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Speaker 1: Welcome to the Bloomberg Markets Podcast. I'm Paul Sweeney, alongside

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Speaker 1: my co host Matt Miller. Every business day, we bring

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Speaker 1: you interviews from CEOs, market pros, and Bloomberg experts, along

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Speaker 1: with essential market moving news. Find the Bloomberg Markets Podcast

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Speaker 1: on Apple Podcasts or wherever you listen to podcasts, and

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Speaker 1: at Bloomberg dot com slash podcast. Auto Nation they put

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Speaker 1: out some good numbers. Stock is up pretty substantially today.

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Speaker 1: But here's something that um talking about the car business. Matt,

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Speaker 1: so I just want to come come along with us.

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Speaker 1: The uh they're talking the CEO is talking about he

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Speaker 1: expects light vehicle sales to be close to fifteen million

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Speaker 1: this year, up from thirteen point seven million in two.

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Speaker 1: Where's the seventeen million number. Let's let's get Kevin Tynan

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Speaker 1: on here. Kevin Tyne he covers all the auto stuff,

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Speaker 1: the car stuff, truck stuff for Bloomberg Intelligence. He is

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Speaker 1: clearly an expert. So Kevin, I look at the Auto

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Speaker 1: Nation numbers, good numbers, But the CEO saying fifteen million SAR?

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Speaker 1: Is that? Is that all you guys can do? Kevin?

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Speaker 1: There's nothing, there's almost nothing that makes Paul angrier than

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Speaker 1: not aiming for peaks are other than working from home,

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Speaker 1: which makes him less angry now that he has a

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Speaker 1: beach house. Yes, Kevin, am I here here all right?

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Speaker 1: So here's I thought was interesting about some of the

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Speaker 1: Auto Nation numbers. Was you know, they talked about beware

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Speaker 1: going forward, you know, chips not so much an issue.

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Speaker 1: Uh uh, left some demand on the table in in two.

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Speaker 1: So automakers ramping up some production and prices are gonna fall,

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Speaker 1: which is not what happened in the fourth quarter, right,

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Speaker 1: It was I think the third consecutive record price or

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Speaker 1: average revenue per transaction for Auto Nations specifically in the quarter.

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Speaker 1: But but gross profit per vehicle new and used was compressed.

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Speaker 1: And really what that comes down too is the manufacturers

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Speaker 1: seeing retailers getting over sticker from November one through November

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Speaker 1: twenty two and saying, well, obviously we're not We're not

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Speaker 1: charging enough at wholesale. So margins are compressing for automation,

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Speaker 1: which is where they kind of directed your eye during

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Speaker 1: the call or during the release. Yet prices are still

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Speaker 1: very high, in fact, another record for them for this quarter.

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Speaker 1: So yeah, I mean, I think the industry or the automakers.

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Speaker 1: The manufacturers don't want to leave sales behind, so that

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Speaker 1: means a little bit more production, which just comes along

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Speaker 1: with with softer pricing. But we're not going back to

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Speaker 1: pricing structures. I always thought, you know in the Sopranos,

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Speaker 1: when Tony takes over that um, gambling addicts sports business,

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Speaker 1: and he just squeezes in for every penny he got

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Speaker 1: until the guys broke. I feel like the automakers are

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Speaker 1: kind of doing that to the average consume. We're right now,

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Speaker 1: the average monthly payment for a new car is seven

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Speaker 1: hundred and seventy seven dollars. That's double what it was

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Speaker 1: in late nineteen pre pandemic. UM. And now we hear

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Speaker 1: uh from the credit card companies that, um, they're having

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Speaker 1: problems meeting those payments. Mary baritole us yesterday. The lower

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Speaker 1: end consumers are starting to miss their auto payments. I mean,

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Speaker 1: at some point this is going to be a problem,

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Speaker 1: a problem. The prices are just too high, Kevin, Yeah,

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Speaker 1: and it's and a lot of that is due to mix. Remember,

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Speaker 1: you know, we we can go back to which was

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Speaker 1: the last time in the US truck and car mix

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Speaker 1: was fifty fifty and it hasn't been closed since, right,

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Speaker 1: So there's there's a part of that that is, hey,

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Speaker 1: if there is a finite amount of chips or production

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Speaker 1: or our cost structure is is lean enough, we're just

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Speaker 1: gonna make the most profitable things. Uh. And along with

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Speaker 1: that comes higher prices. So you know, I don't know,

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Speaker 1: there there's very little opportunity to go back because the

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Speaker 1: more affordable things just don't exist anymore. Right. So I

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Speaker 1: think that's where you get the automakers looking at it

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Speaker 1: and saying, well, buy something certified, pre owned or pre

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Speaker 1: owned from your dealerships. We don't live in that twenty

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Speaker 1: dollar space anymore. And that's you know, even use cars

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Speaker 1: are twenty to thirty dollars now. So yeah, it's it's

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Speaker 1: certainly going to affect demand, but I think at different

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Speaker 1: points in the supply they don't care as much as

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Speaker 1: they used to write because your fixed cost structure is

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Speaker 1: now rationalized to the point where you don't have to

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Speaker 1: sell every possible thing at any possible price, and you

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Speaker 1: can kind of hold out and say, no, we live

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Speaker 1: in this fifty dollar market. And I mean the volume

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Speaker 1: brands that GM has or that Ford has or Toyota,

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Speaker 1: you know those are those are moving up because their

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Speaker 1: mixes so much richer. Hey, Kevin, you know we had

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Speaker 1: Mary Barra here yesterday at Bloomberg talking to our print folks,

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Speaker 1: are radio and TV folks, and boy, really aggressive commentary

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Speaker 1: on their push into evs. Give us your your latest

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Speaker 1: feeling about kind of what we're gonna hear from the Fords,

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Speaker 1: from the GMS, and maybe what it means for the incumbents.

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Speaker 1: Like I gotta say, from what I heard Mary tell

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Speaker 1: us and what she told David Weston on Bloomberg Television

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Speaker 1: and Radio, um, it seems like GM their E V

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Speaker 1: business is a coiled spring that's just about to get

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Speaker 1: set off. I mean they want to make uh and

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Speaker 1: sell fifty billion dollars worth of evs profitable, fifty billion

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Speaker 1: dollars the evs by that's just that's like next year, right, yeah,

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Speaker 1: that is and and and what was you know, unit

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Speaker 1: wise was that's a million, dude, that's a million at

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Speaker 1: fifty grand apiece. Right, It's a million in two years

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Speaker 1: from forty thousand last year. Right. So so the thing

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Speaker 1: I see with that is right, it's it's going to

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Speaker 1: be if, if it's possible, it's going to have to

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Speaker 1: be a lot of the I don't know, thirty dollars

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Speaker 1: you said that, Yester, right, I mean, so, so you

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Speaker 1: have to be concerned about margin and profitability if that's

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Speaker 1: what you're planning to do, because essentially, right, if you

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Speaker 1: look across at Ford who talked about break even on

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Speaker 1: Mustang Maki going back, you know, several quarters fifty dollars

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Speaker 1: now because of material costs, it's maybe sixty dollars. Well,

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Speaker 1: how many thirty thousand dollar things do you want to sell?

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Speaker 1: You know, if your cost to produce them is above that,

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Speaker 1: you know, a million of them, that's you know, that's

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Speaker 1: that's just not how you usually run the business. So

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Speaker 1: one or two things has to happen. Either you're gonna

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Speaker 1: give up a ton of profitability a margin to make

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Speaker 1: that transition and hope you're rewarded with profitability kind of

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Speaker 1: the way you know Tesla operated, I'm going to market.

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Speaker 1: I mean, there are a lot of people out there, Kevin,

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Speaker 1: who were skeptical on Tesla for a long time, and

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Speaker 1: yet that company was worth over a trillion dollars for

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Speaker 1: a substantial period. Right, So maybe that's the trade is

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Speaker 1: that you say, well, we're going to give up some

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Speaker 1: profitability or a lot of profitability to do one million

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Speaker 1: units in the next two years, um, but we'll be

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Speaker 1: rewarded in market cap. What are you driving these days, Kevin?

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Speaker 1: It's still my V twelve. Oh, no, big deal like it.

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Speaker 1: I think the transition from internal combustion engine to e

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Speaker 1: V is gonna ge a tough one. What's the V twelve.

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Speaker 1: It's like an SL six five. It's a nice Yeah,

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Speaker 1: I don't see the I'll be the last one. You're

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Speaker 1: gonna be the last one, all right, Kevin Tyden, thanks

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Speaker 1: so much for joining us. Kevin Titan is the senior

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Speaker 1: Auto's analyst for Bloomberg Intelligence, working out of our lovely

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Speaker 1: Princeton office in Princeton, New New Jersey, and he is

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Speaker 1: a noted card geek of some magnitude. Uh I heard

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Speaker 1: he bought his car based he bought his house based

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Speaker 1: on the garage. Yes, exactly, he said. Went searching for garages,

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Speaker 1: his wife was searching for houses, and they find finally

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Speaker 1: found one that kind of satisfied both to get to

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Speaker 1: these markets. Here Omar Aguilar, he joins us. He's the

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Speaker 1: CEO and c i O. A Schwab asset management swap.

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Speaker 1: Just give you a sense how big these guys are.

