuff like here's some data,
put this in a spreadsheet and do this other cleanup
stuff for me, stuff that might take me fifteen or
twenty minutes. The engine can obviously do a lot faster.
But when you ask it to explore relationships, plot date, chart,
data used, it has no judgment.
Speaker 5 (24:58):
It may someday.
Speaker 2 (25:00):
That's my question is maybe by training it on Well,
that's actual work that you've done.
Speaker 4 (25:04):
That All models are trained on stuff that people have already.
By the way, training just means fit a model to data.
We say training, We give it data, find a relationship.
That's training a model.
Speaker 5 (25:16):
This is this.
Speaker 4 (25:16):
Stuff's been going on for a long for as long
as computer computing power has been available. It's AI is
just a different layer of complaining.
Speaker 3 (25:23):
Guess my point would be at one hundred thousand bucks. Yeah,
that's a.
Speaker 5 (25:27):
Large spend, like how much you spend a night. That's
a question.
Speaker 2 (25:31):
Yeah, I mean to me, one hundred thousand bucks for
a pretty small business to throw at training its own
large language model does not seem.
Speaker 5 (25:38):
Like never gonna happen.
Speaker 4 (25:38):
Now, Well, what's your ad spend. Now, if it's two
hundred o K, then maybe this makes sense. But I
want to see the proofs in the shooting show me
that this isn't just some homogenized PAP that every other
little bank gets. It can have a hard time proving
value added. I mean, if I can have somebody come in,
do a little song and dance for me, present some
you know, present some ad stuff on an easel, the
(26:01):
old fac I know it's not mad men, but you
know I expect to be wooed for my one hundred K.
Speaker 2 (26:08):
Yeah, I agree, but but I don't.
Speaker 3 (26:14):
I would want that.
Speaker 2 (26:15):
But I think there are plenty of bustesses that know
nothing about AI who are feeling behind the eight ball
because they don't have the expertise nor the money to
spend on developing their own internal tool like Goldman Sachs does.
Who say WHOA six figures? And I can customize my
own AI model and Amazon's gonna help me do it.
I think there'll be plenty of customers to pick.
Speaker 4 (26:32):
Okay, maybe maybe the chief marketing officer needs something to
add to burnish their year end stuff so they get
the bonus they will want, and so they come in
and say, well, okay, my big idea is we pay
Amazon another hundred k a year to do this. Yeah,
Ceo says, I don't want to deal with that. Sure,
let's give it a try.
Speaker 3 (26:44):
Yeah, yeah, maybe yeah.
Speaker 7 (26:46):
Uh.
Speaker 2 (26:47):
Mark Financial Times asks how sticky is you in US inflation?
We're gonna get some sense of this on Friday, as
inflation figures for September get published, which, again, if you're
the Federal Reserve trying to make interest rate decisions in December,
I don't know how useful September data is other than
to tell you that directionally inflation usually it kind of
goes in the same direction. But how do we answer
(27:09):
the question of how sticky US inflation is? Because well, ultimately,
in twenty twenty two we were getting readings of nine
percent on its night, and we've come way down from there.
Speaker 4 (27:18):
I think when they say how sticky is it, they
mean how we introduced the concept of correlation and the
for we talked about it.
Speaker 5 (27:23):
We didn't introduce it. Sure, we talked about.
Speaker 4 (27:24):
Correlation in the first hour. The way you measure you
persistence is how correlated is something with its most recent observation,
then it's next most reason. Then it's next most recent
fancy term word of the day. If you want to
impress your boss. Is it auto correlated? Self correlated? Is
it serially correlated? Is another way analysts might say that
inflation is persistent, it's highly auto correlated. I don't that's
(27:45):
not what they mean here, though, I don't think so.
Why did I just go off on that tangent? I
don't really know what they mean. I think yet lost.
Speaker 5 (27:52):
How hard is it going to be?
Speaker 4 (27:53):
Yeah, I don't know where I am, but what I'm talking.
Speaker 3 (27:55):
About I just blacked out what I'm aging and I'm confused.
Speaker 4 (28:00):
I think what they mean is how hard is it
going to be to get inflation down? And all modern
macro whole economy models assume that prices are there's some rigidity,
some stickiness, if you will, in prices. That's why they're
that's why monetary policy works. It's also why inflation is
(28:21):
uh is difficult to get down. So the short answer
to this is, well, prices are rigid, prices are sticky
on average, That's why you get inflation in everything. When
oil why the average rate of inflation goes up when
oil prices jumped, Because you might ask, well, if oil
prices or tariffs are only going up on certain things,
why don't they go down elsewhere? The modern macro answer
(28:43):
to that is, and I'll just be technical, say nominal rigidities.
