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Week at wsj.com. Hey everyone, I'm

0:59

Tellis Dimos. I write for the

1:01

Wall Street Journal's Heard on the Street

1:03

Column. And this is wsj's Take on

1:05

the Week, the weekly show where we

1:07

give you a leg up on the

1:10

worlds of money and investing. Each week,

1:12

we bring you conversations with insiders and

1:14

from inside the Wall Street Journal's newsroom

1:16

about money, finance, finance, banking, Bond stocks,

1:19

all that good stuff. And this week,

1:21

I'm so excited to be joined by my longtime

1:23

colleague and Wall Street Journal reporter Peter

1:25

Rudigier. Peter's joining us while Gungen's

1:27

away. Peter, welcome. Thanks for having

1:29

me, Tellus. Well, we're going to throw

1:32

you into the deep end and we're

1:34

going to talk about what we, I

1:36

seem to always talk about and that

1:38

is inflation. We've got additional data. We

1:40

have the personal consumption expenditures index, the

1:42

PCE, which is not necessarily super different

1:44

from the CPI and the producer price

1:46

index, but it is the thing that

1:48

the Fed looks at. It's the most

1:50

comprehensive inflation measure. And so, of course,

1:53

the CPI came in a little hot

1:55

for January. We'll see if the PCE

1:57

does as well. But I think what's

1:59

interesting is that... There is still an expectation

2:01

in the market that the Fed is going

2:03

to cut rates at some point this year.

2:05

How can that still be the base case,

2:07

do you think? You know, it surprises

2:10

me. I think one interesting tidbit into

2:12

how inflation has been kind of sticky

2:14

was in the journal this week about

2:16

something called the egg clearinghouse. The price

2:18

of eggs is obviously a meme on

2:20

inflation, but unbeknownst to me. There is

2:22

a Wall Street of eggs where farmers

2:24

and... buyers of eggs can come together

2:26

and try to get extra eggs. And

2:29

right now there's really no sellers. It's

2:31

all buyers. The supply has totally gone

2:33

away. The demand is still through the

2:35

roof. That's just a little capsule of the

2:37

inflation picture as it still is. So yeah, I

2:39

am as surprised as you are that a lot

2:41

of investors are still expecting some

2:43

more rate cuts. If there's a case to

2:46

be made that we're once again looking

2:48

at. transitory, teen transitory inflation and

2:50

not the kind of like sticky

2:52

long-term price rise that's driven by

2:54

like kind of fundamental factors. But

2:56

look, there's something going on in

2:58

that market and that's what's driving

3:00

up the grocery basket, which as

3:02

we know was like one of

3:04

the major factors in January's kind

3:07

of hot reading. Yeah, and just

3:09

for future inflation expectations, you're seeing

3:11

some restaurants now adding surcharges to

3:13

eggs, putting lines on the menu

3:15

saying, hey, it's going to people's

3:17

consciousness. So now we're expecting more price rises

3:19

for those to continue. What does that do

3:21

for inflation expectations? That's a great point. Inflation

3:24

is as much about psychology as it is

3:26

about the numbers. Well, one inflation that I

3:28

think we want to kind of think about

3:30

for this upcoming week as well is home

3:32

price, home price inflation. Obviously, we all kind

3:34

of benefit, you know, anybody who's a homeowner

3:36

likes to see that, but I think the

3:39

market though. would like to maybe see home

3:41

prices start to slow down. We get

3:43

a reading this upcoming week, the S&P

3:45

Core Logic Case Shiller National Home Price

3:48

Index, kind of the benchmark I would

3:50

say for home prices, that's still rising,

3:52

but it was slowing going into last

3:54

year. And the reason I think that

3:57

maybe slowing prices are good is because

3:59

that might... open the market a little

4:01

bit for buyers and sellers. So much

4:03

of the market, a lot of companies

4:05

really depend on sales, right? Buyers and

4:07

sellers, people who write mortgages, brokerages that

4:09

make deals. We're going to get earnings

4:12

reports from Home Depot and Lowe's, right?