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Speaker 1: Schwab seven seven seven billion in assets under managed management,

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Speaker 1: the third largest provider of index mutual funds, the fifth

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Speaker 1: largest provider of etf These guys are massive. But I'm

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Speaker 1: not sure I want to go up to Omar Cock

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Speaker 1: to party and initiative discussion. Get this, he's got a

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Speaker 1: PhD Statistics and decision sciences. Now the good news is

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Speaker 1: from Duke. But who gets a pH d in statistics

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Speaker 1: and decisions? I loved statistics. It was brutal. I mean

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Speaker 1: I took one class and I quite enjoyed it. All right,

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Speaker 1: good stup Omar, thanks so much for joining us here. Boy.

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Speaker 1: I think about all of the SWAB clients all over

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Speaker 1: this planet. Boy, I mean, what do you tell them

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Speaker 1: after what was a brutal, brutal year in two, whether

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Speaker 1: those equities or fit s income waity, what are you

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Speaker 1: tell them about three? Well, you know, thanks for having me,

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Speaker 1: and thanks for you know, talking about his statistics. That's

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Speaker 1: definitely been uh, you know a big part of my life. Uh.

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Speaker 1: And it's not as bad as you think once you

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Speaker 1: get used and find the good thing on it on

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Speaker 1: how you can actually use that to help people. But

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Speaker 1: but you're right, you know, two was probably one of

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Speaker 1: the most difficult years for all investors and particularly you know,

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Speaker 1: when people look at their statements, even in the worst

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Speaker 1: possible scenarios. You know, over the last you know, thirty years,

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Speaker 1: when equity markets and risky assets on their perform, you know,

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Speaker 1: everybody counted on the fact that they a you know,

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Speaker 1: could have their bonds or their cash doing you know,

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Speaker 1: most of the you know, saving and in in last year,

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Speaker 1: there were only two asset classes that ended up having

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Speaker 1: you know, positive returns, cash and commodities, and you know,

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Speaker 1: outside of those two asset classes, the rest ended up

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Speaker 1: you know, on their performing. So so clearly just from

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Speaker 1: the perspective of of clients that had expectations of using

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Speaker 1: you know, fixed income as a as a cushion or

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Speaker 1: when when volatility inequities, you know, that obviously didn't work.

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Speaker 1: So what we talk clients, you know, is that these

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Speaker 1: you know, these tends will happen. This is very rare.

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Speaker 1: There are very rare occasions with these happens, and it

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Speaker 1: happens usually because we had something that we didn't expect.

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Speaker 1: Actually would probably say two things that didn't expect. One

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Speaker 1: is we're just coming out of COVID, and in fact,

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Speaker 1: you know, we're still in the process of coming out

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Speaker 1: of COVID. And second, we nobody expected to have a

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Speaker 1: war that just you know, ignorite inflation pressures that made

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Speaker 1: things really, really hard. Um So what we talk about

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Speaker 1: now is what what happens from now on. And the

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Speaker 1: good news is that there is more opportunities to invest

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Speaker 1: in diversify now than what we had even you know,

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Speaker 1: just you know, six to eight months ago. What do

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Speaker 1: you what do you do at Schwab asset Management about

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Speaker 1: the sort of newer or alternative asset classes that retail

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Speaker 1: investors are just starting to dip their toes into. A

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Speaker 1: mean e t f s are just gaining so much ground,

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Speaker 1: I know, spies thirty, but it's still new ish as

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Speaker 1: a rapper at least um uh Crypto has had a

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Speaker 1: rough year obviously, but it's a new asset class that

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Speaker 1: some people are interested in. And then hedge funds did

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Speaker 1: well last year, private credit did well last year, but

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Speaker 1: that's normally just set aside for sophisticated investors. So how

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Speaker 1: do you deal with these things at Schwab? Well, great question,

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Speaker 1: and yes, this happens all the time, and we we

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Speaker 1: have had you know, significant amount of interest, you know,

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Speaker 1: and and this you know happens in many cases. You know,

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Speaker 1: you may recall not too long ago, the discussion about memestocks,

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Speaker 1: and you know what, people can use that information to

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Speaker 1: invest and you know how they can use several information

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Speaker 1: is the good news is that you know, we attract

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Speaker 1: a lot of investors to start in being interested in investing.

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Speaker 1: I think our challenge and our goal and mission continues

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Speaker 1: to be to educate clients on how to think about

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Speaker 1: the long term and what to think about the way

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Speaker 1: to invest from the basic level of what are the

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Speaker 1: fundamentals of what you try to achieve financially an investment

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Speaker 1: wise for each one of your goals. And what that

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Speaker 1: means is that areas like you know, for example, you know,

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Speaker 1: digital assets, any type of of of related information that

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Speaker 1: is more supply and demand that there is little in

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Speaker 1: terms of fundamental there's little in terms of history. You know,

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Speaker 1: they tend to just be an option for clients to

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Speaker 1: start getting their interest in investing, but not necessarily to

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Speaker 1: form the core of their long term strategy. We tend

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Speaker 1: to just you know, continue to educate clients to say, well,

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Speaker 1: you know, the basic asset classes, the basic areas of

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Speaker 1: investing for the long run as of today, you know,

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Speaker 1: still consists on the basic cash fixed income equities, and

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Speaker 1: yes there will be other alternatives that are based on

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Speaker 1: fundamentals that could actually help in the diversification process. So, Mari,

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Speaker 1: I just think it's just a huge, huge number of

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Speaker 1: clients out there. Um, how do you attract new clients,

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Speaker 1: younger clients. What's the schwab way to get some of

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Speaker 1: these young folks to really think about investing for the

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Speaker 1: long term. Yes, we we have done, you know, quite

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Speaker 1: a bit of workfoll and this where you know, we

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Speaker 1: we started at the early stages of working with with

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Speaker 1: our current clients and let them know that it's actually

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Speaker 1: you know, good for for for their own families to

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Speaker 1: just get invested in the clients, you know, whether it's

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Speaker 1: investing in slices of stuffs that they like on their

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Speaker 1: own and create opportunities in areas that they can have

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Speaker 1: like for example, investment teams and things where they can

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Speaker 1: actually start putting you know, information for their own families,

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Speaker 1: for their own kids, to just try to get early

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Speaker 1: into the investment area and understand that it's it's something

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Speaker 1: that they need to balance risk and returns and think

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Speaker 1: about you know, holding and saving, and that's probably the

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Speaker 1: key word, you know, continue to educate clients to save

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Speaker 1: so that they can continue to form you know, a

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Speaker 1: nest you know as they go. The other piece that

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Speaker 1: we actually try to have is we're here to help,

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Speaker 1: you know, trying to work with the financial advisor, trying

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Speaker 1: to work with somebody that has you know, being in

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Speaker 1: the business for a while then can guide them in

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Speaker 1: what is the best way to use their resources. It's

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Speaker 1: another big part. And the last thing we do is

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Speaker 1: understand that we are humans. You know. We do a

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Speaker 1: lot of work in decision sciences and behavioral aspects so

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Speaker 1: that we can understand, you know, when people emotions get high,

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Speaker 1: especially in these periods of high uncertainty, and therefore we

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Speaker 1: try to educate people on what is what is sort

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Speaker 1: of the utility function and the reaction function they can

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Speaker 1: use in periods when things are not as clear. Omar,

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Speaker 1: what are you expecting from the economy this year? We're

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Speaker 1: getting some uh more bad news on the consumer, which

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Speaker 1: seems to be that um he or she is still

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Speaker 1: spending a ton, but a lot of it's going on

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Speaker 1: credit cards and delinquencies are rising. Yes, Um, we expect

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Speaker 1: a really bumpy ride. We expect the economy going in

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Speaker 1: through uh really you know on certain times, you know,

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Speaker 1: for the next three quarters, it's gonna be a roller coaster.

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Speaker 1: I I can I can tell you that you know,

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Speaker 1: we're still in these you know, very confusing set of

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Speaker 1: level of indicators that we get every time that we

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Speaker 1: need to get a new data point, you know, and

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Speaker 1: of course you know, the whole discussion between you know,

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Speaker 1: what will be the reaction from central banks and into

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Speaker 1: their fight of inflation and how much of these inflation

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Speaker 1: is as sticky as it looks like just the Prince

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Speaker 1: this year with cp I p p I suggesting that,

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Speaker 1: you know, the long road to get the two percent

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Speaker 1: target for the FED is really gonna be long and bumpy. Um.

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Speaker 1: You know, not too long ago people were talking about

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Speaker 1: still the rate cuts because they thinking that the economy

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Speaker 1: was going to recover quickly. Well, we are not even

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Speaker 1: in a you know, talking about recession anymore. We're talking

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Speaker 1: about a potentially and re engineering of the economy that

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Speaker 1: may not even get into a landing. So so the

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Speaker 1: strength and receiling of the economy, at least on the

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Speaker 1: data that we have, suggest that it will take some

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Speaker 1: more time for everything that the fettes manufacturing to actually

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Speaker 1: play a role. And when that happens, then we can

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Speaker 1: actually feel a little more you know stable for actually

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Speaker 1: make you know, changes into our economic forecast. So putting that, uh,

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Speaker 1: that motif altogether, that backdrop altogether, omar, what's in thirty

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Speaker 1: seconds kind of what's your main communication point to your

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Speaker 1: clients about well, Tina is no longer in existent, Paul,

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Speaker 1: that there's a lot of opportunities for people to actually invest.

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Speaker 1: I think some of your earlier commentary was that related.

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Speaker 1: If you actually think that the short term of the

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Speaker 1: curve today in fixed income, it's probably giving you as

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Speaker 1: much you know, yield as you can get with earnings.