Speaker 2 (28:47):
And to humanize this a little bit, and not that labor,
not that labor is the only piece of this. But
if your boss came to you and said, hey, you know,
prices have been moderating a little bit, so I need
to take your salary from ninety thousand to eighty eight
thousand dollars, you're not going to say, yes.
Speaker 5 (29:04):
Yeah, wages are rigid to wages.
Speaker 3 (29:06):
Are extremely rigid.
Speaker 2 (29:07):
That is a big portion of what contributes to overall
price levels. And nominally, yes, and so yeah, the idea
that prices they have the pace that there increases have
calmed down quite a bit. But the idea that it's
going to be some easy feat to get inflation from
three percent down to two percent is a big question
(29:31):
mark in my mind. And at this stage I'm not
entirely sure that it is an actual goal of those
who are going to lead the FED.
Speaker 4 (29:38):
We were getting there, but the Fed, the FED is
chickening out essentially, And I'm not saying I wouldn't do
the same thing, by the way, because it's well known
that I'm a coward. The Fed does not. Everybody's just nodding.
Speaker 5 (29:49):
Everybody in the office is yep, his whole family.
Speaker 4 (29:52):
He shaped me, he turns tail. The Fed stopped trying
to get inflation down. It's turned to fighting weakness in
the labor market. Because getting inflation to two percent would
require reducing demand. The Fed is doing the opposite right
now by easing monetary policy. It's goosing demand. To get
(30:13):
inflation down to two would require probably a recession, which,
by the way, is what everybody said in twenty twenty two.
We all acclaimed the immaculate disinflation, but we never really
got to two percent because getting finishing that last mile,
or whatever analogy you want to use, would have been
economically painful. Now it's too late.
Speaker 2 (30:33):
Let's take a quick break. As we head towards the
noon hour. Here, markets are wavering a little bit.
Speaker 3 (30:39):
We've got the S.
Speaker 2 (30:40):
Andp up now only a little bit more than a
tenth of a percent. We'll recap it for you and
play some stack roulette here.
Speaker 5 (30:45):
Next.
Speaker 1 (30:47):
Find daily interviews and full shows of the Financial Exchange
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(31:09):
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He's the Financial Exchange Radio Network.
Speaker 7 (31:28):
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Speaker 2 (32:13):
There it is, Ah Tucker. Are you fed up with
spot me talking slop bowls?
Speaker 3 (32:23):
Also?
Speaker 2 (32:23):
When did we start calling Chipotle bowls slop bowls? Because
that seems.
Speaker 7 (32:28):
Chipotle That term come out maybe six months ago. Is
the first time we put it on.
Speaker 2 (32:34):
They never heard of a garbage plate. No, it's an
upstate New York thing when I was in college. Basically
just French fries, ground beef, cheese, like, basically whatever they
could find they're just toss into a garbage plate.
Speaker 3 (32:46):
And to answer her, that's a slop plate.
Speaker 2 (32:49):
I don't think that a Cova Mediterranean bowl is a
slop bowl. I think I think we're doing that that
branded disservice.
Speaker 7 (32:57):
I mean to answer your question, am I toired of
the said slop bowl? I would say no, because I
think it's the most customizable lunch out there. And I
still don't understand why I'm continuing to see these headlines
of diners pulling back because they're over the slop bowls.
I think it's more of a money thing than anything.
Speaker 2 (33:17):
Tucker, you're old man. You're not the target demo anymore. Right,
sixteen year olds here, I mean don't want slop bowls anymore.
Speaker 7 (33:24):
So what are they going to back to?
Speaker 2 (33:25):
Well again, I think if he stopped calling them slop bowls,
I think it would do a lot for the brand image.
Speaker 3 (33:33):
To me.
Speaker 2 (33:33):
I like you said, I think that this is a
cost issue. If I go to Chipotle, it's going to
be sixteen bucks. If I go to Cava, that new
Mediterranean startup chain. Yeah, you're talking, it's all in the
same about the same, yea. So maybe McDonald's needs to
put together a slop bowl and prove them all wrong.
Just a disgusting bowl field.
Speaker 7 (33:51):
I mean they've done the salad.
Speaker 2 (33:52):
Fried chicken chunks, you know, French fries, and whatever else
they've got, you know, big Max sauce.
Speaker 3 (33:59):
I think that I would work for them.
Speaker 4 (34:01):
Well, big Mac is a slop bowl between two slice.
Speaker 3 (34:04):
It's a sandwich.
Speaker 5 (34:05):
Mark, I love McDonald's.
Speaker 3 (34:06):
It's a sandwich. Yeah.
Speaker 2 (34:08):
So apparently some of these brands pulling back on some
of that stuff and focusing more on there. I mean,
you know, Chipotle was made famous by burritos. I think
that's largely what they still sell. But those those brands
that are focusing on just salad, you know, not just
sout what's the what's the sweet greens and others are
having a tough time attracting.
