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JPMorgan’s Playbook for a 10-15% Correction (or Worse) — ft. Michael Cembalest | Prof G Markets

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JPMorgan’s Playbook for a 10-15% Correction (or Worse) — ft. Michael Cembalest | Prof G Markets

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1706 segments

0:00

Today's number, 104,000. That's how many

0:02

pounds a sperm whale that washed up on

0:05

an Nantucket beach this week weighed. Oh

0:08

gosh. This just everybody sit back and

0:10

buckle up. Okay, so I've never had an

0:13

unplanned pregnancy, uh, Ed, because

0:15

when my sperm [music] finally reaches

0:16

the egg, the egg swipes left.

0:20

My sperm really aren't like swimmers,

0:22

Ed. They're more like a slow jogger

0:24

being chased by a lame dog.

0:27

Um, my sperm are not really swimmers.

0:31

They're more like uh an old man browsing

0:33

at a Costco who's looking for

0:36

gluten-free peanut butter who just had

0:38

cataract surgery. Like, it's

0:39

well-intentioned, but it's just not

0:41

going to reach the goal. [laughter]

0:44

>> I could do this all day. I could I By

0:46

the way, I made up the last one myself.

0:48

Ed. [laughter]

0:55

[music]

0:55

Ed, do you have a nickname for your for

0:57

your sperm?

0:58

>> No, I I I'm not quite there yet. I'm not

1:01

really going to play ball with you on

1:02

this one. [laughter]

1:03

>> Also, let me give you a little tip. Just

1:06

just while we're barreling towards

1:08

cancellation, even Claire looks

1:09

horrified. It's important and it's fun

1:13

that every time you orgasm, you yell out

1:15

the same thing. It's really important.

1:18

You have to come up with the same thing.

1:22

This is the part where you go, "What do

1:23

you yell out, Scott? [laughter]

1:25

I told you I'm not playing ball with

1:27

you.

1:27

>> Ed's got his face in his hands. This is

1:30

not CM. Joe Kernan.

1:33

>> I'm not I'm not going to do you the

1:35

service of asking the question.

1:36

>> Surrender, Dory. That's what I yell out

1:38

from the Wizard [laughter] of Oz. That's

1:40

what I yell out. And my other Wizard of

1:42

Oz references, I I yell out, "I'm

1:45

melting." [laughter]

1:50

[snorts] That's why the fans tune in.

1:51

>> That's why they tune in. Next up, JP

1:53

Morgan, chief economist for the last

1:55

time. [laughter]

1:58

>> Uh, how are you, Ed?

1:59

>> I'm doing well, Scott. How are you

2:00

doing?

2:01

>> I'm good. I've been in LA the last few

2:02

days and I'm at the Beverly Hills Hotel.

2:04

>> Nice.

2:05

>> Where they're charging me $1,800 a night

2:07

so I can have a construction site above

2:09

my room.

2:10

>> But they they stopped the construction.

2:11

I mean, just off Mike here, you gave the

2:14

front desk a call. He asked them to stop

2:17

hammering and they did it. Pretty

2:19

baller. Good stuff.

2:20

>> Yeah. No, I I carry a lot of weight

2:22

here. Yeah, it's [laughter] uh they're

2:24

very scared of me.

2:25

>> Number one client. Um, so what what have

2:28

been the highlights from LA just before

2:30

we get into this conversation?

2:31

>> I had a dinner last night with like a

2:34

small dinner with eight people and I'm

2:35

totally name dropping. What the

2:36

Um, and Larry David. I sat next to Larry

2:39

David.

2:39

>> Wow. How was that?

2:40

>> He is literally the same person in real

2:43

life. It's not a show. It's a camera

2:45

following around. He showed up. He's

2:46

like, "Nice to meet you." He's like,

2:47

"Why do they serve odd derves?" He like

2:50

goes into a bit. He's like like he's

2:53

like why would I like I hate Uber. Do

2:56

you hate Uber? Let me talk about Uber

2:58

for He's literally I'm like oh my god

3:00

it's the show. The guy just shows up and

3:03

starts doing these bits. Uh but he's

3:05

very funny. He seems pretty nice. His

3:09

wife is lovely. I don't know. I enjoyed

3:11

>> How did you wind up at a dinner with

3:12

Larry David?

3:13

>> I'm what you call right now like an

3:15

intellectual support animal. And that is

3:17

all these rich people think it's

3:19

interesting to have me over for dinner

3:21

[laughter]

3:21

and talk about my book. Like so I think

3:25

there's two or three of these people

3:26

every year where they're like, "Okay,

3:27

let's all get together and and also at

3:30

the dinner was my role model Sam Harris

3:33

and I always enjoy seeing Sam."

3:34

>> So when you get invited as the

3:36

intellectual support animal, do you feel

3:38

a pressure to provide the intellectual

3:41

support?

3:41

>> Yeah, that's why you're there.

3:42

>> Is that fun? That sounds stressful.

3:44

Maybe that's why Larry David was doing

3:46

his bit. He was the comedic support

3:48

animal.

3:48

>> The answer is yes. And I find as I get

3:50

older. They called me and they were

3:52

going to invite this fairly

3:56

famous tech couple and I said, "No, I'm

3:58

like, I just don't want to I don't want

4:00

to meet them. I don't want to talk about

4:01

them. I don't I don't I I find that

4:04

stuff is increasingly intimidating me

4:06

and I don't want to I mean, you know

4:08

what? I'd rather just stay at home and

4:10

watch Netflix and have some big Filipino

4:12

man reheat my soup six or seven times

4:14

and just sort of start peeing in

4:16

bottles, grow my nails really long.

4:18

[laughter]

4:22

Surrender, Dorothy, [laughter]

4:25

should we should we get to AI and the

4:28

economy? Ed, [laughter]

4:30

>> you want to move on now?

4:31

>> Somebody gave me mushroom chocolates

4:32

over the weekend. Just saying.

4:34

[laughter] Just saying.

4:35

>> Okay, well that explains a lot. All

4:37

right, let's get to the economy.

4:39

[laughter]

4:39

>> Okay, now that we know what happened in

4:41

LA this weekend, here is our

4:42

conversation with Michael Semblas, the

4:44

chairman of market and investment

4:45

strategy for JP Morgan Asset [music] and

4:48

Wealth Management. Michael, thanks for

4:50

joining us again on Profy Markets. Good

4:52

to see you. Morning. So, I'm going to

4:55

dive right into the questions that we

4:57

have because we've only got you for so

4:58

long. Um, just some context. So, last

5:01

[music] week we had Professor Asworth

5:03

Deodorin on our podcast. He presented

5:07

what we think is kind of the most

5:09

bearish position we've ever seen from

5:11

him. And this is a very level-headed,

5:14

calm guy. Um, who basically told us that

5:17

he thinks that everything in the stock

5:19

market is overvalued. He said there's no

5:21

place to hide in stocks. And I'm just

5:23

going to play you a short clip uh that

5:25

kind of summarizes what he thinks right

5:27

now.

5:27

>> To the extent that there's going to be a

5:29

correction, there's no place to hide in

5:31

stocks. I I can't see a way because if

5:34

the mag 10 go down by 40%. It's not like

5:37

the industrials are going to hold their

5:39

value while this happens. The panic that

5:41

that's going to create is going to

5:42

ripple through stocks. You're an

5:44

investor primarily invest in stocks and

5:46

bonds. My advice is even though

5:49

historically you might never have

5:50

invested in non-financial asset

5:53

categories, this might be a time where

5:54

you think about, you know, kind of at

5:57

least moving a portion of your portfolio

6:00

know bigger chunk than ever into cash or

6:02

something close to cash or maybe even

6:04

collectibles, things that I I've never

6:06

owned collectibles, but you know, for

6:09

the first time in my investing history,

6:11

I'm saying maybe I should hold something

6:14

that is not going to be affecting

6:16

inflation. goes to 10%, there's a mark

6:18

in an economic crisis that is cat

6:21

potentially catastrophic.

6:22

>> So, we were very

6:25

u struck by everything he said in that

6:27

interview. Um, what do you think,

6:30

Michael? Is is he right? Are you

6:32

concerned like he is? What are your

6:34

reactions?