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Speaker 1: And if you think about that, you know, the opportunity

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Speaker 1: to just diversify between you know, the short term, the

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Speaker 1: long term and equities is probably the best we have

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Speaker 1: had in a while. So this is a good opportunity

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Speaker 1: for people to you know, diversify their strategies between bonds

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Speaker 1: and equally is that we probably haven't had for at

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Speaker 1: least fiefteen years. All right, o'mark, I really appreciate you

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Speaker 1: taking a time to check in with us Omar Aguilar.

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Speaker 1: He's CEO and c i O of Schwab Asset Management,

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Speaker 1: talking about diversification, talking about the longer term investment parameters

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Speaker 1: that you know most investors you know, need to probably

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Speaker 1: focus on. Um, we should have got his favorite professor

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Speaker 1: from from Duke from Duke. Yeah, we'll do that next time.

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Speaker 1: I mean these statistics and decision sciences. That sounds pretty

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Speaker 1: heavy on the math. That sounds awesome to me. I

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Speaker 1: don't know. I was told there wouldn't be any math

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Speaker 1: theoris like game theory. I guess. I guess there's some

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Speaker 1: smart people down there at Duke. So uh, good stuff.

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Speaker 1: We had a story overnight that credit card debt for

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Speaker 1: Americans has risen to almost a trillion dollars. I don't

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Speaker 1: know if that means Americans are using credit cards more

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Speaker 1: or that prices are higher. And there's a business I've

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Speaker 1: been looking into for a few weeks now called Imprint,

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Speaker 1: and as far as I can understand, what they do

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Speaker 1: is to try and help other companies with credit card

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Speaker 1: issuance with rewards programs and loyalty programs, that kind of thing.

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Speaker 1: I've managed to get the CEO in here in our

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Speaker 1: studio in New York City. Dara Murphy joins us. He's

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Speaker 1: also the founder of the business. So great to have

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Speaker 1: you here. Dara tell us, first of all, what Imprint

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Speaker 1: does well, thanks for having me on. Imprint was started.

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Speaker 1: It's about two and a half years ago, and the

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Speaker 1: goal was to compete with banks that help America's great

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Speaker 1: bronze launch credit cards. Co branded credit cards have been

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Speaker 1: a thing for thirty years in the America. You can

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Speaker 1: you get a great Delta card if you work with

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Speaker 1: om X. But there's a lot of great bronze out

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Speaker 1: there that the biggest banks, the bulge bracket banks, won't

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Speaker 1: work with. And we saw an opportunity to go help

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Speaker 1: those those great brodens, whether their hotel companies been a

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Speaker 1: around for thirty years, grocery stores, or some of our

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Speaker 1: clients that have been around for a hundred years. Our

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Speaker 1: goal is to help them issue credit cards. And so

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Speaker 1: what we do and we talk to them, is we

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Speaker 1: give them a pitch that we're like a buying plus

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Speaker 1: a technology company and you get everything from us that

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Speaker 1: you would get from Barclays, for example, which is a

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Speaker 1: big co branded credit card business. But in addition, you

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Speaker 1: get an experience that a great brand can be proud of.

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Speaker 1: So what what is um let's take the grocery store,

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Speaker 1: for instance. What is the benefit to them? Is it?

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Speaker 1: I guess loyalty? Right? If you have a brand and

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Speaker 1: credit card, you must really like that business. But do

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Speaker 1: consumers get a discount? Are they encouraged the shop? They're

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Speaker 1: more often? Are there other programs? Does it work? It

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Speaker 1: should be a virtuals cycle, right, so the brand should

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Speaker 1: get a stickier customer that comes back more and more.

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Speaker 1: You get this beautiful boost of incrementality when you put

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Speaker 1: a credit card in the person's pocket. And the reason

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Speaker 1: you get the incrementality is you give the person a

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Speaker 1: reason to come back. So you give them some base rewards.

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Speaker 1: Everybody knows that five at the brand, one and a

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Speaker 1: half two percent everywhere else, so it's a reason to

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Speaker 1: use the card all the time. And then you make

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Speaker 1: them feel more special. Right. We're working with our grocery

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Speaker 1: partner on express checkout lanes only for card holders. UM,

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Speaker 1: we have that in our I just noticed that that's

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Speaker 1: a good enough. That was just in the past couple

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Speaker 1: months at the ACME in UH somewhere in New Jersey.

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Speaker 1: I don't know the shop right by me. The lines

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Speaker 1: are always so damn long. But I feel like I

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Speaker 1: would definitely get a credit card if I could go

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Speaker 1: to I mean, you open a company right at the

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Speaker 1: beginning of a pandemic, but I would think, like, just

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Speaker 1: for me personally, I use my cards much more frequently

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Speaker 1: now than I ever did before. And I'm guessing that's

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Speaker 1: a trend. How did how did? How have you seen

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Speaker 1: the business kind of involved over the past few years.

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Speaker 1: We've just been fortunate over the last few years that

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Speaker 1: customers are coming back to commerce. They're going back into

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Speaker 1: the real world. On brands that we work with, which

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Speaker 1: we call America's great brands, really want to away to

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Speaker 1: lock in their customers. All brands that have been around

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Speaker 1: for over thirty years, they're under threat from the e

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Speaker 1: commerce giants, whether that's Instant Cart or door Dash or Amazon,

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Speaker 1: who have a trove of data. You think about Uber,

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Speaker 1: you open the Uber app. Before you open the Uber app,

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Speaker 1: it knows whether you're going to order food or whether

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Speaker 1: you're going to order an Uber and all of these

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Speaker 1: UH incumbents are in trouble because they don't have access

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Speaker 1: to that data. Well, credit cards are a great way

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Speaker 1: to bothe get your customers to spend more and become

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Speaker 1: more loyal, but also get to know more about your

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Speaker 1: customers and give them reasons to come back. And so

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Speaker 1: when we started the company, we've been riding this wave

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Speaker 1: of all of these great brands that people have tons

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Speaker 1: of affinity for, love the actual experience and go to

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Speaker 1: the hotel or going into the grocery store and giving

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Speaker 1: them the power to lock in their customer better, giving

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Speaker 1: that customer a better deal. And so, as we talked about,

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Speaker 1: it should be this um self propelling circle of you

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Speaker 1: get a better reward, you want to go back, and

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Speaker 1: the brand gets a stick of your customer. There is

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Speaker 1: credit card debt associated with that you brought up with

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Speaker 1: the start, but our goal is to be the most

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Speaker 1: trusted experience, right, So there are definitely credit cards definitely

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Speaker 1: have a bad name in some parts of the economy,

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Speaker 1: particularly with banks sutil you think, I think it's particularly

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Speaker 1: certain store cards where the banks didn't make it easy

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Speaker 1: for you to pay off, where you get these gotcha bills,

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Speaker 1: you get these junk fees that President Biden has been

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Speaker 1: railing against. That's a terrible experience. If we work with

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Speaker 1: the great brand, we want you to We know that

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Speaker 1: you trust the brand already, and our job is to

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Speaker 1: engender more trust, not less trust. And so we actually

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Speaker 1: think that if we work with the brand, if we

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Speaker 1: give the customer better experience, we can make it easier

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Speaker 1: to see what your interest is. You never get a

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Speaker 1: gotcha fee, You're much more likely to use the cards,

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Speaker 1: You're much more likely to be willing to take credit

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Speaker 1: when you need it and then pay it back when

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Speaker 1: you don't, and you're much more likely to shop with

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Speaker 1: the brand. And so that's part of the cycle of

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Speaker 1: if you do right by the customer, you do right

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Speaker 1: by the brand, you get us a better outcome for everyone.

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Speaker 1: Does it make a difference to you if we go

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Speaker 1: into a recession, or let's qualify that better. Does it does?

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Speaker 1: How much does it make a difference to you if

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Speaker 1: we go into a recession? It makes a difference to

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Speaker 1: every business. If we go into a recession, right spending

430
00:22:35,480 --> 00:22:39,159
Speaker 1: goes down, delinquencies naturally go up in a down cycle.

431
00:22:39,600 --> 00:22:42,320
Speaker 1: Our thing is how do you match risk with reward?

432
00:22:42,640 --> 00:22:44,920
Speaker 1: Um we have a risk function of ten or eleven

433
00:22:45,000 --> 00:22:47,879
Speaker 1: people that focus on a multibillion dollar book of loans.

434
00:22:48,440 --> 00:22:50,879
Speaker 1: Their job is to forecast the cycle and keep us

435
00:22:50,880 --> 00:22:53,320
Speaker 1: safe throughout it. And our job is, honestly not to

436
00:22:53,400 --> 00:22:56,320
Speaker 1: give credit to people who haven't figured out yet how

437
00:22:56,400 --> 00:22:58,439
Speaker 1: to responsibly use it, because it's a bad outcome. It's

438
00:22:58,440 --> 00:23:00,320
Speaker 1: a bad outcome for our company, and and it's a

439
00:23:00,359 --> 00:23:02,560
Speaker 1: bad outcome for the brand, and it's a terrible outcome

440
00:23:02,640 --> 00:23:05,159
Speaker 1: for the consumer. And so not are we only are

441
00:23:05,200 --> 00:23:07,040
Speaker 1: we trying to protect our balance sheet or P and

442
00:23:07,119 --> 00:23:09,199
Speaker 1: L when we underwrite people, we're kind of looking at

443
00:23:09,280 --> 00:23:11,439
Speaker 1: for them too, and also looking out for our brand partners.

