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Speaker 1: Bloomberg Audio Studios, podcasts, radio news. You're listening to the

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Speaker 1: Bloomberg Intelligence Podcast. Catch us live weekdays at ten am

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Speaker 2: So we have an economic data out as well, So

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Speaker 2: the Conference Board consumer confidence of falling a little bit

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Speaker 2: and coming in a one hundred point four present situation

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Speaker 2: coming in a little light, Expectations a little light, but

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Speaker 2: we want to get perspective on this, particularly as we

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Speaker 2: head into the debate later on this week. Dani Peterson

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Speaker 2: as chief economist at the Conference Board, and she joins us, now,

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Speaker 2: can you tell me more about this data and what

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Speaker 2: you kind of noticed from this survey.

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Speaker 3: Sure, consumers are still having mixed feelings. For the most part,

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Speaker 3: they're optimistic about their current employment situation, and certainly that's

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Speaker 3: why the present situation index continues.

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Speaker 4: To be buoyant.

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Speaker 3: But they're still very concerned about the future, especially with

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Speaker 3: respect to business conditions and their incomes. And so when

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Speaker 3: you net all that out, we're just seeing kind of

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Speaker 3: treading water here with consumer confidence. It's not terribly different

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Speaker 3: in terms of breaking out of the range we've seen

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Speaker 3: over the last.

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Speaker 5: Year and a half.

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Speaker 6: But still in all, we're.

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Speaker 3: Noticing that expectations are weakening and that could start really

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Speaker 3: weighing on the overall index.

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Speaker 7: Talk to us about that expectations again, it came in

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Speaker 7: its seventy three and that's down from a revived seventy

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Speaker 7: four point nine last period.

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Speaker 4: Where do you want to see that number?

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Speaker 7: Where does that number need to be to suggest a

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Speaker 7: healthy economy?

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Speaker 3: Sure, so, anything below eighty usually signals that the consumer's thinking, well,

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Speaker 3: maybe a recession is on the way. While it's not

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Speaker 3: our expectation, we do think that consumer spending is going

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Speaker 3: to slow over the course of the summer. Probably it

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Speaker 3: already started in the earlier months of this year. It's

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Speaker 3: going to continue. And also we ask consumers do you

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Speaker 3: think a recession's going to happen? That kicked down in

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Speaker 3: terms of the percentage saying yes, But still they're very

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Speaker 3: worried about what's ahead. Again, it's focused on business conditions

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Speaker 3: ahead and their incomes, but they're not complaining much about employment.

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Speaker 3: But even still that employment gauge is below where we'd

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Speaker 3: think it should be.

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Speaker 2: It's interesting you say that because I feel like Michelle

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Speaker 2: Bowman versus Mary Daily over the last twenty four hours

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Speaker 2: told me something. And some are worried about infletion like

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Speaker 2: Michelle Bowman, and some are worried more about growth and

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Speaker 2: employment aka Mary Daily. In your survey, though, it seems

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Speaker 2: like it's still just prices rather than jobs.

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Speaker 3: Exactly. So when it comes to prices, consumers are continuing

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Speaker 3: to complain about the level. They're saying the level of

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Speaker 3: food and gasoline prices are still too expensive, and prices

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Speaker 3: overall are still higher than what they'd like. They're complaining

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Speaker 3: less about the rate of increase in prices, which is inflation,

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Speaker 3: and indeed the inflation expectations gauge continues to take downward.

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Speaker 3: But it's that concern about the fact that well, eggs

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Speaker 3: are eight dollars, bread is ten dollars, and that's really

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Speaker 3: disconcerting consumers.

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Speaker 7: All right, Dan, thank you so much for stepping in

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Speaker 7: and chatting with the Stany Peterson is the chief economist

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Speaker 7: at the Conference Board. On the latest consumer confidence data

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Speaker 7: cap in a little bit weaker than the prior period.

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Speaker 4: Will keep an eye on that.

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Speaker 1: You're listening to the Bloomberg Intelligence podcast Catch US live

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Speaker 1: weekdays at ten am Eastern on applecar Play and Android

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Speaker 1: Just Say Alexa playing Bloomberg eleven thirty.

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Speaker 2: Carnival up over six percent. Here's what I don't understand.

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Speaker 2: Carnival's doing really well. They're looking at good bookings, but

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Speaker 2: then we got consumer confidence or at the top of

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Speaker 2: the ten saying that people are worried and they're worried

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Speaker 2: about rising prices.

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Speaker 6: I don't know how to square these two things.

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Speaker 4: I don't know.

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Speaker 7: People are still spending on experiences. It appears like coming

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Speaker 7: out of pandemic. I guess we kind of thought that

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Speaker 7: would be a year or two. But yeah, they're took

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Speaker 7: great bookings into next year.

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Speaker 2: I know it's like forget eggs, but we're going to

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Speaker 2: go buy a cruise. Brian Egger is Bloomberg Intelligence Senior

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Speaker 2: Gaming and Launching analysts, and he joins us. Now, Brian,

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Speaker 2: can you help me make sense of the strength and

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Speaker 2: the likes of Carnival Carnival versus the overall feeling that

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Speaker 2: consumers continue to say that they are stressed about sure.

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Speaker 5: I think what Carnival is seeing is going beyond pent

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Speaker 5: up demand from the pandemic to genuine, ongoing, sustainable, disposable

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Speaker 5: spending on leisure travel. So if they're seeing it across

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Speaker 5: the board, I mean it really is broad base. They're

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Speaker 5: singing in Europe and North America. They're seeing it for

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Speaker 5: both on board spending and ticket fare gains, and they're

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Speaker 5: seeing it both on new hardware and you know, kind

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Speaker 5: of legacy ships as well, So it is pretty broad based.

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Speaker 7: So is it the typical cruising customer? Is it new

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Speaker 7: people coming into the industry?

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Speaker 4: What are they seeing here?

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Speaker 5: H I think it's both. There's always a focus on

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Speaker 5: new cruise customers and marketing the value relative value of

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Speaker 5: cruises compared to other forms of vacation. I think it's

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Speaker 5: really both, And you know, different brands attract different demographics

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Speaker 5: and age groups, but you know to the extent that

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Speaker 5: it's broad based, and it seems to be happening not

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Speaker 5: only in the first quarter but continuing to the second quarter,

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Speaker 5: and as Alex mentioned next as well, you know, I

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Speaker 5: think it's we're seeing it across the board.

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Speaker 2: If we go into a real slump or if inflation

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Speaker 2: stays sticky. Does that affect this sustainable leisure demand the

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Speaker 2: Carnival and you were talking about, you.