6:35

>> It's hard to react to somebody that

6:38

doesn't have a long-term track record of

6:40

this is when I bought, this is when I

6:42

sold, this is what I bought, this is

6:44

what I sold. You know, professors are

6:47

basically running fantasy baseball teams

6:51

by coming out inter intermittently and

6:54

telling you what who what their trades

6:56

are. It's not real money. It's not real

6:58

life. And so, you know, the purpose of

7:00

Morning Star and Liipper and a lot of

7:03

other entities out there is to kind of

7:05

track the people that actually manage

7:06

money. How do they do over the long run?

7:09

Um, and things like that. So, it's it's

7:12

a little abstract. I a better example

7:14

might be the cash stockpile that's

7:15

that's accumulating at Berkshire Hathway

7:17

is probably a an a much better indicator

7:21

of of people that are having trouble

7:24

putting money to work because they can't

7:25

find any value and certainly it's

7:27

challenging right now. There's a ton of

7:29

dry powder in the in private equity and

7:31

venture that still has to be put to work

7:33

and so it's a challenging time. um his

7:36

his premise of I think I heard him say

7:39

10% inflation like I'm I'm I'm not

7:42

prepared to quite buy into a 10%

7:44

inflation forecast nor am I prepared to

7:46

buy into the the certainty of a 10%

7:50

sorry a 40% correction in the MAG 10 or

7:52

MAG 7. Those stocks have gone up a ton

7:55

and a passing wind could cause profit

7:58

taking right um similar to what took

8:01

place earlier this year with the dollar.

8:03

Dollar went down 10%. It was at its post

8:05

financial crisis high. As soon as any

8:07

asset falls by 10%, Nuriel Rubini and

8:10

the rest of the people come out of the

8:11

woodwork and say, "Okay, this is it.

8:12

This is the big one. Everything's going

8:13

to go down from here." And then, of

8:15

course, the dollar's been flat since

8:16

then. The dollar has been actually flat

8:18

since our podcast in May. So, the last

8:20

time I was on this show, you know, I

8:23

think people have to have some kind of

8:24

discipline to recognize that when assets

8:26

are trading at 20 to 25 year highs, they

8:28

can correct by 10 or 15%. it it doesn't

8:32

necessarily unfold and unravel into the

8:35

big 40% corrections that we had in 2009

8:39

and then he had in 2001. So it's it

8:42

sounds I mean we're positioning more

8:44

defensively than we have but it you know

8:48

what he's describing there is is a

8:50

bridge too far. Plus, our normal

8:52

balanced and conservative portfolios

8:55

already have 30 to 40% in cash, cash

8:58

equivalents, gold, very diversified

9:01

hedge funds, municiples,

9:03

um, some short duration preferred and

9:05

things like that. Just to play defense

9:07

for Asaf, you know, we that clip that we

9:10

got was the most bearish string of

9:13

sentences that he he uttered. um

9:16

otherwise I think if you listen to the

9:18

full podcast it would sound less

9:21

hyperbolic perhaps but you know in some

9:24

he's concerned um but also so is

9:28

everyone else and right now this this AI

9:31

bubble more and more people are talking

9:33

about it more and more people are

9:35

googling it we're now beginning to see a

9:37

little bit of a correction in in tech

9:38

stocks as we speak

9:40

>> small

9:41

>> uh small [snorts]

9:42

um the fears of this AI bubble

9:46

are quite strong or stronger than they

9:48

have been before. Um what do you make of

9:51

those fears? Do you think that they are

9:53

warranted? Um and how are you at JP

9:56

Morgan uh thinking about it?

9:59

>> Something like 75% of all of the

10:01

revenues, profits, and capital spending

10:03

since November 2022 have come from 40 AI

10:07

related stocks. So there's there's

10:09

there's almost no justification to spend

10:11

time on anything but this. And I try to

10:14

be an even keel kind of person, but the

10:15

meta number threw me. You know, a

10:18

company announcing that they're spending

10:20

65 to 70% of their revenues on capital

10:24

spending and R&D without even knowing

10:26

what the destination is that they're

10:29

going to. As an investor, that doesn't

10:33

fill me with a lot of good feeling about

10:36

where we're going to be two years from

10:37

now. And it was only two years ago that

10:40

they did this. they reached the same

10:41

peak of 65% of revenues investing in the

10:44

metaverse, which obviously hasn't really

10:46

turned out to be anything. So, um,

10:49

there's a lot more behind this

10:51

particular generative AI boom, but the

10:55

numbers I I put together something,

10:57

Scott, I think you'd appreciate this

10:59

that you like this kind of historical

11:00

context. The tech capital spending in

11:03

2025

11:05

is equal relative to GDP of

11:10

the moon landing, the Manhattan project,

11:13

the interstate highway system,

11:15

electrification of farming, the tribal

11:17

bridge, the Minttown tunnel, the Golden

11:20

Gate Bridge, and the Hoover Dam

11:21

>> combined. Yeah.

11:23

>> Wow.

11:23

>> Yeah.

11:24

>> There's all these futurists hovering

11:25

around like bats telling us how all of

11:28

this is going to magically make some

11:30

fantastic future. And there are surely

11:33

bits and pieces of evidence here and

11:36

there of real productivity gains coming

11:39

from this. But um this is a this is a

11:43

scarier version of the ICT revolution of

11:47

the early 90s. The only silver lining

11:49

that I latch on to

11:52

is that whether it's 2001 or the casino

11:56

buildout, airlines, fiber optics,

11:59

um the the the the Calpine gas turbine

12:02

era, all of those capital spending booms

12:04

were financed with debt. And this one,

12:08

with the exception of Oracle, is being

12:10

financed with internally generated cash

12:12

flow. But that simply means it can go on

12:14

for longer before it gets unplugged by

12:16

the debt markets. It doesn't relieve you

12:19

of the ultimate need for there to be

12:21

substantial profit generation to

12:23

remunerate the trillion two of capital

12:25

that's been spent since November 2022.

12:28

>> I want to recognize I'm I'm feeling

12:30

defensive around my colleague. I've been

12:31

following ASW for 20 years and he does

12:33

the work around valuations and there's

12:35

few people in the alternative investment

12:37

space or investors that at least in my

12:40

observation have been more right more

12:42

often than him and it did rattle us cuz

12:44

he generally I want to acknowledge your

12:46

point uh it's easier to sound smart when

12:49

you're a catastrophist you just sound

12:51

smarter right and the the best traders

12:55

the best historians the best politicians

12:57

have aired on the side of asking

12:59

themselves what could go fight, you

13:01

know, and cuz the markets over the

13:03

medium and long term are up and to the

13:04

right. So, I want to acknowledge that

13:07

the I want I want to put forward a

13:09

thesis and have you respond to it. And

13:10

that is if you look at every single of

13:12

the company one of the companies we're

13:14

talking about, they have all had years

13:17

where they're down 50 to 70% in that

13:20

12-month period. And the thing that's

13:23

scary now is if a company like Nvidia,

13:24

which hasn't had one of those years, I

13:26

don't think, or maybe it did in 2022, if

13:28

that happens to a company that's now got

13:30

the market cap [snorts] of the GDP of

13:33

whatever Germany, that that that might

13:36

take the entire market down that

13:38

essentially America has become so

13:40

fragile because it is now a giant bet on

13:43

AI. And if open AI which you know I mean

13:47

60% of cap 60% of revenues on capex is

13:50

one thing as far as I can tell open AI

13:52

is about at you know 30 times 30 times

13:56

the revenue going into capex. If open AI

13:59

or some big customers here's the thesis

14:01

and you you tell me where I got this

14:02

wrong. Some standard S&P companies

14:04

PepsiCo Caterpillar PNG announced look

14:07

AI is great but we are out over our

14:09

skis. We're not seeing the return we'd

14:11

hope for. We're scaling back the

14:12

investment. Open AAI in the secondary

14:15

market trades way down and then o and

14:18

then Nvidia is is goes down 60% which

14:22

would not be unusual. it wouldn't look

14:23

cheap. And then we have a $3 trillion

14:27

destruction in the capital markets and

14:29

we basically overnight have flat

14:32

markets, GDP growth of zero and the

14:35

whole market, you know, if these

14:37

companies sneeze, we're not catching a

14:38

cold, we're catching pneumonia. Has the

14:41

thing that worries me the most and I

14:42

want to get your response is we have

14:44

inadvertently turned our markets into

14:46

into a very fragile house of cards.