444
00:23:11,520 --> 00:23:16,720
Speaker 1: Are you threatened by Clarna or what's the other one firm? Yeah,

445
00:23:16,720 --> 00:23:19,200
Speaker 1: a firm where you can buy now, pay later. So

446
00:23:19,960 --> 00:23:22,359
Speaker 1: they're different products that serve different things. And so you

447
00:23:22,440 --> 00:23:24,879
Speaker 1: think about a Clarna, it's great to buy a Peloton,

448
00:23:25,040 --> 00:23:27,600
Speaker 1: I turn up, I want this one thing I want

449
00:23:27,640 --> 00:23:29,399
Speaker 1: to loan, and I'm going to forget about it and

450
00:23:29,480 --> 00:23:31,080
Speaker 1: not come back. The hard thing is when you don't

451
00:23:31,080 --> 00:23:32,840
Speaker 1: have a card, you can't use it every day. The

452
00:23:32,920 --> 00:23:35,240
Speaker 1: card lets you shop with merchants that you go back

453
00:23:35,280 --> 00:23:37,120
Speaker 1: to a bunch. It's not just buying a one time

454
00:23:37,160 --> 00:23:39,800
Speaker 1: peloton or a fridge, and it lets you give rewards.

455
00:23:39,840 --> 00:23:41,879
Speaker 1: You don't get any reward from Klarna. And so the

456
00:23:41,920 --> 00:23:44,520
Speaker 1: whole purpose of Klarna, if you're a business, is help

457
00:23:44,560 --> 00:23:47,520
Speaker 1: me with this incremental conversion. Make it easier to press

458
00:23:47,560 --> 00:23:50,240
Speaker 1: the buy button. Our whole businesses can we bring back

459
00:23:50,280 --> 00:23:52,159
Speaker 1: the customer more and make them stickier? And so we

460
00:23:52,240 --> 00:23:54,760
Speaker 1: serve different problems and a lot of times our partners

461
00:23:54,800 --> 00:23:57,320
Speaker 1: have a Clarina installed of the check out and it

462
00:23:57,359 --> 00:23:59,800
Speaker 1: doesn't cannibalize us because we serve a different thing. How

463
00:24:00,200 --> 00:24:03,680
Speaker 1: millennials gen z, how do they engage with credit cards

464
00:24:03,720 --> 00:24:06,200
Speaker 1: in general? And my daughter is twenty six, she's a

465
00:24:06,320 --> 00:24:09,159
Speaker 1: point maven. I mean, it's amazing what she does with

466
00:24:09,240 --> 00:24:11,320
Speaker 1: the points, and so she's technically gen Z. And if

467
00:24:11,359 --> 00:24:13,000
Speaker 1: you can, if you listen to the media for the

468
00:24:13,080 --> 00:24:15,600
Speaker 1: last around this, for the last ten years, they would

469
00:24:15,600 --> 00:24:18,040
Speaker 1: have said gen Z doesn't like, doesn't want credit cards,

470
00:24:18,240 --> 00:24:20,520
Speaker 1: They're going to not use them. And in reality, what

471
00:24:20,600 --> 00:24:22,680
Speaker 1: we've seen over the last two or three years is

472
00:24:22,680 --> 00:24:25,320
Speaker 1: the highest uptake rate of credit cards is gen Z.

473
00:24:25,480 --> 00:24:27,920
Speaker 1: You have waves like people become consumers, they start to

474
00:24:27,960 --> 00:24:30,080
Speaker 1: worry about their credit score and they can't just use

475
00:24:30,119 --> 00:24:32,800
Speaker 1: buy an out, pay later. And so we've seen a

476
00:24:33,040 --> 00:24:35,440
Speaker 1: real adoption rate by gen Z and by millennials of

477
00:24:35,480 --> 00:24:37,960
Speaker 1: credit cards. They're just more thoughtful. To be honest, a

478
00:24:38,000 --> 00:24:40,040
Speaker 1: lot of people have a hangover seeing their parents in

479
00:24:40,080 --> 00:24:42,720
Speaker 1: the in the global financial crisis, dealing with too much time,

480
00:24:43,400 --> 00:24:45,440
Speaker 1: and there's a lot more thoughtful. They want to do

481
00:24:45,760 --> 00:24:48,040
Speaker 1: more socially conscious things with their rewards. So one of

482
00:24:48,080 --> 00:24:50,280
Speaker 1: the things we offer is, yeah, you can earn your points,

483
00:24:50,359 --> 00:24:52,320
Speaker 1: your cash back that you can use of the brand.

484
00:24:52,400 --> 00:24:54,440
Speaker 1: You can also donate it. And they really like that.

485
00:24:54,600 --> 00:24:57,760
Speaker 1: And so we see gen Z using their rewards to

486
00:24:57,840 --> 00:25:00,399
Speaker 1: make themselves feel better, not just to consume more, and

487
00:25:00,520 --> 00:25:02,040
Speaker 1: to do things like I want to give this to

488
00:25:02,119 --> 00:25:04,520
Speaker 1: the right social cause. There's a real difference between let's

489
00:25:04,560 --> 00:25:08,160
Speaker 1: say older millennials who are buying a home, they have kids,

490
00:25:08,359 --> 00:25:10,639
Speaker 1: their budget conscious for the first time, the boom boomers

491
00:25:10,680 --> 00:25:12,520
Speaker 1: who still carry a wat of cash. There you go.

492
00:25:14,040 --> 00:25:16,600
Speaker 1: Fall's an old school Wall Street bankers, so he's always

493
00:25:16,640 --> 00:25:18,399
Speaker 1: going to carry a roll of cash in this pocket.

494
00:25:18,440 --> 00:25:20,520
Speaker 1: But I'll let you in a little secret. He hasn't

495
00:25:20,640 --> 00:25:23,400
Speaker 1: used any cash for two years. All right, Dark Great,

496
00:25:23,400 --> 00:25:24,960
Speaker 1: get you in here. I want to get you back

497
00:25:25,040 --> 00:25:27,119
Speaker 1: because we can tell by your accent that you're from

498
00:25:27,160 --> 00:25:29,560
Speaker 1: France or something. So I want to hear what it's

499
00:25:29,640 --> 00:25:32,840
Speaker 1: like to start a business, especially in the pandemic um

500
00:25:33,000 --> 00:25:34,639
Speaker 1: and and scale it at the way you have. So

501
00:25:34,760 --> 00:25:36,760
Speaker 1: Dar Murfy Great to get you in here. He is

502
00:25:36,840 --> 00:25:43,480
Speaker 1: the CEO and the founder of Imprint. Let's talk a

503
00:25:43,480 --> 00:25:45,680
Speaker 1: little crypto here. We're gonna check in with Bloomberg Cross

504
00:25:45,720 --> 00:25:48,240
Speaker 1: Asset reporter Katie Griffelgie's here in our Bloomberg inter Active

505
00:25:48,240 --> 00:25:51,240
Speaker 1: Broker studio, and we also have Bloomberg Intelligence Senior macro

506
00:25:51,359 --> 00:25:56,800
Speaker 1: strategist Mike McGlone. He's manning the Bloomberg Intelligence my AMI outpost. Mike,

507
00:25:56,880 --> 00:25:59,120
Speaker 1: hopefully get the work is not too hard down there

508
00:25:59,200 --> 00:26:01,359
Speaker 1: for you here in this Ebruary day. But talk to

509
00:26:01,480 --> 00:26:04,560
Speaker 1: us about crypto. I blinked and this thing is back

510
00:26:04,760 --> 00:26:08,159
Speaker 1: bitcoins back above thousand. Give us your macro call here

511
00:26:08,200 --> 00:26:10,639
Speaker 1: as you talk to clients. The fastest horse in the

512
00:26:10,760 --> 00:26:12,680
Speaker 1: race has bounced the most is here, and I think

513
00:26:12,760 --> 00:26:15,760
Speaker 1: bounces the keyword Paul, because it looks to me more

514
00:26:16,200 --> 00:26:18,760
Speaker 1: at risk of a bear market rally than the beginning

515
00:26:18,840 --> 00:26:21,399
Speaker 1: of something new and enduring. So here's the significance of

516
00:26:21,440 --> 00:26:25,480
Speaker 1: cryptos are facing their first potential US recession and bitcoin

517
00:26:25,560 --> 00:26:28,400
Speaker 1: has never the fifty week moving average technically has never

518
00:26:28,480 --> 00:26:31,160
Speaker 1: dropped below the two week moving average, which it has done.

519
00:26:31,200 --> 00:26:33,720
Speaker 1: So it's somewhat and that all happens around twenty five tho.

520
00:26:34,000 --> 00:26:35,800
Speaker 1: So the markets bumped up to very good level, and

521
00:26:35,840 --> 00:26:37,760
Speaker 1: I look at it is Yes, I think in the

522
00:26:37,800 --> 00:26:39,800
Speaker 1: big picture this is a very good bull market. But

523
00:26:39,880 --> 00:26:42,320
Speaker 1: I think what's happening around these levels that we're seeing

524
00:26:42,359 --> 00:26:45,399
Speaker 1: more of the responsive sellers. Okay, great, I'm bullish, but

525
00:26:45,440 --> 00:26:48,359
Speaker 1: at these levels you gotta prove it. Hey, what do

526
00:26:48,400 --> 00:26:52,080
Speaker 1: you think about You know, as we see regulators cracked

527
00:26:52,119 --> 00:26:56,960
Speaker 1: down the sec sending out wells notices, um settling with

528
00:26:57,280 --> 00:27:00,960
Speaker 1: crack in on the securitization of theorium, which was like,

529
00:27:01,680 --> 00:27:05,320
Speaker 1: I mean, ethereum staking. That was part of the great

530
00:27:05,480 --> 00:27:09,680
Speaker 1: hope of the future of crypto, right, why are we

531
00:27:09,800 --> 00:27:12,480
Speaker 1: still seeing these games? You know, it's a good question.