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Speaker 5: Know, it does. Certainly. Travel prices have increased, and we're

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Speaker 5: seeing that dis manifested of the fact that Carnival raised

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Speaker 5: its net revenue old growth outlook for twenty twenty four

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Speaker 5: from nine point five percent to ten and a quarter percent,

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Speaker 5: So they're partly benefiting from that price. But obviously, you know,

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Speaker 5: inflation cost inflation does affect the disposition of consumers. But

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Speaker 5: from now, at least, you know, the demand on the

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Speaker 5: consumer discretionary side certainly seems to be there.

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Speaker 7: How About on the cost side, I'm thinking fuel, I'm

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Speaker 7: thinking labor. What's going on on the cost side for

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Speaker 7: a lot of these crews companies.

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Speaker 5: Yeah, it's a factor certainly in terms of cost positioning.

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Speaker 5: They've maintained I guess i'd say kind of a stable

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Speaker 5: full year unit cost growth outlook of about four and

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Speaker 5: a half percent or so, excluding the increases in the fuel.

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Speaker 5: There are some increases going on there, but they're also

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Speaker 5: to some degree being offset where they can by operating

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Speaker 5: efficiencies and you know, where they can refinancing of debt

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Speaker 5: and interesting and They've also identified just operational cost savings

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Speaker 5: throughout wherever possible. So it's a challenging cost environment generally

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Speaker 5: for the economy, but they are I think, I think

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Speaker 5: seeing pockets of opportunity to uh to manage and mitigate

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Speaker 5: that cost growth.

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Speaker 2: Is there a distinction between Disney Cruises and Norwegian Cruise,

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Speaker 2: like the ones that take it to Iceland and the

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Speaker 2: Paul would go on versus the ones that, like I

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Speaker 2: would have to go on with my kid, Like, are

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Speaker 2: there a distinction or is this like a broad stroke

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Speaker 2: for the cruise like guys?

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Speaker 5: I mean, there are so many distinction across brands to

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Speaker 5: give you some sense of it, you know, like domestically

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Speaker 5: or in terms of US brands, they saw yields up

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Speaker 5: in the quarter seven percent, European brands up twelve percent,

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Speaker 5: So it's pretty broad based with some differences in comparisons.

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Speaker 5: I will say that the level of yield growth expectation,

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Speaker 5: it's ten percent ish as I mentioned for Carnival, you know,

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Speaker 5: it's nine and a half percent for a while, and

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Speaker 5: it's a touch above seven percent for Norwegian. And while

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Speaker 5: there are differences across companies in terms of comparisons, I

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Speaker 5: think you can say those are roughly the same ballpark

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Speaker 5: in terms of the inertia momentum for bookings.

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Speaker 4: Is this an industry? Are they building new ships?

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Speaker 5: There are new ships in order, you know, the level

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Speaker 5: of supply growth slows down a little bit going into

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Speaker 5: next year. It's kind of like a kind of a

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Speaker 5: mid single digit long term supply growth rate, which historically

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Speaker 5: is actually a little bit more modern than what we've

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Speaker 5: seen over some past decades. So they are building new hardware,

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Speaker 5: but they're also I mean, this is kind of key

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Speaker 5: for Carnival. They have been repositioning some ships and rebranding

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Speaker 5: a lot of the former Costa and Piano Australia ships

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Speaker 5: as Carnival brands. So in addition to some new shipbuilding,

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Speaker 5: there's also some rebranding and brand positioning going on.

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Speaker 6: All right, Brian, we appreciate you. Thank you very much.

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Speaker 2: Brian Egger Bloomberg Intelligence in your gaming and launching analysts.

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Speaker 6: Paul, have you have you booked your cruise?

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Speaker 4: He's been talking about it.

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Speaker 7: There's potential there for the fall of twenty five. Okay,

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Speaker 7: So I'm so we're just we're still in the thinking stage.

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Speaker 2: Okay, So this will be like a good indication. If

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Speaker 2: this is kind of like spread outward.

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Speaker 4: Then Charlie's all over the I mean, he's.

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Speaker 2: The guy who does the weird things and then also cruises.

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Speaker 2: So there is that.

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Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us luck,

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Speaker 1: I have week days at ten am Eastern on Apple

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Speaker 7: Alex Dee and Paul Sweeney were live here from the

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Speaker 7: Bloomberg invest Conference in Lower Manhattan, the World Financial Center,

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Speaker 7: bringing together leaders from asset management, banking, and the private markets. Say,

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Speaker 7: the World Financial Center during the warm weather months is

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Speaker 7: a magical part of Manhattan that I don't think a

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Speaker 7: lot of people know about, right on the Hudson River.

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Speaker 7: Lots of cool yachts, lots of great restaurants, open spaces

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Speaker 7: for the kids to run around.

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Speaker 4: Yeah, it's good stuff down here.

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Speaker 7: So if you haven't been down here at this World

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Speaker 7: Financial Center Battery Park area in warm weather, it's really

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Speaker 7: really a cool part of the city.

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Speaker 6: You Know.

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Speaker 7: What I've noticed over the years is the University of Illinois

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Speaker 7: cranks out a lot of math geeks. I mean, like

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Speaker 7: really smart, mathy people. I didn't know that until I

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Speaker 7: started seeing them all over the place. Daniel Marilla was

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Speaker 7: one of them, co founder and head of quantitative Strategies

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Speaker 7: at Freestone Group. Daniel, thanks so much for joining us

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Speaker 7: live here at the Bloomberg invest Conference. Talk to us

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Speaker 7: about your firm. This is a new firm for you,

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Speaker 7: guys recently set it up. Tell us about your approach

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Speaker 7: to investing.

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Speaker 8: Yeah, I guess well, first of all, actually thank you

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Speaker 8: for having met I do own the math geek thing.

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Speaker 6: Yes, are you a math geek or did just put

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Speaker 6: that on you?

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Speaker 8: I am happy to own HD and I don't know

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Speaker 8: what I'm happy to own it.

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Speaker 9: Yeah.

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Speaker 8: For Freestom Grove co founder Todd Parker and myself, we

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Speaker 8: spent quite a long time et cetera. All And I

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Speaker 8: guess the way you would want to think about our

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Speaker 8: new firm, which we started about a year and a

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Speaker 8: half ago, is we're looking to sort of evolve the

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Speaker 8: integration of fundamental investing with quantitative process.

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Speaker 9: Does the math geek thing right?

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Speaker 8: We believe that the way in which you managed to

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Speaker 8: sustain alpha delivery from the fundamental process is to pair

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Speaker 8: it with the disciplined understanding of what's happening in the

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Speaker 8: market is via all those quantitative tools, right, and so

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Speaker 8: we've made a very signifant investment on our platform, all

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Speaker 8: the math EBITs that go with it, and Rod class

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Speaker 8: fundamental team to sort of look to evolve that process.

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Speaker 2: Right, So what is a quant strategy and then how

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Speaker 2: does that mesh with fundamentals? So that the whole point

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Speaker 2: of quants was because you didn't have to worry about

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Speaker 2: the fundamentals.