4:14

Those companies benefit when people go to

4:16

the store to fix up their home

4:18

or get a new one. And I

4:20

wonder if those prices, if home prices

4:22

do slow down gently, obviously crash wouldn't

4:24

be good. Combined with, you know, now...

4:26

we've got mortgage rates back below 7%

4:28

they're back in the six-ish percent, the

4:30

high six is, if that's enough maybe

4:32

to start opening the market a little

4:35

bit. I wonder how durable you think

4:37

that fall on mortgage rates is. We've

4:39

seen kind of long bond rates kind

4:41

of stay pretty elevated. I think those

4:43

are pretty correlated with mortgage rates historically,

4:45

right? So if those stay pretty high,

4:47

how much relief do you think consumers

4:49

can expect on... kind of mortgage rates

4:51

and mortgage payments. Yeah, that is a

4:53

great point. That is a great point.

4:55

Though I will say that even though

4:58

rates didn't go back to the two,

5:00

three percent... kind of craziness that we

5:02

remember from several years ago, you know,

5:04

the market did pick up late last

5:06

year when rates were closer to 6%.

5:08

So I don't think it'll take a

5:10

huge drop to your point as long

5:12

as those longer term interest rates, which

5:14

is really what mortgages are priced off

5:16

of, stay up. And that, you know,

5:18

has as much to do with like

5:21

inflation and the Fed as it does

5:23

with, you know, longer term expectations for

5:25

growth. The U.S. budget, you know, fiscal

5:27

conversation. But I still think, though, that

5:29

it's worth paying attention to those earnings

5:31

this upcoming week from Home Depot and

5:33

Lowe's, as well as any, like, kind

5:35

of realtors that report, see what their

5:37

outlooks are for the year. Peter, though,

5:39

I want to turn the conversation to

5:41

another kind of earnings, and that is

5:44

for kind of AI-related companies. And I'm

5:46

really interested in your perspective on this,

5:48

because your job here at the journal

5:50

is you write about hedge funds. And

5:52

these are, you know, allegedly, purportedly, you

5:54

know, some of the smartest investors in

5:56

the market, you know, they're the sharks,

5:58

we're the chum, and you wrote a

6:00

fascinating story last year about how hedge

6:02

funders had really keyed in on the

6:04

art. intelligence trend, but weren't necessarily just

6:07

looking at, you know, invidia or even,

6:09

you know, Microsoft or, you know, meta,

6:11

the company's investing in AI, but they

6:13

were looking at that from a different

6:15

angle. Tell us about what they were

6:17

looking at work for. Sure. So, you

6:19

know, when you and I hear AI,

6:21

we think in video, they're reporting earnings

6:23

this coming week, it'll be a big

6:25

bellwether for the whole rest of the

6:27

market, but a lot of hedge funds,

6:30

even those that... bet on tech companies

6:32

gravitated to this pretty snoozy sector of

6:34

the market, power companies and power stocks,

6:36

you know, companies that literally just make

6:38

electricity. And that's because the biggest bottleneck

6:40

in the AI supply chain isn't a

6:42

lack of invidia chips or data center

6:44

capacity. It's literally the power to power

6:46

those data centers to train the models

6:48

to answer your chat GPD queries. So

6:50

we had a lot of hedge funds

6:53

pile into stocks like Vistra, which is

6:55

also reporting earnings this coming week. constellation

6:57

energy which reported earnings this past week.

6:59

And as those companies were able to

7:01

charge more for power, selling power to

7:03

companies like Microsoft and Amazon, they were

7:05

able to just pocket more of that

7:07

for themselves. So their profits went way

7:09

up. That's fascinating that they look at

7:11

this from a different angle, but I

7:13

do want to know when a hedge

7:16

fund manager, like a really kind of

7:18

smart long-term investor looks at earnings, right?

7:20

when they're looking at, when in video

7:22

reports, what are they looking for? They're

7:24

not just looking at like, okay, what's

7:26

the sales number? They already kind of

7:28

feel like they know what that's gonna

7:30

be. What are they actually listening for?

