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Speaker 1: Bloomberg Audio Studios, podcasts, radio news. You're listening to the

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Speaker 1: Bloomberg Intelligence podcast. Catch us live weekdays at ten am

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Speaker 1: Eastern on Apple card playing Android Auto with the Bloomberg

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Speaker 1: Business App. Listen on demand wherever you get your podcasts,

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Speaker 1: or watch us live on YouTube.

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Speaker 2: Going back to that Tesla story, disappointing Quartered socks off

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Speaker 2: twelve percent, Elon must trying to redirect the focus of

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Speaker 2: investors on other parts of the company, AI, robotaxis and

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Speaker 2: the like. Steve Man joins as he covers the global

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Speaker 2: auto industry for Bloomberg Intelligence.

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Speaker 3: Steve, what you make of the quarter last night? Holistically?

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Speaker 3: For the Tesla.

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Speaker 4: Story, I mean, I still like their long term, medium

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Speaker 4: term A look on AI, I'm not you know, in

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Speaker 4: our view were not including eight billion optimous robots. I

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Speaker 4: think that's a little bit out there. But AI is

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Speaker 4: will continue to drive the stock. But I think today

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Speaker 4: people are focused on their auto business. It's it's a

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Speaker 4: little bit worrying. I think investors were expecting their automotive

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Speaker 4: gross margin to flatten out in the second quarter versus

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Speaker 4: the first, but it did decline about one hundred and

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Speaker 4: fifty basis points to thirteen thirteen point nine percent, which

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Speaker 4: is in line with you know, the legacy automaker's automotive

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Speaker 4: growth marginal fourteen percent. So there is some concerns with

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Speaker 4: the investors. Is you know, are there any more upside

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Speaker 4: on margin? Are they you know, are they really that

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Speaker 4: good with cost?

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Speaker 5: But I guess the question is how do we value

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Speaker 5: the stock?

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Speaker 6: So I hear you that the auto part of their

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Speaker 6: business is very much maybe in line with what other

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Speaker 6: auto companies are talking about, but they trade an estimated

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Speaker 6: pe of like ninety times, Like is it worth it

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Speaker 6: for that? If it's if it's also being valued as

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Speaker 6: an AI company.

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Speaker 4: I think there's a couple of things that the investors

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Speaker 4: are focused on beyond this second quarter. You know, they

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Speaker 4: did pull ahead the start of production for a more

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Speaker 4: affordable EV from like the second half of next year

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Speaker 4: to the first half, which is critical. I think the market,

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Speaker 4: the the EV market today globally is actually consumers in

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Speaker 4: the EV market actually looking for a more affordable EV

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Speaker 4: something that's you know, less than fifty thousand US dollars.

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Speaker 4: You know, most of the EV's offered today are above

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Speaker 4: fifty thousand dollars, So, you know, I think the investors

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Speaker 4: are hoping that, you know, into twenty twenty five and

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Speaker 4: into twenty twenty six, we're gonna get a rebound in

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Speaker 4: EV sales because there's gonna be more affordable EV's, budget friendly,

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Speaker 4: EV's for the mass market.

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Speaker 2: Steve Tesla right now is an auto company and it's

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Speaker 2: an other company. Elon wants you to focus on the

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Speaker 2: other Can you define what's in that other bucket and

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Speaker 2: when investors believe it will be material to their revenution profits.

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Speaker 4: Yeah, you know, he talks about AI quite a bit,

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Speaker 4: you know, robo taxi, optimism, robot but if you think

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Speaker 4: of AI, I think there's you know, potentially even more

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Speaker 4: ways to generate revenues from AI. One of the things

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Speaker 4: that I think the market is also focused on other

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Speaker 4: than robotaxi, taking a passenger from point A to point

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Speaker 4: B is for example. You know, these cars have huge

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Speaker 4: battery storage capacity, right, and these things, if they can

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Speaker 4: move about on its own, you can really help out

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Speaker 4: the utilities in terms of, you know, redistributing power across

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Speaker 4: the grid.

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Speaker 6: Well to that point, I mean, their energy business was

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Speaker 6: actually quite impressive. It had its highest installation of batteries

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Speaker 6: and revenue ever and energy accounted for just twelve percent

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Speaker 6: and sixteen percent of Tesla's revenue and gross profit, respectively.

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Speaker 6: I mean, yeah, it's going to fluctuate, but that's pretty strong.

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Speaker 4: Yeah, it's it's a good good sign. I think, uh,

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Speaker 4: you know, those those tend to be a little bit

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Speaker 4: lumpy because the orders are big, and so whenever they

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Speaker 4: deliver the the the order and when they ever they

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Speaker 4: book it that that tends to be lumpy. I think

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Speaker 4: we'll have to see if it's going to be consistent.

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Speaker 4: But I think the investors are very focused on the

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Speaker 4: auto business. You know, what are they when are they

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Speaker 4: going to roll out the new are they going to

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Speaker 4: be on time? And rolling out the new EV the

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Speaker 4: affordable EV? And then longer term it's really uh, you

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Speaker 4: know AI, is he going to deliver? What what is

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Speaker 4: he going to say in October?

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Speaker 1: Uh?

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Speaker 4: You know the the AI event that he's hosting. You know,

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Speaker 4: there was there were a lot of questions about that

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Speaker 4: during the call, but he's pretty they were pretty tight lip.

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Speaker 3: So what is that October evan?

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Speaker 2: You tell us what the company says it is and

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Speaker 2: what you think it may be good distinction?

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Speaker 4: Yeah, yeah, I think I think for the most part,

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Speaker 4: it's going to be, you know, what is this new

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Speaker 4: vehicle they're launching. I think investors will be focused on,

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Speaker 4: what is this new vehicle, What is the price of

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Speaker 4: this vehicle? How are you going to manufactures so it

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Speaker 4: further cuts you know, per unit costs. The other one

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Speaker 4: is the full self driving, the full driving system that

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Speaker 4: they're trying to roll out, the robo taxi that they're

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Speaker 4: trying to roll out. I think people are going to

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Speaker 4: be focused on when is that going to generate you know,

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Speaker 4: material earnings and material revenue. Now I think it's not

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Speaker 4: going to be until twenty thirty, but so but I

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Speaker 4: really think the other thing that's going to get really

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Speaker 4: people really excited is is it is the Optimist robot.

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Speaker 4: Because the Optimist Robot, they really haven't talked too much

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Speaker 4: about it yet. I don't think it's going to get

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Speaker 4: to eight billion unit sales anytime soon. But you know,

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Speaker 4: if they can incorporate those Optimist robot into their manufacturing,

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Speaker 4: I think there's going to be a lot of potential

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Speaker 4: for cost cuts.

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Speaker 6: Okay, so the addressable market isn't John Tucker buying one.

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Speaker 6: The adressible market is must using them to build a car.

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Speaker 6: That's right, Okay, so don't worry you disappointed?

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Speaker 5: Now everything for me to this.

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Speaker 6: Point, like if John Tucker wanted one, could eventually he

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Speaker 6: actually buy one?

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Speaker 7: No, I don't.

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Speaker 4: I don't think he doesn't. It's not for sale right now.

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Speaker 4: I think what he's he's I think what he's going

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Speaker 4: to try to do is, uh, you know, built this robot,

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Speaker 4: optimize this robot. Uh, you know within the confines of

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Speaker 4: Tesla first be you know, they're going to make it

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Speaker 4: good enough, then they're going.

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Speaker 8: To offer it to the public.

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Speaker 4: All right, So maybe that's going to be not soon.

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Speaker 6: Yeah, yeah, So you gotta wait, you gotta wait, John Tucker,

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Speaker 6: all right, Steve thinks lot really appreciated. Steve Man Bloomberg Intelligence,

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Speaker 6: Global Autos and Industrials research analysts. You have to wonder,

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Speaker 6: just people on the call, like really addressable mark? Is

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Speaker 6: everyone on the planet? I don't know that's could you.

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Speaker 2: Look at the stands, I mean from starting the year

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Speaker 2: till like the third week of April, the stock was

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Speaker 2: down fifty percent. Since then up seventy five percent. So

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Speaker 2: I mean it's just do you buy off on all

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Speaker 2: these other bets outside of the car business.

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Speaker 3: You have to bend metal or don't you?

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Speaker 5: And then how do you?

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Speaker 8: That's always been the.

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Speaker 3: Case for Tessa story. You have to believe in Elon.

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Speaker 3: That's simple as that.

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Speaker 6: But it's going even bigger and bigger. It's like the

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Speaker 6: other gets bigger and bigger with more stuff.

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Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live

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Speaker 1: weekdays at ten am Eastern on applecar Play and Android

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Speaker 1: Auto with the Bloomberg Business app. You can also listen

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Speaker 1: live on Amazon Alexa from our flagship New York station

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Speaker 1: Just Say Alexa, playing Bloomberg eleven thirty.

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Speaker 6: This Bloomberg Intelligence Radio, Happy Wednesday, everybody, Happy hump Day,

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Speaker 6: and Alex c alongside Paul Sweeney and John Tucker. We

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Speaker 6: are broadcasting to you live from Interactive Broker Studio right

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Speaker 6: here in Midtown Manhattan. So John Tucker laid out, the

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Speaker 6: market declined perfectly. And my really silly question is well,

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Speaker 6: Wire stocks down? And I say silly because you can say, oh,

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Speaker 6: of course, you know Google Tesla the disappoint and therefore

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Speaker 6: stocks are down.