14:50

There's the S&P 490 and there's the S&P

14:52

10 and right now everything is banking

14:55

on these 10 companies living up to these

14:57

extraordinary expectations. Your

15:00

thoughts?

15:00

>> I agree with most of that. Um, one of

15:03

the data points that was really

15:05

disturbing is two years ago someone

15:08

talking about GDP growth would not have

15:09

mentioned tech capital spending. It

15:11

would have been a rounding error. Last

15:13

quarter it was a third of GDP growth and

15:16

US GDP growth would already be 1% if it

15:19

weren't for this tech AI buildout. And

15:22

you know how people get upset when the

15:24

private sector gets bailed out by the

15:26

public sector. I would argue this year

15:29

Generative AI has bailed out the public

15:31

sector like the you know these the

15:33

hyperscalers bailed out the Trump

15:35

administration because without them

15:37

they'd be staring a 1% GDP growth number

15:39

in the face

15:40

>> and having to explain it which they're

15:42

in really no position to do. And by the

15:44

way, I don't think it's a coincidence

15:47

that uh we we track all of the country

15:50

product tariff matrix combinations. Um

15:53

the AI infrastructure about 70 to 90% of

15:57

those imports are exempt from tariffs

15:58

right now. So the the those sectors and

16:01

companies have also done a very good job

16:03

navigating however one has to these days

16:06

um Washington in order to get their

16:10

imports which are critical to their

16:11

survival exempt from tariffs. So, yeah,

16:14

I'm I'm nervous about it. Um, again, the

16:16

the the fact that it's being financed

16:19

through cash flow

16:21

means that we don't have quite the same

16:23

risk of a sudden seize up because, you

16:27

know, bonds can't be placed. Um, you

16:30

know, you're not going to have a hung

16:32

bridge loan that that gets like the

16:35

broker dealers in trouble and have to go

16:37

to the Fed's primary dealer credit

16:38

facility. You're not have something like

16:40

that. Um, Oracle is really the only one

16:43

that's financing any material amount of

16:44

this through debt,

16:45

>> my understanding. So, Oracle is is

16:48

raising a ton of debt and it's it's, you

16:50

know, capital markets are concerned

16:52

about this and that and we're seeing

16:53

that reflected in the stock price is

16:55

essentially underwater since the um

16:58

since the the deal with with OpenAI was

17:01

announced for my understanding though is

17:03

that the other big hyperscalers are

17:06

going out and beginning to raise debt.

17:08

Um, I mean, we just saw a big

17:10

announcement from Amazon. I think we saw

17:12

that from Meta a couple weeks ago as

17:14

well. I don't know the exact numbers,

17:16

but my understanding is they are going

17:18

and financing this with a ton of debt.

17:20

Perhaps not debt that they necessarily

17:22

have to raise. Perhaps they have the

17:24

cash surplus to to to finance this, but

17:28

they are going and raising debt. And

17:29

it's record amounts of debt that they

17:31

are raising. Is that wrong? Of the 40

17:34

companies I mentioned, there's AI

17:36

stocks. 30 are technology what you and I

17:38

would agree are technology companies.

17:40

Five are capital equipment companies

17:42

like GE Vernova that make the turbines.

17:44

And then five are utilities. Let's look

17:47

at the 30 AI stocks. Something like 25

17:50

of them actually have negative net debt

17:53

to Ebbitar ratios because they have more

17:55

cash and cash equivalents on their

17:57

balance sheet than debt. So for the most

17:59

part, um the debt's not an issue. The

18:02

Oracle is an exception and is in part a

18:04

reflection of the fact that or that that

18:06

Ellison's been buying back stock for 15

18:07

years and you know taking taking money

18:11

out that way. At some point Oracle is

18:13

going to have to be recapitalized if

18:15

it's going to be borrowing like this.

18:16

The Meta deal was interesting and when I

18:20

explain how I view it, you'll probably

18:22

say, "Well, that that's even scarier

18:24

than if it was Meta."

18:26

>> I hear it. The meta partnership with

18:29

Blue Owl that borrowed 27 billion in the

18:31

investment grade bond markets was an SPV

18:34

with a strange French name and the debts

18:37

not consolidated onto Meta's balance

18:39

sheet. Initially, I was concerned that

18:41

that was some kind of slight of hand.

18:42

It's not. It's worse.

18:44

They basically have walk away rights

18:46

every four years and a declining

18:49

residual value guarantee. Blue Owl's

18:52

holding the bag. So, Blue Owl is at

18:55

risk. If at any point Meta basically

18:59

says, you know, this this we're not

19:01

getting a return on this particular data

19:02

center complex, we're out. And Blue and

19:06

the people that have put up the money

19:07

for Blue Owl are the ones holding the

19:09

bag. So I think S&P was right to kind of

19:12

withhold consolidation of that

19:15

obligation, but it says it says a lot

19:17

about the underwriting discipline that's

19:19

taking place in in you know in private

19:22

credit and in other places that are

19:24

financing these data centers because

19:26

they're the ones that are taking the

19:27

risk. It's essentially releasing risk

19:29

the likes of which you've seen forever

19:31

in the commercial real estate markets.

19:33

>> So it sounds like someone is on the

19:35

hook. In this case, it's Blue Owl and

19:37

we're probably seeing equivalence in

19:38

these other debt deals. And by the way,

19:40

we're seeing this kind of reflect in the

19:41

stock right now. Blue Owl is publicly

19:43

traded and it's been it's declining this

19:45

week. Um, but is the is the conclusion

19:48

then? Because it sounds like you agree

19:50

with ASW. We are seeing some we're

19:53

seeing some form of a bubble. People are

19:55

exuberant. There's a lot of hype and a

19:57

lot of excitement that isn't fully

19:59

tethered to reality right now when it

20:01

comes to AI. But it sounds like where

20:03

you disagree is the extent and scale of

20:06

the damage that we're going to see if

20:08

something blows up or at least the

20:10

likelihood that there will be some sort

20:12

of blowout.

20:12

>> Last year was a perfect example. My

20:14

forecast for the year was the Trump

20:16

people were going to break something.

20:17

We'd have a 15% to 20% correction, but

20:20

stocks would end the year higher than

20:21

where they began. Um it happened within

20:24

50 days 50 days of the inauguration.

20:26

They broke everything. Um markets went

20:29

down. They eventually came back. I I

20:31

wouldn't I wouldn't describe any of the

20:33

subsequent recovery as as as the

20:35

byproduct of administration policy, but

20:37

I think I think you and Scott are right,

20:40

which is it would be kind of shocking if

20:43

you didn't have some kind of profit

20:45

taking correction

20:47

in 2026 at some point on the order of 10

20:50

to 15%. It would be I'd be I'd be really

20:54

surprised not to see that. The the big

20:57

question is if you told me the draw down

21:00

is 12%. I don't really have to make any

21:03

substantial portfolio allocation changes

21:06

here. We can we can work through that

21:07

with the way that we manage money. If

21:09

it's 40, that's different. And so that's

21:12

the that's essentially the big call that

21:14

asset allocators and Orisa plans and

21:16

endowments and foundations have to make.

21:18

Are we looking at a 12 to 15% correction

21:20

or are we looking at something that's

21:21

going to end up at 40 right now? uh with

21:25

with a little bit of Fed easing and and

21:29

some steady momentum, I I'm I'm I'm more

21:32

inclined to think of the 12 to 15 and

21:34

the 40.

21:37

We'll be right back after the break. And

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22:53

>> We're back with property markets.

22:55

>> I just want to unpack something you said

22:57

about the Trump administration would not

22:59

have nearly the cloud cover for some of

23:00

the things he was doing. If if these 10

23:03

companies were off, the S&P would be

23:05

flat or down. GDP I the stuff I've said

23:07

is that we'd actually be already be in a

23:09

recession.

23:09

>> Y

23:10

>> So he has a vested interest in this boom

23:13

continuing, right? I won't even say this

23:15

bubble but this boom continuing doesn't

23:17

that I feel like all paths lead to the

23:19

same place and that is the government

23:20

will back the debt to continue to make

23:23

these extraordinary capital purchases

23:26

which in my view weakens the strength

23:30

and integrity of the US debt markets or

23:33

treasuries and is like a further move

23:36

into socialism. But I predict he is

23:39

going to back uh these companies. Not

23:42

the other, not the real economy, not the

23:44

main street economy, not the 490

23:46

companies in the S&P that got to

23:47

actually compete in the capital markets.

