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Speaker 1: Bloomberg Audio Studios, Podcasts, radio News, Bloomberg Money.

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Speaker 2: This is the Bloomberg Money Podcast. I'm Tom Keen with

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Speaker 2: Scarlett Foo. Join us each week for a smart look

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Speaker 2: at the forces shaping your financial life. On personal finance,

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Speaker 2: on retirement and wealth management. We will explore how people

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Speaker 2: are earning, investing, and building wealth. We are live Fridays

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Speaker 2: at noon Eastern on Bloomberg Television. Subscribe to the podcast

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Speaker 2: wherever you listen, and is always on the Bloomberg terminal

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Speaker 2: and the Bloomberg Business App. We've got a Bloomberg panel,

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Speaker 2: so worthies here to get us start to day.

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Speaker 3: David Gura is with us.

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Speaker 2: Lots to talk about with him really closer to the

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Speaker 2: election in November, Man Deep saying hasn't slept in the

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Speaker 2: three days.

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Speaker 3: He joins us with Bloomberg and tells you two were

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Speaker 3: just together, Yes we were Technology show.

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Speaker 4: Well, yeah, thank you, thank you.

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Speaker 3: And with us today is Katherine Greyfield.

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Speaker 2: Katie Greyfield, expert on ETFs and I got out the

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Speaker 2: surveillance rolodex and the Bloomberg money both on Rolodex, and

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Speaker 2: I said, who knows about Trump accounts? And we had

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Speaker 2: exactly one person within the system.

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Speaker 4: Ready to look it.

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Speaker 3: Are you going to have a Trump account with a

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Speaker 3: newly issued child?

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Speaker 1: I mean it's for children kids born between twenty twenty

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Speaker 1: five and twenty twenty eight, So I'm in the sweet

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Speaker 1: spot here.

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Speaker 4: She gets a thousand bucks. Yeah, it's like an extra

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Speaker 4: thousand I would never say.

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Speaker 3: No, but critically here grandparents could put money in.

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Speaker 1: Yes, but only up to five grand a year a year, yes, but.

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Speaker 2: They can do that till the kids eighteen or twenty

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Speaker 2: or that. This is a building account. It goes into ETFs.

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Speaker 2: How big a deal is this.

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Speaker 3: For Eric belchuness world.

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Speaker 1: I mean he's just been on fire this week, as

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Speaker 1: Scarlett who knows well since we co.

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Speaker 5: Anchor ETFIQ with him.

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Speaker 1: I mean, it is really interesting that the five initial

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Speaker 1: accounts that were selected were ETFs. There's one default account

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Speaker 1: to start.

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Speaker 5: That's the ticker is spy M. It's a State Street

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Speaker 5: S and P five hundred ETF.

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Speaker 1: The fee, the annual fee on that account is just

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Speaker 1: two basis points. That's point two percent, and that's pretty

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Speaker 1: much I think why it was chosen.

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Speaker 5: It's super cheap, so baby Greyfeld is going to win.

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Speaker 2: There you go the ETF market is extraordinary. I mean,

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Speaker 2: it just builds out and builds out. What I think

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Speaker 2: is cool is if the Trump account extends out into

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Speaker 2: the like the Gura offspring, so it goes from one

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Speaker 2: to two years, you know, they build it out of that.

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Speaker 6: Well, the industry loves what's happening, and we really see

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Speaker 6: that with State Street and all the other etf issuers

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Speaker 6: as well. Of course, when we talk about ETFs, I

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Speaker 6: want to bring in man deep here, especially with the

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Speaker 6: start of sk Heinex trading, there are a lot of

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Speaker 6: ETFs that are really tied to sk Heinex's performance and

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Speaker 6: memory chip makers as a whole, and this just kind

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Speaker 6: of supercharges that obsession.

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Speaker 4: It does.

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Speaker 7: And look, we heard quite a few new terms today

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Speaker 7: from the chairman's and of view memory as a service.

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Speaker 3: That really caught my attention.

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Speaker 7: You know, we talk about memory in the context of

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Speaker 7: a commodity, and you know, with booms and bus he

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Speaker 7: sounded a lot more confident in terms of one he

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Speaker 7: has visibility to this cycle in terms of extending through

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Speaker 7: the end of the decade, and also new things like

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Speaker 7: memory as a service where they're thinking about new business

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Speaker 7: models in terms of kind of just being the memory

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Speaker 7: provider and kind of doing sometime.

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Speaker 3: We're just going out to a new high keep talking, man.

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Speaker 6: Yes, wait, South Korea is kind of the at the

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Speaker 6: center of the AI trade right now, right, I mean

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Speaker 6: they are really where the market is booming. The South

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Speaker 6: Queen stock market that costs ME is the world's best

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Speaker 6: performing index. There's a lot of retail participation in that market,

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Speaker 6: and that's kind of spilling over to the rest of

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Speaker 6: the world.

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Speaker 3: It is.

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Speaker 7: And look, when it comes to HPM, you have to

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Speaker 7: look at the exposure. So Skehinex has told us they

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Speaker 7: have fifty seven percent market share, So if that is

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Speaker 7: the hot part of the AI market, then they have

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Speaker 7: a much bigger market share than a Micron, which is

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Speaker 7: being on a tier of you.

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Speaker 3: Yeah, this is way too technically. He lost me with

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Speaker 3: the HGM.

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Speaker 5: Yeah, all that the two of you.

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Speaker 3: I want to talk about this.

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Speaker 2: The political shtick of this is we're going to employ America.

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Speaker 2: Do you believe that the Asian manufacturers could come over

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Speaker 2: here and get the quality of employment that they have

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Speaker 2: in Asia?

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Speaker 7: I think again, based on the chairman's comments, it sounded

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Speaker 7: like it's going to take a couple of years just

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Speaker 7: to set the initial thirty five billion dollar investment kind

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Speaker 7: of show some reason.

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Speaker 3: Answer my question.

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Speaker 2: Do we have the bodies, the intellect, the drive to

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Speaker 2: be as quality of employees as we see in Asia.

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Speaker 8: No.

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Speaker 7: I think we may be better off on the infrastructure side,

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Speaker 7: but in terms of their talent side, there is more work.

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Speaker 9: There's a political football, yeah, But I was struck by

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Speaker 9: how agnostic the chairman seemed in talking about this. He said,

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Speaker 9: what's the best talent anywhere? And he's focused here on

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Speaker 9: the US. He seemed gleeful to say there'd been this

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Speaker 9: thirty five billion doll dollar investment, and so there's the

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Speaker 9: prospect for much more investment in the US going forward. Here,

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Speaker 9: we kind of look at that in Jex's position with

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Speaker 9: what we heard from Howard Lutnik, the Commerce Secretary yesterday

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Speaker 9: saying he's kind of tightening the screws on the SSK,

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Speaker 9: Heinez and Samsung as well to do more in the

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Speaker 9: United States. And to me, yes, there's the kind of

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Speaker 9: talent and resources side of this.

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Speaker 4: Tom. The other facet here is will that be effective?

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Speaker 9: Is he going to be able to is the administration

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Speaker 9: going to be able to get these companies to do

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Speaker 9: more in the US by sheer Will.

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Speaker 6: I think that's a really good point, especially because Mandeep

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Speaker 6: this listing is to fund the build out of factories

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Speaker 6: in South Korea. Isn't that going to be a problem

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Speaker 6: David Gerrow for this administration that they're raising money in

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Speaker 6: the US to build more factories in Korea.

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Speaker 4: Yes, and they have this, correct me if I'm wrong.

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Speaker 9: I think like an eight hundred million dollar commitment to

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Speaker 9: eight hundred million one commitment to do more work in

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Speaker 9: South Korea. I think he was saying this would be

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Speaker 9: kind of complementary to this that he has focused on

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Speaker 9: the US as well. But yeah, that is part and

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Speaker 9: parcel of this. How much of this is going to

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Speaker 9: be raised in the US and stay in the US

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Speaker 9: versus go back?

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Speaker 7: When it comes to the factories, you also have to

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Speaker 7: think about what is leading note versus what is you know,

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Speaker 7: technology that is more mature. I doubt they are going

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Speaker 7: to set up their leading note factories, you know, being

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Speaker 7: the first one here in the US to do that.

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Speaker 7: It will be more advanced note like the mature notes.

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Speaker 2: What are you looking at Bloomberg this weekend? What are

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Speaker 2: you looking at in Washington? Where sides everyone worried about

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Speaker 2: the Senator.

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Speaker 9: Yes, yes, Mitch mcconne's still ailing. We're looking at obviously

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Speaker 9: the conflict in the Middle East. We had the presence

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Speaker 9: today the ceasefire is off formerly but the talks continue.

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Speaker 4: What can be accomplished here.

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Speaker 9: We have Michael McCall, the Chairman emeritus the House for

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Speaker 9: an Affairs Committee joining us, and the Chief of Naval

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Speaker 9: Operations as well, so get a sentence of how things.

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Speaker 3: Are in the control room.

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Speaker 2: They have Greyfeld's people saying we haven't spent enough time

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Speaker 2: with Katie, you know save me.