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Speaker 5: Is that it?

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Speaker 6: Or is it a continuation of last week? And the

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Speaker 6: rotation theme is still intact? Is there something else going

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Speaker 6: on here. Bill Dudley talking in a Bloomberg opinion article

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Speaker 6: about how he changed his mind. He thinks that a

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Speaker 6: cut should come in July because employment doesn't look that good.

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Speaker 5: So let's get the.

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Speaker 6: Read here with Kim Forrest, founder and chief investment officer

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Speaker 6: of Boca Capital Partners, joining us from Pittsburgh. Kim, it's

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Speaker 6: a dumb question. Wire stocks down so much?

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Speaker 9: Okay, I'm going to answer it with a dumb answer.

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Speaker 8: Are you ready?

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Speaker 9: Yeah, because there's more sellers than buyers.

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Speaker 4: No.

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Speaker 5: I love this answer. Actually I know well.

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Speaker 9: I learned this on my very first day at Parker

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Speaker 9: Hunter when I was a cell side analyst. That's how

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Speaker 9: one of the radio announcers would say, Parker Hunter anyhow. Yes,

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Speaker 9: And they didn't cover this in MBA program on valuation.

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Speaker 9: But when people get afraid that maybe they've paid too

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Speaker 9: much for a stock, or maybe that things aren't going

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Speaker 9: the way they think, they sell and selling makes stocks

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Speaker 9: go down because when there's more sellers and buyers, the

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Speaker 9: prices fall. And that is why we love markets, because

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Speaker 9: it does the inverse. When there are more buyers than sellers,

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Speaker 9: prices go up. But the fundamentals really are is everything okay,

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Speaker 9: And it looks like some things are okay and some

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Speaker 9: things aren't, and it depends on what day the market

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Speaker 9: thinks more of one than the other.

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Speaker 2: What do you make of this whole AI trade in

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Speaker 2: the marketplace certainly was a theme not just for tech

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Speaker 2: companies but for the whole market beginning in twenty twenty three.

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Speaker 3: How do you view it?

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Speaker 2: Because again we've had Tesla talking about it last night,

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Speaker 2: Google talking about it still.

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Speaker 9: Well, I have a nuanced view because I was a

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Speaker 9: software developer in company that actually developed neural networks and

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Speaker 9: then used neural networks. So and that is the underlaying

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Speaker 9: technology that's behind chat, GPT and autonomous driving and all

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Speaker 9: of that kind of stuff. So here's the skinny on that.

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Speaker 9: I strongly believe the moment for AI is finally here

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Speaker 9: because computers can be fast enough and we have enough

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Speaker 9: of the right data to be able to train models.

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Speaker 9: But investors are always impatient with new technology, and they thought,

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Speaker 9: just like they thought autonomous druck cars were just around

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Speaker 9: the corner in twenty sixteen, they're not. It always takes

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Speaker 9: longer to develop really good technology. AI is really good,

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Speaker 9: but it's not going to pay off in the next

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Speaker 9: fifteen to twenty minutes. So investors are becoming aware of

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Speaker 9: that right now, especially as Google kind of outlined its

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Speaker 9: spending plans that go on for the foreseeable future.

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Speaker 6: Well, that's where I think that question then goes to

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Speaker 6: my first question of why our stocks are selling off,

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Speaker 6: and that basically they have to spend to then monetize,

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Speaker 6: and there's going to be a gap between the spending

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Speaker 6: and the monetization and there's still a race to spend.

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Speaker 6: And as an investor, how do you value something like that?

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Speaker 9: Well, in my mind, you don't yet, right I don't

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Speaker 9: know what Google is going to be able to monetize

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Speaker 9: because we're not clear what problem they're solving. Like that's

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Speaker 9: the first thing we have to ask, what problem are

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Speaker 9: you solving? Is it worth solving with technology? And how

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Speaker 9: much money will you get? And we don't have any

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Speaker 9: of those answers, But we do have this idea that

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Speaker 9: AI is going to work out. So how we play

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Speaker 9: this is we've been buying the semis and then storage

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Speaker 9: companies or semis that have to do with storage, because

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Speaker 9: we know AI takes tons of data, unbelievable amounts of data,

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Speaker 9: probably more data than it takes electricity. I mean, I

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Speaker 9: can't emphasize how much data is needed. Okay, I've ever

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Speaker 9: done that, but that's what we've been doing. So we

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Speaker 9: buy companies like net app, which makes storage enterprise storage devices,

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Speaker 9: and then Micron because they make one of the elements

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Speaker 9: of storage, which is called nand it's a technology a

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Speaker 9: chip that you can store things on. And that is

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Speaker 9: how we've played it because we don't know what time

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Speaker 9: frame we're going to be in. We just know somewhere

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Speaker 9: within the next ten years, AI is going to be

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Speaker 9: a thing and show productivity and people will pay for it.

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Speaker 2: Outside of technology, Kim, are there areas that are interest you?

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Speaker 8: Oh?

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Speaker 9: All of them are interesting, honestly. You know, energy is

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Speaker 9: a big question mark because it's been kind of unloved

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Speaker 9: as we've done the move towards green and now we're

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Speaker 9: kind of going maybe we need you know, energy for

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Speaker 9: a while longer, you know, the old fashioned kind that

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Speaker 9: we dig out of the earth. That's kind of interesting,

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Speaker 9: and I think if we're going to be in a

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Speaker 9: declining interest rate environment, maybe things like housing and then

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Speaker 9: ancillary areas around housing, like home goods and that sort

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Speaker 9: of thing. You know, items that people buy when they

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Speaker 9: buy a new house that might be interesting. And again,

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Speaker 9: these are kind of three to five year time periods

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Speaker 9: for us. We don't ever really want to make bets

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Speaker 9: on the next six months because anything can happen, right,

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Speaker 9: So we're always looking out three to five.

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Speaker 6: Years, which brings me though to the election can because

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Speaker 6: I appreciate that you're not going to tradeer on the election,

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Speaker 6: But there are some policies that feel binary and election

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Speaker 6: and energy maybe one of them in a Trump versus

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Speaker 6: Harris world, which would then affect investment and returns and

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Speaker 6: prices in the next, say, three to five years, which

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Speaker 6: is your time frame.

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Speaker 5: How do you wind up thinking about it?

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Speaker 9: Sure, well, I'm kind of a realist too. As much

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Speaker 9: as you would like the world to be driven by renewables,

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Speaker 9: it's not practical, isn't if you look at any of

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Speaker 9: the numbers. Even as the use of renewables have gone up,

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Speaker 9: so too has the use of non renewables. Right, So

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Speaker 9: I think if you you know, sure the scale may

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Speaker 9: be tilted towards renewables, maybe you play it by finding

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Speaker 9: a company that does both. And a lot of the

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Speaker 9: energy companies are trying to get a green footprint somehow,

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Speaker 9: so I think that might be where you look.

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Speaker 2: Fixed income, Kim, how are you guys allocating to fixed

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Speaker 2: income these days? Because you know, folks can sit into

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Speaker 2: your treasure and get down your you know, four point

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Speaker 2: four percent.

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Speaker 9: I know, well, we're short. We're still in the short term,

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Speaker 9: right Like whenever I have to replace a bond, I'm

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Speaker 9: trying to go as short as I can to get

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Speaker 9: the highest amount. And two to three years is where

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Speaker 9: we're liking to buy. Anything longer than that, I don't know.

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Speaker 9: It just seems too risky because it could go literally

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Speaker 9: either way. Right if we're going to reinflate, if the

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Speaker 9: curve is going to go back to normal, maybe long

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Speaker 9: term rates will go up a bit, short term rates

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Speaker 9: will fall. So let's live it up and buy some

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Speaker 9: short term rates because we usually we don't trade them.

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Speaker 9: We just let them expire, right, So we're buying the

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Speaker 9: yield so maturity.

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Speaker 5: Before we let you go.

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Speaker 6: Let's get into the debate about small caps. Do you

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Speaker 6: say yay or nay to small caps?

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Speaker 9: I am a big ya. I have about half of

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Speaker 9: my portfolios in small I would say mid cap. I

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Speaker 9: can't really look at anybody less than a billion dollars,

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Speaker 9: I don't have the temperament for the companies that live there.

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Speaker 9: That being said, those high quality small companies often get

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Speaker 9: bought by larger companies, and that's kind of what we're

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Speaker 9: looking for, is companies that have a really great track

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Speaker 9: record of making products that their clients love, and a

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Speaker 9: lot of them tend to get bought out and it

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Speaker 9: really does add a boost to your returns. So that's

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Speaker 9: what we look for.

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Speaker 5: All right, good stuff, Kim, We appreciate you.

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Speaker 6: Thank you very much, Kim. Forrest founder and CIO. A

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Speaker 6: book of capital partners joining us on that. Okay, de reine.

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Speaker 5: But it's interesting.

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Speaker 6: It's an M and A play. It's not like a

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Speaker 6: fed cutting play. It's not necessarily a rotation play, but

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Speaker 6: at takeout play.

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Speaker 5: So that's also quite interesting.