23:50

But he has such a vested interest in the

23:52

in the music continuing here that the

23:55

government will step in and offer in

23:57

some way to back the exceptional capital

24:00

expenditures such so they can continue

24:02

to make them and that is only inflating

24:04

the bubble to very dangerous territory.

24:06

your thoughts on that thesis?

24:08

>> That would worry me if I saw it. Um I

24:11

would they've done a couple things so

24:13

far that I would in fairness put in

24:14

different bucket. I like I you know

24:16

Jamie is a very inspirational CEO and

24:19

one of the things I admire most about

24:20

him is he calls it like he sees it,

24:22

right? So um

24:25

they've done a couple of deals with MP

24:27

Materials and Intel. Both of those deals

24:31

fall under traditional industrial policy

24:35

of of trying to rescue supply chains

24:37

that are rapidly diminishing in the

24:38

United States with respect to domestic

24:40

semiconductor production and critical

24:43

minerals.

24:43

>> I think you're being generous when they

24:45

pick one company and take a stake and

24:47

they take a golden share in one steel

24:48

company. I would argue that is not

24:50

structural or there's not a systemic

24:51

strategy there. That's the blood sugar

24:53

of a man who thinks he can run these

24:54

businesses better than the private

24:56

sector. I'm going to disagree with you

24:58

on that one and NP materials in

25:00

particular. Um I mean they they have

25:03

provided a price floor on on neodymium

25:06

and praise demium which is needed by the

25:07

US military. It's the last man standing

25:10

in that sector. Um I if you told me that

25:13

that an adi a presidential

25:15

administration had to administer an

25:18

industrial policy to pick winners and

25:19

losers,

25:21

this might be the last administration I

25:23

would want to see do that. That said,

25:25

you know, you don't get to pick your

25:26

time and place. And as things stand

25:29

right now, China has a chokeold on those

25:32

critical minerals. And whatever

25:34

administration is is in power is

25:36

responsible for making sure uh

25:39

particularly with China flexing its

25:40

muscles on export controls that we start

25:42

the process of trying to rebuild both

25:45

mining and processing of critical

25:47

minerals. If you can't do that, you've

25:48

got a wide range of both renewable

25:50

energy and military applications that

25:52

will soon become untenable. That has to

25:55

be done. I I I would have preferred for

25:57

Eisenhower to do it. Okay. But, you

26:00

know, I'm 63. So, uh I probably would

26:04

have preferred for George Bush Senior to

26:05

do it. Um right. I'm not sure I would

26:08

have wanted Obama to do it. Those I'm

26:11

not sure I would have wanted Jennifer

26:12

Granholm to do it. Um so, but you don't

26:14

get to pick your time and place. Intel

26:17

was different. There's there's no

26:18

guarantee of demand. There's no price

26:21

floors. It's basically just a cash

26:23

infusion. And based on everything I

26:25

understand about Intel, their problem

26:26

isn't money. So, the worst thing about

26:29

that one is I don't even think whatever

26:30

it is they did is going to be very

26:33

impactful.

26:35

But I I and I but I do expect to see

26:38

more

26:40

intervention by the administration

26:43

in in companies that represent the the

26:46

tail end of surviving supply chains,

26:49

whether it's ship building or anything

26:51

else. And and I'm actually I'm actually

26:54

I'm I'm not a I'm not a heritage KO guy.

26:57

So I'm in support of that. you oversee

27:00

and kind of set the strategy and the

27:02

narrative and the theme for one of the

27:04

deepest pools of capital in the world.

27:07

What other than just moving to cash and

27:10

maybe that's the only thing you can do.

27:12

How do you I don't want to say become

27:13

defensive but just recognize that

27:15

traditionally when stocks are this fully

27:17

valued the markets tend to have a pretty

27:20

serious correction or go flat for 10

27:22

years like how is your recommended asset

27:24

reallocation

27:25

what has it been what are you

27:28

recommending to those deep pools of

27:29

capital uh other than just going into

27:32

cash

27:32

>> so the answer to that question I think

27:34

you'll find interesting because it's

27:36

less about changing the asset allocation

27:39

of of the different portfolios it's more

27:42

about explaining to clients that they

27:46

they may be better off switching from

27:48

balanced to conservative or from growth

27:50

to balanced. When we define the risk

27:52

contours of a balanced portfolio, there

27:54

are certain parameters that we can go

27:56

outside of but usually tend not to want

27:59

to do. And so if if if we're really

28:03

feeling that the risk return of a growth

28:05

portfolio is changing, we would rather

28:07

have the student body, you know, change

28:10

from being premed to pre-law and migrate

28:13

down to the balanced portfolio risk

28:15

rather than have to turn the balanced

28:18

portfolio or the growth portfolio into

28:19

something it isn't. because there's

28:21

always going to be people with

28:23

generational money or or or quite

28:26

frankly

28:28

this the city of Chicago, Cook County,

28:31

Illinois, New Jersey, plans that are

28:34

kind of on paper in extreme distress.

28:37

[clears throat]

28:38

They their inclination is to take a lot

28:41

of risk. And so I don't want to change

28:43

what a growth portfolio does because

28:45

there are people that are going to

28:48

allocate to that and have have every

28:49

right to expect a growth portfolio to be

28:51

positioned the way a growth portfolio

28:53

looks. So part of our job is to explain

28:55

to whoever wants to listen that that the

29:00

risk return is skewing because of where

29:01

the valuations are. So you might want to

29:03

kind of move down the portfolio chain.

29:05

What does a balanced or more defensive

29:08

portfolio look like for those I mean

29:10

just at a very high high level general

29:13

level like what is that portfolio look

29:15

like bonds versus stocks

29:17

>> you're talking about 30 to 40% of the

29:19

portfolio being in some combination

29:23

of cash

29:25

short-term A1 P1 commercial paper um m

29:30

municiples for taxable clients um super

29:33

diversified

29:35

um hedge funds like 30 to 40 of them

29:39

where where like the V turns out to be

29:42

something like five or 6%.

29:45

Um and uh some preferred stock things

29:48

like that. So you you're kind of taking

29:50

a lot of the directional beta risk out

29:52

of it. Um you you would

29:56

>> you know you're obviously positioning

29:57

much more defensively. Healthcare is

30:00

trading at like the cheapest valuation

30:03

on record relative to itself and

30:05

relative to the market. So if you're

30:07

going to take a position someplace,

30:10

go someplace where you can be paid for

30:12

the risk a little bit better, you know?

30:13

So stuff like that.

30:14

>> How is tech uh valued at large right now

30:17

in terms of paying you for the risk? The

30:19

first thing people tend to do is say I'm

30:21

going to look at the PE of tech and then

30:23

I'm going to look at the PE of something

30:24

else whether it's industrials or basic

30:26

materials consumer discretionary or

30:28

staples. But for a hundred years people

30:31

have been adjusting PE ratios for growth

30:34

like for earnings growth and ROE and ROA

30:36

and capital efficiency. So if and one of

30:39

the things we do and we share this in

30:41

all our publications is we plot both

30:44

stocks and sectors and industries with

30:47

return on equity on the x- axis and

30:50

either PE or price to book on the y-

30:52

axis. And so

30:54

there's a lot more consistency to the

30:57

way the market's valued once you adjust

30:58

for earnings growth. Now you may think

31:00

the slope of the curve is too steep and

31:01

I wouldn't disagree with you but to just

31:03

kind of look at PE differentials is

31:05

really missing the point that even

31:08

before this generative AI boom and we

31:10

roll back the clock to 2019 the tech

31:13

sector had double the margins of the

31:15

rest of the market. They had become the

31:18

things that the tech investors of 2000

31:20

would eventually dream they would be

31:23

which is highly capital efficient

31:25

lowemployment businesses with huge

31:27

operating margins. So that's what they

31:30

were even before this whole AI boom

31:32

started.

31:32

>> Yeah. Something that I was thinking

31:33

about after we spoke with Assworth. I

31:35

mean his his core valuation tool is the

31:38

equity risk premium which basically you

31:40

know he's taking the the rate of return

31:42

on stocks minus the risk-free rate and

31:45

that and he sort of plots that out.

31:47

>> Yeah.

31:47

>> And you don't you you're not a fan.