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Speaker 8: Yeah, So I think you want to think in alpha

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Speaker 8: space if you're looking to deliver alpha as opposed to

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Speaker 8: just take risk, right. I think the objective of the

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Speaker 8: quantity side and the fundamental side is essentially the same, right,

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Speaker 8: which is you're looking for a differentiated view about the

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Speaker 8: prospects of a firm. And I think the difference tends

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Speaker 8: to be that in quantitative land, you're looking to get

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Speaker 8: that differentiative view via taking advantage of a very high breath, right,

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Speaker 8: So you look for some subtle bit of data that

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Speaker 8: tells you a very little bit about many firms, right,

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Speaker 8: And so you essentially create what people would use a

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Speaker 8: factor where a little bit of information helps you make

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Speaker 8: a small bed across I don't know, a thousand stocks, right,

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Speaker 8: Russell one thousand in the US or something right, Whereas

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Speaker 8: on the fundamental side you're looking for the same thing

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Speaker 8: at differentiative view, But there you're much more focused on

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Speaker 8: the idea that a human has the ability to come

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Speaker 8: to understand a level of subtle detail about an individual

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Speaker 8: firm at real debt that you couldn't get if you

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Speaker 8: tried to do it as sort of automatically across all

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Speaker 8: the firms, right, So you focus on maybe twenty, maybe

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Speaker 8: thirty firms, and you'd spend your life literally thinking about

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Speaker 8: these firms, right, And so it's a breath versus depth thing, right.

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Speaker 8: We think that in a sense, you could put the

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Speaker 8: both of our worlds together.

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Speaker 10: Right.

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Speaker 8: There many firms out there who do each of these well.

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Speaker 8: We think that putting them together actually is sort of

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Speaker 8: the right way of actually thinking about it. There's no

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Speaker 8: reason why they can't be together other than it's hard.

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Speaker 9: You need two types of expertise.

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Speaker 8: You need the management, you need the systems and all

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Speaker 8: these things.

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Speaker 9: So it is hard to put them together.

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Speaker 8: But we believe you can, and that that leads to

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Speaker 8: sustainable alpha essentially.

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Speaker 9: Quote from both sides.

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Speaker 7: So I'm a former equity research analyst, so covering the

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Speaker 7: media space. So let's say I come in one day

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Speaker 7: and say, got to buy the walk this company here today,

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Speaker 7: but the black box says sell it.

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Speaker 4: Do what happens?

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Speaker 8: Then? I think in you would like to think that

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Speaker 8: in most cases, that situation doesn't arise, right, And the

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Speaker 8: reason why it shouldn't arise is because.

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Speaker 9: That last step that you talk about, right, which is

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Speaker 9: I want.

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Speaker 8: To buy the stock, should occur on the back of

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Speaker 8: a traceable discipline investment process.

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Speaker 10: Right.

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Speaker 8: So by the time you come to me and say

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Speaker 8: I want to buy the stock, presumably we would have

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Speaker 8: had a conversation or in the tooling, you would have

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Speaker 8: spent that whole bunch of time going to conferences, talking

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Speaker 8: to firm management, you know, building a financial model and

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Speaker 8: putting estimates out there such that your conclusion I want

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Speaker 8: to buy the stock sort of naturally flows from all

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Speaker 8: the notes that you've done, all the work that you've done.

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Speaker 8: Let's say you're producing estimates for earnings, and earnings is

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Speaker 8: next week. Let's say your estimates are higher than the street, right,

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Speaker 8: I think the street is missing something, right, And here's

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Speaker 8: all the work that backs that up.

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Speaker 9: Therefore I want to buy it.

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Speaker 10: Right.

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Speaker 8: So in that context, the quote black box is essentially

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Speaker 8: all the tooling that helps you do that, right, So

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Speaker 8: all the signals, the data that informs all the modeling

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Speaker 8: that you do. It could be everything from satellite data

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Speaker 8: that tells you how many cars were parked in front

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Speaker 8: of whatever the shops are. Essentially they work together, so

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Speaker 8: by the time that decision happens, there's no sort of

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Speaker 8: separation essentially, or there shouldn't be at least, right, So

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Speaker 8: it's not something that we actually worry very much about

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Speaker 8: because if you put them together properly in a sense,

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Speaker 8: that conclusion falls out from sort of having that traceable work,

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Speaker 8: if you will.

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Speaker 2: So you were here, you just did a panel and

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Speaker 2: the panel name was the right mix of humans and machines.

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Speaker 2: So it's going to be about using AI in this model. Correct,

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Speaker 2: How have you found a good balance? How are you

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Speaker 2: thinking about that balance?

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Speaker 8: Yeah, I guess that sounds kind of a trite thing

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Speaker 8: to say, but the answer is basically depends. It depends

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Speaker 8: on the thing.

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Speaker 9: Right.

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Speaker 8: We like to make a distinction between automation questions, right,

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Speaker 8: the technology AI now, but in the passive would have

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Speaker 8: been machine learning, neural networks, you know, data signs of

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Speaker 8: all kinds. It's evolved into being able to take on

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Speaker 8: more of this kind of unstructured data stuff on the

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Speaker 8: language side, but it's an evolution of the same, right,

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Speaker 8: And we find that for automation tasks, the more you

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Speaker 8: can push on things that are sort of not insight generation, right,

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Speaker 8: not where the idea comes from, but just automating the tasks,

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Speaker 8: it's quite effective. And we generally have been sort of

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Speaker 8: big believers that you want to invest in your ability

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Speaker 8: to do that.

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Speaker 9: On the judgment side, which.

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Speaker 8: Is, will AI helped me produce better insight like actually

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Speaker 8: a differentiated idea, we've been significantly more cautious on that end.

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Speaker 8: And the reason for it is if you think about

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Speaker 8: how AI is built out. You feeded all this augmentation

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Speaker 8: and it produces essentially a probabilistic forecast or what is

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Speaker 8: the next word in a sentence or people use the

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Speaker 8: word token right, next sentence, next individual.

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Speaker 9: Word, et cetera.

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Speaker 8: It is essentially built if in our parlance you would

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Speaker 8: call it it's built to produce the consensus. Right, you

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Speaker 8: ask it a question and the answer to that question

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Speaker 8: comes from here's all the documents about this topic, and

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Speaker 8: the average answer quote, the most likely answer is this.

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Speaker 6: So that's differentiated.

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Speaker 9: Correct.

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Speaker 8: That's a problem, and so into asset management when you're

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Speaker 8: interested in a differentiative view, AI is inherently not built.

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Speaker 9: For that, or at least not quote out of the box.