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Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live

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Speaker 6: We bring you all the top news and business finance,

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Speaker 6: economics and earnings. There are lens of our Bloomberg Intelligence

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Speaker 6: folks that cover two thousand companies and one hundred and

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Speaker 6: thirty industries worldwide, and now is our great time we

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Speaker 6: get to focus on Google aka Alphabet that's dock down,

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Speaker 6: following the most since February twenty six and hitting its

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Speaker 6: lowest level since June eighteenth. This is really hitting it

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Speaker 6: the earnings from yesterday. So Man Deep saying Bloomberg Intelligence

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Speaker 6: senior tech industry analyst is joining us now in studio

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Speaker 6: to dissect it. So on the one hand, we have

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Speaker 6: the CAPEX spend and the other hand we have.

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Speaker 5: The YouTube stuff. Which one you want? Which is the

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Speaker 5: bigger driver of the downside today?

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Speaker 10: Capex I mean simply because this quarter companies are not

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Speaker 10: getting a pass on boosting CAPEX. That wasn't the case

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Speaker 10: last quarter. But clearly I think investors vary about how

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Speaker 10: much CAPEX these companies are going to throw on AI.

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Speaker 10: And look, in the case of Alphabet, there is revenue

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Speaker 10: in the cloud segment, so they quantified the AI impact

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Speaker 10: on cloud which was high single digit contribution to cloud segment,

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Speaker 10: and cloud segment actually saw on acceleration in top line growth.

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Speaker 10: But YouTube miss, I think I attribute that more to

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Speaker 10: software spending outside of financial services and retail sectors like automotive.

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Speaker 10: They're not spending on digital ads right now because the

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Speaker 10: sector is going through a cyclical downturn. So there is

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Speaker 10: that cyclical element to YouTube's business. But I think there

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Speaker 10: are a lot of positives. Course search growing at fourteen percent.

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Speaker 10: I mean, think about the scale of search and the

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Speaker 10: fact that they are able to grow double digits. That's

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Speaker 10: quite impressive, and that too at a very healthy margin.

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Speaker 10: I mean, the biggest fear for this company was margins

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Speaker 10: are going to get degraded because of you know, AI

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Speaker 10: and whatnot. That we haven't seen that. So a lot

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Speaker 10: of positives, but clearly kapex was an overhang.

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Speaker 2: All right, I've been making a point today. If any

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Speaker 2: team deserves a benefit of the doubt of higher CAPEX,

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Speaker 2: it's Sundar, Punchai and all the folks at Google. Let's

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Speaker 2: stop whining about capex. Have they ever not generated to

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Speaker 2: return on their spending?

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Speaker 10: I mean, the problem with Google's management team is they

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Speaker 10: say very little on their earnings call. Like even when

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Speaker 10: you answer them, like ask a question, they would answer

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Speaker 10: it with as little words as possible, So you know

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Speaker 10: it sounded like they are bullish on their AI opportunity

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Speaker 10: and it's actually monetizing. Uh, some of that capex is

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Speaker 10: going towards Wemo. If you think about you know, robotaxis

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Speaker 10: and what Tesla had to go through their call last night.

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Speaker 10: Wemo actually did two million rides here to date and

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Speaker 10: these are all autonomous rides and they're expanding to other cities.

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Speaker 10: So think about, you know, the skill in that business

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Speaker 10: if they're able to do actually autonomous driving successfully. So

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Speaker 10: I do think their capex as well spent, but they

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Speaker 10: just don't explain it that well to the street, you know,

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Speaker 10: to get the credit.

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Speaker 6: So when it comes to then the AI spend, what

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Speaker 6: other companies are going to get judged in the same

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Speaker 6: harsh light and what's Google's one up on them?

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Speaker 10: If any Meta I mean you saw a negative reaction

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Speaker 10: with Alphabet, I mean think about what happened to be worse.

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Speaker 10: Meta is going to be worse. Even last quarter when

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Speaker 10: they raise their capex, Meta had a negative stock reaction

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Speaker 10: simply because investors are concerned about how much this company

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Speaker 10: is going to spend on metaverse versus AI. And so

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Speaker 10: in the case of Meta, they're losing eighteen billion dollars

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Speaker 10: a year on reality labs. They're spending Capex in addition

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Speaker 10: to the AI Capex, which they launched a new large

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Speaker 10: anglid model. And to my mind, any company right now

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Speaker 10: with their own large anglid model, whether it's Alphabet, Meta

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Speaker 10: or a Microsoft Open AI, they have an advantage. They

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Speaker 10: have the best reasoning capability when it comes to the

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Speaker 10: AI spend and it's actually a future driver of revenue.

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Speaker 10: So it all comes down to how they are going

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Speaker 10: to monetize it. And I think with Microsoft and Google

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Speaker 10: they have an advantage because it shows up in the

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Speaker 10: cloud revenue. In the case of Meta, they have to

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Speaker 10: monetize the AI spend through ad revenue or a subscription

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Speaker 10: based you know, chat pot offering, which nobody knows when

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Speaker 10: that will come.

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Speaker 2: What is Gemini and John Talker and I be using it.

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Speaker 10: It's a better way to search for certain type of queries.

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Speaker 10: So whenever you want you know something with a detailed

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Speaker 10: answer as opposed to going through ten blue links to

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Speaker 10: find that answer. Gemini is great. The one good thing

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Speaker 10: about Gemini is when you search for a query, it's

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Speaker 10: going to show you the relevant YouTube link, whereas if

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Speaker 10: you search that on chatch Ept or Claude. It's not

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Speaker 10: going to have that YouTube link. So it's going to

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Speaker 10: generate the text, it's going to generate a summary, it's

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Speaker 10: going to answer your query, but it won't have that

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Speaker 10: appropriate YouTube link. And that's Google's biggest advantage with the

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Speaker 10: large anguage models.

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Speaker 3: It's do you have to pay for that?

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Speaker 10: Yeah, it's a twenty dollars subscription for the advanced version

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Speaker 10: that app will that that's kind of and that's where

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Speaker 10: I mean you are not like you don't think it's

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Speaker 10: a big deal, But I think Google owning maps and

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Speaker 10: YouTube is such a big deal in this arena of

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Speaker 10: large anglid models, because it's one thing to generate a

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Speaker 10: text based response, it's another thing to have a blue

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Speaker 10: link with the YouTube video that they want you to

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Speaker 10: see or the map link that they want you to

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Speaker 10: click on inside that response. And other large anglid models

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Speaker 10: can't do it because they don't own these assets.

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Speaker 5: So well, before we go.

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Speaker 6: One thing though, but the meta is that if if

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Speaker 6: these companies, though don't spend, then at some point when

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Speaker 6: all this is monetizable in a big, big way, all

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Speaker 6: of a sudden numbers Gonta complain that then Meta's super

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Speaker 6: far behind.

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Speaker 5: So what's the chicken in the egg here?

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Speaker 10: I mean, I still think nobody wants to be the

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Speaker 10: first one to pull back on capex. So it really

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Speaker 10: is a question of when do we have sufficient supply

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Speaker 10: of GPUs, And because the market is supply constrained when

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Speaker 10: it comes to the chip side of the equation, nobody

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Speaker 10: wants to come across and say, oh, I have enough

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Speaker 10: and I don't need to spend on cap anymore. And

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Speaker 10: I think right now, these companies generate so much cash

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Speaker 10: every year, like Alphabet will generate over one hundred billion

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Speaker 10: in free cash flow, so they can afford to spend

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Speaker 10: sixty billion in capex, and they're looking to make a

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Speaker 10: twenty three billion dollar acquisition that fell through, but clearly

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Speaker 10: they want to spend their free cash flow, which.

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Speaker 6: To your point, like, yeah, go ahead, you earned it,

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Speaker 6: you spend it, all right, Mandy, you're the best, so helpful,

438
00:23:25,320 --> 00:23:26,600
Speaker 6: so great, I asked Mabe slept.

439
00:23:26,600 --> 00:23:29,359
Speaker 5: He said yes, but I don't know if that's as

440
00:23:29,400 --> 00:23:31,080
Speaker 5: at home too, to make it even worse, I know, I.

441
00:23:31,040 --> 00:23:33,439
Speaker 6: Know, but he was on late yesterday, early today and

442
00:23:33,480 --> 00:23:35,399
Speaker 6: all that stuff. All right, Mandy, the best Mandy is

443
00:23:35,400 --> 00:23:38,680
Speaker 6: saying Bloomberg Intelligence senior tech industry analysts.

444
00:23:38,680 --> 00:23:39,280
Speaker 5: It's like, I feel like.

445
00:23:39,320 --> 00:23:42,000
Speaker 6: Investors want both, Like they want the growth and they

446
00:23:42,040 --> 00:23:43,919
Speaker 6: want the company to be profitable with it, but then

447
00:23:43,920 --> 00:23:45,040
Speaker 6: they don't want the CAPEC spend.

448
00:23:45,080 --> 00:23:46,160
Speaker 5: It's like, dude, you can't have both.

449
00:23:46,240 --> 00:23:48,159
Speaker 2: Yeah, But then you get analysts like Dan Ives It

450
00:23:48,280 --> 00:23:50,800
Speaker 2: just says, you know, you pick the manager teams, you

451
00:23:50,840 --> 00:23:52,720
Speaker 2: pick the technology, and you just go and you just

452
00:23:52,760 --> 00:23:55,080
Speaker 2: got to shut your eyes and you know, not worry

453
00:23:55,119 --> 00:23:57,560
Speaker 2: about the peaks and valleys, and you think that Tesla again.