31:50

[laughter]

31:51

>> It doesn't have any nuance to it. It

31:52

doesn't look at earnings growth and it

31:54

doesn't differentiate between sectors

31:56

and you know and it's I understand why

31:59

people want to look at it over the

32:00

really long run. It can be obviously a

32:01

helpful tool.

32:02

>> Yeah. I Well, I think it's it's helpful.

32:04

It's helpful when you're trying to take

32:06

a bird's eye view and understand where

32:07

we are in terms of sentiment. And the

32:09

thing that kind of surprised me is, you

32:11

know, we're at around 3.7% by that

32:14

measure. And, you know, to be fair to

32:16

him, he says, you know, anything below

32:18

4% is a little bit dangerous. But we're

32:20

also nowhere near where we were in 99

32:23

when it was around 2%. And you know, you

32:26

you're someone I mean, you were a

32:28

managing director during the the the.com

32:31

boom and bust. you were you were the

32:33

chief investment officer of JP Morgan

32:35

during the 2008 financial crisis. So

32:38

you've seen these cycles before and I

32:40

think what we're describing here is like

32:42

how do we put this in the context of not

32:44

just tech versus industrials versus

32:47

consumer but how do we put it in the

32:50

context of all of history and what does

32:52

this look like compared to previous

32:54

crises and previous cycles.

32:56

>> I couldn't sleep

32:58

in March of 2008. like I couldn't sleep.

33:01

Um the things that we were seeing on a

33:03

daily basis were so bad.

33:06

Um and and we knew that it was infecting

33:10

the entire like network of the financial

33:13

system and we went underweight both

33:15

stocks and high yield. The only mistake

33:18

we made is we didn't do more of it. Just

33:20

to show you how hidden those risks were,

33:22

JP Morgan, which is an exceptionally run

33:25

bank, bought a couple of billion dollars

33:28

worth of Fanny and Freddy preferreds

33:29

that summer for its own balance sheet

33:31

three months before they went to

33:33

conservatorship. Right? So that's how

33:34

hidden the the depth of the problems

33:37

were. Um 2001 was easier because the

33:44

companies weren't making any money. And

33:46

so as long as you had some degree of

33:49

discipline and support from your

33:51

investment committee to to to go through

33:53

a period of temporary underperformance

33:54

as the market was rocking, you did fine,

33:57

right? And so that in a way that was the

34:00

easiest one. Um uh I I remember

34:04

um we had this annual MD meeting and um

34:07

the chairman at the time invited a

34:09

company to come speak to us in 1999. He

34:12

invited a CEO to come on stage and

34:13

address all the MDs and he was the CEO

34:15

of a company called the globe.com. So I

34:18

pulled up the globe.com on Bloomberg and

34:21

I hit dees and it said this company has

34:24

no business model at the time. [snorts]

34:26

So we're sitting there like the chairman

34:29

has invited a guy who runs a company

34:31

with no business model to address us. I

34:33

think we're underweight now. Right. I

34:35

mean so that that was [laughter] pretty

34:36

easy. Th this this is this is a harder

34:40

one.

34:41

because you know in many ways Google's

34:44

one of the most successful companies in

34:46

the history of the markets. Um I I

34:49

personally think their AI related

34:50

language model products are better than

34:52

everybody else and I think they're the

34:54

long-term winners in this race. And so I

34:56

I have a lot of respect for what that

34:58

company's accomplished. Um you know I I

35:01

I have similar feelings about what

35:03

Amazon and and Microsoft are doing. Um,

35:07

but like Microsoft signed a deal

35:09

recently

35:11

with Constellation Energy to turn back

35:13

on a nuclear power plant in um,

35:15

>> Three-Mile Island.

35:16

>> Three Mile Island. They've agreed to pay

35:19

something in the neighborhood of $130 a

35:21

megawatt hour. Now, most of your

35:23

listeners don't know what that means.

35:25

That's double wholesale power prices for

35:28

for an average 20-year, you know, PPA

35:30

agreement. The other risk that we need

35:33

to acknowledge is we're getting closer

35:35

to a power wall

35:38

that will prevent OpenAI from getting

35:40

anywhere near like they've announced

35:43

partnerships with Broadcom, Oracle, AMD,

35:48

and Nvidia that would require 30

35:52

gigawatts of power, which is the

35:55

equivalent of 16 Hoover Dams. Like,

35:58

that's just not going to happen.

36:00

>> [snorts]

36:00

>> So what what we're trying to figure out

36:02

is how much of what's in the price of

36:05

this whole AI boom is the expectation

36:08

that these announcements are actually

36:09

going to come to fruition under some 3

36:12

to 5 year time frame because it's

36:14

impossible.

36:15

>> Yeah, it seems it seems kind of obvious

36:17

to almost everyone that the I mean if

36:19

you look at the numbers when you see the

36:21

the amount of power that it's going to

36:23

take to build out AI the way OpenAI

36:25

would like it's like oh yeah that's

36:28

that's not possible. And you know, one

36:30

of the things that we've been talking a

36:31

lot about recently is that crazy

36:33

interaction between Sam Alman and Brad

36:36

Gersonner. I don't know if you saw this,

36:38

where Brad Gersonner says, you know,

36:40

you're going to spend, you're making $13

36:41

billion in revenue. You you plan to

36:43

spend $1.5 trillion over the next few

36:45

years. How are you going to pay for it?

36:47

To which Salman responds, if you want to

36:50

sell your stock, you can. Be my guest.

36:52

There are plenty of other buyers out

36:54

there who would love to buy OpenAI

36:56

stock.

36:56

>> [laughter]

36:57

>> It sounds like what happens when when

36:59

there's a syndicated loan

37:02

um distribution now on Wall Street,

37:04

there's so much demand that if you if

37:07

you press the button that says on the

37:09

syndicate call, I have a question about

37:10

the documents, you get disconnected.

37:13

Like if you have a question on the docs,

37:15

we you don't need to be part of the

37:16

syndicate. So that those I would agree

37:19

with you. Those are the signs that are

37:21

kind of telling me that we've entered

37:23

into a period where where the the

37:25

risk-taking isn't there. Um that the

37:28

underwriting has gotten sloppy. Um when

37:31

we look at like in the inards of the

37:34

private credit markets, private credit

37:37

five years ago was substantially

37:39

different than leverage loans in really

37:41

boring ways having to do with

37:43

maintenance covenants, IP blockers, and

37:46

all sorts of stuff. And over that 5year

37:48

period, it's converging rapidly towards

37:51

the leverage loan market, which

37:52

basically doesn't apply much of an

37:54

underwriting

37:55

wall at all. You know, so we're we're

37:57

we're kind of preparing for a uh um

38:02

profit taking spark that comes from

38:06

things we might not be able to

38:07

anticipate,

38:09

a violent, you know, correction in over

38:12

bid assets.

38:14

um and then some period of kind of

38:16

recovery and calm that follows.

38:19

>> In a previous life, Michael, I used to

38:20

take boards and management teams outside

38:22

and do scenario planning as as an

38:24

exercise for how they allocate their

38:26

capital. And if I were going to do this

38:29

for a bank or anyone else, there's a

38:31

couple scenarios I want to outline and

38:33

you tell me if they're realist

38:34

realistic, if you think they might

38:35

happen, and if so, how to respond.

38:38

The first scenario is all right. Built

38:40

into these baked into these valuations

38:42

of these AI companies is what I've read

38:45

the assumption that they're going to be

38:46

able to find or inspire across their

38:49

clients 3 to 5 trillion in incremental

38:52

revenues or efficiencies. Now I don't

38:55

see a lot of AI moisturizer out there.

38:57

What I do see is companies saying okay

39:00

we're cutting our legal expenses. We're

39:02

cutting compliance. There's real savings

39:04

and efficiencies. which is sort of Latin

39:06

for layoffs. And if you think that 160

39:10

million people in the nation work, if

39:13

half of them are in industries immune to

39:15

AI, chiropractors, you know, welders, 80

39:18

million are quote unquote vulnerable. If

39:21

you were to not inspire, which I have

39:23

not seen, a ton of incremental revenue

39:25

growth from AI products, but but all

39:29

efficiencies, say a trillion a year,

39:31

$100,000 average load per job, you're

39:34

talking about a destruction in the labor

39:36

market of 10 million jobs a year across

39:40

the 80 million jobs that are vulnerable

39:42

or a 12 a.5%

39:45

labor destruction per year in certain

39:46

industries, which may not sound like a

39:48

lot, but that's chaos. or or these

39:52

companies valuations get cut in half. I

39:55

I see this as a pretty definitive fork

39:57

in the road. Either pretty much chaos in

39:59

the labor markets for the next 3 years

40:01

or these companies adjust down their

40:04

expectations and valuations.