Speaker 3 (34:28):
Again. I go back to.
Speaker 2 (34:30):
These are all sixteen to twenty dollars lunches, and I
think people are just feeling like they should pinch some
pennies at this stage because they don't have enough money
to do a four to twenty dollars lunches.
Speaker 7 (34:41):
If I'm Chipotle, I'm coming out with like eight ninety
nine burrito, like a smaller one man that's available now.
Speaker 2 (34:50):
Yeah, I guess if you can be popular, if you
can do it without worsening your ingredients, then maybe that works.
But it's just a smaller brand nine dollars burrito. You're
gonna have to only after like ground beef.
Speaker 7 (35:01):
Just have a smaller, tour less yeah, and basic ingredients.
Speaker 5 (35:07):
That's a terrible idea.
Speaker 7 (35:08):
It's not a terrible idea, Michael. It's a great idea,
and they should do it.
Speaker 3 (35:12):
What do you got for us? Mark?
Speaker 4 (35:14):
Bringing things back to finance, I like talking about earlier
on not this close to lunch, though very distracting. Earlier on,
we were talking about the S and P as being
composed of of sectors information technology, financials.
Speaker 5 (35:29):
There are eleven of them.
Speaker 4 (35:31):
Information technology is the biggest, Like we said, thirty five
percent of the S and P. So if every dollar ahead, Mike.
Speaker 2 (35:37):
I just wanted to mention a confusing part of this.
The technology sector is comprised of a bunch of those
big names. Other sectors, though, are also comprised of what
we would consider to be big tech companies. The communication
services sector, for instance, is a big one, and you'd think, oh,
communication service, we're talking about AT and T. Well, yeah,
but we're mainly talking about alphabet We're mainly talking about
(35:59):
meta I think in the communications services sector, even though
largely we talk about them as though they're teching.
Speaker 4 (36:03):
But you made the point that when you put a
dollar in the S and P, thirty five cents is
going into more narrowly defined tech companies, and in turn,
twenty percent of every dollar currently this changes every day,
goes into Nvidia fifteen percent of every so six percent
of your nearly six percent.
Speaker 3 (36:22):
Twenty percent of the tech okay, twenty percent.
Speaker 4 (36:24):
Of techs on multiplying fractions here or proportions point two
times point three five, blah blah blah. That's how I
get to that number. And Nvidia, I'm rounding up.
Speaker 5 (36:34):
A little bit.
Speaker 4 (36:35):
Your point was, well, it's it's never been more dominated
by one sector and that sector has never been as
large as it is today.
Speaker 5 (36:44):
Did I get something wrong? You know you do? Okay, good? Good.
Speaker 4 (36:48):
My point is, on a daylight today, you're glad that
I'm not saying you shouldn't consider something other than a
market cap weighted index. That's a personal decision. I am
saying that the whole investment for fashion starts with market
cap weighted and then makes bets relative to that. But
on a daylight today, infotech is, with the exception of
one other sector, industrials, infotech is the only sector in
(37:11):
the green. So as distended as that part of the
S and P may seem, there are times plenty of times,
like the year to date period, for example, when it
can pull the whole index along. And why if your
objective is just to match the market, not necessarily to
beat it, so you don't consider yourself to be a
savvy active manager, for example, why it can be dangerous
(37:33):
to tilt away from market cap weights.
Speaker 2 (37:35):
Yeah, it most certainly can. I when I was trying
to pull up here, I'm going to see if I
can find it. Yeah, here we've I don't have the percentages, though,
what is it?
Speaker 3 (37:43):
What are you looking on that I was looking up?
Speaker 2 (37:45):
What are the what is the composition of the s
and P five hundred? So to your point, if I
invest a dollar, I believe something like not. No, I
want the company weights because I think if I invest
a dollars, something like nine cents is going into a video,
eight cents into Apple, and another seven into Microsoft or
something along those lines.
Speaker 3 (38:06):
And so yeah, you take a look at that.
Speaker 2 (38:08):
And so the top ten in Vidia, Apple, Microsoft, Amazon, Broadcom, Alphabet, Meta, Tesla, Berkshire.
I believe those ten are making up nearly fifty percent.
And you've got it. So between the top three, what
do we have.
Speaker 4 (38:22):
Having seven six is twenty three three three? Called that
thirty ten now doesn't quite get you. They're more like
thirty five.
Speaker 2 (38:30):
Yeah, but quite swesome. As we close out the show,
markets are still holding on too gains here, SMP up
one fifth of a percent, NASDAK up a half percent,
Dow Jones Industrial average up about a third of a percent.
We'll be back at it tomorrow. Folks, Stay tuned and
have a great rest of your day.
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