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Speaker 6: Yes, absolutely, and Katie, I know that you are on

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Speaker 6: top of all the ETFs. There's going to be leverage

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Speaker 6: ets tied to sk Heinex. That is going to be

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Speaker 6: a big deal next week.

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Speaker 5: Oh big time.

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Speaker 1: I mean you think about all the different issuers trying

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Speaker 1: to get out their products out there, not that sk

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Speaker 1: Heinex the way it trades needs leverage on top of it.

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Speaker 1: But certainly that is the gold rush going on in

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Speaker 1: the ETF industry.

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Speaker 5: I will point.

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Speaker 1: Out, you know, you think about us appetite for exposure

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Speaker 1: to sk Heinex. We have, you know, one facet to

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Speaker 1: look at that. It's an ETF called d RAM, which

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Speaker 1: we talk about a lot. It launched three months ago.

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Speaker 1: It's already more than twenty billion dollars in assets and

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Speaker 1: shine with Eric Alchunis of course before the show.

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Speaker 5: Right it trades about as much as Apple.

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Speaker 1: So this is an extremely popular trade right now, and

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Speaker 1: you're seeing that in the retail recailvessors.

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Speaker 2: Yeah, I don't have time to talk to you. I

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Speaker 2: have time to talk to you. I have SpaceX below

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Speaker 2: one forty nine. Is it going to one thirty five?

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Speaker 2: I mean, is it like where we're one ten and

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Speaker 2: we're enjoying sixty and so we're gonna have SpaceX fai.

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Speaker 2: I'm not comparing it to skhinex, but this isn't good

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Speaker 2: right Well.

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Speaker 1: I would say that SpaceX I've been thinking about it

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Speaker 1: as a really interesting Petri dish because you have all

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Speaker 1: the index inclusions.

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Speaker 5: This is the most the.

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Speaker 1: General public has ever cared about index methodology. But you

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Speaker 1: also have the lockup Expert is starting off this month,

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Speaker 1: so it's going to be you know, some really interesting

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Speaker 1: forces all coming together on spacets. I'm not sure if

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Speaker 1: you can say right now it's trading on fundamentals.

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Speaker 9: Yes, the Tom King triple leveraged all cash fund made

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Speaker 9: a transition to tea.

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Speaker 2: But we did a fifteen percent gross after three percent

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Speaker 2: pre three hundred basis points.

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Speaker 3: We came into the twelve percent in that clean.

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Speaker 4: Lass quarter put in the Trump accadey it was great.

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Speaker 3: Maybe actually we could do that.

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Speaker 2: So the three of you, thank you, but particularly to

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Speaker 2: math Saying and honorag Rana and all of our tech people.

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Speaker 3: Your leadership on this has just been absolutely.

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Speaker 2: A superb Randy Krasner is a math prodigy out of

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Speaker 2: Brown University. He owns a high ground in financial economics

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Speaker 2: in America so good. At a very young age, he

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Speaker 2: became a governor of the Fund Reserve System foundational to

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Speaker 2: the University of Chicago Boost School and particularly their expansion

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Speaker 2: over to your Europe orre thrilled he could join us today.

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Speaker 3: Randy, thank you.

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Speaker 2: So much for being with us. I'm not going to

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Speaker 2: mince it. It's about inflation. Bring up the chart right now, Randy.

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Speaker 2: I'm glad you're remote because you'd be in.

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Speaker 3: Tears if you saw this chart. It's the inflation we're

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Speaker 3: living and the idea here, Thank you.

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Speaker 2: John Taylor Stanford is we need two percent inflation. Okay, Well,

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Speaker 2: there's two percent inflation. It's the green line, and the

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Speaker 2: answer is the presidential moving average, four quarter moving average

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Speaker 2: is elevated COVID and all the rest.

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Speaker 3: Randy, do you, on a first order basis.

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Speaker 2: Have a real conviction we can get back anywhere near

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Speaker 2: two percent inflation?

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Speaker 1: Oh?

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Speaker 8: I think we can. It's not going to happen in

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Speaker 8: the next quarter. It's not going to happen by the

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Speaker 8: end of the year. But I do think that within

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Speaker 8: let's see a year to eighteen months, we can be

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Speaker 8: pretty close.

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Speaker 6: Okay, So when we talk about two percent inflation, the

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Speaker 6: FED focus is on core PC, which backs out food

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Speaker 6: and gas, not the headline inflation number. The new fetcher,

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Speaker 6: Kevin Walsh, prefers Dallas Fed trimmed mean, which moves that

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Speaker 6: takes out the outliers, so kind of like a judge

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Speaker 6: and figure skating you throughout the top score and the

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Speaker 6: bottom score. So my question is, Randy, for consumers, this

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Speaker 6: can feel like a very narrow way of measuring inflation.

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Speaker 6: You remove food, you remove gas, you remove the outliers

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Speaker 6: at both ends. It leaves you something in the middle

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Speaker 6: that doesn't reflect anyone's lived experience. And then making policy

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Speaker 6: based on it. Is this something that can or should

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Speaker 6: be fixed.

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Speaker 8: So I always joked that it's only an economists who

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Speaker 8: could think about the consumer basket as excluding anything about

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Speaker 8: eating so you starve stiff, and anything about driving or

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Speaker 8: keeping your house warm or cool. So the reason for

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Speaker 8: doing that is not because of concerned about people, but

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Speaker 8: it's really looking for what is going to be the

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Speaker 8: best metric for seeing where inflation is going, rather than

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Speaker 8: looking at inflation in the rear view mirror, because we're

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Speaker 8: of course always getting data from the past, not from

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Speaker 8: you know, we want to figure out what.

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Speaker 10: Start in the future.

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Speaker 8: So the idea behind it is the starting in the

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Speaker 8: nineteen seventies was taking up high volatility sectors things like

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Speaker 8: food and energy, because that's a lot of noise. It's

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Speaker 8: not necessarily telling you where things are are going. Trim

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Speaker 8: mean in some sense, it's a version of that, because

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Speaker 8: if you think about what taking out food and energy is,

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Speaker 8: you're just saying, well, we always want to trim out

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Speaker 8: the volatile food and energy sectors because we think of

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Speaker 8: those as outliers. The Dallas FED approach is saying, well,

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Speaker 8: we don't know from month to month what the extreme

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Speaker 8: is going to be, So let's trim those out because

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Speaker 8: if something is moving a lot one month might be

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Speaker 8: coming back the next month.

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Speaker 2: Randy, I want to cut to the chase round university

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Speaker 2: tuition since COVID has gone from seventy four thousand their

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Speaker 2: top and ticking it this year at ninety seven thousand.

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Speaker 2: That's what our viewers and personal finance retirement, that's what

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Speaker 2: they feel. And the worry here is a sustained inflation

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Speaker 2: where we don't get legitimate real wage growth. Is that

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Speaker 2: a risk for our savers, our personal finance in America,

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Speaker 2: that we don't get legitimate wage growth.

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Speaker 8: That's a real risk, And that's really the key thing,

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Speaker 8: and you really put your finger on it, because the

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Speaker 8: key is how much are people making relative to how

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Speaker 8: much things would cost. So if your wages are going

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Speaker 8: up at ten percent and inflation is five percent, you're

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Speaker 8: feeling pretty good because even though prices are higher, you

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Speaker 8: still have really strong purchasing power. But if it's the opposite,

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Speaker 8: the price has gone up ten percent and your wage's

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Speaker 8: only gone five percent, you're pretty upset because you can

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Speaker 8: barely put food on the table. So that's really the

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Speaker 8: relevant thing. And That's what Kevin is focusing on, because

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Speaker 8: he's saying, well, I'm very optimistic about what AI is

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Speaker 8: going to do increasing productivity and increasing real wages.

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Speaker 10: Of course that's a bet, but you know, that's what

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Speaker 10: he's focusing on.

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Speaker 3: No, we don't have time for this on Bloomberg Money.

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Speaker 2: But I'm just going to say I was blown away

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Speaker 2: by everything about the worst task forces except Krasner's on there.

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Speaker 3: Why is Randy Krasner not on the task force?

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Speaker 2: You know this, Let's go to right now, Adam Posen

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Speaker 2: and Peter Orzagan maybe my essay of the year, the

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Speaker 2: risk of higher US inflation or Zagon Posen push against

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Speaker 2: hot Siistict Golden Sachs a tighter labor market reflecting the

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Speaker 2: effects of the shifted immigration, monetary policy, looser than commonly appreciated,

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Speaker 2: and inflationary expectations inflation, they would suggest Scarlett is drifting higher.

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Speaker 5: Right.

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Speaker 6: I mean, what it comes down to, Randy, is that

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Speaker 6: a meaningful segment of the population, the hollowed out middle

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Speaker 6: class young people in particular, they've lost faith in the

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Speaker 6: ability of the FED to do anything on reducing inflation.

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Speaker 6: They've gravitated to things like crypto or prediction markets as

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Speaker 6: a solution. From their point of view, the system is

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Speaker 6: broken and they might as well bet on low probability,

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Speaker 6: high impact outcomes. How problematic is this behavior for the

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Speaker 6: stability of the economy, disability of financial system?