40:07

What are your thoughts on that scenario?

40:09

>> Those are some important questions. Um

40:11

[laughter] that says it all.

40:14

The first kind of thought piece that

40:16

OpenAI published after GPT was released

40:19

was a piece that kind of jumped out and

40:21

said Generative AI is going to be

40:23

complimentary to workers and not

40:25

destructive. And I remember thinking,

40:27

uhoh, it's going to be bad [laughter]

40:30

because they they they they they were

40:33

ready to go out of the gate with a paper

40:35

to defend the labor market of this stuff

40:38

like right away to try to get out in

40:40

front of it, which which which

40:42

demonstrates that they kind of knew what

40:44

this would would be able to do to

40:45

certain industries. You know, the other

40:47

thing that happened uh and I wrote about

40:49

this a couple months ago, there was a

40:52

couple of papers that came out. There

40:53

was there's this chart showing that the

40:55

um unemployment rate for reaching

40:58

college graduates for the first time in

40:59

about 60 years is higher now than the

41:02

overall unemployment rate rather than

41:03

lower. So the first two pieces that come

41:06

out say it has nothing to do with

41:07

generative AI. So you know you go to the

41:09

back and you like who wrote this piece

41:11

and as you unravel the threads they're

41:14

Silicon Valley think tanks. And so then

41:18

I kind of went to David Our and Darren

41:20

Osamoglu at Harvard at MIT and and um um

41:24

John Bjolson at Stanford. You get a

41:26

different answer which is yes, it's kind

41:30

of looking like generative AI is

41:32

beginning to affect um uh those young

41:35

college graduates. So so we're starting

41:39

to see that. We made this pyramid of

41:42

things about AI and the bottom of the

41:44

pyramid is the most ubiquitous thing you

41:46

can find which is like futurist

41:49

forecasts and all sorts of stuff and

41:51

then as you go a little narrower it's

41:54

um study lab studies of AI doing non-b

41:57

businessiness related things. They're

41:58

great, right? It's it plays chess. It

42:01

plays go. It plays It can do all sorts

42:04

of non-b businessiness related things

42:05

extremely well. It can play your Wordle

42:07

for you, right? Then now let's see how

42:11

does it do in actual business related

42:13

tasks. Pyramid's getting narrower, but

42:16

there are some studies out there showing

42:17

this in a lab setting. Then you want

42:20

like surveys of adoption, but then you

42:23

get those kind of bland, you know, cream

42:26

of chicken soup pieces from McKenzie

42:29

where all they do is call companies and

42:31

say, "Hey, do are you using it?" Right?

42:33

And you [snorts] don't really learn

42:34

anything from that. And then you keep

42:36

going up the pyramid to hardcore stuff

42:39

where what are the revenue and profit

42:43

and productivity consequences of doing

42:45

this stuff? There's only a handful of

42:47

those. And what you can't find at all is

42:51

the top of them pyramid which are

42:53

pathways

42:55

explicit pathways to profitability for

42:57

generative AI adoption for the

42:59

hyperscalers. [music]

43:02

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44:26

>> I think China's pissed off. I I think

44:28

they're sick of trying to figure out the

44:30

US China relationship, plan their

44:33

economy, and they're diversifying away

44:34

from us. 24% of their exports used to

44:36

come to the US, now 17. But they really

44:39

feel as if they have, I believe they

44:42

feel we have declared economic war on

44:44

them. and that they are going to punch

44:45

back. And one way they might punch back

44:47

or what I would do if I were she, we run

44:50

companies for profit. They sort of run

44:52

companies for control and geopolitical

44:55

advantage. And if I were them, I would

44:57

begin a government sponsored drive of

45:00

capital and strategy to essentially

45:02

engage in

45:05

what in the 80s they did with steel, but

45:07

with AI and engage in massive AI

45:09

dumping. and that is create a ton of

45:12

LLMs that have near par technically to

45:15

US LLMs and then dump them into mark the

45:18

market you know uh kind of these openw

45:21

weight open-source LLMs that basically

45:23

do what China does and that is offer 95

45:26

97% of the premium high-end US product

45:29

for 5% of the price and then essentially

45:33

cut go for the jugular just flood the

45:37

market with openweight LLMs and AI

45:39

products for nearfree that takes down

45:43

massively erodess the margin power of

45:45

these companies takes them down and

45:48

thereby takes the US economy down. Your

45:51

thoughts?

45:52

>> So the the outlook for this year has

45:54

four major risks. Number one is the

45:57

power constraint wall. Number two is the

45:58

thing you just said which is that China

46:01

basically scales the moat on its own. As

46:04

as recently as three years ago that

46:06

scenario you just described would have

46:07

been impossible. Um, China is the

46:10

world's leader in a lot of things. You

46:12

know, fish, they've made more fusion

46:14

advances. They're ahead in genetic

46:16

testing of certain new drugs. They have

46:19

there's a really cool thing that looks

46:21

at the complexity of exports. Um, it's I

46:25

think the it's one of the Harvard labs

46:26

that does it. They've converged now with

46:28

the United States. So, the complexity in

46:31

the industrial complexity and

46:32

sophistication of their exports has

46:35

matched that of the United States. But

46:36

as recently as 5 years ago, they

46:39

couldn't figure out the semiconductor

46:41

thing. And the through a combination of

46:46

ingenuity and theft, they have now

46:49

acquired um a lot of things. There's a

46:52

long list of people that used to work

46:54

for for you know either TSMC or ASML

46:58

that are now working for Huawei. And

47:00

Huawei has announced that next year they

47:03

expect to sell to your points got a chip

47:06

cluster

47:08

that matches or exceeds the performance

47:10

of what you can get from Nvidia.

47:13

Um now it's got more it it matches the

47:17

power the chip on a per chip basis. It's

47:19

only let's say a third as powerful but

47:21

they say fine we'll just use three times

47:22

as many chips. And so that's they're

47:26

they're trying to use a combination of

47:27

brain and brawn to do that. I I that

47:30

feel that kind of still feels twina's

47:34

on a really long-term journey and I

47:36

would agree that that is very much

47:38

explicitly their goal. I want to talk

47:40

more about the your 2026 outlook. Um so

47:45

you mentioned that the number one risks

47:47

or the number one risk is power

47:49

constraints. We don't have enough power

47:51

to build all the things that we want to

47:53

build particularly AI. You said number

47:55

two is China. Uh what else should we

47:58

know in terms of risks?

48:00

>> Well, the two other ones is the the the

48:02

more that China is able to

48:07

[sighs and gasps]

48:07

rely on its own chip ecosystem, the that

48:10

means that number three risk has to be

48:12

Taiwan because um you know the the

48:17

Taiwan essentially was always

48:20

protected by the fact that China relied

48:22

90% for its advanced chips on Taiwanese

48:24

output. you know, the the day we wake up

48:27

and that number is below 50%. I think

48:29

you have to start to re-evaluate some of

48:31

the geopolitical contingencies around

48:32

this whole thing. Um, there's great

48:36

work. CSIS is the best think tank in the

48:38

world on this kind of stuff. And they

48:41

showed us some data. Something like 85%

48:44

of Chinese military assets are in the

48:47

Taiwanese Strait. They have been

48:49

partnering with Russia to do drills on

48:52

how to drop heavy equipment out of

48:54

specially designed parachutes from

48:56

helicopters. Um, you know that this is

49:01

this is moving in another direction in

49:03

another clear direction here. Uh, and

49:06

again, you don't know when and you don't

49:07

know how and you don't know why. And

49:08

maybe it's a quarantine, maybe it's a

49:10

blockade, maybe it's not a full-out

49:12

invasion. But there are going to be some

49:14

challenging times for the west

49:18

within the next 5 years as it relates to

49:21

its almost exclusive reliance on this

49:24

you know Nvidia ASML TSMC partnership.