7:32

They're listening for the future. What is

7:34

management saying about what sales are going

7:36

to be next quarter, next year? And

7:39

if you think back a couple years,

7:41

what really kind of kick-started the rally

7:43

in Invidia was when they reported some

7:45

outlook guidance for sales that was way

7:47

above what Wall Street had expected what

7:49

Wall Street expects are going to earn.

7:51

You're going to see a pretty big

7:53

move in the stock usually. That's interesting.

7:55

And that's often I feel like when

7:57

you open up the slides when a

7:59

company reports earnings. It's like the first

8:02

page has the kind of numbers that

8:04

everyone knows. Oh, sales and profit. It's

8:06

that last page where they're like 2025.

8:08

guidance. Yeah, you got to skip to

8:10

the end. The answer isn't in the

8:12

front of the book. It's in the

8:14

back of the book. Is that how

8:16

you read most books? You just go

8:18

right to the... Yeah, who needs to

8:20

spend? Just bring me the heat. Well,

8:22

I think that within this AI conversation

8:25

there's a lot going on and the

8:27

way that hedge funds have looked at

8:29

the longer term questions about power consumption,

8:31

the fundamental infrastructure that will support a

8:33

transition to, you know, using... using intelligence

8:35

and stuff for day-to-day tasks. We dove

8:37

into that pretty deep with our guest

8:39

this week. Our guest is Chris Hansen.

8:41

He is the founder and portfolio manager

8:43

of a hedge fund, Valiant Capital Management.

8:45

And Chris talked to us about not

8:48

only big tech companies that are investing

8:50

a lot in AI, like... the Microsofts

8:52

and Metas of the World, and chipmakers

8:54

like Invidia, but about power companies, including,

8:56

like you said, Vistra and Constellation. These

8:58

are companies that provide the electricity that,

9:00

like you said, fuels the data centers

9:02

that are needed to support AI. Chris

9:04

was gracious enough to talk to us

9:06

while he was on the road about

9:08

all of this. And we should note

9:11

that Valiant is invested in a lot

9:13

of tech companies, such as Invidia, Amazon,

9:15

and Microsoft, and in some of the

9:17

power companies that we will talk about.

9:19

have that conversation with Chris Hansen. This

9:21

podcast is brought to you by Northern

9:23

Trust for where wealth goes next.

9:25

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9:28

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9:30

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9:32

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9:35

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9:37

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9:39

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9:42

Whatever your ambitions for your wealth,

9:44

Talk to a Northern Trust advisor

9:46

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your family there. Learn more at

9:53

Northern Trust.com/institute. Today

10:00

we are with Chris Hansen.

10:02

He is the founder of

10:04

a hedge fund, valiant capital

10:07

management. Chris manages a fund

10:09

that's invested in power and

10:11

power adjacent sectors, stocks such

10:13

as G.E. Vernova, Mitsubishi Heavy

10:15

Industries, Vistra, Tailen Energy, Wildan

10:17

Group, among many others, I'm

10:19

sure. Chris, welcome to the

10:21

show. Thanks for having, guys.