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Speaker 8: Right, So you need to think much more carefully about

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Speaker 8: how do I use it as a starting point for

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Speaker 8: thinking about summarization questions, directing and attention, detecting themes, measuring sentiment,

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Speaker 8: all very useful things that might lead you to have

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Speaker 8: a better insight. But it's not inside generation itself, right,

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Speaker 8: And so then the topic really sort of matters, right

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Speaker 8: is it writing code for the engineers? Maybe not so much,

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Speaker 8: but is it The ability to summary is a huge

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Speaker 8: amount of data. You know you were an equity analyst, right,

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Speaker 8: part of the job is you show up in the morning.

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Speaker 9: There's like a million things to read.

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Speaker 8: Right, There's all the cell side analyze, all the transcripts

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Speaker 8: from conferences, all the news about the company.

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Speaker 9: Right.

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Speaker 8: Just the act of reading is a big deal. Right,

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Speaker 8: So you can imagine how I might be helpful in

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Speaker 8: directing attention and highlighting new emerging themes.

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Speaker 9: Et cetera.

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Speaker 8: You probably still want to be reading at least some

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Speaker 8: of the key pieces of it, because you'd worry about

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Speaker 8: where the insight comes from as opposed to where the

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Speaker 8: summarization comes from.

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Speaker 9: Does that sort of make sense?

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Speaker 7: Yeah, real quickly, thirty seconds. How some of the early

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Speaker 7: returns been for your firm?

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Speaker 8: Give us we've been doing sort of about what we plan.

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Speaker 8: We did you call me a math nerd. We did

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Speaker 8: quite a We did quite a lot of simulation about

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Speaker 8: how the thing should work when we started going, right,

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Speaker 8: what sort of returns with what assumptions, and we're basically

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Speaker 8: tracking to what we would.

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Speaker 9: Have expected at this point.

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Speaker 4: What's what's your benchmark?

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Speaker 8: No benchmark? Right, we bark in neutral. We are perfectly

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Speaker 8: hedged to in the S and P. Five hundred. We

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Speaker 8: also take no factor risk, and so essentially the benchmark

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Speaker 8: is our ability to deliver uncorrelated returns to the other

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Speaker 8: benchmarks is essentially how you think?

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Speaker 6: Does AI real quick for go? Does AI stress you out?

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Speaker 6: In what way? Might AI stress you out?

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Speaker 9: It doesn't test me out?

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Speaker 8: You know, it's kind of exciting, right, The new things

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Speaker 8: are always exciting.

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Speaker 6: Huh.

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Speaker 4: That's because he's a PhD in math, right, why they

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Speaker 4: like this?

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Speaker 6: The math gee's like new nerdy thing.

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Speaker 4: Yes, got it.

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Speaker 9: We definitely liked the cool stuffy.

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Speaker 2: Thank you all right, Daniel Marillo, thank you so much.

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Speaker 2: It was a pleasure to have you stopping by. Thank

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Speaker 2: you very much. Co founder and head of Quantitative Strategies

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Speaker 2: at Freestone Grove Partners. He coined himself a math geek,

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Speaker 2: so we'll.

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Speaker 6: Just go with that.

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Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live

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00:18:30,720 --> 00:18:33,760
Speaker 1: weekdays at ten am Eastern on Apple car Play and

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00:18:33,760 --> 00:18:37,040
Speaker 1: Android Auto with the Bloomberg Business. You can also listen

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00:18:40,640 --> 00:18:43,679
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Speaker 2: From Alexi alongside Paul Sweeney, we are live from the

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Speaker 2: Bloomberg and Best Conference in Lower Manhattan, bringing together leaders

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Speaker 2: from asset management, banking, and private markets to ask questions

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Speaker 2: about what's going on. How do you think about AI,

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00:18:56,119 --> 00:18:58,359
Speaker 2: how do you think about cash? And luckily we have

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Speaker 2: one with us right now. Ed Cass's chief investment Officer

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Speaker 2: at CPP Investments, that's Canada Pension Plan Investment Board. Now, Ed,

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00:19:06,960 --> 00:19:10,440
Speaker 2: thanks for joining us. I'm asking for a friend. Say

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Speaker 2: you have some money in a higheld savings account or

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Speaker 2: in a money market fund, and you're sitting pretty right now.

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Speaker 2: You're getting paid between four and five and a half percent,

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Speaker 2: and you know that's fine, and you're young and all

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Speaker 2: so nice, and I may be somewhere in the middle

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Speaker 2: of young.

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Speaker 9: What do we do?

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Speaker 6: What does one do?

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Speaker 10: What does one do? If you're young, then you're The

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Speaker 10: way we think about it is you have a longer

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Speaker 10: investment horizon, You have a certain capacity to take risk.

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Speaker 10: When I think about investing, the first thing I think

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Speaker 10: about is what kind of risk should you be targeting

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Speaker 10: in your in your account and your overall portfolio, and

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Speaker 10: then trying to design a portfolio at that targeted level

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Speaker 10: of risk that kind of maximizes returns. So if you're young,

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Speaker 10: you probably have a pretty high risk tolerance.

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Speaker 6: So we're defining younge. I've defined it because I have

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Speaker 6: no risk tolerance.

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Speaker 2: But does cash play a valid part in how you

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Speaker 2: guys think about stuff right now?

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Speaker 6: In allocation?

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Speaker 10: Not for us, because we think we think we're really

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Speaker 10: really young. So if you think about an institutional investor,

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Speaker 10: you try and transpose that in the years where we

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Speaker 10: think like we're a teenager with a whole bunch of savings,

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Speaker 10: which kind of an oxymoron, but that's where we start.

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Speaker 10: And the way we think about risk, way we communicate

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Speaker 10: risk is we put it in what we call equity

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Speaker 10: debt risk equivalents, because that's kind of an easy way

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Speaker 10: to explain or communicate risk tolerance to someone. So we

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Speaker 10: target a portfolio that has the risk equivalence of eighty

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Speaker 10: five percent equities fifteen percent debt. So if I'm explaining

446
00:20:33,560 --> 00:20:36,399
Speaker 10: the that to my mother, she knows, hey, typical person's

447
00:20:36,400 --> 00:20:38,440
Speaker 10: probably fifty to fifty. You're a little bit aggressive, you're

448
00:20:38,440 --> 00:20:40,199
Speaker 10: sixty five thirty five. We're all the way up at

449
00:20:40,200 --> 00:20:44,040
Speaker 10: eighty five fifteen. And then we try and maximize our

450
00:20:44,040 --> 00:20:46,800
Speaker 10: return at that level. And that's where you start thinking about, hey,

451
00:20:46,800 --> 00:20:49,520
Speaker 10: what are the relative returns of stocks and bonds and

452
00:20:49,560 --> 00:20:53,239
Speaker 10: cash right now? And how do you construct a portfolio that,

453
00:20:53,280 --> 00:20:57,199
Speaker 10: as I said, at that targeted level of risk, maximizes returns.

454
00:20:57,359 --> 00:21:00,879
Speaker 7: How about alternatives, how do they fit into your portfolios?