454
00:23:58,080 --> 00:24:01,720
Speaker 3: First, you know, the first quarter through the third.

455
00:24:01,760 --> 00:24:05,480
Speaker 2: Week of April down fifty percent, only to bounce back

456
00:24:05,520 --> 00:24:06,520
Speaker 2: seventy five percent, So you.

457
00:24:06,600 --> 00:24:08,800
Speaker 3: Gotta be ready for those roller coachs with these tech names.

458
00:24:08,840 --> 00:24:09,400
Speaker 8: I guess yeah.

459
00:24:09,440 --> 00:24:11,280
Speaker 6: But then the problem with Tesla is, at least I

460
00:24:11,280 --> 00:24:13,359
Speaker 6: feel like it's clearly laid out if you're listening to

461
00:24:13,440 --> 00:24:16,040
Speaker 6: a Google conference call. The problem with Texla A Tesla

462
00:24:16,200 --> 00:24:18,399
Speaker 6: is like when he says something about a robotaxi and

463
00:24:18,440 --> 00:24:21,119
Speaker 6: Elon Musk says, our solution would work anywhere, even a

464
00:24:21,200 --> 00:24:24,879
Speaker 6: New Earth. What I don't understand, like that they're all

465
00:24:24,960 --> 00:24:26,840
Speaker 6: these it's Elon musky stuff.

466
00:24:26,520 --> 00:24:27,720
Speaker 5: And that must be very difficult.

467
00:24:27,720 --> 00:24:29,879
Speaker 3: Where is that elon musk risk that you take.

468
00:24:29,960 --> 00:24:31,800
Speaker 5: Or musky stuff? As I am saying it.

469
00:24:33,280 --> 00:24:37,200
Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live

470
00:24:37,280 --> 00:24:40,800
Speaker 1: weekdays at ten am Eastern on applecar Play and Android

471
00:24:40,800 --> 00:24:43,600
Speaker 1: Auto with the Bloomberg Business App. You can also listen

472
00:24:43,720 --> 00:24:46,800
Speaker 1: live on Amazon Alexa from our flagship New York station.

473
00:24:47,160 --> 00:24:52,120
Speaker 1: Just say Alexa, play Bloomberg eleven thirty.

474
00:24:51,720 --> 00:24:53,560
Speaker 2: Alex Steel false when you're live here on our Bloomberg

475
00:24:53,560 --> 00:24:56,600
Speaker 2: Interactive Broker Studio doing that streaming thing on the internet,

476
00:24:56,840 --> 00:24:59,920
Speaker 2: YouTube dot com search Bloomberg Podcasts, and that's where you'll.

477
00:25:00,320 --> 00:25:02,640
Speaker 2: Let's tell commercial real estate because I have no idea

478
00:25:03,000 --> 00:25:05,160
Speaker 2: what's going on here. I need to see some price action,

479
00:25:05,320 --> 00:25:06,440
Speaker 2: price discovery out.

480
00:25:06,320 --> 00:25:07,200
Speaker 3: There in the marketplace.

481
00:25:07,359 --> 00:25:08,920
Speaker 2: If I'm going to buy an office building on Third

482
00:25:08,920 --> 00:25:11,000
Speaker 2: Avenue in Manhattan, what kind of discount am I going

483
00:25:11,040 --> 00:25:14,800
Speaker 2: to get? Fortunately, Abbail Duolottle knows a ton of people

484
00:25:14,960 --> 00:25:18,400
Speaker 2: in that business. Abigail Doulttle's on markets reporter, but she's

485
00:25:18,480 --> 00:25:21,040
Speaker 2: got her She's wired into that commercial real estate business,

486
00:25:21,040 --> 00:25:25,480
Speaker 2: which means the whole Morgan Stanley real estate mafia.

487
00:25:25,600 --> 00:25:26,720
Speaker 3: Alumni crew.

488
00:25:27,200 --> 00:25:31,040
Speaker 2: One of them is Sunny Kelsey Co Chief executive Officer Bgo.

489
00:25:31,520 --> 00:25:34,120
Speaker 2: I said, who is bgl? They got eighty five billion

490
00:25:34,320 --> 00:25:37,280
Speaker 2: in assets under management? What rock have I been sleeping under?

491
00:25:37,320 --> 00:25:39,080
Speaker 2: So these guys are big, Sonny. Thank you so much

492
00:25:39,080 --> 00:25:40,720
Speaker 2: for joining us here in our studio. Abbigil, thank you

493
00:25:40,760 --> 00:25:42,240
Speaker 2: so much for joining us as well.

494
00:25:42,440 --> 00:25:42,800
Speaker 3: Sonny.

495
00:25:43,560 --> 00:25:45,520
Speaker 2: All I know is I walk down Third Avenue in

496
00:25:45,600 --> 00:25:47,840
Speaker 2: a lot of empty buildings, and I'm just wondering how

497
00:25:47,920 --> 00:25:51,040
Speaker 2: representative is that of the commercial real estate business. How

498
00:25:51,080 --> 00:25:53,560
Speaker 2: do you guys view the commercial real estate business today?

499
00:25:53,560 --> 00:25:56,000
Speaker 2: It's got to be like something you've never seen before.

500
00:25:56,400 --> 00:25:58,440
Speaker 7: It is something like we've never seen before. And you think,

501
00:25:58,480 --> 00:26:01,280
Speaker 7: after thirty four years, you see everything, and you know,

502
00:26:01,400 --> 00:26:04,040
Speaker 7: we always get asked to compare cycles, and every cycle

503
00:26:04,119 --> 00:26:07,600
Speaker 7: is different, and this one is definitely different. I'll answer

504
00:26:07,640 --> 00:26:09,800
Speaker 7: your question in a second. But the context around it

505
00:26:09,840 --> 00:26:12,000
Speaker 7: is you just pick the asset class that's been hit

506
00:26:12,000 --> 00:26:14,200
Speaker 7: the worst in the last four years, right two years

507
00:26:14,240 --> 00:26:17,120
Speaker 7: of a pandemic call it, where people were working from home,

508
00:26:17,200 --> 00:26:19,360
Speaker 7: and a bunch of other stuff, and then you've got

509
00:26:19,359 --> 00:26:23,600
Speaker 7: it piling on in terms of kind of bad secular

510
00:26:23,680 --> 00:26:27,520
Speaker 7: news for the for the office sector. Right. Work from

511
00:26:27,520 --> 00:26:29,240
Speaker 7: home was one problem on real estate owner, so I

512
00:26:29,280 --> 00:26:31,199
Speaker 7: think it's a problem. Work from home was one problem

513
00:26:31,200 --> 00:26:33,959
Speaker 7: which never would have happened without technology like Zoom. But

514
00:26:34,000 --> 00:26:35,760
Speaker 7: then you have AI, you have a bunch of other

515
00:26:35,800 --> 00:26:37,919
Speaker 7: stuff coming, which are all going to come after jobs.

516
00:26:37,960 --> 00:26:44,199
Speaker 7: Presumably office and gateway cities like New York City is

517
00:26:44,320 --> 00:26:47,320
Speaker 7: probably the if you want to take about lower left,

518
00:26:47,320 --> 00:26:49,240
Speaker 7: if that's the bad place to be, that's a bad

519
00:26:49,280 --> 00:26:52,320
Speaker 7: place to be, right. I do agree when the baby

520
00:26:52,320 --> 00:26:54,080
Speaker 7: gets thrown out with the bathwater and they say all

521
00:26:54,119 --> 00:26:56,399
Speaker 7: real estate is bad. You know, people focus on that

522
00:26:56,440 --> 00:26:57,840
Speaker 7: because it's kind of what's present.

523
00:26:57,960 --> 00:26:58,120
Speaker 6: Right.

524
00:26:59,119 --> 00:27:01,840
Speaker 7: We're Abigail and our talking about how the streets and

525
00:27:01,880 --> 00:27:03,920
Speaker 7: not here in the retailers are all empty that used

526
00:27:03,920 --> 00:27:06,800
Speaker 7: to be here. That's what you see, right. What you

527
00:27:06,840 --> 00:27:09,400
Speaker 7: don't see as much is people are still living somewhere.

528
00:27:09,840 --> 00:27:12,080
Speaker 7: You still get your goods and services. Somehow those are

529
00:27:12,080 --> 00:27:14,560
Speaker 7: coming to you from a warehouse somewhere as opposed to

530
00:27:14,560 --> 00:27:16,960
Speaker 7: coming to you because you're going to a store. Not

531
00:27:17,040 --> 00:27:21,240
Speaker 7: that those have been immune, right, But office it's been tough,

532
00:27:21,560 --> 00:27:23,480
Speaker 7: and honestly, I don't see it getting better in the

533
00:27:23,560 --> 00:27:24,240
Speaker 7: near term.

534
00:27:24,280 --> 00:27:27,359
Speaker 6: Well, then to that point, what part of real estate

535
00:27:27,800 --> 00:27:32,240
Speaker 6: is cyclical versus secular? Yes, so like the warehouse point

536
00:27:32,280 --> 00:27:34,480
Speaker 6: you make, that has to be a secular shift. But

537
00:27:34,520 --> 00:27:36,680
Speaker 6: we're still in a cyclical market, so that's going to

538
00:27:36,720 --> 00:27:37,959
Speaker 6: be very tricky, correct.