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Speaker 8: And you also see with memestocks too, it's another example

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Speaker 8: of people taking the high risk bets and maybe it'll

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Speaker 8: pay off, but it's awfully risky. So I think there

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Speaker 8: is a breakdown of trust, and I think that is

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Speaker 8: a real problem. We saw that because inflation went up

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Speaker 8: so high when the FED was saying transitory transtory transittory as.

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Speaker 10: Ination kept spiraling higher and higher. And Kevin Marsh has

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Speaker 10: made it really.

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Speaker 8: Clear when asked about these sorts of things that I'm

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Speaker 8: not getting into that game of saying what's transitory or not.

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Speaker 8: What I'm going to do is try to get big

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Speaker 8: picture trends in the economy where broadly is inflation going,

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Speaker 8: what are the key drivers behind inflation, and what is

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Speaker 8: the role of productivity growth. So that's what he's going

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Speaker 8: to try to do to get restore faith in the

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Speaker 8: FED rather than those short term predictions that although the

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Speaker 8: FED is probably the.

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Speaker 10: Best predictor of anybody, They're still not very good.

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Speaker 2: Grandy your advice here, I think of Booth School in Chicago,

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Speaker 2: Steve Lovett, freakonomics, everything that Becker did, I mean the

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Speaker 2: heritage he of our system economics. Do you have a

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Speaker 2: confidence that we will solve our retirement system the next

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Speaker 2: go around of social security reform and indeed retirement reform?

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Speaker 10: I think it'll never be fully solved.

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Speaker 8: You know, we had we've had patchworks that come every

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Speaker 8: decade or so when we see that the Soial Security

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Speaker 8: Trust Fund is going to run out of resources, and

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Speaker 8: the most recent reports is it's common pretty soon twenty thirty,

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Speaker 8: twenty thirty two. And so it's really it's it's not

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Speaker 8: purely economics, it's really political economy.

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Speaker 10: What will the politicians be willing to do?

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Speaker 8: So one of the obvious fixes is to increase retirement age.

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Speaker 8: When this was first implemented by Roosevelt, people's expected lifetime.

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Speaker 10: Was much much shorter than it is today.

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Speaker 8: Yes, and we've moved things up a little bit, but

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Speaker 8: not nearly as much to reflect much better health outcomes

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Speaker 8: that people have totally and so their whole right of things,

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Speaker 8: it could be done to address that.

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Speaker 3: Randy I gotta go. We got to get you in

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Speaker 3: New York.

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Speaker 2: Next time for Bloomberg Money, Governor Krasner, Professor Krausner. Of course,

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Speaker 2: always forever with the University of Chicago.

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Speaker 3: We're going to.

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Speaker 2: Migrate here to the equity Marcus's continued bull market coming up,

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Speaker 2: Cameron Dawson, a new edge ausre What am I going

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Speaker 2: to focus on? Scarlett's got a list of questions. I'm

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Speaker 2: going to focus on my need to rebalance. I'm unbalanced.

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Speaker 2: I'm not to rebalance this, Cameron. Next, it's Bloomberg Money.

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Speaker 3: Stay with us.

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Speaker 2: On a Friday, Bloomberg Good Money. Tom Keene with Scarlett

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Speaker 2: fu Scarlett Well.

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Speaker 6: Sk Heinex the Queen Memory ship maker searching above its

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Speaker 6: offer priced.

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Speaker 5: It's the US debut.

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Speaker 6: So let's go out to b Tech anchor live at

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Speaker 6: the NASAC and ed you got to speak with the

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Speaker 6: chairman of s k Heinicks. What did you learn from

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Speaker 6: him that's relevant to retail investors looking to thank big

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Speaker 6: on ske Heynicks.

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Speaker 11: Three things, big, big investments in the USA are coming.

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Speaker 11: They're committed to thirty five billion, and that number is

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Speaker 11: going to get much, much, much much bigger. This was

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Speaker 11: an ADR listing. That wasn't just about the proceeds. He's

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Speaker 11: coming for the talent chairman Cha. He wants to see

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Speaker 11: American engineers powering their position in the merry market, which

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Speaker 11: is number three. They got fifty seven percent, seven percent

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Speaker 11: market share in high bandwidth memory. That is the chip.

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Speaker 11: The thing that everyone cares about in this AI story

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Speaker 11: right now. The main thing is that the US retail

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Speaker 11: investor is sophisticated and educated about what goes into a

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Speaker 11: server design in the data center. They know how critical

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Speaker 11: that HBM is and that's why sk came knocking at

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Speaker 11: the NASDAK.

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Speaker 6: Fantastic, thank you go for that round of s Khinex

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Speaker 6: of course trading in his market debut here in the

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Speaker 6: US at Ludlow b Tech anchor joining us from the NASAC.

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Speaker 6: It is time for banking on books and my book

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Speaker 6: is Strangers, a Memoir of marriage by Belle Burden, first

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Speaker 6: publisher Generary now and it's twelfth printing.

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Speaker 5: This is a financial course rate.

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Speaker 6: Yes, because Bell Burdon's husband walked out on her and

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Speaker 6: the kids at the start of COVID. She had quit

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Speaker 6: her job to raise the kids, her husband worked and

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Speaker 6: manage of family finances. That was not a good setup

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Speaker 6: for that situation. And there's also this fascinating overlap with

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Speaker 6: privilege and status because she's in New York society. There's

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Speaker 6: trust funds involved. Buthering glare's from Mary Tumban.

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Speaker 2: Did Wich stillman define the Upper east Side Lottie world

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Speaker 2: and then she just absolutely nailed it.

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Speaker 10: Well.

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Speaker 6: This was a fantastic read, and it's so interesting because

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Speaker 6: it's sparked a lot of conversation among people, certainly in

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Speaker 6: New York, you know, because she's a New York society woman.

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Speaker 6: And that gets to what we've done here at Bloomberg Money.

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Speaker 6: The Bloomberg Money team wrote about this book and how

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Speaker 6: it's sparking all these discussions everywhere about marital finance. Nikki

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Speaker 6: Waller leads that coverage for us here at Bloomberg and

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Speaker 6: she joins us now and Nikki, this is something where

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Speaker 6: women are in book clubs, are talking about it, and

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Speaker 6: they are taking more control of their finances and taking

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Speaker 6: a deep dive into financial planning to understand their household finances.

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Speaker 12: It's just as you said, people are reading this book

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Speaker 12: as a cautionary tale and a horror story, and they

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Speaker 12: are phoning their financial advisors and saying I need to

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Speaker 12: crack open the books on my finances with my husband

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Speaker 12: or partner.

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Speaker 6: And this is the case where women often out earn

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Speaker 6: their husbands or they're at parody, except when they take

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Speaker 6: time off to have kids, and they kind of lose

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Speaker 6: some ground here. So there's this extra urgency and this

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Speaker 6: once there was a stigma about talking about all of

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Speaker 6: this before getting married, but it's not becoming the case anymore.

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Speaker 5: It's more practical now, it is.

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Speaker 12: Less of a stigma. But even so, the numbers show

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Speaker 12: that a lot of women, close to half are entrusting

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Speaker 12: their husbands with all of the financial decision making.

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Speaker 2: Boy read we all have our horror stories and our

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Speaker 2: families of this. I have multiple horror stories of I'm

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Speaker 2: the man, I'm smarter than you are, leaving alone. Just

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Speaker 2: trust me. I'll give you the passwords when I die.

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Speaker 2: That's the status quo.

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Speaker 3: Still.

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Speaker 12: Yeah, and we have really smart people. I mean, take

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Speaker 12: Bell Burden. She has an ivy lea educated corporate lawyer,

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Speaker 12: and she still hated this over And I think a

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Speaker 12: lot of this talks about comes back to the gendered

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Speaker 12: ways we think about money. That this is men's work,

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Speaker 12: and this is women's work, and it's kind of cool

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Speaker 12: to hear from these women who are cracking the books,

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Speaker 12: and even their husbands are saying, well, finally, there is.

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Speaker 6: A broader trend and this is something you guys wrote

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Speaker 6: about too, of young couples signing pre nups, This idea

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Speaker 6: that it's not just men or wealthy the wealthy partner

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Speaker 6: in the group. Everyone is kind of inquiring about this

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Speaker 6: and looking into this to protect whatever assets or liabilities

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Speaker 6: that they come into the marriage with.

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Speaker 12: And there are so many reasons for this. People are

444
00:20:36,760 --> 00:20:39,479
Speaker 12: marrying later in life. They we talk about this all

445
00:20:39,520 --> 00:20:42,840
Speaker 12: the time. They have more investments, more stockholdings, so it's

446
00:20:42,880 --> 00:20:45,120
Speaker 12: not like getting married at age twenty or twenty one,

447
00:20:45,359 --> 00:20:49,080
Speaker 12: and both both partners have very little. People are coming

448
00:20:49,119 --> 00:20:51,640
Speaker 12: into marriage with their own kind of book of business.

449
00:20:52,119 --> 00:20:53,640
Speaker 5: Frozen eggs also.

450
00:20:53,520 --> 00:20:55,480
Speaker 6: One of the assets that people you know have to

451
00:20:55,680 --> 00:20:57,720
Speaker 6: kind of delineate student debt.