455
00:21:00,960 --> 00:21:03,600
Speaker 7: When I think about some of these endowments, how aggressive

456
00:21:03,640 --> 00:21:07,040
Speaker 7: they've become in alternatives, I aus the Yale model for

457
00:21:07,119 --> 00:21:08,560
Speaker 7: lack of a better term, How do you guys think

458
00:21:08,600 --> 00:21:09,359
Speaker 7: about alternatives.

459
00:21:09,840 --> 00:21:12,919
Speaker 10: Well, there's a pretty big difference I think between the

460
00:21:12,960 --> 00:21:14,879
Speaker 10: objective function that some people have and the one that

461
00:21:14,920 --> 00:21:17,679
Speaker 10: we have. So I said, we're risk targeters, so we

462
00:21:17,800 --> 00:21:19,439
Speaker 10: kind of set that level of risk, and then we

463
00:21:19,440 --> 00:21:21,399
Speaker 10: try and maximize returns. A lot of people are return

464
00:21:21,480 --> 00:21:23,920
Speaker 10: targeters and they're trying to maximize returns, so they don't

465
00:21:23,920 --> 00:21:26,919
Speaker 10: mind increasing the risk profile of their portfolio to achieve

466
00:21:26,920 --> 00:21:30,280
Speaker 10: those higher returns. For us, if we're targeting risk, then

467
00:21:30,280 --> 00:21:34,359
Speaker 10: we have to say, do alternatives to private assets provide

468
00:21:34,400 --> 00:21:37,879
Speaker 10: some measure of diversification and a portfolio context that is

469
00:21:37,880 --> 00:21:39,960
Speaker 10: different than what we get in the public markets, And

470
00:21:40,000 --> 00:21:42,439
Speaker 10: we don't think so. So we think at a very

471
00:21:42,480 --> 00:21:45,280
Speaker 10: high level, if you invest in private equity that's like

472
00:21:45,440 --> 00:21:49,280
Speaker 10: levered public equity, it's not really different in terms of

473
00:21:49,280 --> 00:21:52,640
Speaker 10: the drivers of returns, So you don't get any diversification

474
00:21:52,720 --> 00:21:56,200
Speaker 10: benefit per se. A bit of a generalization, but it's true.

475
00:21:56,200 --> 00:21:58,960
Speaker 10: So then you're really into returns. And from a return

476
00:21:59,040 --> 00:22:02,119
Speaker 10: perspective is can you pick up alpha by investing in

477
00:22:02,160 --> 00:22:04,199
Speaker 10: private assets? And I think there's a lot of reasons

478
00:22:04,200 --> 00:22:07,800
Speaker 10: why you can't, especially if you have some comparative advantages,

479
00:22:08,640 --> 00:22:11,000
Speaker 10: whether you can do some direct investing yourself to lower

480
00:22:11,040 --> 00:22:15,040
Speaker 10: the feedburden, or whether you can negotiate particularly good terms

481
00:22:15,040 --> 00:22:17,160
Speaker 10: for going in a fund you can generate additional alpha,

482
00:22:17,200 --> 00:22:19,960
Speaker 10: and that kind of that, more than anything, really drives

483
00:22:19,960 --> 00:22:21,639
Speaker 10: a demand for private assets for us.

484
00:22:22,400 --> 00:22:23,080
Speaker 6: That's interesting.

485
00:22:24,359 --> 00:22:27,199
Speaker 2: What do you make of things like crypto and like

486
00:22:27,320 --> 00:22:28,920
Speaker 2: bitcoin where you can get.

487
00:22:28,720 --> 00:22:32,480
Speaker 6: That don't understand in the public market, I.

488
00:22:32,440 --> 00:22:34,440
Speaker 2: Mean, like, but you can invest in, say a micro

489
00:22:34,520 --> 00:22:38,040
Speaker 2: strategy that's basically going to just invest in crypto, I

490
00:22:38,040 --> 00:22:40,880
Speaker 2: mean in the public market, Like, is that anything interesting there?

491
00:22:42,400 --> 00:22:44,960
Speaker 10: I think there's Let me start with your think. So

492
00:22:45,000 --> 00:22:48,399
Speaker 10: crypto has an asset class, I don't understand what the

493
00:22:48,520 --> 00:22:52,159
Speaker 10: drivers are in particular, so I don't understand what, in

494
00:22:52,240 --> 00:22:54,600
Speaker 10: our parlance would say, what is it loaded on? Is

495
00:22:54,640 --> 00:22:57,040
Speaker 10: it loaded on growth, is it loaded on inflation? Is

496
00:22:57,040 --> 00:22:59,600
Speaker 10: it loaded on something else? Or is it just an

497
00:22:59,640 --> 00:23:02,080
Speaker 10: instrument that kind of goes up and down with market sentiment?

498
00:23:02,760 --> 00:23:05,040
Speaker 10: And I think the jury's still out there. I certainly

499
00:23:05,080 --> 00:23:07,680
Speaker 10: don't have enough conviction as to the drivers of bit

500
00:23:07,760 --> 00:23:10,119
Speaker 10: coin or some kind of crypto asset to build them

501
00:23:10,119 --> 00:23:13,400
Speaker 10: into a portfolio design. I do think there's spaces within

502
00:23:13,480 --> 00:23:15,560
Speaker 10: crypto where people can kind of get in the nooks

503
00:23:15,600 --> 00:23:18,440
Speaker 10: and crannies and generate additional alpha. So can you give

504
00:23:19,520 --> 00:23:21,760
Speaker 10: money or capital as someone that can take advantage of

505
00:23:21,760 --> 00:23:24,000
Speaker 10: those and generate alpha and can use that in some

506
00:23:24,080 --> 00:23:28,399
Speaker 10: kind of portfolio construct. Maybe, But so far we haven't

507
00:23:28,400 --> 00:23:30,320
Speaker 10: gone into any of those assets or any of those

508
00:23:30,359 --> 00:23:32,640
Speaker 10: funds that kind of try to take advantage of that feature.

509
00:23:32,960 --> 00:23:35,879
Speaker 4: So where do you guys see opportunities now?

510
00:23:39,000 --> 00:23:41,119
Speaker 10: Lots of different opportunities in a lot of different spaces.

511
00:23:41,160 --> 00:23:42,879
Speaker 10: I'd say the one that a lot of people are

512
00:23:42,880 --> 00:23:46,639
Speaker 10: most excited about right now is private credit markets. Certainly,

513
00:23:46,720 --> 00:23:48,840
Speaker 10: private credit is something that we've been involved with for

514
00:23:48,880 --> 00:23:50,960
Speaker 10: a very long period of time. I think you're we're

515
00:23:51,000 --> 00:23:53,320
Speaker 10: close to fifteen or twenty years in terms of it.