49:27

And then the fourth one is the stuff

49:28

we've been talking about which is this

49:31

kind of collective

49:33

metaverse moment where investors in

49:35

aggregate say like okay it's not a waste

49:38

of money but the we don't we can't see

49:40

the ROI we're going to take profits

49:42

until we have a clearer vision of of

49:45

where this is going. I I'm still digging

49:48

through it. There was a for every good

49:51

paper there's a negative paper right so

49:53

that for every good paper on AI adoption

49:56

there was one that you should read it it

49:57

came from this group called MIT Nanda

49:59

NDA

50:00

>> yeah the 95% one yeah

50:02

>> yeah like you know I read through the

50:04

details on that one that uh those are a

50:07

lot of companies that that kind of tried

50:09

it played around with it and said you

50:10

know what we're just going to keep doing

50:12

things the way we're doing them

50:13

>> the other um thing that the outlook

50:15

mentions there are three forces that

50:18

will define next years market. Um they

50:21

are according to your report AI. We've

50:24

discussed that. I think everyone

50:25

understands that global fragmentation

50:27

and inflation. Describe global

50:29

fragmentation and inflation for us.

50:31

>> Let me just summarize by saying like the

50:33

the Fed is is facing a peculiar fork in

50:35

the road here. It's not a violent

50:38

differential, but there's a meaningful

50:41

differential right now between we look

50:43

at the PMI surveys, right? The ISM and

50:45

PMI surveys of prices paid. those are

50:48

going up. Uh the PMI survey is on labor,

50:51

they're going down, right? So what's a

50:53

Federal Reserve to do when you have a

50:55

dual mandate that are going in opposite

50:57

directions? Um historically, the Fed has

51:00

almost never cut rates when prices paid

51:03

surveys are going up. Why would they,

51:05

right? I mean, you'd be easing into an

51:06

inflationary environment. Um it looks

51:10

like they're going to do that and it's a

51:12

it's a huge gamble. Um the gamble is

51:15

that the inflationary increase is tariff

51:17

related and once it makes its way

51:19

through the system it will not ignite

51:21

some kind of wage price spiral and

51:23

inflation will be coming down by the

51:24

spring and the Fed will be vindicated.

51:26

But that's that's a big bet and that's

51:29

the bet that's you know that we're

51:31

looking at as we're heading into you

51:33

know the end of the year and early next

51:34

year and the markets are pricing in a

51:36

couple of cuts here uh because of that.

51:39

Um, I'm I'm less worried about tariffs

51:42

than immigration policy as it relates to

51:44

this stuff we're talking about. I I

51:47

think the president is less committed to

51:50

some of these things than he appears to

51:52

be. Um, they're they're already adding

51:56

massive numbers of products to the

51:57

exemption list of tariffs. So, I think

52:00

the tariff stuff will turn out to be

52:01

less damaging.

52:03

But the um the latest data from the Fed

52:06

is that 50,000 payroll growth is is is

52:10

inflationary. Like the nu of inflation

52:13

for wages is 50,000, right? So they

52:16

Yeah, they shut the border. We all

52:18

understand what political forces they

52:20

were reacting to. But the United States

52:22

needs people to grow. And if if if you

52:25

get wage inflation at 50,000 payroll

52:28

growth, you have a labor supply problem.

52:30

And so they're they're gonna have to

52:32

they're gonna have to make a change

52:35

soon on that one or else they're going

52:37

to have bigger problems.

52:38

>> Yeah. The report also says it says um

52:41

tariffs are here to stay no matter what

52:43

the Supreme Court rules. What are you

52:46

thinking about in terms of the Supreme

52:47

Court ruling on tariffs right now?

52:49

>> You know Gorsuch has been kind of

52:51

tilting his showing I don't know the

52:54

poker analogy because I don't play I

52:55

don't gamble. Um but what what is is it

52:58

the thing where you hold your cards and

53:00

people can see what you have or

53:01

something? I mean, he's he's been

53:03

showing his cards a little um during

53:06

during the hearing and um I think he and

53:09

Barrett will side with the Liberals and

53:13

um that would reduce the effective

53:16

tariff rate from like 15 to 7 and then

53:20

they would try to replace 2 or 3% of

53:22

them with some other clauses, but a

53:25

bunch of them get defanged and are not

53:27

so easy to replace. Do you think there

53:28

might be a ruling where they have to pay

53:30

back the tariffs to the companies the

53:31

tariffs were imposed on?

53:32

>> I do over some period of time and you

53:35

know they would make that as difficult

53:36

as possible and you know that it would

53:39

be extremely messy um you know it would

53:43

be you know think think about the

53:46

messiness of the PPP loans as people

53:48

started to kind of clean up after them.

53:50

I mean the it's it's it's a messy thing

53:52

to do. And of course the the Doge people

53:55

cut a lot of the staffing as it relates

53:57

to the enforcement and tracking of this

53:59

stuff. So one of the reasons the tariffs

54:01

haven't been quite as much of an impact

54:03

on the economy is a lot of companies are

54:05

recategorizing goods so that they fall

54:08

under different tariff buckets that they

54:11

may not necessarily supposed to apply

54:13

to. But if you've gutted the enforcement

54:15

of the people that look at that then

54:17

that's what companies are going to do.

54:20

So, um, you know, earlier in the year, a

54:24

lot of people were trying to convince me

54:26

that there was this holistic vision that

54:30

they had about what they were trying to

54:32

accomplish. And I'm I'm I've struggled

54:36

with that because I see too many

54:38

policies that conflict with each other.

54:40

Like, if you're really trying to attract

54:41

foreign direct investment, why would you

54:44

expel all of those South Korean factory

54:46

workers? There's just too many policies

54:48

that don't seem to be aligned with what

54:51

the administration says its goals are.

54:53

So, which has given me less confidence

54:55

that that they that there's a kind of a

54:57

a playlist here that is all adding up to

55:00

some big coherent grand vision. You've

55:03

got to work over time to justify how it

55:06

all makes sense and how it all plays

55:08

into a specific strategy and then which

55:11

leads you to believe okay that's not

55:13

what's happening. This is this is policy

55:16

by tweets.

55:17

>> If you have time on the weekend and you

55:18

really want to, you know, read something

55:21

interesting, the Washington Post had an

55:24

editorial recently from every single

55:28

living prior surgeon general about what

55:32

they thought about the leadership at

55:34

HHS. And uh I'm not going to go into any

55:37

more detail. [laughter]

55:38

Okay, we'll check it out on our own

55:41

time. Um just start Final question from

55:44

me. Scott might have one as well. Um,

55:47

we've talked about some kind of

55:49

concerning stuff on this podcast and you

55:51

said that you thought it was, and

55:54

correct me if I'm wrong, you thought it

55:55

would be unlikely to see some sort of

55:57

profit taking event to the tune of 10 to

56:00

12 to 15%.

56:02

>> No, that's the one I thought was likely.

56:04

>> I I misspoke. That's what I meant. That

56:06

is a likely scenario. You That's almost

56:08

your base case for next year. and

56:11

perhaps there is a a more shocking event

56:14

like 40%. But you're thinking, you know,

56:16

you're going to see 10, 12, 15%

56:18

correction. Um, for for someone who has

56:21

kind of a regular portfolio, a regular

56:23

investor who is, you know, dollar cost

56:26

averaging into the market, into the S&P,

56:28

they've been doing that for a few years,

56:30

maybe they haven't looked at bonds too

56:32

closely in the past. What is your

56:34

general advice for those people going

56:37

into 2026? How should they think about

56:39

their portfolio and how should they

56:41

invest right now?

56:42

>> Well, you know, based on what we've just

56:44

discussed, it would make sense to start

56:46

accumulating some

56:48

dry powder to take advantage of whatever

56:51

opportunities may exist. A lot of times

56:53

when you get selloffs like that, a bunch

56:55

of things sell off. All of a sudden, you

56:57

start seeing industrial and utility

57:00

preferred stock sell off two to three

57:02

points, which is can be the equivalent

57:04

of 50, 60, 80 basis points. So, you

57:07

know, um having having some spare cash

57:12

and and and credit to be able to draw on

57:15

when these things happen can be helpful.

57:17

Um a lot of these things tend to be very

57:19

v-shaped, right? If you look back at

57:21

almost every single one of these

57:23

corrections, including the one that

57:24

happened last year, there's this rapid

57:27

violent unwinding of risk. Uh I think a

57:30

lot of the hedge fund, the big risk

57:32

parity funds are kind of um partially

57:34

responsible for that. But then it tends

57:36

to snap back where it comes back roughly

57:39

at the same speed at which it declined.