452
00:20:57,840 --> 00:21:00,560
Speaker 5: In terms of liabilities, these are all things to consider. Pets,

453
00:21:00,600 --> 00:21:02,080
Speaker 5: social media followers.

454
00:21:02,400 --> 00:21:04,760
Speaker 6: Pets and social media followers is part of your prenup.

455
00:21:04,800 --> 00:21:07,560
Speaker 6: I bet that came up in the tailor swift Travis

456
00:21:07,600 --> 00:21:09,000
Speaker 6: Kelsey prenuptial agreement.

457
00:21:09,240 --> 00:21:11,560
Speaker 3: Did you like the wedding? I mean, did you get

458
00:21:12,200 --> 00:21:12,760
Speaker 3: the pictures?

459
00:21:12,800 --> 00:21:14,880
Speaker 5: I've only seen other people. I thought you went out.

460
00:21:16,400 --> 00:21:17,640
Speaker 5: There was a limited invite list.

461
00:21:17,680 --> 00:21:19,720
Speaker 3: There's a limited list. We'll have to see.

462
00:21:19,840 --> 00:21:22,560
Speaker 2: We were advantaged because cam Dawson was with us day

463
00:21:22,600 --> 00:21:25,600
Speaker 2: of the wedding, and she knows every Taylor swift lyric

464
00:21:25,680 --> 00:21:27,919
Speaker 2: there is to know it, does she, which is almost

465
00:21:27,960 --> 00:21:30,560
Speaker 2: as good as their equity knowledge here Bloomberg Money, we'd

466
00:21:30,560 --> 00:21:32,720
Speaker 2: like to talk to people with deep knowledge, what is

467
00:21:33,040 --> 00:21:37,719
Speaker 2: known as domain knowledge. Cameron Dawson owns absolute high ground

468
00:21:37,760 --> 00:21:39,280
Speaker 2: on the equity markets.

469
00:21:38,880 --> 00:21:39,639
Speaker 3: At the New Edge.

470
00:21:40,080 --> 00:21:42,400
Speaker 2: Well, I'm thrilled to have a year for a two

471
00:21:42,440 --> 00:21:45,679
Speaker 2: hour conversation. We're going to squeeze in and next to nothing.

472
00:21:45,840 --> 00:21:48,040
Speaker 2: Ow bull market? Is this bull market?

473
00:21:48,359 --> 00:21:48,520
Speaker 3: Oh?

474
00:21:48,880 --> 00:21:51,960
Speaker 13: It is certainly a bull market, not just within prices,

475
00:21:52,000 --> 00:21:54,760
Speaker 13: but certainly within the earnings. And that's why this market

476
00:21:54,800 --> 00:21:58,720
Speaker 13: has been so powerful and resilient to everything you've thrown

477
00:21:58,720 --> 00:22:02,160
Speaker 13: at it this year is because, unlike prior times when

478
00:22:02,160 --> 00:22:05,320
Speaker 13: you've had things like energy shocks and geopolitical crises and

479
00:22:05,359 --> 00:22:08,399
Speaker 13: you would see earning sestiments get cut, you've seen earning

480
00:22:08,440 --> 00:22:11,280
Speaker 13: sestments go up twenty percent on a twelve month four

481
00:22:11,400 --> 00:22:14,120
Speaker 13: basis this year, which is why this market has been

482
00:22:14,160 --> 00:22:16,840
Speaker 13: able to shake off any kind of negative news.

483
00:22:16,680 --> 00:22:18,840
Speaker 3: On a personal finance basis.

484
00:22:18,960 --> 00:22:21,600
Speaker 2: Are we enjoying it or are we totally on a

485
00:22:21,680 --> 00:22:23,720
Speaker 2: whack where our allocation should be.

486
00:22:23,960 --> 00:22:26,760
Speaker 13: Well, if you look at the aggregate allocation metrics out

487
00:22:26,760 --> 00:22:30,720
Speaker 13: of something like in American Association of Individual Investors, what

488
00:22:30,840 --> 00:22:33,160
Speaker 13: you can see is equity allocations are at all time

489
00:22:33,240 --> 00:22:36,119
Speaker 13: highs at seventy one percent allocations. So this gets you

490
00:22:36,200 --> 00:22:38,199
Speaker 13: back to prior highs that we saw in times like

491
00:22:38,240 --> 00:22:41,879
Speaker 13: twenty twenty one or twenty eighteen. So certainly this looks

492
00:22:41,960 --> 00:22:45,679
Speaker 13: like an individual or a household area that is all

493
00:22:45,680 --> 00:22:48,560
Speaker 13: in on equities. You see a very different story when

494
00:22:48,600 --> 00:22:51,240
Speaker 13: you look at institutions, where institutions are the ones who've

495
00:22:51,240 --> 00:22:54,200
Speaker 13: been sitting on the sideline. Something like Deutsche Bank's consolidated

496
00:22:54,240 --> 00:22:57,479
Speaker 13: equity positioning is just in the forty first percentiles. So

497
00:22:57,840 --> 00:23:01,240
Speaker 13: it's a tale of very different cities. Households are all in,

498
00:23:01,240 --> 00:23:02,919
Speaker 13: institutions are on the sidelines.

499
00:23:03,119 --> 00:23:06,159
Speaker 6: Interesting dichotomy there. You look at the SMP five hundred,

500
00:23:06,160 --> 00:23:08,600
Speaker 6: we've had three straight years of double digit gains. The

501
00:23:08,680 --> 00:23:11,080
Speaker 6: SMP is up about ten and a half percent. Now,

502
00:23:11,320 --> 00:23:13,560
Speaker 6: when we're in this long running bull market like we

503
00:23:13,640 --> 00:23:17,639
Speaker 6: have right now, do individual investors tend to turn more conservative,

504
00:23:17,800 --> 00:23:20,639
Speaker 6: stay with what's worked, you know, buy and hold, or

505
00:23:20,760 --> 00:23:22,480
Speaker 6: are they more willing to go out on a limb

506
00:23:22,480 --> 00:23:28,199
Speaker 6: and consider, you know, moving some assets into uncorrelated securities

507
00:23:28,280 --> 00:23:30,840
Speaker 6: or products, you know, maybe venture into private assets.

508
00:23:30,960 --> 00:23:34,000
Speaker 13: Well, I think there's two different questions there, because the

509
00:23:34,040 --> 00:23:36,880
Speaker 13: first one is do people start chasing the hot dot

510
00:23:36,960 --> 00:23:39,479
Speaker 13: when it comes to market leadership. And one of the

511
00:23:39,520 --> 00:23:42,720
Speaker 13: reasons why the quality anomaly exists, why if you look

512
00:23:42,760 --> 00:23:46,119
Speaker 13: over the long run, the quality factor has actually added

513
00:23:46,160 --> 00:23:49,119
Speaker 13: a lot to portfolios from a return basis and not

514
00:23:49,280 --> 00:23:52,040
Speaker 13: added to risk, is because people do tend to chase

515
00:23:52,080 --> 00:23:54,480
Speaker 13: the hot dots and markets like this. They want the

516
00:23:54,680 --> 00:23:57,600
Speaker 13: non profitable tech company, they want this shiny new object.

517
00:23:57,920 --> 00:23:59,919
Speaker 13: But what you find is that just as fast as

518
00:24:00,080 --> 00:24:02,840
Speaker 13: those kind of assets go up, you have the same

519
00:24:02,960 --> 00:24:05,680
Speaker 13: kind of problem where they can have very deep corrections.

520
00:24:05,720 --> 00:24:06,360
Speaker 5: On the other.

521
00:24:06,240 --> 00:24:09,680
Speaker 13: Side, when we think about allocating to private markets, that's

522
00:24:09,680 --> 00:24:12,200
Speaker 13: where you're looking and saying, look, we've had fifteen years

523
00:24:12,200 --> 00:24:15,879
Speaker 13: of effectively double the average returns for public markets. So

524
00:24:16,040 --> 00:24:19,560
Speaker 13: we need to diversify the return streams, diversify the income streams,

525
00:24:19,760 --> 00:24:21,680
Speaker 13: and you need to look to private markets in order

526
00:24:21,720 --> 00:24:24,560
Speaker 13: to find those different sources of ways to get to

527
00:24:24,600 --> 00:24:26,120
Speaker 13: overall portfolio diversification.

528
00:24:26,359 --> 00:24:29,200
Speaker 2: Let's go, comingo Matthey on a Friday. Come, let's go Mathey.

529
00:24:29,280 --> 00:24:30,800
Speaker 2: Here it is right now. This is one of the

530
00:24:30,800 --> 00:24:34,680
Speaker 2: most famous money must reads out of the Wall Street

531
00:24:34,800 --> 00:24:37,480
Speaker 2: Journal years and years ago, two thousand.

532
00:24:37,160 --> 00:24:38,639
Speaker 5: And three, back in the archive.

533
00:24:38,840 --> 00:24:40,000
Speaker 3: Mark Yeah.