516
00:23:53,359 --> 00:23:55,720
Speaker 7: Really, we just started hearing about it in the news,

517
00:23:55,800 --> 00:23:57,160
Speaker 7: I guess in the last three or four years.

518
00:23:57,160 --> 00:23:57,600
Speaker 4: It seems like.

519
00:23:57,800 --> 00:23:59,320
Speaker 10: It's become a huge thing in the last three or

520
00:23:59,320 --> 00:24:02,280
Speaker 10: four years because a lot of the traditional GPS general

521
00:24:02,280 --> 00:24:04,359
Speaker 10: partners that were involved in private equity have kind of

522
00:24:04,359 --> 00:24:07,520
Speaker 10: branched out and private data as an alternative asset class

523
00:24:07,600 --> 00:24:10,960
Speaker 10: or an alternative way to gather aum. So that's really

524
00:24:11,000 --> 00:24:12,800
Speaker 10: the big impetus, And of course you've got some big

525
00:24:12,840 --> 00:24:15,520
Speaker 10: macro drivers behind it in terms of regulation and bank

526
00:24:15,600 --> 00:24:19,240
Speaker 10: balance sheets and trying to to feeze risk through putting

527
00:24:19,240 --> 00:24:22,040
Speaker 10: money into private hands as opposed to bank hands that

528
00:24:22,080 --> 00:24:25,320
Speaker 10: have been supportive of the asset class. But we identified

529
00:24:25,359 --> 00:24:26,960
Speaker 10: it as something that could be interesting, as I said

530
00:24:26,960 --> 00:24:30,280
Speaker 10: a long time ago, and started kind of building out

531
00:24:30,280 --> 00:24:34,239
Speaker 10: the internal capabilities to invest in it. So we're kind

532
00:24:34,280 --> 00:24:37,040
Speaker 10: of lucky. I think we're we're in at the start,

533
00:24:37,080 --> 00:24:40,080
Speaker 10: so we've got developed capabilities, and the rest of the

534
00:24:40,119 --> 00:24:41,560
Speaker 10: market seems to be catching.

535
00:24:41,240 --> 00:24:41,840
Speaker 4: On right now.

536
00:24:42,119 --> 00:24:43,760
Speaker 2: So if we just took a step back and look

537
00:24:43,800 --> 00:24:47,200
Speaker 2: at maybe some of the risks, how much of what

538
00:24:47,960 --> 00:24:49,680
Speaker 2: how much of the risk that you want to take

539
00:24:49,840 --> 00:24:53,440
Speaker 2: is dependent or not on like geopolitics, on fiscal policy,

540
00:24:53,880 --> 00:24:56,480
Speaker 2: on things you have a zero control over that definitely

541
00:24:56,560 --> 00:24:58,720
Speaker 2: can affect how asset prices move.

542
00:25:00,040 --> 00:25:05,080
Speaker 10: A super interesting question obviously these days. Again, if we're

543
00:25:05,640 --> 00:25:07,920
Speaker 10: an eighteen year old investing money over a seventy five

544
00:25:08,000 --> 00:25:11,480
Speaker 10: year time horizon, and we have a reasonable amount of money,

545
00:25:11,480 --> 00:25:13,920
Speaker 10: which is I think the situation we're in right now,

546
00:25:14,000 --> 00:25:16,080
Speaker 10: if we project out the size of our fund. Another

547
00:25:16,960 --> 00:25:19,640
Speaker 10: ten years, we're up to a trillion dollars. I don't

548
00:25:19,640 --> 00:25:23,159
Speaker 10: think at that level you can be as flexible or

549
00:25:23,200 --> 00:25:25,520
Speaker 10: as reactive to say, what's going into the market, I'm

550
00:25:25,520 --> 00:25:27,399
Speaker 10: going to change my asset mix, and I'm going to

551
00:25:27,440 --> 00:25:30,199
Speaker 10: respond to it dynamically and take advantage of all these shifts.

552
00:25:30,280 --> 00:25:32,600
Speaker 10: That's not the way we think about it. We think more,

553
00:25:33,200 --> 00:25:36,719
Speaker 10: how can we build something that, irrespective of what happens

554
00:25:36,720 --> 00:25:40,760
Speaker 10: in the market, irrespective of what geopolitical risks emerge, that

555
00:25:40,840 --> 00:25:44,000
Speaker 10: we can survive that outcome and continue to invest over

556
00:25:44,040 --> 00:25:47,840
Speaker 10: a seventy five year time horizon. So for us, you know,

557
00:25:47,840 --> 00:25:50,359
Speaker 10: a lot of people use the analogy to like a supertanker,

558
00:25:50,400 --> 00:25:54,480
Speaker 10: and how tough it is to turn a supertanker. I

559
00:25:54,480 --> 00:25:56,600
Speaker 10: think the analogy that we're kind of landing on more

560
00:25:56,600 --> 00:25:58,960
Speaker 10: internally these days is where, like an icebreaker, you got

561
00:25:59,000 --> 00:26:00,760
Speaker 10: to be able to drive through a whole bunch of

562
00:26:00,920 --> 00:26:03,080
Speaker 10: geopolitical risks. You have to be able to drive through

563
00:26:03,119 --> 00:26:05,199
Speaker 10: a whole bunch of regulatory risks and be able to

564
00:26:05,240 --> 00:26:07,920
Speaker 10: merge out the outside of the other side and still

565
00:26:07,960 --> 00:26:11,200
Speaker 10: be in a position to invest money and take advantage

566
00:26:11,440 --> 00:26:13,639
Speaker 10: of those longer term opportunities.

567
00:26:14,359 --> 00:26:15,480
Speaker 6: Hey, and we really appreciate it.

568
00:26:15,560 --> 00:26:19,919
Speaker 2: Those really interesting a cast Chief Investment Officer CPP investments.

569
00:26:20,000 --> 00:26:23,280
Speaker 2: It's just always those black swans, right, Like what happens

570
00:26:23,280 --> 00:26:25,320
Speaker 2: if there's another war somewhere, like no one expected, what

571
00:26:25,320 --> 00:26:26,959
Speaker 2: would happen with Ukraine and Russia?

572
00:26:27,080 --> 00:26:29,280
Speaker 6: Like no one expected what's happening in Gaza.

573
00:26:29,359 --> 00:26:31,480
Speaker 2: So it's like, how do you deal with those situations,

574
00:26:31,960 --> 00:26:34,160
Speaker 2: particularly as we head towards a presidential election. I definitely

575
00:26:34,200 --> 00:26:35,919
Speaker 2: do not end being a Chief Investment officer.