10:23

Chris, last year you said

10:25

that you saw what was

10:27

the most hitable pitch in

10:29

your history as a hedge

10:31

fund manager. You also called

10:33

it the most compelling thematic

10:35

investment in your 30 odd

10:37

years in the business. This

10:39

was, of all things, power,

10:41

power companies. To most investors,

10:43

that would be kind of

10:45

a news fest, right? Not

10:47

very hedge fundy, electricity, how

10:49

fast could that possibly be

10:51

growing. But tell us, what

10:53

was it that you were

10:55

seeing? Our thoughts on power

10:57

really developed initially from our

10:59

work on AI. And the

11:01

more work that we did

11:03

on AI, proceeding and immediately

11:05

following the launch of chat,

11:07

GBT, and in video, like

11:09

a lot of other people,

11:11

let us down the path

11:13

of just really trying to

11:15

understand the power consumption forecasts,

11:17

how much power the forward

11:19

forecast of data centers and

11:21

in video. And we had

11:23

kind of an aha moment

11:25

in that we realized there

11:27

wasn't going to be enough

11:30

power to meet the data

11:32

center demands and GPU demands

11:34

that were being forecasted. So

11:36

that really set off for

11:38

us a path to try

11:40

to understand a sector that

11:42

we really hadn't spent a

11:44

lot of time on. And

11:46

I don't really think a

11:48

lot of other people had

11:50

spent a lot of time

11:52

on and that's understandable if

11:54

you're looking at a sector

11:56

that had. 10, 15, 20

11:58

years of very low growth.

12:00

And I still don't think

12:02

people have grasped the extent

12:04

of the problem. the opportunity.

12:06

So even just for the

12:08

economy as it stands today,

12:10

you know, if you just

12:12

took population growth and the

12:14

devices and things we all

12:16

do every day, you're saying

12:18

that we've collectively under-invested in

12:20

in power generation and it's

12:22

difficult and it takes a

12:24

long time. So even without

12:26

some big kind of driver

12:28

like AI, you're saying we

12:30

don't have enough electricity generation.

12:32

Let's put some numbers behind

12:34

it. Our forecast is that

12:36

power demand. between now and

12:38

2030 will grow at about

12:40

4%. Those forecasts are based

12:42

largely on forecasted approved and

12:44

budgeted plans from grids and

12:46

electrical utilities regulated and unregulated

12:48

around the country. They're not

12:50

valiant estimates. They're a summation

12:52

of scraped and downloaded data

12:55

from these companies and grids.

12:58

We can probably only add about

13:01

2% and it is not just

13:03

generation. I really want to make

13:05

sure that people understand that you

13:08

cannot build Generation without transmission and

13:10

distribution What was it that happened

13:12

last year to some of these

13:15

power stocks? With the benefit of

13:17

hindsight now, you were talking about

13:19

this investment last year, now we

13:22

know that some power stocks, particularly

13:24

nuclear power stocks, like Constellation and

13:26

Vistra, surged in 2024. Constellation was

13:29

up more than 90% last calendar

13:31

year. Vistra was up well over

13:33

200%, both top 10 S&P 500

13:36

stocks. What was the catalyst that

13:38

kind of woke people up to

13:40

this? What you described as this

13:43

kind of slow moving thing that...

13:45

you know really we all should

13:47

have seen coming like what what

13:50

catalyze those stocks in 2024 would

13:52

you say? I would say that

13:54

part is pretty simple and is

13:57

fairly well understood in that the

13:59

hyperscalers Probably

14:01

have a collection of the smartest

14:04

people in the world working for

14:06

them. I want to say hyperscalers

14:08

just can you define that for

14:11

us that that's like the invidious

14:13

right those no Amazon Facebook or

14:15

meta Grock trying to build out

14:18

their data centers Microsoft they are

14:20

obviously Google in the cloud business

14:22

and have been building Cloud-based computer

14:24

now, AI compute for a very

14:27

long time. So they identified the

14:29

power bottleneck. And so they started

14:31

reaching out and trying to find

14:34

solutions to ensure, you know, Azure

14:36

and Amazon both reached capacity on

14:38

Data Center last year. So naturally

14:41

this is one of the most

14:43

acute problems. And as they tried

14:45

to solve this problem, they started

14:48

trying to grab power where they

14:50

could. And nuclear, if you were

14:52

just to think about it at

14:55

a... Super basic level. It's clean.

14:57

No one wants to live near

14:59

a nuclear facility. So there's going

15:02

to be very little permitting issues,

15:04

you know, or environmental approvals required

15:06

from putting a data center on

15:09

a nuclear site. Chris, I wanted

15:11

to ask you, you know, we're

15:13

in a moment where, you know,

15:16

investors are moving a little bit

15:18

away from ESG considerations. Is there

15:20

a benefit for nuclear companies from

15:23

this movement? Of course, nuclear is

15:25

the cleanest fuel that we have.