532
00:27:12,560 --> 00:27:14,800
Speaker 1: I have something very scary to tell you about though,

533
00:27:15,280 --> 00:27:18,960
Speaker 1: a death cross it could be approaching when it comes

534
00:27:19,040 --> 00:27:21,920
Speaker 1: to bitcoin. Matt Mayley. He pointed this out in a note.

535
00:27:21,960 --> 00:27:24,520
Speaker 1: I think it was yesterday. He was looking at bitcoin's

536
00:27:24,560 --> 00:27:29,360
Speaker 1: fifty week moving average. It touched the two hundred week

537
00:27:29,480 --> 00:27:33,960
Speaker 1: moving average. When that happens, apparently it's very he's looking

538
00:27:34,000 --> 00:27:37,560
Speaker 1: at weeks we Typically it's the daily moving average, but

539
00:27:37,600 --> 00:27:40,960
Speaker 1: he's looking at the the moving averages when it comes

540
00:27:41,000 --> 00:27:43,160
Speaker 1: to the weeks. But in any case, that has never

541
00:27:43,880 --> 00:27:47,080
Speaker 1: happened before, and I don't know, the name implies that

542
00:27:47,160 --> 00:27:48,920
Speaker 1: that could be bad. I'd be curious to hear Mike's

543
00:27:48,920 --> 00:27:52,800
Speaker 1: thoughts on it. Yeah, well that's the death cross bad Mike, Well,

544
00:27:52,880 --> 00:27:54,919
Speaker 1: that's the thing. But the key thing I learned as

545
00:27:54,920 --> 00:27:57,239
Speaker 1: the traders, once it hits the popular press like us,

546
00:27:57,320 --> 00:27:59,240
Speaker 1: then you want to do the opposite. But the key

547
00:27:59,280 --> 00:28:01,720
Speaker 1: thing point Katie point out, it is the weekly so

548
00:28:01,840 --> 00:28:04,760
Speaker 1: it's a significant rollover. Everything is kind of tilting down

549
00:28:05,040 --> 00:28:07,000
Speaker 1: in cryptos, and they bounced up to very good levels.

550
00:28:07,080 --> 00:28:09,159
Speaker 1: The key thing I look at is what was the

551
00:28:09,280 --> 00:28:12,320
Speaker 1: major force of pressured almost all risk asses, most notaly

552
00:28:12,359 --> 00:28:16,119
Speaker 1: cryptos last year, and that was expectations for FED right hikes,

553
00:28:16,359 --> 00:28:18,960
Speaker 1: and that's still there. The s don't fight the FED

554
00:28:19,040 --> 00:28:21,160
Speaker 1: mantras still there. So I see the risk is now

555
00:28:21,320 --> 00:28:24,920
Speaker 1: that the stock markets rolling over, cryptos are rolling over.

556
00:28:24,960 --> 00:28:26,879
Speaker 1: But you can see what's going to happen in the

557
00:28:26,960 --> 00:28:29,720
Speaker 1: long term when this whole thing bottoms, is crypto should

558
00:28:29,720 --> 00:28:31,360
Speaker 1: come out ahead. The key things right now is we're

559
00:28:31,359 --> 00:28:34,480
Speaker 1: still fighting the FED and markets have bounced, and my

560
00:28:34,720 --> 00:28:37,440
Speaker 1: bias is the macro. In terms of the macros, the

561
00:28:37,440 --> 00:28:39,600
Speaker 1: stock market low is probably not in typically goes down

562
00:28:39,680 --> 00:28:42,000
Speaker 1: a lot more in a recession, that which means more

563
00:28:42,080 --> 00:28:44,400
Speaker 1: pressure for cryptos, most normally bitcoin. I just want to

564
00:28:44,440 --> 00:28:46,680
Speaker 1: know how these prices are going up. Like Katie, you

565
00:28:47,600 --> 00:28:51,120
Speaker 1: talk to investors all morning long, right Bill, Donna sits

566
00:28:51,200 --> 00:28:55,400
Speaker 1: right behind you. She talks to investors constantly. Mike, I'm

567
00:28:55,480 --> 00:28:58,040
Speaker 1: sure that you, you know, probably go to lunch or

568
00:28:58,160 --> 00:29:00,680
Speaker 1: some steakhouse with a bunch of investors at least once

569
00:29:00,720 --> 00:29:03,520
Speaker 1: a week. Have has either one of you talked to

570
00:29:03,800 --> 00:29:08,440
Speaker 1: anyone who's bought bitcoin. I haven't you know? You know,

571
00:29:08,520 --> 00:29:10,840
Speaker 1: I'm obsessed with cash right now. So that's like the

572
00:29:10,920 --> 00:29:14,640
Speaker 1: spiritual opposite of bitcoin, I would say. But it is interesting.

573
00:29:14,680 --> 00:29:16,440
Speaker 1: For a while, it felt like you could just like

574
00:29:16,640 --> 00:29:20,720
Speaker 1: neatly put the macro conversation on bitcoin. Stocks are rallying,

575
00:29:20,760 --> 00:29:22,800
Speaker 1: so of course bitcoin is ralling to it feels like

576
00:29:22,880 --> 00:29:25,960
Speaker 1: it's almost broken away from that. And I don't have

577
00:29:26,080 --> 00:29:28,720
Speaker 1: a good narrative right now for why it's rallying the

578
00:29:28,760 --> 00:29:30,200
Speaker 1: way it is. I mean, I'm sure some of that

579
00:29:30,320 --> 00:29:33,200
Speaker 1: just comes down to really pour liquidity and you can

580
00:29:33,360 --> 00:29:35,880
Speaker 1: really push it around. My Katie wrote a great story

581
00:29:35,960 --> 00:29:38,800
Speaker 1: the other day about how cash is basically yielding five percent.

582
00:29:38,880 --> 00:29:41,800
Speaker 1: What's the yield on bitcoin? Well, exactly, Matt, I agree

583
00:29:41,840 --> 00:29:44,160
Speaker 1: with you. To me, this is a boomer dream when

584
00:29:44,160 --> 00:29:45,720
Speaker 1: you can go plunk into a two you note and

585
00:29:45,760 --> 00:29:47,840
Speaker 1: get an over nine percent for two years, you say so,

586
00:29:47,880 --> 00:29:49,320
Speaker 1: thank you very much. I haven't been able to do

587
00:29:49,400 --> 00:29:51,800
Speaker 1: that predicting, but I did get a call from of

588
00:29:51,840 --> 00:29:53,600
Speaker 1: the smartest people I know in the bid is a

589
00:29:53,640 --> 00:29:57,080
Speaker 1: big arbitrage hedge fund last last in December. In the minute,

590
00:29:57,160 --> 00:30:00,640
Speaker 1: he said to me, Mike, what's this gbtcson? I knew

591
00:30:00,680 --> 00:30:03,680
Speaker 1: that was a bottom because the discount got so extreme,

592
00:30:03,720 --> 00:30:06,200
Speaker 1: and this is a distress distressed debt person. So to me,

593
00:30:06,360 --> 00:30:09,120
Speaker 1: this is a beer market. Explain to everyone else. There

594
00:30:10,720 --> 00:30:13,640
Speaker 1: is a great scale bitcoin trust. It's the most widely

595
00:30:14,160 --> 00:30:18,440
Speaker 1: tracked bitcoin um exchange trading product. It's not an e

596
00:30:18,520 --> 00:30:23,760
Speaker 1: t F but it's a trusts not yet, but it

597
00:30:23,840 --> 00:30:26,120
Speaker 1: got to extreme discount and had you know, hit the

598
00:30:26,200 --> 00:30:33,520
Speaker 1: stops and it's up what fifty percent since like this year.

599
00:30:34,040 --> 00:30:36,520
Speaker 1: Now that's a beer bear market rally. But it just

600
00:30:36,640 --> 00:30:39,560
Speaker 1: got too cheap on a discounted you know, discount to

601
00:30:39,720 --> 00:30:42,080
Speaker 1: premium basis. So I look at it. Okay, market get

602
00:30:42,120 --> 00:30:44,440
Speaker 1: way over sold. It's bounced, but we still face so

603
00:30:44,600 --> 00:30:47,120
Speaker 1: significant headwinds that yes, and the big picture, I think

604
00:30:47,160 --> 00:30:49,479
Speaker 1: bitcoin is gonna go continue to go up a lot

605
00:30:49,560 --> 00:30:51,800
Speaker 1: more like most assets. But right now, what are we

606
00:30:51,880 --> 00:30:53,600
Speaker 1: looking at from the Fed? They are still tightening into

607
00:30:53,600 --> 00:30:56,120
Speaker 1: stock markets rolling over and we're potentially heading towards the recession.