539
00:27:38,119 --> 00:27:39,960
Speaker 7: Yeah. Well so look, I would say as I think

540
00:27:40,000 --> 00:27:42,320
Speaker 7: about investing, I think about the four quadrants. And people

541
00:27:42,359 --> 00:27:44,920
Speaker 7: think about dead equity, public, private, I actually think about cyclical,

542
00:27:45,040 --> 00:27:49,000
Speaker 7: secular and headwind tailwind Right, So if you think about

543
00:27:49,080 --> 00:27:53,560
Speaker 7: who what's in secular decline and as secular headwinds, office

544
00:27:53,600 --> 00:27:55,640
Speaker 7: is the best asset class to think about, right, All

545
00:27:55,680 --> 00:27:57,920
Speaker 7: the top down news is bad, the bottom up news

546
00:27:57,960 --> 00:28:00,600
Speaker 7: is bad. Capital markets are bad. Terms of what has

547
00:28:00,600 --> 00:28:08,800
Speaker 7: cyclical tailwinds? Right, What has cyclical tailwinds and secular tailwinds?

548
00:28:09,280 --> 00:28:11,680
Speaker 7: Anything related to technology. So I'm sure you've had a

549
00:28:11,680 --> 00:28:13,240
Speaker 7: lot of people come in to talk about data centers.

550
00:28:13,440 --> 00:28:15,760
Speaker 7: We have a big data center business too. It's been great.

551
00:28:16,840 --> 00:28:19,159
Speaker 7: The issue is it's no secret that it's great. So

552
00:28:19,200 --> 00:28:20,960
Speaker 7: there's a lot of money piling in. There's a huge

553
00:28:21,000 --> 00:28:25,240
Speaker 7: amount of demand, which is what makes great secular cyclical opportunity.

554
00:28:25,720 --> 00:28:27,399
Speaker 7: I think where we actually do our job, where we

555
00:28:27,480 --> 00:28:29,159
Speaker 7: make where we can be in a position to make

556
00:28:29,200 --> 00:28:32,600
Speaker 7: the most money is places that have secular tailwinds and

557
00:28:32,680 --> 00:28:36,280
Speaker 7: cyclical headwinds. Okay, right now, most things have cyclical headwinds

558
00:28:36,320 --> 00:28:38,760
Speaker 7: right now because the capital markets. When you ask Paul

559
00:28:38,840 --> 00:28:41,040
Speaker 7: when things are going to come back, until credit comes

560
00:28:41,040 --> 00:28:42,560
Speaker 7: back into the market, we're not going to see it.

561
00:28:42,760 --> 00:28:45,600
Speaker 7: But right now it's a great time to be in warehouses.

562
00:28:45,640 --> 00:28:48,200
Speaker 7: The secular tailwinds are still pretty good, but it's expensive

563
00:28:48,240 --> 00:28:50,800
Speaker 7: to build them, it's expensive to buy them. And so

564
00:28:50,880 --> 00:28:54,360
Speaker 7: if you can figure that out with data, with anything

565
00:28:54,360 --> 00:28:56,520
Speaker 7: else to kind of get an edge, that's good. Housing

566
00:28:56,640 --> 00:28:58,640
Speaker 7: is the best bet in my view right now. And

567
00:28:58,800 --> 00:29:01,120
Speaker 7: this is a US common hap of our portfolios. US

568
00:29:01,160 --> 00:29:03,520
Speaker 7: half as non US people have to live somewhere. We

569
00:29:03,560 --> 00:29:07,440
Speaker 7: have a structural housing shortage, but we have some issues,

570
00:29:07,560 --> 00:29:10,000
Speaker 7: and so to me, it's actually the really interesting.

571
00:29:09,720 --> 00:29:10,160
Speaker 1: Place to be.

572
00:29:10,320 --> 00:29:12,520
Speaker 11: Well, speaking of your portfolio, it's not all bad because

573
00:29:12,600 --> 00:29:15,080
Speaker 11: right here over on Park Avenue four twenty five, I've

574
00:29:15,080 --> 00:29:16,360
Speaker 11: walked by that building many times.

575
00:29:16,360 --> 00:29:17,640
Speaker 8: It's the new Citadel building.

576
00:29:17,720 --> 00:29:21,880
Speaker 11: It is absolutely beautiful and there is the Bental Greek green.

577
00:29:21,680 --> 00:29:23,360
Speaker 8: Oak stamp right on it.

578
00:29:23,720 --> 00:29:26,080
Speaker 11: You know, when we think about this pain though, it

579
00:29:26,160 --> 00:29:29,719
Speaker 11: really comes back to rates, and you've had you know,

580
00:29:30,000 --> 00:29:33,280
Speaker 11: we've stayed in touch, and I know that you've had

581
00:29:33,280 --> 00:29:36,040
Speaker 11: a great call on rates that back in twenty twenty one,

582
00:29:36,080 --> 00:29:39,360
Speaker 11: twenty twenty two, when the Fed forecast or telegraph that

583
00:29:39,360 --> 00:29:42,320
Speaker 11: they were going to raise, you took a particular view.

584
00:29:42,360 --> 00:29:43,880
Speaker 11: Bond traders didn't do this. I know a lot of

585
00:29:43,920 --> 00:29:46,360
Speaker 11: other commercial real estate investors that were more the hopium

586
00:29:46,680 --> 00:29:49,160
Speaker 11: talk to us about what you were seeing, what you did,

587
00:29:49,320 --> 00:29:50,760
Speaker 11: and what it meant for your portfolio.

588
00:29:50,880 --> 00:29:53,200
Speaker 7: So I think, and again I'm not an economist, but

589
00:29:54,080 --> 00:29:56,720
Speaker 7: my philosophy has always been you can do nothing about

590
00:29:56,720 --> 00:29:58,760
Speaker 7: what you can't control, so focus on what you can control.

591
00:29:58,800 --> 00:30:01,160
Speaker 7: We can control the rate environment. So when the FED

592
00:30:01,240 --> 00:30:03,560
Speaker 7: raise rates, and they did it at the pace they

593
00:30:03,560 --> 00:30:06,280
Speaker 7: did it and at the you know, the slope at

594
00:30:06,280 --> 00:30:08,960
Speaker 7: which they did it, our view was we couldn't count

595
00:30:08,960 --> 00:30:10,480
Speaker 7: on when they were going to come back down again.

596
00:30:10,760 --> 00:30:13,440
Speaker 7: That was and so what do we do We invested

597
00:30:13,480 --> 00:30:16,640
Speaker 7: against that. Now, part of it is why did we

598
00:30:16,760 --> 00:30:18,880
Speaker 7: think they were doing what they were doing right? And

599
00:30:18,920 --> 00:30:20,760
Speaker 7: I think a lot of people focused what I would

600
00:30:20,800 --> 00:30:23,160
Speaker 7: say on the demand side. They focus on cash. They

601
00:30:23,160 --> 00:30:26,040
Speaker 7: talked on central banks had pumped in COVID money all

602
00:30:26,080 --> 00:30:28,560
Speaker 7: that stuff. We actually focus on the supply side, the

603
00:30:28,560 --> 00:30:31,560
Speaker 7: benefit of having a big global industrial portfolios. We see

604
00:30:31,560 --> 00:30:33,800
Speaker 7: three put we have a big business in Asia. We

605
00:30:33,800 --> 00:30:36,680
Speaker 7: saw China shut down, the world's largest manufacturer shut down

606
00:30:36,680 --> 00:30:39,120
Speaker 7: for three years. It's a little bit of a statement

607
00:30:39,160 --> 00:30:41,760
Speaker 7: of hyperbole, but they shut down for three years. Our

608
00:30:41,880 --> 00:30:43,400
Speaker 7: view was, you are not going to get back to

609
00:30:43,440 --> 00:30:46,600
Speaker 7: normality until China reopened. China didn't reopen until the end

610
00:30:46,640 --> 00:30:48,800
Speaker 7: of twenty two beginning of twenty twenty three, after the

611
00:30:48,960 --> 00:30:52,040
Speaker 7: five year Congress. So until that happened, it was our

612
00:30:52,080 --> 00:30:53,800
Speaker 7: vu that you weren't going to see stuff come back

613
00:30:53,840 --> 00:30:56,520
Speaker 7: to normal again, right, whatever normal is, by the way,

614
00:30:57,600 --> 00:30:59,680
Speaker 7: And so the way we kind of thought about it

615
00:30:59,720 --> 00:31:01,400
Speaker 7: is we're going to ignore it. There are a lot

616
00:31:01,400 --> 00:31:04,760
Speaker 7: of people that are trying to invest against, hoping cap rate,

617
00:31:05,080 --> 00:31:07,640
Speaker 7: interest rates to come down quickly and then bet against that.

618
00:31:08,880 --> 00:31:10,840
Speaker 7: I have too much scar tissue from too many other cycles.

619
00:31:10,880 --> 00:31:14,280
Speaker 2: Which you buy a third Avenue office building today at

620
00:31:14,280 --> 00:31:16,160
Speaker 2: thirty cents on the dollar, I think.

621
00:31:16,640 --> 00:31:19,680
Speaker 7: They're plenty on offer, and we haven't bought any yet.