534
00:24:40,040 --> 00:24:44,359
Speaker 2: As an extreme example, consider the equity allocation of seventeen

535
00:24:44,480 --> 00:24:47,600
Speaker 2: ninety three. Today you would be ninety nine percent equities

536
00:24:47,760 --> 00:24:50,960
Speaker 2: and all stock portfolio over time, much riskier than a

537
00:24:51,000 --> 00:24:55,760
Speaker 2: classic sixty forty cam Dawson explain the best approach on

538
00:24:55,800 --> 00:24:59,360
Speaker 2: the X access to proper retirement allocation.

539
00:25:00,000 --> 00:25:02,960
Speaker 13: Well, I think that there has to be a very

540
00:25:03,000 --> 00:25:05,920
Speaker 13: holistic approach to the entirety of somebody's not.

541
00:25:05,960 --> 00:25:07,800
Speaker 5: Formulate life, not formulaic.

542
00:25:07,920 --> 00:25:10,080
Speaker 13: And I think that this is the big issue within

543
00:25:10,160 --> 00:25:13,159
Speaker 13: wealth management, is that most people try to make everything.

544
00:25:12,880 --> 00:25:16,240
Speaker 5: Institutional and homogeneous. They try to treat everybody the same.

545
00:25:16,359 --> 00:25:18,680
Speaker 13: But just as we talked about with things like financial

546
00:25:18,720 --> 00:25:22,360
Speaker 13: planning and well strategy and something like prenups, those considerations

547
00:25:22,400 --> 00:25:25,320
Speaker 13: have to be reflected in the portfolio. Those liquidity needs

548
00:25:25,320 --> 00:25:28,040
Speaker 13: have to be reflected in the portfolio. So having the

549
00:25:28,119 --> 00:25:31,400
Speaker 13: right allocation is not just going on the efficient frontier.

550
00:25:31,560 --> 00:25:34,760
Speaker 13: It's actually doing the holistic work to understand somebody's complete

551
00:25:34,840 --> 00:25:37,320
Speaker 13: balance sheet in order to get the mix of assets

552
00:25:37,320 --> 00:25:39,520
Speaker 13: that allows them to withstand volatility.

553
00:25:39,640 --> 00:25:43,080
Speaker 2: Nicky, help me here with all your experience on this,

554
00:25:43,160 --> 00:25:47,760
Speaker 2: from John Templeton to William Bernstein to all of rebalancing

555
00:25:47,800 --> 00:25:52,160
Speaker 2: in the formulate approach. It's the cottage industry of reallocation

556
00:25:52,280 --> 00:25:54,200
Speaker 2: along the way rebalancing.

557
00:25:53,680 --> 00:25:54,000
Speaker 3: Isn't it.

558
00:25:54,080 --> 00:25:56,560
Speaker 12: Yeah, No one makes money if you just leave everything

559
00:25:56,600 --> 00:25:59,000
Speaker 12: alone said.

560
00:25:58,880 --> 00:26:00,840
Speaker 5: That's very well said.

561
00:26:00,840 --> 00:26:03,640
Speaker 6: The part out cuts to these the pipart out.

562
00:26:03,960 --> 00:26:05,399
Speaker 3: That's an interest thing, right.

563
00:26:05,760 --> 00:26:07,960
Speaker 12: I mean, one of the most interesting stories we're seeing

564
00:26:07,960 --> 00:26:11,399
Speaker 12: this morning is that JP Morgan built an AI that

565
00:26:11,440 --> 00:26:13,440
Speaker 12: can outdo the sixty forty portfolio.

566
00:26:14,320 --> 00:26:15,320
Speaker 5: These are really good points.

567
00:26:15,359 --> 00:26:18,199
Speaker 2: And I guess that way Gabby Santos was on the

568
00:26:18,200 --> 00:26:20,119
Speaker 2: other day, is she out of a job? Is Gabby

569
00:26:20,200 --> 00:26:22,160
Speaker 2: Santos out of a job with AI?

570
00:26:22,520 --> 00:26:25,080
Speaker 12: I think Gabby Santos will always have a job. But

571
00:26:25,520 --> 00:26:28,520
Speaker 12: the ways that people are using AI to trade and

572
00:26:29,160 --> 00:26:31,680
Speaker 12: beat the formulas we've always had.

573
00:26:31,880 --> 00:26:32,919
Speaker 5: This is something to watch.

574
00:26:33,240 --> 00:26:34,720
Speaker 6: I want to go back to that point, Cam where

575
00:26:34,720 --> 00:26:40,000
Speaker 6: you talked about tailored portfolios, tailored allocations, and tailored approaches

576
00:26:40,040 --> 00:26:42,760
Speaker 6: to managing your portfolio. Does that mean things like model

577
00:26:42,760 --> 00:26:45,400
Speaker 6: portfolios which are kind of cookie cutter don't make sense

578
00:26:45,520 --> 00:26:47,040
Speaker 6: for wealth investors?

579
00:26:47,280 --> 00:26:50,600
Speaker 13: I think that as somebody's wealth grows, and as they

580
00:26:50,640 --> 00:26:54,280
Speaker 13: get even more complicated, typically we do see complications or

581
00:26:55,119 --> 00:26:58,680
Speaker 13: I mean they certainly expand as the amount of assets

582
00:26:58,720 --> 00:27:00,879
Speaker 13: do grow that we find that we have to tailor

583
00:27:00,920 --> 00:27:04,000
Speaker 13: different portions of the portfolio to have the right kind

584
00:27:04,000 --> 00:27:07,680
Speaker 13: of allocation. Because if you have high liquidity means having

585
00:27:07,720 --> 00:27:11,879
Speaker 13: something that's invested in completely private markets means absolutely no sense.

586
00:27:12,200 --> 00:27:14,879
Speaker 13: So instead of treating an allocation like going to a

587
00:27:14,920 --> 00:27:18,040
Speaker 13: big golden corral and putting everything off the menu, you

588
00:27:18,080 --> 00:27:20,040
Speaker 13: really have to choose the things that are having the

589
00:27:20,080 --> 00:27:21,520
Speaker 13: right functions for what you need.

590
00:27:21,600 --> 00:27:24,639
Speaker 2: How much of our certitude about this what Nikki Waller

591
00:27:24,720 --> 00:27:26,200
Speaker 2: deals with every single day.

592
00:27:26,720 --> 00:27:27,840
Speaker 3: The myth that we have.

593
00:27:28,200 --> 00:27:32,120
Speaker 2: The foundations was built on the Great moderation where it

594
00:27:32,160 --> 00:27:35,480
Speaker 2: was just price up, yield down forever, and then in

595
00:27:35,520 --> 00:27:37,320
Speaker 2: twenty twenty two, we hit a wall.

596
00:27:37,520 --> 00:27:40,520
Speaker 14: Well, and I think that all of these acid allocations,

597
00:27:40,560 --> 00:27:45,000
Speaker 14: these mean variance optimizations are all built on one very

598
00:27:45,040 --> 00:27:49,000
Speaker 14: problematic assumption, which is that you'll have standard normal outcomes

599
00:27:49,040 --> 00:27:51,400
Speaker 14: that you will have you connect to outcomes.

600
00:27:51,840 --> 00:27:54,880
Speaker 2: Could you see did you cheer up over that standard

601
00:27:54,960 --> 00:27:56,000
Speaker 2: normal outcomes?

602
00:27:57,000 --> 00:27:59,040
Speaker 3: We're going to go Gaussian in a moment, finish up

603
00:27:59,080 --> 00:27:59,960
Speaker 3: and save the interview.

604
00:28:00,240 --> 00:28:03,160
Speaker 6: So I guess what it comes down to is any portfolio,

605
00:28:03,480 --> 00:28:05,879
Speaker 6: especially one tailored for an individual, needs to account for

606
00:28:05,920 --> 00:28:08,680
Speaker 6: emergency liquidity. Yes, where does that come from?

607
00:28:08,880 --> 00:28:11,480
Speaker 13: Well, I think that it's building out a certain degree

608
00:28:11,520 --> 00:28:14,400
Speaker 13: of a cash side of portfolios to meet the liquidity

609
00:28:14,400 --> 00:28:17,119
Speaker 13: needs over a shorter period of time, having an income

610
00:28:17,160 --> 00:28:20,680
Speaker 13: generation part of the portfolio that has income sources from

611
00:28:20,880 --> 00:28:25,000
Speaker 13: different sources. So this is not just fixed income bonds

612
00:28:25,040 --> 00:28:28,399
Speaker 13: generating income. It's looking at something like potentially private credit

613
00:28:28,400 --> 00:28:30,960
Speaker 13: if you can absorb the ill liquidity there in certain

614
00:28:31,000 --> 00:28:33,600
Speaker 13: areas to do it carefully, GP stakes and so you

615
00:28:33,720 --> 00:28:36,480
Speaker 13: have to think about diversification not just within the overall

616
00:28:36,520 --> 00:28:38,920
Speaker 13: asset class, but what you're trying to achieve by each

617
00:28:38,960 --> 00:28:40,000
Speaker 13: asset class.

618
00:28:40,160 --> 00:28:43,440
Speaker 2: Was becoming a ballerina years ago. Seriously, you like really

619
00:28:43,440 --> 00:28:44,520
Speaker 2: good at it?

620
00:28:44,560 --> 00:28:45,440
Speaker 3: Is it expensive?