608
00:30:56,120 --> 00:30:58,479
Speaker 1: These are bad for risk gus. It's in bitcoins when

609
00:30:58,480 --> 00:31:03,920
Speaker 1: the risk rolled in incredibly bearish calling about three seconds there. Well,

610
00:31:04,000 --> 00:31:06,120
Speaker 1: it's the key fact that I really have to point

611
00:31:06,160 --> 00:31:09,120
Speaker 1: out is bitcoin is the leading indicator. If it sustains

612
00:31:09,160 --> 00:31:11,680
Speaker 1: above this twenty five thousand lover, that means a lot

613
00:31:11,800 --> 00:31:13,960
Speaker 1: for everything. And I look at as an next trader,

614
00:31:13,960 --> 00:31:15,920
Speaker 1: and may you say to yourself, Okay, prove it. I'll

615
00:31:15,960 --> 00:31:18,320
Speaker 1: structure a put position here and make you prove it.

616
00:31:18,440 --> 00:31:19,800
Speaker 1: And if it does work, and then we'll get into

617
00:31:19,800 --> 00:31:21,600
Speaker 1: the longer term trade. Remember the old thing on Wall

618
00:31:21,640 --> 00:31:24,040
Speaker 1: Street and people would say, oh, I'm bullish, and then

619
00:31:24,120 --> 00:31:26,600
Speaker 1: boss would say, okay, well of south housand, what do

620
00:31:26,640 --> 00:31:28,640
Speaker 1: you mean I'm bullish? And you say, well, sell thousand.

621
00:31:28,680 --> 00:31:31,000
Speaker 1: We see what happens the market doesn't go down, Okay,

622
00:31:31,040 --> 00:31:35,640
Speaker 1: we'll buy ten THO. He just said, g BTC isn't

623
00:31:35,960 --> 00:31:38,880
Speaker 1: an e t F yet. What do you say if

624
00:31:38,880 --> 00:31:40,920
Speaker 1: I told you I haven't seen Evil Dead two yet,

625
00:31:42,520 --> 00:31:45,200
Speaker 1: that implies that you're going to in the future, which Mike,

626
00:31:45,240 --> 00:31:47,400
Speaker 1: you're implying this will become an e t F in

627
00:31:47,480 --> 00:31:51,000
Speaker 1: the future. Have you ever heard of Gary Gensler? Terribly unlikely,

628
00:31:51,760 --> 00:31:54,000
Speaker 1: But I think that's what's happening. And so we launched

629
00:31:54,000 --> 00:31:57,120
Speaker 1: a Bloomberg Galaxy Cryptoline XS almost five years ago. What's

630
00:31:57,160 --> 00:31:59,840
Speaker 1: the main thought is this space needs to track in

631
00:32:00,080 --> 00:32:02,280
Speaker 1: decks and E t F to track and indext like

632
00:32:02,400 --> 00:32:04,480
Speaker 1: the S and B five founder, I think you're gonna

633
00:32:04,480 --> 00:32:07,160
Speaker 1: protect investors. That's where it's going to go. I think

634
00:32:07,400 --> 00:32:09,880
Speaker 1: right now, typically it isn't. We're in a pretty extreme

635
00:32:09,920 --> 00:32:12,000
Speaker 1: regulation mode and a lot of firms in the US

636
00:32:12,040 --> 00:32:14,280
Speaker 1: are are not they're leaving the US are trying to

637
00:32:14,880 --> 00:32:17,760
Speaker 1: avoid the regulation. But to me, to protect investors and

638
00:32:17,840 --> 00:32:20,480
Speaker 1: not pick winners, that's we're eventually gonna go. It's just

639
00:32:20,520 --> 00:32:24,800
Speaker 1: gonna take a while. So, Mike, you're down in Miami,

640
00:32:24,880 --> 00:32:28,480
Speaker 1: the self proclaimed capital, bitcoin capital or crypto capital of

641
00:32:28,600 --> 00:32:30,720
Speaker 1: the U S the I guess the Austin, Texas or

642
00:32:30,760 --> 00:32:32,680
Speaker 1: the you know, something like that, trying to be cool.

643
00:32:32,960 --> 00:32:35,840
Speaker 1: What's the mood down there of the folks that have

644
00:32:35,920 --> 00:32:38,280
Speaker 1: come down there and really planted their flag in this

645
00:32:38,400 --> 00:32:42,800
Speaker 1: crypto space. I was at a conference in the December

646
00:32:43,000 --> 00:32:46,960
Speaker 1: right near the Lows and it was packed and Mayor

647
00:32:47,000 --> 00:32:49,400
Speaker 1: Swore has spoken. The people there were all focused on

648
00:32:49,480 --> 00:32:52,880
Speaker 1: the macro big picture and seemed quite positive that the

649
00:32:52,960 --> 00:32:55,360
Speaker 1: problem is some of the retail people got hurt from

650
00:32:55,480 --> 00:32:58,200
Speaker 1: ft X. That that really is sad. I mean, they

651
00:32:58,520 --> 00:33:00,360
Speaker 1: haven't been able to have they put their trust with

652
00:33:00,400 --> 00:33:04,160
Speaker 1: an exchange that was not a good fiduciaring. It wouldn't

653
00:33:04,160 --> 00:33:05,840
Speaker 1: be able to do it through n ET for something,

654
00:33:06,120 --> 00:33:08,040
Speaker 1: so to me, that's scary. But overall the mood is

655
00:33:08,040 --> 00:33:10,240
Speaker 1: still quite positive. In the big picture. You look at bitcoin,

656
00:33:10,680 --> 00:33:13,880
Speaker 1: it looks like it's potentially body but it's four thousand

657
00:33:14,000 --> 00:33:16,040
Speaker 1: right now. The last time it put a significant low

658
00:33:16,080 --> 00:33:19,680
Speaker 1: around eighteen or nineteen in two thoust and around three

659
00:33:19,720 --> 00:33:22,520
Speaker 1: to four thousand, so it's still we'll get the big,

660
00:33:22,560 --> 00:33:27,320
Speaker 1: big sure yep from its lows. Uh. So you know

661
00:33:27,440 --> 00:33:30,280
Speaker 1: that's pretty good. You bought something, you think about it,

662
00:33:30,360 --> 00:33:33,200
Speaker 1: and as a class a major exchange goes belly up.

663
00:33:33,600 --> 00:33:37,800
Speaker 1: Potential for fraud we'll find out. And yet the underlying

664
00:33:37,800 --> 00:33:40,400
Speaker 1: sec you think some fraud may have been in the

665
00:33:40,440 --> 00:33:43,680
Speaker 1: crypto industry. Possibly, well, I can't say for certain. We can't.

666
00:33:43,680 --> 00:33:45,280
Speaker 1: We'll have that trial to figure it all out. But

667
00:33:45,560 --> 00:33:48,080
Speaker 1: interesting to see that assets still trading well. All right,

668
00:33:48,320 --> 00:33:51,280
Speaker 1: good stuff. Mike McGlone, Bloomberg Intelligence. He's down in our

669
00:33:51,360 --> 00:33:55,040
Speaker 1: Miami outpost manning all things crypto from down there. Katie

670
00:33:55,080 --> 00:34:00,840
Speaker 1: Riefeld Cross Asset reported one of the big inners in

671
00:34:00,920 --> 00:34:03,880
Speaker 1: the stock market today is dear income stocks up six

672
00:34:04,080 --> 00:34:06,240
Speaker 1: per cent on the back of some good, good numbers.

673
00:34:06,560 --> 00:34:08,160
Speaker 1: Let's break it all down with Chris Chile. You know

674
00:34:08,239 --> 00:34:11,839
Speaker 1: he's an equity research channelst at Bloomberg Intelligence. So Chris,

675
00:34:11,920 --> 00:34:14,320
Speaker 1: when I when I think of deer, I think of

676
00:34:14,480 --> 00:34:17,360
Speaker 1: the American farmer. So can I surmise that the American

677
00:34:17,400 --> 00:34:20,920
Speaker 1: farmers doing pretty well these days. They sure are, and

678
00:34:21,000 --> 00:34:23,600
Speaker 1: we're not really seeing much signs of the slowdown either. UM.

679
00:34:23,800 --> 00:34:27,440
Speaker 1: It was a real solid, beaten raised quarter. UM pricing

680
00:34:27,520 --> 00:34:31,960
Speaker 1: continues to be unbelievably strong, up double digits again, and

681
00:34:32,080 --> 00:34:35,040
Speaker 1: we also saw higher production, particularly in the large jag

682
00:34:35,200 --> 00:34:38,560
Speaker 1: business and construction as some of these UM supply constraints

683
00:34:38,600 --> 00:34:41,279
Speaker 1: are beginning to show, you know, real tangible evidence of

684
00:34:41,360 --> 00:34:45,520
Speaker 1: easing UH. And the demand for farm equipment again remarkably

685
00:34:45,560 --> 00:34:48,800
Speaker 1: strong with no signs of slowing. Orders are essentially filled

686
00:34:48,840 --> 00:34:51,880
Speaker 1: out into four Q and for some products were booked

687
00:34:51,920 --> 00:34:55,200
Speaker 1: for the entire year UM. So this is going to

688
00:34:55,280 --> 00:34:58,520
Speaker 1: even spill over into four because inventories are quite lean.

689
00:34:58,719 --> 00:35:01,360
Speaker 1: So there's certain the legs to the cycle, you know.

690
00:35:01,440 --> 00:35:03,680
Speaker 1: I'm UH next week, I'm gonna go down to the

691
00:35:03,760 --> 00:35:07,880
Speaker 1: Duccatti dealership in Soho and talk to the North American

692
00:35:07,960 --> 00:35:10,440
Speaker 1: CEO of that business. Nice They have a similar issue.