622
00:31:20,000 --> 00:31:23,120
Speaker 7: All Right, at some point it will get interesting. I

623
00:31:23,120 --> 00:31:25,600
Speaker 7: think the issue right now, back to the cyclical secular

624
00:31:25,680 --> 00:31:29,080
Speaker 7: thing is there's so many headwinds to office right now, and.

625
00:31:29,000 --> 00:31:30,040
Speaker 11: We're about conversion.

626
00:31:30,840 --> 00:31:34,840
Speaker 7: So conversion looks great theoretically. It sounds great theoretically, but

627
00:31:34,880 --> 00:31:36,720
Speaker 7: if you talk about one of those Third Avenue office

628
00:31:36,720 --> 00:31:39,080
Speaker 7: buildings with a forty thousand square foot floor plate and

629
00:31:39,120 --> 00:31:42,000
Speaker 7: you try to actually cut that up into an apartment,

630
00:31:42,000 --> 00:31:44,239
Speaker 7: people are going to be living in Bowling alleys. And

631
00:31:44,280 --> 00:31:48,000
Speaker 7: that's basically if you just visualize it. So, actually, conversion

632
00:31:48,000 --> 00:31:51,440
Speaker 7: work great. Downtown after nine to eleven, a lot of

633
00:31:51,480 --> 00:31:54,800
Speaker 7: stuff got converted, but those are older buildings with better ceiling,

634
00:31:54,840 --> 00:31:57,600
Speaker 7: heights and other stuff. They converted a lot to multifamily

635
00:31:57,680 --> 00:32:00,720
Speaker 7: and a lot to hotels, bigger window, every of that

636
00:32:00,760 --> 00:32:02,760
Speaker 7: sounds but yeah, yeah, people never used to live on

637
00:32:02,800 --> 00:32:07,200
Speaker 7: Wall Street. Now people live on Wall Street. But that's why, Look,

638
00:32:07,200 --> 00:32:09,320
Speaker 7: it's gonna be a it's gonna be a slow grind too.

639
00:32:09,600 --> 00:32:11,960
Speaker 6: So when you say office building is publishing thirty cents

640
00:32:11,960 --> 00:32:14,400
Speaker 6: on the dollar, yeah, I get that. We're still in

641
00:32:14,400 --> 00:32:17,280
Speaker 6: the headwind place. Yeah, but is it like fifteen cents

642
00:32:17,280 --> 00:32:19,800
Speaker 6: on the dollar. You're like, okay, fine, like it when

643
00:32:19,840 --> 00:32:21,360
Speaker 6: did it become a valuation thing.

644
00:32:23,680 --> 00:32:25,600
Speaker 7: It becomes a valuation thing when you have some degree

645
00:32:25,640 --> 00:32:27,080
Speaker 7: conviction you can lease that space.

646
00:32:27,360 --> 00:32:28,680
Speaker 5: Okay, So it still has to come back.

647
00:32:28,600 --> 00:32:30,320
Speaker 7: To the fun It has to come back to the fundamental.

648
00:32:30,360 --> 00:32:31,920
Speaker 7: So that has to come back to that number one.

649
00:32:32,000 --> 00:32:35,080
Speaker 7: Number two, the financing markets are upside down for real estate.

650
00:32:35,720 --> 00:32:37,360
Speaker 7: You know there's news today about it.

651
00:32:37,360 --> 00:32:41,040
Speaker 2: You've got banks that they kill free business. They wine

652
00:32:41,120 --> 00:32:43,600
Speaker 2: and dine you for thirty years. Now you go back

653
00:32:43,640 --> 00:32:45,840
Speaker 2: to them. Now I need the money. Well, I could

654
00:32:45,880 --> 00:32:48,960
Speaker 2: buy this B plus property on Third Aven thirty cents

655
00:32:49,000 --> 00:32:49,400
Speaker 2: on a dollar.

656
00:32:49,520 --> 00:32:50,720
Speaker 3: You know this is a good deal.

657
00:32:51,000 --> 00:32:51,120
Speaker 4: Right.

658
00:32:51,360 --> 00:32:53,959
Speaker 7: Well, look, first of all, most many managers of our

659
00:32:54,000 --> 00:32:56,360
Speaker 7: scale are both on the equity. So twenty billion of

660
00:32:56,360 --> 00:32:58,400
Speaker 7: our eighty five billion. We're a lender, okay, all right,

661
00:32:58,440 --> 00:33:00,640
Speaker 7: So we have a lending business. So the pain I

662
00:33:01,280 --> 00:33:04,040
Speaker 7: am seeing our lenders bear right now, we bear as

663
00:33:04,040 --> 00:33:10,760
Speaker 7: a lender as well. So that's complicated the regulators. Basel three.

664
00:33:10,960 --> 00:33:14,600
Speaker 7: There are a lot of headwinds against banks, regular way

665
00:33:14,640 --> 00:33:17,640
Speaker 7: banks coming back into commercial real estate lending. That's why

666
00:33:17,640 --> 00:33:19,680
Speaker 7: the private markets have exploded the way they have, and

667
00:33:19,720 --> 00:33:21,480
Speaker 7: I think our views that they're going to continue to

668
00:33:21,480 --> 00:33:25,080
Speaker 7: be really robust. But the problem is a first mortgage

669
00:33:25,520 --> 00:33:28,560
Speaker 7: on sixty percent loan to today's value that costs someone

670
00:33:28,680 --> 00:33:31,840
Speaker 7: nine to ten percent is not a normally functioning capital market.

671
00:33:32,000 --> 00:33:33,520
Speaker 11: This is not well, you know, to pick up on

672
00:33:33,600 --> 00:33:36,240
Speaker 11: something that Alex and Paul were just asking about relative

673
00:33:36,320 --> 00:33:40,560
Speaker 11: and Alex in particular the valuation so Igon Namdar not

674
00:33:40,640 --> 00:33:43,080
Speaker 11: so long ago one even further, he was saying some

675
00:33:43,120 --> 00:33:44,840
Speaker 11: of these buildings you could get them at less than

676
00:33:44,840 --> 00:33:47,280
Speaker 11: ten cents on the dollar. He was saying, he thinks

677
00:33:47,320 --> 00:33:49,440
Speaker 11: it's the bottom. It's hard to not think that's the bottom.

678
00:33:49,440 --> 00:33:51,120
Speaker 11: But so many people that I talked to, so many

679
00:33:51,160 --> 00:33:53,240
Speaker 11: of my sources, this is the one point of agreement

680
00:33:53,320 --> 00:33:55,880
Speaker 11: as to whether how much pain is ahead or not.

681
00:33:56,320 --> 00:33:59,000
Speaker 11: That it's going to take a long, long, long time

682
00:33:59,040 --> 00:34:00,640
Speaker 11: to work out. So how long do we just skirt

683
00:34:00,640 --> 00:34:04,800
Speaker 11: along the BOTO just have about twenty seconds?

684
00:34:04,920 --> 00:34:07,760
Speaker 7: Well, if we're just talking about office, I'm not.

685
00:34:07,760 --> 00:34:08,799
Speaker 3: Sure we're at the bottom of out.

686
00:34:08,840 --> 00:34:10,520
Speaker 8: They that's gonna that's interesting though.

687
00:34:10,600 --> 00:34:11,719
Speaker 3: Yeah, I don't know.

688
00:34:12,000 --> 00:34:13,560
Speaker 2: Until I start seeing some of these things on Third

689
00:34:13,560 --> 00:34:16,319
Speaker 2: Avenue start trading in the comparable place in Boston and

690
00:34:16,360 --> 00:34:18,680
Speaker 2: San Francisco, we'll see Sonny CALSI thank you so much

691
00:34:18,719 --> 00:34:19,160
Speaker 2: for joining us.

692
00:34:19,160 --> 00:34:21,640
Speaker 3: Sonny Cawsei is a co chief executive officer.

693
00:34:21,400 --> 00:34:26,080
Speaker 2: B g and Ablegail do Little, markets reporter for Bloomer News,

694
00:34:26,160 --> 00:34:28,040
Speaker 2: joining Talk a little bou comercial real estate. You can't

695
00:34:28,040 --> 00:34:30,400
Speaker 2: put it all in one bucket. It's not all office.

696
00:34:30,440 --> 00:34:32,280
Speaker 2: It's a lot of different stuff out there, but office

697
00:34:32,360 --> 00:34:33,919
Speaker 2: is tough, like keeping track.

698
00:34:35,320 --> 00:34:39,200
Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live

699
00:34:39,280 --> 00:34:42,359
Speaker 1: weekdays at ten am Eastern on Apple card Play and

700
00:34:42,360 --> 00:34:45,280
Speaker 1: Android Auto with the Bloomberg Business App. You can also

701
00:34:45,360 --> 00:34:48,520
Speaker 1: listen live on Amazon Alexa from our flagship New York

702
00:34:48,600 --> 00:34:51,960
Speaker 1: station Just Say Alexa playing Bloomberg eleven thirty.

703
00:34:53,080 --> 00:34:56,200
Speaker 6: Let's get more Now on the money behind this race,

704
00:34:56,520 --> 00:35:00,880
Speaker 6: Max Abelson joins us Bloomberg News finance reporter article about

705
00:35:00,920 --> 00:35:04,160
Speaker 6: the get rich quicks ideas. I was gonna call them schemes,

706
00:35:04,160 --> 00:35:07,000
Speaker 6: but they're not ideas. They're not schemes, they're ideas from

707
00:35:07,000 --> 00:35:10,080
Speaker 6: Wall Street donors. They need to raise money fast for

708
00:35:10,120 --> 00:35:12,560
Speaker 6: president for Vice President Harris Well.