621
00:28:45,720 --> 00:28:45,880
Speaker 14: Oh?

622
00:28:45,920 --> 00:28:46,760
Speaker 5: Extraordinarily?

623
00:28:46,920 --> 00:28:48,560
Speaker 3: Yeah, it was like stupid expensive.

624
00:28:48,600 --> 00:28:50,120
Speaker 13: I mean my parents told me that they spent all

625
00:28:50,160 --> 00:28:52,040
Speaker 13: my college money on doing that, so to figure out

626
00:28:52,080 --> 00:28:53,000
Speaker 13: something else for college.

627
00:28:53,120 --> 00:28:55,360
Speaker 2: That's what we're going to cover next. Thank you, Kim Dawson,

628
00:28:55,440 --> 00:28:57,640
Speaker 2: Thank you so much for being with us fabuous. I'm

629
00:28:57,680 --> 00:29:00,239
Speaker 2: going to feature my Twitter feed and LinkedIn and I'm

630
00:29:00,280 --> 00:29:02,080
Speaker 2: going to be doing this afternoon is off of Ken

631
00:29:02,200 --> 00:29:05,560
Speaker 2: Dawson's work. It's on rebalancing. Coming up, what are we

632
00:29:05,560 --> 00:29:08,120
Speaker 2: gonna do on Blueberg running? We're going to talk about

633
00:29:08,440 --> 00:29:14,960
Speaker 2: youth sports in the expense Soccer, BLA, hockey.

634
00:29:15,080 --> 00:29:17,920
Speaker 5: Niki Waller, did you play sport in your youth poorly?

635
00:29:18,240 --> 00:29:20,800
Speaker 5: I played softball? She plays off all your parents went

636
00:29:20,880 --> 00:29:21,760
Speaker 5: money on it? I'm sure.

637
00:29:21,800 --> 00:29:24,400
Speaker 2: Yeah, Lisa Mateo's the whole softball thing as.

638
00:29:24,200 --> 00:29:26,160
Speaker 3: Well as hockey the worst, I think so.

639
00:29:26,400 --> 00:29:27,840
Speaker 5: Yeah. Well, the travel part is a one.

640
00:29:27,760 --> 00:29:32,000
Speaker 3: Youth sports stay with US.

641
00:29:34,240 --> 00:29:37,320
Speaker 6: France winning last night in a World Cup match against Morocco,

642
00:29:37,440 --> 00:29:40,120
Speaker 6: Spain and Belgium facing off tonight in the quarterfinals.

643
00:29:40,160 --> 00:29:41,600
Speaker 5: Is this all you guys watch at home? Now?

644
00:29:41,880 --> 00:29:43,880
Speaker 3: It's it's like ridiculous when it go away.

645
00:29:43,920 --> 00:29:47,520
Speaker 2: It's changed our lives. It's really enjoyable. I love watching

646
00:29:47,560 --> 00:29:48,800
Speaker 2: Telemundo to be honest.

647
00:29:49,160 --> 00:29:51,480
Speaker 6: Oh, yes, because it's it's a whole different it's.

648
00:29:51,320 --> 00:29:54,200
Speaker 3: A different culture and energy and that it's just fabulous.

649
00:29:54,360 --> 00:29:56,080
Speaker 5: Were you following to USA is carefully?

650
00:29:56,280 --> 00:29:56,360
Speaker 8: No?

651
00:29:56,880 --> 00:29:59,640
Speaker 6: Well, yeah, I mean after last week, you know, it's

652
00:29:59,640 --> 00:30:01,200
Speaker 6: a kind of a disappointment.

653
00:30:00,640 --> 00:30:03,640
Speaker 3: Really upset about that many I was not alone on them.

654
00:30:03,800 --> 00:30:04,000
Speaker 5: Yeah.

655
00:30:04,000 --> 00:30:05,800
Speaker 6: Well, the US team's loss of Belgium in the World

656
00:30:05,800 --> 00:30:08,840
Speaker 6: Cup has revived this growing concern among Americans, which is

657
00:30:08,840 --> 00:30:12,080
Speaker 6: a rising cost of youth sports. According to one estimate

658
00:30:12,080 --> 00:30:14,960
Speaker 6: from the Aspen Institute, Family spending on youth sports is

659
00:30:15,040 --> 00:30:18,360
Speaker 6: up forty six percent over the last five years. Our

660
00:30:18,400 --> 00:30:21,760
Speaker 6: senior reporter Randall Williams, he covers Business of Sports, has

661
00:30:21,760 --> 00:30:24,360
Speaker 6: been following the story and he joins us Now and Randall.

662
00:30:24,400 --> 00:30:27,120
Speaker 6: By some estimates, this is a forty billion dollar plus

663
00:30:27,160 --> 00:30:30,560
Speaker 6: industry that is funded by private equity, and so no

664
00:30:30,680 --> 00:30:33,480
Speaker 6: surprise that has become hyper competitive and hyper specialized.

665
00:30:33,880 --> 00:30:34,080
Speaker 11: Yeah.

666
00:30:34,080 --> 00:30:36,560
Speaker 15: I mean, when private equity gets into something, of course,

667
00:30:36,560 --> 00:30:38,760
Speaker 15: they want to maximize profit, and that's not always a

668
00:30:38,800 --> 00:30:41,600
Speaker 15: good thing for youth sports. People think of youth sports

669
00:30:41,640 --> 00:30:44,440
Speaker 15: as the level before college sports, and college sports of

670
00:30:44,440 --> 00:30:47,520
Speaker 15: course is welcoming private equity as well, but with NIL

671
00:30:47,560 --> 00:30:50,000
Speaker 15: with a bunch of different mechanisms, it's sort of the

672
00:30:50,040 --> 00:30:52,600
Speaker 15: amateur level, and I think youth sports isn't meant to

673
00:30:52,600 --> 00:30:54,920
Speaker 15: be that, but it's becoming that because you can identify

674
00:30:55,000 --> 00:30:58,520
Speaker 15: talent earlier on, which therefore could lead to brand collaborations

675
00:30:58,560 --> 00:31:01,880
Speaker 15: and so many other things. Is a huge industry that

676
00:31:01,880 --> 00:31:04,320
Speaker 15: we're saying private equity get into, get into, and other

677
00:31:04,360 --> 00:31:05,240
Speaker 15: investors as well.

678
00:31:05,480 --> 00:31:09,000
Speaker 6: How has technology accelerated this Because we talk about private

679
00:31:09,000 --> 00:31:11,440
Speaker 6: equity getting in, we talked about NIL that those are

680
00:31:11,440 --> 00:31:14,680
Speaker 6: two distinct things, but technology has made it even more

681
00:31:15,600 --> 00:31:16,719
Speaker 6: hyper intense.

682
00:31:16,880 --> 00:31:19,200
Speaker 15: Well, it's interesting like when I was growing up, like

683
00:31:19,320 --> 00:31:21,920
Speaker 15: my dad and my mom would have a film camera

684
00:31:22,240 --> 00:31:23,680
Speaker 15: that they would shoot it for, but that was just

685
00:31:23,720 --> 00:31:25,840
Speaker 15: for fun, Like I had my aspirations of going to

686
00:31:25,840 --> 00:31:28,760
Speaker 15: the NFL ended at fifteen. But now you have people

687
00:31:28,880 --> 00:31:31,760
Speaker 15: using apps like game Changer, which you can literally just

688
00:31:31,800 --> 00:31:34,280
Speaker 15: film the entire thing, create a highlight reel for your child,

689
00:31:34,440 --> 00:31:35,160
Speaker 15: and then email it.

690
00:31:35,200 --> 00:31:36,200
Speaker 4: To scouts themselves.

691
00:31:36,240 --> 00:31:38,840
Speaker 15: And of course the supporters behind an app like game

692
00:31:38,960 --> 00:31:41,280
Speaker 15: Changer are going to pour money into it, say hey,

693
00:31:41,400 --> 00:31:44,000
Speaker 15: use our app and then you can go and market yourself.

694
00:31:44,040 --> 00:31:46,880
Speaker 15: And a lot of times, this nil money that athletes

695
00:31:46,880 --> 00:31:48,960
Speaker 15: are able to sign earlier and earlier can change a

696
00:31:49,040 --> 00:31:51,280
Speaker 15: family's life, so the parents are pushing it and having

697
00:31:51,280 --> 00:31:52,280
Speaker 15: to spend more as well.

698
00:31:52,120 --> 00:31:53,400
Speaker 3: Exactly like you.

699
00:31:53,920 --> 00:31:56,920
Speaker 2: I remember exactly where I was standing when I realized

700
00:31:56,960 --> 00:32:00,400
Speaker 2: I would not play for the Montreal Canadians. Only the

701
00:32:00,480 --> 00:32:04,240
Speaker 2: kids today, I'm sorry, name what's that name? Image likeness?

702
00:32:04,600 --> 00:32:07,440
Speaker 2: You're playing D three if you're lucky. Are we within

703
00:32:07,560 --> 00:32:11,560
Speaker 2: all the different sports informing the children of how special

704
00:32:12,160 --> 00:32:14,800
Speaker 2: those people are playing Major D one and pro?

705
00:32:15,000 --> 00:32:16,320
Speaker 3: I don't think so, not anymore.