57:41

In in that regard,

57:43

individual investors have an advantage

57:45

over some of the large institutional

57:47

investors. I mean, the average the

57:48

average endowment or foundation meets

57:51

quarterly. They're they're not even set

57:53

up to respond to some of these things.

57:55

>> Yeah.

57:55

>> So, um I think it's, you know, in retail

57:58

investors have at least the flexibility

58:00

to try to act when these things happen.

58:02

>> Make the bull case for 2026. you start

58:05

seeing more concrete evidence of of AI

58:10

adoption

58:12

that companies are willing to pay for

58:15

and

58:16

you you you start seeing

58:19

productivity benefits that are based

58:21

equally on revenues and not entirely on

58:24

the backs of lower rates of hiring. Um,

58:30

China starts to cut back on its excess

58:33

production policy. They announced this

58:35

involution campaign a few months ago

58:37

that's designed to make Chinese

58:39

companies more profitable by telling

58:40

them to stop overproducing. I'll believe

58:42

it when I see it. Um, you get fiscal

58:45

stimulus in Europe in part because Trump

58:49

is basically forcing them to defend

58:50

themselves. Uh, another policy that I

58:52

think is long overdue, um, Europe agreed

58:56

in 2006 to spend 2% of GDP on defense

58:58

and it took them until 2021 to finally

59:01

get there. And, uh, so you're starting

59:04

to see more defense spending in Europe,

59:06

which is stimulative. And um and then in

59:10

the US the Fed is vindicated

59:14

where inflation starts to roll over

59:17

aided and emedded by an enormous amount

59:20

of multif family and single family real

59:22

estate supply uh pushing down housing

59:25

related inflation.

59:27

and and the administration figures out

59:31

through some combination of relaxation

59:34

in certain regulations and things like

59:37

that

59:38

to to ramp up US oil and gas production.

59:42

So energy prices come down. So that's

59:45

that's kind of your your bull case.

59:48

Michael San is the chairman of market

59:49

and investment strategy for JP Morgan

59:51

Asset and wealth management. a global

59:53

leader in investment management and

59:54

private banking with $6 trillion dollars

59:56

of client assets under management

59:58

worldwide. He's responsible for the

60:00

development of market and investment

60:02

insights across the firm's institutional

60:04

funds and private banking businesses.

60:05

Michael joined JP Morgan in 1987. His

60:09

previously served as chief investment

60:10

officer for the firm's global private

60:12

bank and head strategist for emerging

60:14

markets fixed income. And you can

60:15

discover more of his insights by reading

60:17

Eye on the Market or listening to his

60:19

podcast by the same name, Michael. Uh,

60:23

always really insightful. Uh, really

60:25

appreciate your time. Thank you.

60:26

>> Good to see you, Michael.

60:27

>> Thank you very much. Good to see you,

60:28

Scott.

60:38

>> Ed, what' you think?

60:39

>> Uh, I thought that was very I He knows

60:41

everything, which is so It's so helpful.

60:44

Um I mean he's kind of overseeing one of

60:48

the largest

60:50

portfolios in terms of

60:51

aumumumumumumumumumumumumumumumumumumumum

60:51

in the world. So I mean he's got so much

60:53

data.

60:55

Um I I I'm

60:57

I think I agree with him on pretty much

60:59

everything he said. I mean our reactions

61:02

to interview I thought it was really

61:04

striking but I didn't feel quite as

61:06

bearish um as as Professor Deodum was

61:09

when we interviewed him. I feel like

61:12

Michael's sentiment is more where I'm at

61:15

right now in terms of valuations. Um,

61:18

where I'm kind of expecting some sort of

61:21

correction, but not something that is

61:23

kind of going to cause a a major major

61:26

crisis. So,

61:29

yeah, I thought that was informative,

61:31

made me feel maybe a little better. I

61:34

think he's very measured because he the

61:36

last thing he wants to do is spook, you

61:38

know, the $2 trillion in value or in

61:41

assets they oversee. But he sounded

61:44

he sounded measured and a little bit I

61:47

don't want to say nervous but and I

61:50

might be it might be just confirmation

61:51

bias but whether it's Sam Alman or Alex

61:53

Kart getting defensive or deodorant

61:56

saying

61:58

Asworth is the least panicked person

61:59

I've ever met and and then Michael sort

62:04

of Michael seems really measured not to

62:08

a fault but really measured like Okay, I

62:12

don't want to I don't want to spook all

62:13

the capital I oversee, but I'm having a

62:16

tough time defending this market. Um,

62:20

and I think part of the reason he's in

62:22

the position he is is this guy is just

62:25

he's very measured. He just doesn't

62:26

scare easily, right? But I don't know.

62:30

And again, I I can't figure I can't sus

62:33

out [snorts]

62:34

like when I hate everyone around me, I

62:36

know it's my depression. like when I

62:38

literally hate everybody. Um I know it's

62:41

my depression speaking and I'm pretty

62:44

convinced now we're in for a serious

62:46

pretty rocky road in the next 12 months

62:48

and I can't I can't sus out my old man

62:51

boomer anger from the actual data. But

62:54

the data I just think looks I think if

62:57

the market goes down 40% if the NASDAQ

62:59

goes down 40% in the next 90 days or 100

63:01

we're going to be like well of course it

63:03

did. I think it's going to be

63:05

like the most obvious thing in the

63:07

rearview mirror that it happens. So, but

63:09

anyways, back to Michael. I I like him

63:11

because he's measured and just I like

63:13

that he pauses and thinks about

63:15

questions. He wants to answer them

63:18

answer them correctly.

63:19

>> I appreciate that too. Yeah. And and you

63:21

know what he saids with what you're

63:24

saying. I think he he is anxious and

63:27

kind of expressed that. I mean, he said

63:29

that his base case is a 10 to 12 to 15%

63:32

correction, which is kind of a big deal

63:35

in and of itself. I mean, the question

63:36

is, do you think it's going to be like

63:38

that or do you think it's going to be

63:39

40%, which again, he didn't rule out. He

63:42

said that it was unlikely. He doesn't

63:44

think it's going to happen, but he

63:45

didn't fully rule it out. I think the

63:47

the the the part that he's gotten right

63:51

is that there is crazy amounts of

63:53

leverage and debt that's being

63:55

accumulated, but only in certain

63:58

contained spaces. So, he mentioned

64:00

Oracle. I've talked about how Open AI,

64:03

they haven't gotten there yet, but

64:05

they're going to have to raise huge

64:07

amounts of debt in order to support the

64:09

amount of um AI that they want to build

64:12

and and spend on over the next few

64:13

years.

64:14

uh he mentioned Blue Owl and the idea

64:17

that Meta is raising debt but using

64:19

these SPVS to sort of protect

64:21

themselves. So I think where he's

64:23

probably right is that the debt and the

64:26

leverage that we're seeing isn't quite

64:28

as systemic as we've seen in previous

64:31

crises which is probably going to be a

64:33

good thing. It means that whatever

64:35

correction we see is going to be at

64:37

least more contained than it has been in

64:40

previous crises. I think that's quite a

64:43

a a sound analysis. The question then

64:46

becomes, well, how much more debt are we

64:49

going to see in the pipeline? I mean, is

64:51

it just Oracle or are we going to start

64:53

seeing crazy amounts of debt from Amazon

64:55

and Microsoft and Meta? Are they going

64:58

to ramp it up? Um, that that that's sort

65:01

of the next question. But in terms of

65:04

his views on like what the implosion

65:06

will look like, um [music] I think he I

65:10

think he's pretty spot on.

65:12

Thank you for listening to Prof Markets

65:14

from Prof Media. If you liked what you

65:16

heard, give us a follow and join us for

65:19

a fresh take on markets on Monday.

65:22

[music]

Interactive Summary

This video discusses the current state of the economy, focusing on the AI bubble, potential market corrections, and global economic fragmentation. Michael Semblas from JP Morgan Asset and Wealth Management provides insights into these topics, contrasting his views with more bearish predictions from other economists. Key discussion points include the sustainability of the AI boom, the role of tech companies in GDP growth, the potential for market downturns, and geopolitical risks associated with China and Taiwan. Semblas also touches upon government intervention in the economy, the impact of tariffs, and the Federal Reserve's challenges in managing inflation and labor market issues. The conversation highlights concerns about high valuations, excessive debt accumulation in specific sectors, and the potential for significant market corrections.

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