576
00:26:36,040 --> 00:26:38,040
Speaker 7: No, No, it's not all of that or to set

577
00:26:38,080 --> 00:26:40,159
Speaker 7: allocator one of those folks. Yeah, so they get you,

578
00:26:40,240 --> 00:26:41,640
Speaker 7: but you know, you have to deal with these things

579
00:26:41,640 --> 00:26:43,320
Speaker 7: and you've got to try to price into some level

580
00:26:43,359 --> 00:26:45,080
Speaker 7: of risk, and that's what those smart people do.

581
00:26:46,640 --> 00:26:50,520
Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live

582
00:26:50,600 --> 00:26:54,120
Speaker 1: weekdays at ten am Eastern on applecar Play and Android

583
00:26:54,160 --> 00:26:57,320
Speaker 1: Auto with the Bloomberg Business. You can also listen live

584
00:26:57,400 --> 00:27:00,600
Speaker 1: on Amazon Alexa from our flagship New York State Just

585
00:27:00,680 --> 00:27:03,200
Speaker 1: Say Alexa playing Bloomberg eleven.

586
00:27:05,240 --> 00:27:06,360
Speaker 6: Paul Sweeney, Alex Deal.

587
00:27:06,400 --> 00:27:09,680
Speaker 2: We are here at Bloomberg invest broadcasting to you live

588
00:27:09,760 --> 00:27:12,760
Speaker 2: in Lorier, Manhattan, we're bringing together leaders from asset management,

589
00:27:12,800 --> 00:27:15,879
Speaker 2: banking and private markets for over the next two days.

590
00:27:16,040 --> 00:27:18,320
Speaker 2: Joining us on set is Kristin Roth de Clark. She

591
00:27:18,400 --> 00:27:22,240
Speaker 2: is Global head of Technology Investment Banking over at Barclays.

592
00:27:22,760 --> 00:27:26,560
Speaker 2: Kristin what is Global head of Technology Investment Banking.

593
00:27:27,040 --> 00:27:30,560
Speaker 11: Yeah, So within Barclays, I run the team that helps

594
00:27:30,600 --> 00:27:36,439
Speaker 11: advise companies board members in terms of on the technology

595
00:27:36,480 --> 00:27:40,320
Speaker 11: side with things like fundraising in the capital markets IPOs,

596
00:27:40,560 --> 00:27:45,119
Speaker 11: debt capital markets, leverage finance or on M and a advisory.

597
00:27:45,920 --> 00:27:47,080
Speaker 4: How does private credit?

598
00:27:47,200 --> 00:27:49,800
Speaker 7: We talk a lot about private credit, private capital, I

599
00:27:49,800 --> 00:27:53,160
Speaker 7: know in your business and technology Sandhill road is we're

600
00:27:53,160 --> 00:27:56,880
Speaker 7: all the equity money talks about private equity and private

601
00:27:57,200 --> 00:27:58,879
Speaker 7: credit and technology these days.

602
00:27:59,160 --> 00:27:59,400
Speaker 6: Yeah.

603
00:27:59,440 --> 00:28:01,760
Speaker 11: So on the then equity side, and if you look

604
00:28:01,800 --> 00:28:05,560
Speaker 11: at the growth stage investing that's happening, you know, kind

605
00:28:05,560 --> 00:28:09,080
Speaker 11: of late stage growth is where a lot of funds

606
00:28:09,119 --> 00:28:13,800
Speaker 11: are focused kind of the pre IPO rounds. The earlier

607
00:28:13,880 --> 00:28:19,080
Speaker 11: stage stuff is more some of the AI companies that

608
00:28:19,119 --> 00:28:21,920
Speaker 11: are coming out. There's like the venture investing that's happening there,

609
00:28:21,920 --> 00:28:23,919
Speaker 11: but it's a little bit more of a portfolio approach

610
00:28:23,960 --> 00:28:26,399
Speaker 11: because it's too early to kind of tell who the

611
00:28:26,440 --> 00:28:28,720
Speaker 11: winners are going to be. As you get to the

612
00:28:28,760 --> 00:28:32,760
Speaker 11: growth stage investing, there's more focus on where the likely

613
00:28:32,800 --> 00:28:35,600
Speaker 11: exits could happen. I think there's been a meaningful shift

614
00:28:36,040 --> 00:28:39,120
Speaker 11: in focus on unit economics companies that have a path

615
00:28:39,120 --> 00:28:42,800
Speaker 11: of profitability or are profitable, because those are the companies

616
00:28:42,840 --> 00:28:45,320
Speaker 11: that have the most likely exit into the IPO market

617
00:28:45,560 --> 00:28:49,040
Speaker 11: or joining a strategic For example, how.

618
00:28:48,920 --> 00:28:52,880
Speaker 2: Is technological innovation going in a world where rates are higher?

619
00:28:53,200 --> 00:28:53,400
Speaker 6: Right?

620
00:28:54,240 --> 00:28:57,440
Speaker 2: Policy in the US is questionable of where it's going

621
00:28:57,480 --> 00:28:59,680
Speaker 2: to be in November. Where I'm thinking of energy right,

622
00:28:59,720 --> 00:29:01,520
Speaker 2: Like a lot of the cool new stuff are coming

623
00:29:01,520 --> 00:29:04,000
Speaker 2: out of these startups that you need in order to

624
00:29:04,000 --> 00:29:06,400
Speaker 2: sort of the energy transition, but that's not as popular

625
00:29:06,440 --> 00:29:07,920
Speaker 2: with certain folks in DC.

626
00:29:08,800 --> 00:29:10,680
Speaker 6: Where is the cool stuff happening?

627
00:29:12,360 --> 00:29:14,680
Speaker 11: I would say a lot of it still is in software.

628
00:29:15,000 --> 00:29:18,640
Speaker 11: The biggest area probably that's had the most investment dollars

629
00:29:18,640 --> 00:29:20,960
Speaker 11: recently and more that's on the public side is on

630
00:29:21,000 --> 00:29:23,560
Speaker 11: the chips in the because it's sort of an easy

631
00:29:23,600 --> 00:29:29,600
Speaker 11: way for investors to get behind the boom in AI

632
00:29:29,840 --> 00:29:32,480
Speaker 11: without picking which software winners are going you know which

633
00:29:32,520 --> 00:29:34,880
Speaker 11: software companies are going to be the winners. The other

634
00:29:35,000 --> 00:29:37,320
Speaker 11: area within tech that we're seeing a lot of investment

635
00:29:37,400 --> 00:29:41,640
Speaker 11: is on payments fintech type businesses that that continues to

636
00:29:41,640 --> 00:29:42,440
Speaker 11: be very popular.

637
00:29:43,080 --> 00:29:46,800
Speaker 7: Where is the IPO market these days for technology companies.

638
00:29:47,440 --> 00:29:48,719
Speaker 4: Yeah, so I'd like to see more.

639
00:29:48,800 --> 00:29:51,360
Speaker 7: Quite frankly, I would tear back on my compital markets days.