706
00:32:16,360 --> 00:32:18,480
Speaker 15: And the reason for that is because you know, do

707
00:32:18,520 --> 00:32:21,280
Speaker 15: you have low level athletes who can make anywhere from

708
00:32:21,320 --> 00:32:24,160
Speaker 15: fifty to sixty to twenty to thirty to sometimes hundreds

709
00:32:24,160 --> 00:32:27,600
Speaker 15: of thousand dollars a semester, and so their families are like, listen,

710
00:32:27,640 --> 00:32:29,800
Speaker 15: you don't have to go to the NFL, the NBA,

711
00:32:29,920 --> 00:32:32,720
Speaker 15: the MLB, the MLS and so many other leagues anymore.

712
00:32:32,840 --> 00:32:34,520
Speaker 15: You just have to go and play in college as

713
00:32:34,560 --> 00:32:36,720
Speaker 15: long as you can, so that you can provide for

714
00:32:36,760 --> 00:32:38,520
Speaker 15: our family for a four to five year periods and

715
00:32:38,520 --> 00:32:40,840
Speaker 15: then they go into jobs like us. And so it

716
00:32:41,440 --> 00:32:44,680
Speaker 15: is a very interesting time in college sports where you

717
00:32:44,760 --> 00:32:47,440
Speaker 15: have people who want to play for five, six, sometimes

718
00:32:47,440 --> 00:32:49,600
Speaker 15: seven years in college just so they can make money

719
00:32:49,600 --> 00:32:50,560
Speaker 15: and name, image and likeness.

720
00:32:50,600 --> 00:32:50,840
Speaker 3: Seven.

721
00:32:50,960 --> 00:32:54,280
Speaker 6: I started off by talking about the World Cup. How

722
00:32:54,360 --> 00:32:58,280
Speaker 6: has the professionalization of youth sports contributed perhaps to the

723
00:32:58,400 --> 00:33:00,360
Speaker 6: US not being as well prepared for thing like the

724
00:33:00,400 --> 00:33:02,240
Speaker 6: World Cup, because that's the criticism, right.

725
00:33:02,440 --> 00:33:05,360
Speaker 15: I think that if you look at Europe, and Europe

726
00:33:05,360 --> 00:33:08,480
Speaker 15: has these youth camps that you think of Lionel Messi,

727
00:33:08,560 --> 00:33:10,880
Speaker 15: he was with Barcelona at a very young age and

728
00:33:10,880 --> 00:33:13,640
Speaker 15: then raised in that system against a lot of top

729
00:33:13,640 --> 00:33:16,280
Speaker 15: tier competition that doesn't really exist here. Of course we

730
00:33:16,400 --> 00:33:19,480
Speaker 15: have youth soccer clubs and camps, but it's not to

731
00:33:19,560 --> 00:33:22,320
Speaker 15: the same level. You've never seen a thirteen or thirteen

732
00:33:22,400 --> 00:33:25,280
Speaker 15: year old signed to NYCFC. It just doesn't happen the

733
00:33:25,280 --> 00:33:27,480
Speaker 15: same way. And so because of that, and because of

734
00:33:27,480 --> 00:33:29,440
Speaker 15: the rise and costs. You think of the travel, you

735
00:33:29,480 --> 00:33:32,680
Speaker 15: think of the cleats, you think of lodging and tournaments

736
00:33:32,680 --> 00:33:34,840
Speaker 15: and all of these different fees. You have parents who

737
00:33:34,880 --> 00:33:36,920
Speaker 15: are like, you know, I think I'm good. You can

738
00:33:36,960 --> 00:33:39,160
Speaker 15: play a different sport, or you could just go and

739
00:33:39,200 --> 00:33:40,280
Speaker 15: be an academic scholar.

740
00:33:40,320 --> 00:33:41,440
Speaker 3: Can anybody beat France?

741
00:33:42,280 --> 00:33:44,360
Speaker 15: I think they can. I think Spain can. I think

742
00:33:44,400 --> 00:33:46,800
Speaker 15: England can. I think Argentina can. But it's going to

743
00:33:46,880 --> 00:33:48,520
Speaker 15: take you on your best day and you're gonna have

744
00:33:48,560 --> 00:33:50,680
Speaker 15: to shut down a bunch of different superstars. It's like

745
00:33:50,680 --> 00:33:53,200
Speaker 15: playing against the Golden State Warriors with Steph Curry and

746
00:33:53,480 --> 00:33:55,440
Speaker 15: Kevin Durant and Klay Thompson and Draymond Green.

747
00:33:55,480 --> 00:33:56,480
Speaker 4: They are that level good.

748
00:33:57,200 --> 00:33:58,479
Speaker 5: That was a good way to put it. Who are

749
00:33:58,480 --> 00:34:00,120
Speaker 5: you rooting for?

750
00:34:00,120 --> 00:34:00,959
Speaker 3: For a good story?

751
00:34:01,040 --> 00:34:03,800
Speaker 15: So of course it's either I'd rather I would like

752
00:34:03,880 --> 00:34:06,440
Speaker 15: to see a rematch of the twenty twenty two final,

753
00:34:06,920 --> 00:34:09,800
Speaker 15: which was Argentina and France. That is probably the greatest

754
00:34:09,800 --> 00:34:11,720
Speaker 15: sporting event that I've ever watched.

755
00:34:12,080 --> 00:34:14,359
Speaker 5: So seeing that we're out of time, we're out of time.

756
00:34:14,400 --> 00:34:16,279
Speaker 3: The control room never talks to me, They only talk

757
00:34:16,320 --> 00:34:18,520
Speaker 3: to you. Luigi's vicious.

758
00:34:18,600 --> 00:34:20,919
Speaker 2: I mean, you know, I want to answer like six

759
00:34:20,960 --> 00:34:21,640
Speaker 2: more questions.

760
00:34:21,640 --> 00:34:23,000
Speaker 5: We'll get him back on next We'll get him out

761
00:34:23,080 --> 00:34:24,960
Speaker 5: next week. I'm all right, thanks so much.

762
00:34:25,000 --> 00:34:28,640
Speaker 6: Randon Williams or Bloomberg Business of Sports Senior reporter.

763
00:34:28,840 --> 00:34:35,200
Speaker 3: Bloomberg money. Where we do Shakespeare, We'll do that right now.

764
00:34:36,120 --> 00:34:39,080
Speaker 2: Shakespeare, where the sky meets to see It calls me

765
00:34:39,760 --> 00:34:41,800
Speaker 2: and no one knows how far it goes.

766
00:34:42,120 --> 00:34:44,400
Speaker 3: It's the wind in my sail on the sea stays

767
00:34:44,440 --> 00:34:44,880
Speaker 3: behind me.

768
00:34:45,040 --> 00:34:46,120
Speaker 10: This is one they all know.

769
00:34:46,280 --> 00:34:48,839
Speaker 3: If I go, there's just no telling how far.

770
00:34:49,000 --> 00:34:50,800
Speaker 5: This is not Shakespeare, who's bwana?

771
00:34:50,880 --> 00:34:51,520
Speaker 3: Okay, there we.

772
00:34:51,560 --> 00:34:56,680
Speaker 6: Go Shakespeare twenty twenty six. It is truly and it's Friday,

773
00:34:56,680 --> 00:34:59,000
Speaker 6: so of course we're looking ahead to the weekend into

774
00:34:59,040 --> 00:35:01,400
Speaker 6: next week. So for that we bring in Bloomberg's This

775
00:35:01,480 --> 00:35:05,840
Speaker 6: Weekend's anchor, Lisa Mattale. Lisa, all right, Mawana.

776
00:35:06,320 --> 00:35:08,400
Speaker 16: If you're going into the theaters this weekend, it's going

777
00:35:08,440 --> 00:35:10,759
Speaker 16: to be Mawana. Tom knows of course why this is

778
00:35:10,840 --> 00:35:13,200
Speaker 16: tough so on my list because Scarlett, I don't know

779
00:35:13,200 --> 00:35:15,520
Speaker 16: if I have a huge crush on Dwayne the Rod Johnson.

780
00:35:15,640 --> 00:35:17,520
Speaker 5: Oh, that's the reason for it.

781
00:35:17,719 --> 00:35:20,440
Speaker 16: But this is the remake of the twenty sixteen animated

782
00:35:20,480 --> 00:35:23,919
Speaker 16: film that's done phenomenal. So now they're doing the live action,

783
00:35:24,080 --> 00:35:25,879
Speaker 16: so now you have the real actors, So you have

784
00:35:26,040 --> 00:35:29,680
Speaker 16: Dwayne Johnson himself actually out there, so he's out.

785
00:35:29,480 --> 00:35:33,600
Speaker 3: There shown, So it's out there. My Dane is now

786
00:35:33,680 --> 00:35:34,480
Speaker 3: part of the show.

787
00:35:35,520 --> 00:35:36,640
Speaker 5: It's part of this show.

788
00:35:37,239 --> 00:35:39,919
Speaker 16: The reviews haven't been so great, but that's out there

789
00:35:39,920 --> 00:35:43,480
Speaker 16: and that's at the box office this weekend for music fanatics. Okay,

790
00:35:43,520 --> 00:35:47,239
Speaker 16: for those, the Rolling Stones are back there this week.