693
00:35:10,520 --> 00:35:14,520
Speaker 1: So if you want UM like a Ducatti multi strata,

694
00:35:15,040 --> 00:35:17,160
Speaker 1: you're probably gonna wait until the end of the year

695
00:35:17,200 --> 00:35:19,760
Speaker 1: before they can fill your order. They're all sold out already,

696
00:35:20,040 --> 00:35:24,160
Speaker 1: pretty much everything they make and UM But the thing is,

697
00:35:25,239 --> 00:35:28,880
Speaker 1: I wonder about new buyers who may have to finance.

698
00:35:29,000 --> 00:35:32,640
Speaker 1: Maybe with Ducatti, it's a little different because it's kind

699
00:35:32,719 --> 00:35:35,840
Speaker 1: of a wealthier person's product and it's a toy. They

700
00:35:35,840 --> 00:35:38,160
Speaker 1: could buy it in cash if finance costs are too high.

701
00:35:38,480 --> 00:35:41,160
Speaker 1: But what's the deal with financing, Chris, You know a

702
00:35:41,320 --> 00:35:44,160
Speaker 1: tractor or a plow or something that you get from deer,

703
00:35:44,440 --> 00:35:48,880
Speaker 1: because I imagine rates are around seven percent? UM? Do

704
00:35:49,440 --> 00:35:53,200
Speaker 1: farmers just pay cash? Are the buyers all institutional? How

705
00:35:53,200 --> 00:35:55,759
Speaker 1: does that work out? You know, it's kind of a

706
00:35:55,880 --> 00:35:59,759
Speaker 1: tale of two farmers. UM on the small end of

707
00:35:59,840 --> 00:36:04,360
Speaker 1: the spectrum and the small local farmers. No doubt that

708
00:36:04,520 --> 00:36:07,200
Speaker 1: is having a material impact. And that's the one area

709
00:36:07,239 --> 00:36:10,239
Speaker 1: of the business where you're starting to see a slowdown. UM.

710
00:36:10,560 --> 00:36:13,279
Speaker 1: When it comes to your large professional farmers who made

711
00:36:13,360 --> 00:36:16,879
Speaker 1: record profits last year, yes they are using cash UM,

712
00:36:17,040 --> 00:36:20,640
Speaker 1: and yes they could weather these little bit higher rates UM.

713
00:36:20,960 --> 00:36:24,120
Speaker 1: So as you look at the large corporate you know,

714
00:36:24,239 --> 00:36:27,400
Speaker 1: professional farmers UM, it tends to have less of an

715
00:36:27,440 --> 00:36:31,560
Speaker 1: impact UM. But you know, we're coming off record profitability

716
00:36:31,680 --> 00:36:34,719
Speaker 1: last year. Farming comes going to be down this year,

717
00:36:34,920 --> 00:36:37,840
Speaker 1: but still it would be above any prior peak cycle,

718
00:36:38,000 --> 00:36:41,200
Speaker 1: So farmers are still in a healthy financial position. How

719
00:36:41,360 --> 00:36:45,400
Speaker 1: is the family farm in America? Chris? I mean, um,

720
00:36:46,200 --> 00:36:50,200
Speaker 1: what's the split, you know, big institutional corporate farms to

721
00:36:50,360 --> 00:36:53,239
Speaker 1: family farms. What's it looked like right now? Yeah, it's

722
00:36:53,320 --> 00:37:00,120
Speaker 1: something similar to you know, it's like UM farmers or

723
00:37:00,200 --> 00:37:02,759
Speaker 1: you know, corporate owned, but account for nearly like eighty

724
00:37:02,800 --> 00:37:06,080
Speaker 1: percent of our production. Something in that ballpark. So when

725
00:37:06,160 --> 00:37:11,440
Speaker 1: we think about the the large professional farmers that that

726
00:37:11,560 --> 00:37:14,440
Speaker 1: moved the needle, the small egg business is important, and

727
00:37:14,520 --> 00:37:18,440
Speaker 1: it's somewhat split between um like agg production systems and

728
00:37:18,560 --> 00:37:20,640
Speaker 1: haying forage. And then they have the you know, the

729
00:37:20,880 --> 00:37:23,560
Speaker 1: traditional kind of turf and utility business that caters more

730
00:37:23,600 --> 00:37:26,920
Speaker 1: towards your consumer oriented products, and that's where the biggest

731
00:37:26,960 --> 00:37:30,200
Speaker 1: weakness is within their portfolio. But really that's it. I

732
00:37:30,239 --> 00:37:34,840
Speaker 1: mean construction strong, large egg, very strong. That is referred

733
00:37:34,840 --> 00:37:38,080
Speaker 1: to as the Peretto principle. The Peretto principle, right, So

734
00:37:38,400 --> 00:37:40,840
Speaker 1: it's the same in a lot of different things. You

735
00:37:40,880 --> 00:37:44,040
Speaker 1: could say, for example, of the people have eighty percent

736
00:37:44,120 --> 00:37:46,399
Speaker 1: of the wealth yep got it? Okay, that makes sense?

737
00:37:46,480 --> 00:37:49,120
Speaker 1: So all right, Chris. So if if I'm a family

738
00:37:49,200 --> 00:37:52,560
Speaker 1: farmer in Western Jersey. And that can happen because we

739
00:37:52,640 --> 00:37:54,440
Speaker 1: are the guarded state, and I want to go and

740
00:37:54,480 --> 00:37:55,920
Speaker 1: I gotta buy a couple of plows, a couple of

741
00:37:55,960 --> 00:37:58,480
Speaker 1: big tractors from my farm. Can I haggle with the

742
00:37:58,560 --> 00:38:02,200
Speaker 1: sales person because I can't haggle with the car salesman anymore.

743
00:38:02,760 --> 00:38:06,520
Speaker 1: Not this year. There's just no inventory out there. So

744
00:38:06,760 --> 00:38:10,640
Speaker 1: pricing has just been remarkably strong. Pricing in their large

745
00:38:10,680 --> 00:38:14,319
Speaker 1: egg business was up in the first quarter here, which

746
00:38:14,400 --> 00:38:17,520
Speaker 1: is phenomenal. We've never seen anything like that before. UM.

747
00:38:18,360 --> 00:38:20,279
Speaker 1: And the other the problem to also if you try

748
00:38:20,320 --> 00:38:22,680
Speaker 1: to find a use piece of equipment, use prices are

749
00:38:22,719 --> 00:38:25,400
Speaker 1: near record levels. There's just no inventory in the channel,

750
00:38:26,120 --> 00:38:28,640
Speaker 1: partly due to the the supply chain and then just

751
00:38:28,719 --> 00:38:31,920
Speaker 1: partly we've been under producing for the past few years. UM.

752
00:38:32,000 --> 00:38:34,319
Speaker 1: This is going to be another year in three were

753
00:38:34,360 --> 00:38:38,800
Speaker 1: demand outstrips supply. So UH pricing, while it will moderate

754
00:38:38,920 --> 00:38:41,680
Speaker 1: as we progress through the year, UM, we still expect

755
00:38:41,719 --> 00:38:44,600
Speaker 1: it to remain quite strong and from a price cost perspective,

756
00:38:45,120 --> 00:38:48,279
Speaker 1: UM will be a significant margin teil win for deer

757
00:38:49,000 --> 00:38:51,879
Speaker 1: who is the big I remember when my buddy Adam

758
00:38:52,000 --> 00:38:55,560
Speaker 1: Johnson needed to buy a tractor for his farm up state.

759
00:38:55,680 --> 00:38:57,719
Speaker 1: He won. He lives in Manhattan. Yeah no, but I

760
00:38:57,800 --> 00:39:00,200
Speaker 1: think he wanted to get like a Mahindra, who were

761
00:39:00,239 --> 00:39:03,840
Speaker 1: the big competitors to John Dear. If you think about

762
00:39:03,920 --> 00:39:07,080
Speaker 1: the large act business in North America, it's really a

763
00:39:07,200 --> 00:39:12,080
Speaker 1: duopoli with Deer and CNH Industrial. The case brand um

764
00:39:12,200 --> 00:39:14,960
Speaker 1: As is another big player who has made some pretty

765
00:39:15,000 --> 00:39:17,920
Speaker 1: significant strides to get into some larger equipment. And then

766
00:39:17,960 --> 00:39:19,880
Speaker 1: you also have Caboda, which tends to be more on

767
00:39:19,960 --> 00:39:22,080
Speaker 1: the kind of the small mid horse power, but if

768
00:39:22,120 --> 00:39:25,279
Speaker 1: you're talking large high horse power equipment, it's really Deer.

769
00:39:25,360 --> 00:39:29,759
Speaker 1: In case Lamborghini, what Lamborghini was a tractor brand to

770
00:39:29,800 --> 00:39:32,439
Speaker 1: start with you? What was it really? Yeah? Uh, what's

771
00:39:32,480 --> 00:39:36,720
Speaker 1: his name? Ferrucio Lamborghini. He was rich from his tractor

772
00:39:36,800 --> 00:39:40,200
Speaker 1: business and he loved Ferrari's cars, but he thought Enzo's

773
00:39:40,200 --> 00:39:42,680
Speaker 1: clutches were crap. I found out it was the same

774
00:39:42,719 --> 00:39:44,439
Speaker 1: clutch that he used in this tractor. So he said,

775
00:39:44,440 --> 00:39:46,360
Speaker 1: you know what, I'm gonna build my own. There you go,

776
00:39:46,480 --> 00:39:48,600
Speaker 1: good story. I haven't heard that before from Matt Miller.