15:27

You're talking about the time to

15:29

build a new large nuclear reactor

15:32

probably being on the realistically on

15:34

the order of 20 years Maybe

15:36

15, but you can imagine all

15:39

the like Where are you going

15:41

to put one of the things?

15:43

Well with the pushback B all

15:46

the approvals required Then we have

15:48

these small module nuclear reactors SMR

15:50

surcalled which are at least probably

15:53

eight years away much smaller probably

15:55

easier to get approved not sure

15:57

the technologies completely there Still will

16:00

not be enough not going to

16:02

solve the problem problem. And if

16:04

you think about it from a

16:07

large IP, which would be a,

16:09

you know, independent electricity producer, you

16:11

could build a natural gas, large

16:14

scale natural gas site. We have

16:16

plenty of natural gas, which is

16:18

also very clean. And you could

16:21

probably have that up and running

16:23

six, seven, eight years with a

16:25

defined cost, defined time frame, and

16:27

defined ROI for you. If

16:30

you want to build a

16:32

nuclear facility, how do you

16:34

know where power prices are

16:36

going to be in 25

16:38

or 30 years to make

16:40

this calculation? So new nuclear

16:42

is really difficult and that

16:44

also makes existing nuclear more

16:46

valuable. One of the things

16:48

that happened, and we shouldn't

16:50

miss this point because it's

16:53

important not just to stocks,

16:55

but to America in general,

16:57

is the regulator. called

16:59

FERC if you look back at

17:01

the nuclear deal between Amazon and

17:03

Talon. It says something very important.

17:05

After approving their initial deal, the

17:08

upgraded capacity that they were going

17:10

to take, they said, wait a

17:12

minute. Given the capacities constraints that

17:14

we see on new generation and

17:16

transmission and distribution, it doesn't really

17:19

make sense to allow the hyperscalers

17:21

to go around the country and

17:23

just... pull out capacity for themselves

17:25

because everybody else is getting left

17:27

holding the bill whether it's industrial.

17:30

Well, the regulator stepped in to

17:32

sort of say, let's slow this

17:34

down. Wow. Yeah, we need to

17:36

slow it down till we can

17:38

figure this out. And you at

17:40

least need to be bringing new

17:43

capacity into the market. So the

17:45

answers aren't clear. I just say

17:47

for for an investor who'd watched.

17:49

those nuclear companies kind of skyrocket

17:51

last year. Is it kind of

17:54

too late would you say for

17:56

them to get into them or?

17:58

Should an investor just sort of

18:00

think about these as a long-term

18:02

play and not be thinking about

18:05

the 2025, you know, kind of

18:07

repetition of 2024? How would you

18:09

describe the right way to think

18:11

about those stocks at this point? I

18:13

would say that every investor should

18:16

make their own judgment, of course,

18:18

and I'm not in the business

18:20

to dole out stock-specific advice to

18:22

people. But if you... are interested in

18:24

these stocks you should remember that this

18:27

is a very long-term thesis it's not

18:29

the type of things you want to

18:31

be trading quarters over and the

18:34

cost to operate the nuclear

18:36

facility are relatively fixed there is

18:38

going to be a huge amount of

18:40

cash flow and predictability of that cash

18:42

flow that is going to flow out

18:45

for these companies over like a 20 year

18:47

period so the stocks have moved up

18:49

in anticipation of that But I still

18:51

think if you have a very long-term

18:53

perspective, they will be great things to

18:56

own. I do think there's better things

18:58

to own. I want to make that

19:00

clear in this sector that will also

19:02

be very long-duration, great bets. But I

19:04

think that's the framework that you should

19:06

use for your analysis. Chris, I do want

19:09

to ask you about some of those

19:11

opportunities, but maybe first, a more recent

19:13

development that hit some of those power

19:15

stocks was a few weeks ago when

19:18

news broke that the Chinese model Deep

19:20

Seek was said to run. on a

19:22

fraction of the power that competitors run,

19:24

we saw a big sell-off in tech

19:27

and power stocks. What did that development

19:29

do to kind of your thesis on

19:31

the whole sector there? I would say

19:33

the first thing I would say about any

19:35

thesis that we would have is that

19:37

we're, it's important to always

19:40

be intellectually curious and open

19:42

to new information and not get

19:44

grounded in any biases you have.