791
00:35:48,480 --> 00:35:50,200
Speaker 5: They're making music.

792
00:35:50,200 --> 00:35:52,320
Speaker 16: I'm telling you the twenty fifth studio album.

793
00:35:52,080 --> 00:35:53,560
Speaker 5: Foreign Tongues, that's what it's called.

794
00:35:53,600 --> 00:35:58,200
Speaker 16: So it's fourteen tracks, there's twelve original, two covers, and

795
00:35:58,200 --> 00:36:01,200
Speaker 16: they're they're grouping up with different people. They're in different collaborations.

796
00:36:01,239 --> 00:36:04,160
Speaker 5: One is with Paul McCartney. The last album.

797
00:36:03,880 --> 00:36:05,799
Speaker 16: Released in twenty twenty three. So this is I know

798
00:36:05,840 --> 00:36:07,320
Speaker 16: Tom's weekend is going to be spent.

799
00:36:07,640 --> 00:36:10,080
Speaker 2: I will put headphones on and I will listen and

800
00:36:10,160 --> 00:36:12,760
Speaker 2: it will be with immense respect for Charlie Watts.

801
00:36:13,160 --> 00:36:15,120
Speaker 5: How much did album costs these days?

802
00:36:15,160 --> 00:36:15,359
Speaker 10: Now?

803
00:36:16,239 --> 00:36:18,440
Speaker 2: Like I don't know, I was just streaming on title

804
00:36:18,560 --> 00:36:20,000
Speaker 2: is what I'm going to do. But the answer is

805
00:36:20,040 --> 00:36:21,839
Speaker 2: how much did it cost to make this? It took

806
00:36:21,840 --> 00:36:24,239
Speaker 2: them years to put this thing together. Yeah, this was

807
00:36:24,320 --> 00:36:27,600
Speaker 2: not some rich guys six week project. This is They've

808
00:36:27,719 --> 00:36:29,120
Speaker 2: really put a lot of effort.

809
00:36:29,160 --> 00:36:31,239
Speaker 6: It had to mend a lot of what else you

810
00:36:31,239 --> 00:36:34,080
Speaker 6: got say, they're still going, They're still going.

811
00:36:34,680 --> 00:36:36,520
Speaker 16: So I want to go to ECO Data because we

812
00:36:36,520 --> 00:36:40,400
Speaker 16: have a jam packed calendar coming up. So we start

813
00:36:40,400 --> 00:36:43,279
Speaker 16: off on Tuesday we have CPI, oh yes, yes, and

814
00:36:43,320 --> 00:36:45,759
Speaker 16: then on Wednesday we have BBI. So aside from that,

815
00:36:45,840 --> 00:36:48,880
Speaker 16: then we go into Thursday. Retail sales is a big number, sure,

816
00:36:49,120 --> 00:36:51,920
Speaker 16: and then Friday we have housing starts building permits. When

817
00:36:51,920 --> 00:36:54,319
Speaker 16: I was looking at the prior and then what the

818
00:36:54,400 --> 00:36:56,400
Speaker 16: expectations are, the biggest kind of difference I saw was

819
00:36:56,440 --> 00:36:59,120
Speaker 16: actually in housing starts. You know, the prior was a

820
00:36:59,200 --> 00:37:01,960
Speaker 16: dip of about fifty eighteen percent. The forecast is for

821
00:37:02,040 --> 00:37:04,600
Speaker 16: a horizon about thirteen percent. So that was a difference there.

822
00:37:04,800 --> 00:37:06,600
Speaker 16: And then I also want to point out this Bank

823
00:37:06,640 --> 00:37:09,839
Speaker 16: of America survey that talked about how much consumers are

824
00:37:09,840 --> 00:37:12,680
Speaker 16: spending for June, and they're spending more.

825
00:37:13,280 --> 00:37:15,680
Speaker 5: This is looking at credit card data. This is also

826
00:37:15,719 --> 00:37:17,200
Speaker 5: looking at prices are higher.

827
00:37:17,440 --> 00:37:19,880
Speaker 16: Well, the reason why is because they're not. The prices

828
00:37:19,920 --> 00:37:23,000
Speaker 16: aren't higher, but they're spending more because gas is cheaper, right,

829
00:37:23,000 --> 00:37:25,920
Speaker 16: so they have a little bit more disctionary income. And

830
00:37:25,960 --> 00:37:29,120
Speaker 16: the World Cup of course June, so they're starting to

831
00:37:29,120 --> 00:37:29,680
Speaker 16: spend more.

832
00:37:30,040 --> 00:37:32,719
Speaker 2: Yeah, are you doing like ten thousand steps a day now?

833
00:37:32,719 --> 00:37:34,719
Speaker 2: After Nathan's famous last week you.

834
00:37:34,680 --> 00:37:37,520
Speaker 5: Did see like did you of July?

835
00:37:37,600 --> 00:37:40,040
Speaker 16: You were out in living in Cody Island from Bloomberg

836
00:37:40,080 --> 00:37:44,440
Speaker 16: this weekend, Yes, I had a tru I did not

837
00:37:44,680 --> 00:37:47,160
Speaker 16: have any of them because they were in the boiling

838
00:37:47,280 --> 00:37:48,200
Speaker 16: sun for so long.

839
00:37:48,239 --> 00:37:50,799
Speaker 5: I was like, maybe I shouldn't meet these But it

840
00:37:50,840 --> 00:37:52,440
Speaker 5: was fun. It was a good experience.

841
00:37:52,680 --> 00:37:54,440
Speaker 16: I'm a Brooklyn girl, so being back, you know, in

842
00:37:54,480 --> 00:37:55,520
Speaker 16: Cony Island, you're good.

843
00:37:56,120 --> 00:37:56,919
Speaker 5: Was it was just nice.

844
00:37:56,920 --> 00:37:57,760
Speaker 4: It was a good experience.

845
00:37:58,160 --> 00:38:00,480
Speaker 5: What do you have coming up this weekend? I'm we're

846
00:38:00,480 --> 00:38:01,120
Speaker 5: talking a lot.

847
00:38:01,000 --> 00:38:03,160
Speaker 16: Because all the talk has been about s k HEINEX,

848
00:38:04,160 --> 00:38:07,520
Speaker 16: so we're tapping into that as at Ludlow is going

849
00:38:07,560 --> 00:38:10,960
Speaker 16: through the weekend. He's joining us as well, so that'll

850
00:38:11,000 --> 00:38:11,640
Speaker 16: be a good time.

851
00:38:11,920 --> 00:38:13,319
Speaker 4: On top of that, he's just killed it.

852
00:38:13,680 --> 00:38:16,440
Speaker 2: We make jokes about it, folks, but ed Ludlow's leadership

853
00:38:16,520 --> 00:38:19,640
Speaker 2: here on all this technology. I'm looking literally right now

854
00:38:20,040 --> 00:38:22,120
Speaker 2: at these SpaceX.

855
00:38:21,440 --> 00:38:24,279
Speaker 3: Thirty year bond I get killed on it? Are you

856
00:38:24,360 --> 00:38:24,759
Speaker 3: kidding me?

857
00:38:24,800 --> 00:38:27,719
Speaker 2: It's gone priced down, yield up, and it hasn't found

858
00:38:27,760 --> 00:38:30,520
Speaker 2: a bid yet it's ugly. That'll be a theme for

859
00:38:30,640 --> 00:38:33,440
Speaker 2: Ed Ludlow on Bloomberg this weekend. Look for that with

860
00:38:33,560 --> 00:38:36,600
Speaker 2: David and all this weekend.

861
00:38:36,600 --> 00:38:38,520
Speaker 6: All right, Lisa Mitail, thank you so much, and of

862
00:38:38,520 --> 00:38:40,840
Speaker 6: course be sure to watch Bloomberg this weekend. Every Saturday

863
00:38:40,880 --> 00:38:44,040
Speaker 6: and Sunday morning, starting at seventy in Eastern Time.

864
00:38:44,440 --> 00:38:48,240
Speaker 2: This is the Bloomberg Money Podcast, bringing you a smart look.

865
00:38:48,640 --> 00:38:49,399
Speaker 3: Three two.

866
00:38:50,080 --> 00:38:53,760
Speaker 2: This is the Bloomberg Money Podcast, bringing you a smart

867
00:38:53,800 --> 00:38:57,759
Speaker 2: look at the forces shaping your financial life. I'm Tom

868
00:38:57,840 --> 00:39:01,400
Speaker 2: Keen with Scarlet Foo. I watch the show live on

869
00:39:01,480 --> 00:39:03,800
Speaker 2: Bloomberg TV every Friday at.

870
00:39:03,680 --> 00:39:04,880
Speaker 3: Noon Wall Street Time.

871
00:39:05,320 --> 00:39:09,800
Speaker 2: Subscribe to the podcast on Apple, Spotify or wherever you listen,

872
00:39:10,239 --> 00:39:13,560
Speaker 2: and as always, on the Bloomberg Terminal and the Bloomberg

873
00:39:13,640 --> 00:39:14,400
Speaker 2: Business app.