709
00:35:12,560 --> 00:35:13,799
Speaker 12: First of all, I have to give a shout out

710
00:35:13,800 --> 00:35:16,279
Speaker 12: to the journalists who's really responsible.

711
00:35:15,719 --> 00:35:16,160
Speaker 8: For this work.

712
00:35:16,200 --> 00:35:18,680
Speaker 12: Who is Amanda Gordon, My friend and colleague who's been

713
00:35:18,680 --> 00:35:22,600
Speaker 12: reporting on the rich people who love Donald Trump, the

714
00:35:22,640 --> 00:35:25,040
Speaker 12: former president, and the rich people who want to make

715
00:35:25,200 --> 00:35:26,880
Speaker 12: Kamala Harris the next president.

716
00:35:27,280 --> 00:35:29,320
Speaker 8: And you know, listen, I don't want to give the

717
00:35:29,360 --> 00:35:29,920
Speaker 8: wrong idea.

718
00:35:30,040 --> 00:35:34,839
Speaker 12: I mean, wealthy Democratic donors on Wall Street have been,

719
00:35:34,960 --> 00:35:37,160
Speaker 12: you know, putting a lot of money, were putting a

720
00:35:37,200 --> 00:35:39,480
Speaker 12: lot of money into the effort to reelect Biden. It's

721
00:35:39,520 --> 00:35:41,880
Speaker 12: not as if they had closed their purses and their

722
00:35:41,920 --> 00:35:44,000
Speaker 12: wallets and then all of a sudden they're opening it up.

723
00:35:44,040 --> 00:35:47,480
Speaker 12: But I think what Amanda's journalism highlights in a really

724
00:35:47,600 --> 00:35:51,680
Speaker 12: vivid way is that they are going strong, and they're

725
00:35:51,680 --> 00:35:52,560
Speaker 12: going hard, and.

726
00:35:52,520 --> 00:35:54,760
Speaker 8: They don't have a lot of time to raise this money.

727
00:35:55,080 --> 00:35:57,120
Speaker 12: And when I say they, I want to be clear

728
00:35:57,160 --> 00:35:59,600
Speaker 12: that we're talking about, like, you know, essentially the krem

729
00:35:59,640 --> 00:36:02,800
Speaker 12: Delak of Democratic donors. You've got you know, do you

730
00:36:02,840 --> 00:36:05,400
Speaker 12: all know the name Blair Ephron su yep Center View.

731
00:36:05,480 --> 00:36:08,600
Speaker 12: I mean, you got Brad carp that's a Bradcarpey is

732
00:36:08,600 --> 00:36:10,440
Speaker 12: technically a lawyer, but I think there's a part of

733
00:36:10,480 --> 00:36:11,240
Speaker 12: big law that's.

734
00:36:11,120 --> 00:36:12,720
Speaker 8: Essentially an extension of Wall Street.

735
00:36:12,960 --> 00:36:16,239
Speaker 12: You've got Mark Lazari, Ray MacGuire where a profile of

736
00:36:16,320 --> 00:36:17,320
Speaker 12: for BusinessWeek back.

737
00:36:17,160 --> 00:36:18,239
Speaker 8: When he was running for mayor.

738
00:36:18,239 --> 00:36:22,320
Speaker 12: If you all remember that, you know it's funny at Blackstone. Obviously,

739
00:36:22,400 --> 00:36:25,920
Speaker 12: the most important donor inside Blackstone is Steve Schwartzman, who's

740
00:36:25,920 --> 00:36:27,200
Speaker 12: giving a lot of money to Republicans.

741
00:36:27,239 --> 00:36:28,520
Speaker 8: But don't forget Blackstones.

742
00:36:28,600 --> 00:36:30,840
Speaker 12: John Gray is there to you know, I don't know

743
00:36:30,880 --> 00:36:34,319
Speaker 12: if he's essentially probably I'm assuming not wealthy enough to

744
00:36:34,360 --> 00:36:38,040
Speaker 12: counterbalance Schwartzman, but still a lot of money. The list

745
00:36:38,040 --> 00:36:41,560
Speaker 12: goes on, Peter Orzag, Roger Altman. These are the people

746
00:36:41,560 --> 00:36:45,520
Speaker 12: who've been at the highest levels of Wall Street's kind

747
00:36:45,560 --> 00:36:49,719
Speaker 12: of democratic caucus for a long time. And you know,

748
00:36:49,760 --> 00:36:53,040
Speaker 12: you just you just sense a lot of excitement about Harris,

749
00:36:53,040 --> 00:36:54,720
Speaker 12: and they're going to be spending a lot of money.

750
00:36:54,960 --> 00:36:57,120
Speaker 2: It's interesting because I think Wall Street and just business

751
00:36:57,160 --> 00:36:58,719
Speaker 2: in general is trying to get a sense of these

752
00:36:58,719 --> 00:37:03,040
Speaker 2: early days. What is what would a Harris presidency.

753
00:37:02,560 --> 00:37:04,640
Speaker 3: Mean for business? Would it be good for business?

754
00:37:04,640 --> 00:37:07,280
Speaker 2: And I see a man that quotes uh Jim Kramer

755
00:37:07,320 --> 00:37:11,000
Speaker 2: in here telling investors on CNBC Wednesday that Harris Winn

756
00:37:11,040 --> 00:37:14,239
Speaker 2: would quote absolutely absolutely.

757
00:37:13,719 --> 00:37:16,520
Speaker 3: No doubt about an end quote be good for us business.

758
00:37:16,640 --> 00:37:19,360
Speaker 12: Only Jim Kramer would would say no doubt about it,

759
00:37:19,400 --> 00:37:21,680
Speaker 12: when of course no one ever knows what the future holds.

760
00:37:21,719 --> 00:37:24,640
Speaker 12: But you know, speaking of business, I think it's important

761
00:37:24,640 --> 00:37:28,279
Speaker 12: to pause and to remind our listeners that you know

762
00:37:28,400 --> 00:37:31,080
Speaker 12: Donald Trump, we know what Donald Trump will do for

763
00:37:31,080 --> 00:37:32,759
Speaker 12: the business community, and let's talk about it. I mean,

764
00:37:32,800 --> 00:37:36,680
Speaker 12: the big the big news is that he likes low taxes,

765
00:37:36,760 --> 00:37:39,200
Speaker 12: and I mean I mean low corporate taxes and then

766
00:37:39,239 --> 00:37:43,600
Speaker 12: low taxes on on onnwealthy people. He also has pledged

767
00:37:43,640 --> 00:37:45,920
Speaker 12: to deregulate and and he has shown that that that

768
00:37:45,960 --> 00:37:52,080
Speaker 12: he wants to That's why you have real enthusiasm for

769
00:37:52,200 --> 00:37:55,760
Speaker 12: him on Wall Street. You know Howard Lutnick, John Paulson,

770
00:37:56,239 --> 00:38:02,320
Speaker 12: Woody Johnson, John Katzvetids. There are really really deep wells

771
00:38:02,600 --> 00:38:05,960
Speaker 12: of really rich Wall Street executives who want this guy

772
00:38:06,000 --> 00:38:06,200
Speaker 12: to win.

773
00:38:06,400 --> 00:38:07,120
Speaker 8: A Meed Malik.

774
00:38:07,719 --> 00:38:10,080
Speaker 12: They've been raising money for him, They're going to be

775
00:38:10,160 --> 00:38:12,320
Speaker 12: raising money for him. I don't want listeners to think

776
00:38:13,040 --> 00:38:15,120
Speaker 12: that when Wall Street looks at the twenty twenty four

777
00:38:15,160 --> 00:38:17,840
Speaker 12: presidential election, all of their money is going to Democrats,

778
00:38:17,880 --> 00:38:21,120
Speaker 12: because that is not the case. But I think that

779
00:38:21,160 --> 00:38:25,080
Speaker 12: there is a really big part of Wall Street that

780
00:38:25,120 --> 00:38:28,200
Speaker 12: looks at Kamala Harris with a kind of optimism, with

781
00:38:28,280 --> 00:38:31,120
Speaker 12: the kind of optimism that she gets them, that she

782
00:38:31,320 --> 00:38:33,840
Speaker 12: understands them. I don't think they look at her the

783
00:38:33,880 --> 00:38:36,080
Speaker 12: way that they would look at Bernie Sanders or Elizabeth

784
00:38:36,160 --> 00:38:38,880
Speaker 12: Warren as a sort of is a loaded word, but

785
00:38:38,920 --> 00:38:39,120
Speaker 12: as a.

786
00:38:39,160 --> 00:38:41,120
Speaker 8: Kind of enemy. I think they look at her.

787
00:38:41,120 --> 00:38:42,719
Speaker 12: Maybe the right way to say this is as a

788
00:38:42,760 --> 00:38:44,080
Speaker 12: potential ally well.