777
00:39:49,040 --> 00:39:51,560
Speaker 1: Um So, Chris, let's let's switch gears. Since I'm gonna

778
00:39:51,719 --> 00:39:53,480
Speaker 1: since we got on the phone, another one of my

779
00:39:53,640 --> 00:39:58,239
Speaker 1: favorite companies that you cover, Caterpillar. Now, Caterpillars not tied

780
00:39:58,280 --> 00:40:00,719
Speaker 1: to the farmer as much as obviously dear, and I'm

781
00:40:01,040 --> 00:40:03,400
Speaker 1: guessing there's some recession risk in a name like that.

782
00:40:03,920 --> 00:40:06,920
Speaker 1: What's the calling Caterpillar here? You know what there is,

783
00:40:07,400 --> 00:40:09,960
Speaker 1: and you know it's somewhat similar if you think about it.

784
00:40:10,440 --> 00:40:13,239
Speaker 1: The weakness is really kind of isolated right now, more

785
00:40:13,320 --> 00:40:17,280
Speaker 1: in their residential construction exposure, which really is quite small

786
00:40:17,680 --> 00:40:21,080
Speaker 1: if you think about their construction business that is non

787
00:40:21,200 --> 00:40:25,320
Speaker 1: resi UM, and there's significant tail winds there with the

788
00:40:25,400 --> 00:40:28,600
Speaker 1: government investments, whether it be the infrastructure i RA A

789
00:40:29,680 --> 00:40:31,920
Speaker 1: chip sack. I mean, we've got billions and billions of

790
00:40:31,960 --> 00:40:34,000
Speaker 1: dollars that are going to start flowing through the system.

791
00:40:34,040 --> 00:40:36,920
Speaker 1: We're only seeing that begin to hit the backlog now,

792
00:40:37,400 --> 00:40:39,520
Speaker 1: so we think that's a significant tail wind. And then

793
00:40:39,640 --> 00:40:41,920
Speaker 1: over the next two or three years, you also have

794
00:40:42,440 --> 00:40:47,160
Speaker 1: UM mining equipment continues to be UM historically old age

795
00:40:47,200 --> 00:40:50,480
Speaker 1: of the fleet. We we have a replacement cycle there

796
00:40:50,520 --> 00:40:52,960
Speaker 1: that's unfolding, and you know, we're still seeing pretty good

797
00:40:52,960 --> 00:40:57,800
Speaker 1: investments when it comes to energy, UM and commodity related products.

798
00:40:57,840 --> 00:41:02,000
Speaker 1: So there's certainly some favorite bull Macro tail winds, notwithstanding

799
00:41:02,080 --> 00:41:05,920
Speaker 1: some of the the slower residential spending. You know why

800
00:41:05,960 --> 00:41:09,680
Speaker 1: I brought up Lamborghini because now because Chris was saying

801
00:41:09,760 --> 00:41:13,120
Speaker 1: CNCH Industrial is the big competitor to Deer, and Chris,

802
00:41:13,239 --> 00:41:19,359
Speaker 1: you know who owns CNH Industrial Fiat UH, which also

803
00:41:19,480 --> 00:41:23,520
Speaker 1: owns Ferrari or a sizeable steak in Ferrari. That's I

804
00:41:23,600 --> 00:41:26,520
Speaker 1: think really fascinating that those tests supercarmakers have said just

805
00:41:26,560 --> 00:41:28,759
Speaker 1: clicked in CNH for the timble symbol and it says

806
00:41:28,960 --> 00:41:34,200
Speaker 1: acquired by Fiat I am on so and by the way,

807
00:41:34,680 --> 00:41:38,360
Speaker 1: if you've seen you know top Gear, Jeremy Clarkson, he

808
00:41:38,760 --> 00:41:41,200
Speaker 1: has a new show where he buys a farm and

809
00:41:41,239 --> 00:41:43,560
Speaker 1: tries to run it. He gets a big Lamborghini tractor

810
00:41:43,880 --> 00:41:45,640
Speaker 1: because he likes the brand name, and then he finds

811
00:41:45,640 --> 00:41:48,960
Speaker 1: out it's too large to fit in his barn. Tough

812
00:41:49,000 --> 00:41:52,440
Speaker 1: problems there, Chris, So, China reopening, what does that mean

813
00:41:52,840 --> 00:41:55,719
Speaker 1: for your big industrial companies, whether it's like a Cat

814
00:41:55,920 --> 00:41:58,719
Speaker 1: or Deer or some many other big industrial companies that

815
00:41:58,840 --> 00:42:02,279
Speaker 1: you cover. Yeah, with the with the China reopening, I

816
00:42:02,440 --> 00:42:05,360
Speaker 1: think um as it relates to deer, I think this

817
00:42:05,960 --> 00:42:08,200
Speaker 1: is another tail when for them. Now you know they

818
00:42:08,239 --> 00:42:10,800
Speaker 1: don't sell a lot of equipment directly into China, just

819
00:42:10,960 --> 00:42:12,840
Speaker 1: the farms over there aren't conducive to a lot of

820
00:42:12,880 --> 00:42:16,320
Speaker 1: these larger equipment. But why I do think it helps is,

821
00:42:16,520 --> 00:42:21,120
Speaker 1: you know, global crop supplies are historically tight, largely due

822
00:42:21,160 --> 00:42:23,640
Speaker 1: to the to the war in Ukraine and the restriction

823
00:42:23,719 --> 00:42:26,320
Speaker 1: of shipments and fertilizer coming out of that market. But

824
00:42:26,440 --> 00:42:31,120
Speaker 1: now you throw on the China reopening, um, grain supplies

825
00:42:31,160 --> 00:42:33,600
Speaker 1: are going to remain historically tight. So we think this

826
00:42:33,760 --> 00:42:36,399
Speaker 1: keeps crop prices elevated for the next couple of years

827
00:42:36,520 --> 00:42:39,680
Speaker 1: and really gives additional legs to the cycle. So we

828
00:42:39,760 --> 00:42:42,880
Speaker 1: see China reopening as a tail when there. As you

829
00:42:42,960 --> 00:42:46,040
Speaker 1: think about cat you know, China's only roughly five percent

830
00:42:46,120 --> 00:42:49,320
Speaker 1: of their sales, but it's the largest equipment market in

831
00:42:49,320 --> 00:42:53,680
Speaker 1: the world. Any kind of reopening infrastructure investments over there

832
00:42:54,080 --> 00:42:56,880
Speaker 1: certainly would add some upside well. And if they let

833
00:42:56,960 --> 00:43:00,600
Speaker 1: the ethanol um proportion of gasoline and rise up to

834
00:43:00,680 --> 00:43:04,040
Speaker 1: fift that's going to be another tail wind, right for

835
00:43:04,120 --> 00:43:07,600
Speaker 1: corn prices. Yeah, we're we're looking at kind of I

836
00:43:07,680 --> 00:43:11,720
Speaker 1: think a structural deficit um when it comes to crops

837
00:43:11,719 --> 00:43:16,920
Speaker 1: supply demand. So barring some kind of unforeseen weather events

838
00:43:17,000 --> 00:43:19,880
Speaker 1: and um, you know, we're still going to look at

839
00:43:20,080 --> 00:43:23,200
Speaker 1: you know, historically tight supplies here probably for the next

840
00:43:23,280 --> 00:43:25,680
Speaker 1: several years. Um. And at the end of the day,

841
00:43:25,800 --> 00:43:28,080
Speaker 1: you know, if farmers continue to make money, they tend

842
00:43:28,160 --> 00:43:30,960
Speaker 1: to reinvest in equipment. Where where are you based, Chris,

843
00:43:31,280 --> 00:43:35,520
Speaker 1: You're you're down in Princeton. Princeton, New Jersey is a

844
00:43:35,600 --> 00:43:37,440
Speaker 1: very nice little farm area. I was gonna say, if

845
00:43:37,440 --> 00:43:38,840
Speaker 1: you're in the Midwest, you don't want to miss the

846
00:43:38,920 --> 00:43:42,680
Speaker 1: Miller's Port Corn Festival. Miller's Sport, the Miller's Port, Ohio

847
00:43:42,920 --> 00:43:46,000
Speaker 1: of course, best corn festival in the country. Really the

848
00:43:46,200 --> 00:43:50,200
Speaker 1: most delicious corner that I imagine. It's in the fall

849
00:43:50,280 --> 00:43:53,120
Speaker 1: at some point, right around right around October Fest. All right, Chris,

850
00:43:53,200 --> 00:43:55,840
Speaker 1: great stuff. Chris Chile and equity research channels for Bloomberg

851
00:43:55,960 --> 00:44:02,759
Speaker 1: Intelligence joining us here. Thanks for listening to the Bloomberg

852
00:44:02,840 --> 00:44:06,239
Speaker 1: Markets podcast. You can subscribe and listen to interviews of

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00:44:06,280 --> 00:44:11,080
Speaker 1: Apple podcasts or whatever podcast platform you prefer. I'm Matt Miller.

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Speaker 1: I'm on Twitter at Matt Miller three on Fall Sweeney.

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Speaker 1: I'm on Twitter at pt Sweeney Before the podcast, you

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Speaker 1: can always catch us worldwide at Bloomberg Radio