19:46

So I think we have a

19:49

very few unique takeaways. We did discussions

19:51

in the subsequent just three

19:53

days with 15 AI researchers,

19:55

deep secretly showcase was reasoning

19:57

and the power of a

19:59

reason. model, which is largely

20:02

a new engineering technique

20:04

for inferencing. So while they

20:06

may have figured out a way to

20:08

build the model cheaper, the way that

20:11

we all interface with the

20:13

model is by asking a

20:15

question, and that's called inferencing.

20:18

And what Deep Seek's reasoning

20:20

does is basically keep asking

20:22

a question trying to find

20:24

the best fit for that

20:27

answer. A reasoning question.

20:29

Based on the research we've done

20:31

and really just hearing from other

20:34

people testing, Deep Seek versus

20:36

Lama 3, uses about almost

20:38

90% more compute and power

20:40

than a normal inferencing request.

20:43

And I don't think that that

20:45

part is well understood. So it

20:47

is more energy intensive, even

20:50

if it lessens the burden on

20:52

the model building, it is increasing

20:54

the burden for the same request.

20:57

The more useful it gets. The

20:59

more requests we're going to

21:01

submit. And the more requests

21:03

we submit, the more commute, compute,

21:06

and power we're going to use. We've

21:08

got to take a quick break, and

21:10

when we come back, we'll have one

21:12

final question for Chris Hansen.

21:14

This podcast is brought to you

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21:54

The Trump administration says that it wants an

21:56

all of the above energy strategy for

21:58

the US. Is there a... form of

22:00

energy that you see as

22:03

benefiting the most from that

22:05

kind of approach? Definitely. We

22:07

have plenty of natural gas. It's

22:09

clean, widely available. So the longer

22:11

term answer for the U.S. I

22:13

think is natural gas. Maybe ultra

22:15

long term might be nuclear, but

22:17

for the time period of which

22:19

your listeners are listening, I think

22:21

it's natural gas. And I think

22:24

when we look back in 20

22:26

years from now. That will have

22:28

proven to be the thing that

22:30

gets us through. Well, we've got

22:32

some one year, two year, 20

22:34

year, 50 year ideas here. Chris,

22:36

thanks so much for joining us.

22:38

This has been fascinating and we

22:40

really appreciate it. Thank you guys

22:43

for having me. It's been my

22:45

pleasure. Thanks, Chris. And

22:47

that's everything you need to know

22:49

to take on your week. This

22:51

show is produced by Trina Manino

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and Jessica Fenton with help from

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Michael also wrote our fantastic theme

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development producer, and Scott Salaway and

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Chris Zinslie are the deputy editors.

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Velana Patterson is the head of

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news audio for the Wall Street

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Journal. For even more, head to

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WSJ.com. I'm Tellis Demes. Do

23:18

you remember there was like during like

23:20

Saturday morning cartoons they would play like

23:23

a sort of like ad council ad

23:25

like the incredible edible egg? The incredible

23:27

edible egg. Yeah. The incredibly expensive egg.

23:30

They should bring it back. This podcast

23:32

is brought to you by Northern Trust

23:34

for where wealth goes next. Modern wealth

23:37

is more complex than ever. Is your

23:39

wealth manager ready for those conversations? That's

23:41

why Northern Trust created the Northern Trust

23:44

Institute, a research center dedicated to surfacing

23:46

new insights and the best financial advice

23:48

to serve your unique needs. Whatever your

23:51

ambitions for your wealth, talk to a

23:53

Northern Trust advisor about where the world

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