789
00:38:43,960 --> 00:38:48,879
Speaker 2: I mean, Bloomberg's been reporting that the Harris campaign pulled

790
00:38:48,920 --> 00:38:51,839
Speaker 2: in one hundred million dollars just from the announcement through

791
00:38:51,880 --> 00:38:56,080
Speaker 2: Monday evening. Presumably that's from smaller donations, as opposed to

792
00:38:56,160 --> 00:38:59,080
Speaker 2: point in somebody's Wall Street it is from smaller donations.

793
00:38:59,120 --> 00:39:00,600
Speaker 6: Well, I was going to say to that point that

794
00:39:01,000 --> 00:39:03,839
Speaker 6: it also is from new donors, not just smaller but new,

795
00:39:03,880 --> 00:39:07,160
Speaker 6: which also raises the question that she would be the

796
00:39:07,200 --> 00:39:12,200
Speaker 6: first woman and the first Indian American to be elected president.

797
00:39:12,400 --> 00:39:15,040
Speaker 6: Obviously President Obama was African American, so she would not

798
00:39:15,080 --> 00:39:17,120
Speaker 6: be the first African American. But and the idea is

799
00:39:17,160 --> 00:39:19,319
Speaker 6: are that it is that hope going to bring in

800
00:39:19,320 --> 00:39:22,360
Speaker 6: a lot of new donors that otherwise wouldn't have donated,

801
00:39:22,480 --> 00:39:23,440
Speaker 6: even on the high end.

802
00:39:23,600 --> 00:39:26,200
Speaker 8: Yes, listen to the statistics. That's as stittius, you're ready.

803
00:39:26,880 --> 00:39:31,239
Speaker 12: There are one point one million unique donors, not one

804
00:39:31,239 --> 00:39:34,759
Speaker 12: point one donations, one point one million different donors who

805
00:39:34,800 --> 00:39:35,719
Speaker 12: contributed in that.

806
00:39:35,640 --> 00:39:36,080
Speaker 8: What was it?

807
00:39:35,920 --> 00:39:40,240
Speaker 12: It was like thirty six hours after she announced two thirds,

808
00:39:40,800 --> 00:39:44,279
Speaker 12: not fully two thirds, sixty two percent giving for the

809
00:39:44,320 --> 00:39:45,120
Speaker 12: first time.

810
00:39:45,280 --> 00:39:45,560
Speaker 1: Wow.

811
00:39:46,520 --> 00:39:50,120
Speaker 12: But no matter how much how many small, small donations

812
00:39:50,120 --> 00:39:52,480
Speaker 12: she gets, she's gonna have to raise a lot of money,

813
00:39:52,560 --> 00:39:53,960
Speaker 12: and she's gonna have to do it quickly. So I

814
00:39:53,960 --> 00:39:56,560
Speaker 12: think that the way the landscape looks is that she's

815
00:39:56,600 --> 00:39:59,240
Speaker 12: getting support from like a you know, a Barry Diller,

816
00:40:00,040 --> 00:40:04,880
Speaker 12: you know, a literal billionaire, and she's going to need

817
00:40:04,920 --> 00:40:08,680
Speaker 12: support from from those one point one million unique donors,

818
00:40:08,719 --> 00:40:10,919
Speaker 12: you know, practically two thirds doing it for the first time.

819
00:40:11,200 --> 00:40:13,120
Speaker 8: She is going to be embracing I.

820
00:40:13,080 --> 00:40:16,440
Speaker 12: Think both of those, although obviously I'm pretty sure that

821
00:40:16,480 --> 00:40:18,719
Speaker 12: when it comes to publicly bragging, she's going to be

822
00:40:18,719 --> 00:40:22,000
Speaker 12: publicly bragging about those small donors and not publicly bragging

823
00:40:22,000 --> 00:40:22,840
Speaker 12: about the building.

824
00:40:23,040 --> 00:40:26,400
Speaker 2: On Saturday coming up, Harris is scheduled to appear at

825
00:40:26,440 --> 00:40:29,799
Speaker 2: a donor event featuring the performances of James Taylor, Yo

826
00:40:29,880 --> 00:40:32,440
Speaker 2: Yo Ma and Emmanuel ax sounds.

827
00:40:32,520 --> 00:40:33,839
Speaker 3: It's like an episode from the West Wing.

828
00:40:35,080 --> 00:40:39,359
Speaker 8: Shout out to Yoyoma though I love I love the box, but.

829
00:40:39,320 --> 00:40:41,680
Speaker 3: Don't you want somebody who's more in tune with, you know,

830
00:40:41,880 --> 00:40:42,920
Speaker 3: the younger generation.

831
00:40:43,000 --> 00:40:45,080
Speaker 6: Well she also came out yesterday to Beyonce, which she

832
00:40:45,120 --> 00:40:49,480
Speaker 6: had full rights to use. So there's also that Yo Yoma. Yeah,

833
00:40:49,880 --> 00:40:52,279
Speaker 6: well that's really Beyonce. Yea, this is but this is

834
00:40:52,800 --> 00:40:54,160
Speaker 6: pane Is. You got to have the different level.

835
00:40:54,200 --> 00:40:55,480
Speaker 3: Well, her husband's also in the game.

836
00:40:55,520 --> 00:40:58,240
Speaker 2: He will attend several fundraisers next week, including an event

837
00:40:58,280 --> 00:41:00,920
Speaker 2: in Martha's Vineyard featuring me David Letterman.

838
00:41:01,040 --> 00:41:03,120
Speaker 8: Listen, the kids love Yo Yoma, though, I'm telling you

839
00:41:04,120 --> 00:41:04,480
Speaker 8: they do.

840
00:41:06,120 --> 00:41:07,320
Speaker 5: So I guess, like, what are you trying to appeal to?

841
00:41:07,360 --> 00:41:09,799
Speaker 5: Are you trying to appeal to the kids base?

842
00:41:09,920 --> 00:41:11,960
Speaker 6: So you're trying to appeal to heavy donors, Like what

843
00:41:12,080 --> 00:41:15,160
Speaker 6: is that goal when you're coming out to Beyonce or your.

844
00:41:15,760 --> 00:41:19,280
Speaker 1: You're trying to appeal to the voters, the younger voters especially.

845
00:41:19,560 --> 00:41:20,360
Speaker 8: I can I answer that.

846
00:41:20,600 --> 00:41:22,560
Speaker 12: I want to answer the question. Though Emmanuel axe Ye

847
00:41:22,800 --> 00:41:25,680
Speaker 12: really lovely pianist. Okay, we have listeners to when when

848
00:41:25,719 --> 00:41:27,279
Speaker 12: you're not listening to Blue mcg radio, listen to some

849
00:41:27,400 --> 00:41:29,320
Speaker 12: Manuel acts, great pianists.

850
00:41:29,360 --> 00:41:31,080
Speaker 6: I do love Yo Yom, but then again, I don't

851
00:41:31,080 --> 00:41:32,879
Speaker 6: think I'm the young kids.

852
00:41:33,360 --> 00:41:35,320
Speaker 8: But it's a good metaphor though. It's a good metaphor.

853
00:41:35,360 --> 00:41:38,759
Speaker 12: She's gonna want Beethoven listeners and Mozart listeners and she's

854
00:41:38,760 --> 00:41:41,200
Speaker 12: gonna want Beyonce listeners, And that's a way.

855
00:41:41,200 --> 00:41:43,440
Speaker 8: It's kind of a good simile for the Swifties.

856
00:41:43,080 --> 00:41:45,520
Speaker 3: Where the Swifties, can I get the swiftiest thing that's

857
00:41:45,560 --> 00:41:46,000
Speaker 3: a big coach.

858
00:41:46,120 --> 00:41:48,720
Speaker 6: Actually funny you say that Michael McKee has been texting

859
00:41:48,719 --> 00:41:50,879
Speaker 6: a group chat that we have kind of NonStop as

860
00:41:50,880 --> 00:41:52,560
Speaker 6: to who Taylor swift full indoors?

861
00:41:52,640 --> 00:41:53,600
Speaker 5: Will she endorse.

862
00:41:53,400 --> 00:41:56,520
Speaker 6: Kamala Harris, and will that, you know, move her away

863
00:41:56,560 --> 00:41:58,480
Speaker 6: from any MAGA attendees.

864
00:41:58,560 --> 00:42:00,879
Speaker 5: And I'm trying to be like, dude, chill, that's not.

865
00:42:00,800 --> 00:42:03,040
Speaker 3: Gonna happen, all right, I mean, jesus, this.

866
00:42:03,160 --> 00:42:06,360
Speaker 5: Band's won't for Harris. Yeah, we're good anyway.

867
00:42:06,440 --> 00:42:08,600
Speaker 6: Much more coming up rather at the state of commercial

868
00:42:08,600 --> 00:42:09,000
Speaker 6: real Estate.

869
00:42:09,000 --> 00:42:11,399
Speaker 5: Hey, Max, really appreciate it. Max Abilson joining us.

870
00:42:11,680 --> 00:42:16,160
Speaker 1: This is the Bloomberg Intelligence podcast available on Apples, Spotify,

871
00:42:16,400 --> 00:42:20,040
Speaker 1: and anywhere else you'll get your podcasts. Listen live each weekday,

872
00:42:20,160 --> 00:42:23,120
Speaker 1: ten am to noon Eastern on Bloomberg dot Com, the

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Speaker 1: iHeartRadio app tune In, and the Bloomberg Business app. You

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Speaker 1: can also watch us live every weekday on YouTube and

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Speaker 1: always on the Bloomberg terminal