640
00:29:51,680 --> 00:29:53,040
Speaker 7: I can get a lot more deals done. I don't

641
00:29:53,040 --> 00:29:53,800
Speaker 7: know what you guys are doing.

642
00:29:54,080 --> 00:29:55,280
Speaker 4: So what's happening out there?

643
00:29:55,840 --> 00:29:57,480
Speaker 11: Well, A couple of things happened over the last couple

644
00:29:57,480 --> 00:30:01,080
Speaker 11: of years. There have been there been two things. One

645
00:30:01,320 --> 00:30:06,400
Speaker 11: a meaningful valuation reset where we had you know, companies

646
00:30:06,400 --> 00:30:09,440
Speaker 11: coming public at two x, three x the you know,

647
00:30:09,600 --> 00:30:12,040
Speaker 11: historical norms for on a multiple basis.

648
00:30:12,440 --> 00:30:14,160
Speaker 6: There's that resets happened.

649
00:30:14,200 --> 00:30:16,400
Speaker 11: The other thing is there's been a much more meaningful

650
00:30:16,440 --> 00:30:20,440
Speaker 11: focus on profitability, and so a lot of the private

651
00:30:20,440 --> 00:30:23,240
Speaker 11: companies that were poised to hit the public market, say

652
00:30:23,360 --> 00:30:27,800
Speaker 11: in twenty twenty three, twenty twenty four, have now had

653
00:30:27,800 --> 00:30:30,400
Speaker 11: to come back and figure out, you know, how to

654
00:30:30,480 --> 00:30:33,800
Speaker 11: accelerate their path. The profitability also get to bigger scale.

655
00:30:33,880 --> 00:30:35,840
Speaker 11: I mean, one of the issues that we've seen from

656
00:30:35,880 --> 00:30:39,120
Speaker 11: the class of twenty twenty and twenty twenty one IPOs.

657
00:30:39,440 --> 00:30:43,440
Speaker 11: The ones that have massively underperformed have been the smaller scale,

658
00:30:43,520 --> 00:30:46,720
Speaker 11: less liquid names, and so there's a focus on scale,

659
00:30:47,400 --> 00:30:51,320
Speaker 11: profitability and growth and finding that balance. And then we're

660
00:30:51,320 --> 00:30:54,000
Speaker 11: also at this very moment in a bit of a

661
00:30:54,040 --> 00:30:56,920
Speaker 11: pocket of uncertainty leading into the election, leading into a

662
00:30:57,000 --> 00:31:01,000
Speaker 11: seeing where where and when rates start coming down. So

663
00:31:01,560 --> 00:31:04,000
Speaker 11: for that reason, we just haven't We've seen a handful

664
00:31:04,040 --> 00:31:06,320
Speaker 11: of tech IPOs, but not a significant number.

665
00:31:06,400 --> 00:31:08,680
Speaker 2: We clearly see a ton of public money going into

666
00:31:08,720 --> 00:31:11,800
Speaker 2: like Nvidia and Peers and derivative plays. Right, is it

667
00:31:11,840 --> 00:31:14,520
Speaker 2: the same kind in private capital like you were mentioning,

668
00:31:14,560 --> 00:31:16,600
Speaker 2: it's still in software and the chips, right, Like that's

669
00:31:16,640 --> 00:31:18,959
Speaker 2: where the money is flowing. Is it the same kind

670
00:31:19,080 --> 00:31:23,320
Speaker 2: of ferocity when it comes to money blowing.

671
00:31:23,040 --> 00:31:27,400
Speaker 11: In les less in companies that haven't reached a significant scale.

672
00:31:27,440 --> 00:31:30,240
Speaker 11: And part of that is because the obvious exit is

673
00:31:30,280 --> 00:31:32,840
Speaker 11: an IPO or a sale, And we haven't seen a

674
00:31:32,840 --> 00:31:36,520
Speaker 11: lot of strategic buying yet of late earlier stage AI

675
00:31:36,640 --> 00:31:41,200
Speaker 11: type businesses, some aqua hiers like just buying you know, entrepreneurs, engineers,

676
00:31:41,480 --> 00:31:44,760
Speaker 11: but not necessarily the kind of larger M and A.

677
00:31:45,400 --> 00:31:48,440
Speaker 11: And so once you start feeling confident. Once investors can

678
00:31:48,440 --> 00:31:50,800
Speaker 11: feel confident in the private world that they have a

679
00:31:50,880 --> 00:31:53,520
Speaker 11: path to exit, whether it be IPO or sale, then

680
00:31:53,560 --> 00:31:57,640
Speaker 11: you get more courage to invest in the growth stage companies.

681
00:31:57,880 --> 00:32:00,680
Speaker 7: How frustrated are your private equity and your venture capital

682
00:32:00,720 --> 00:32:04,400
Speaker 7: clients in the in the fact that the IPI market

683
00:32:04,440 --> 00:32:07,680
Speaker 7: is not robust and maybe exits are not as fundamental,

684
00:32:07,680 --> 00:32:09,400
Speaker 7: So they're holding onto these things much longer than they

685
00:32:09,400 --> 00:32:10,760
Speaker 7: would typically like.

686
00:32:11,240 --> 00:32:12,200
Speaker 4: What are those conversations.

687
00:32:12,440 --> 00:32:14,840
Speaker 6: Yeah, look, there's a huge pent up.

688
00:32:15,000 --> 00:32:17,720
Speaker 11: You know, number of companies that have stayed within venture

689
00:32:17,840 --> 00:32:21,360
Speaker 11: or private equity for much longer than they'd anticipated. I

690
00:32:21,360 --> 00:32:24,920
Speaker 11: think there's a difference though that the venture backed businesses,

691
00:32:24,960 --> 00:32:28,120
Speaker 11: some of them haven't been able to figure out the

692
00:32:28,160 --> 00:32:30,840
Speaker 11: path to profitability and actually get to a place where

693
00:32:30,880 --> 00:32:33,320
Speaker 11: they could easily go public. So it's more about finding

694
00:32:33,320 --> 00:32:36,320
Speaker 11: a strategic home on the private equity side. A lot

695
00:32:36,320 --> 00:32:39,160
Speaker 11: of these companies that were LBOs or have gone typically

696
00:32:39,200 --> 00:32:42,360
Speaker 11: sponsor to sponsor sales have now gotten so big inside

697
00:32:42,400 --> 00:32:43,760
Speaker 11: private equity that.

698
00:32:43,760 --> 00:32:45,720
Speaker 6: Really there are two options.

699
00:32:45,720 --> 00:32:48,960
Speaker 11: It's either sell to a very large strategic or or

700
00:32:49,080 --> 00:32:51,960
Speaker 11: take the company's public And most of them have financial

701
00:32:51,960 --> 00:32:53,840
Speaker 11: profiles that it would actually look good in the public

702
00:32:53,880 --> 00:32:57,360
Speaker 11: market because they're profitable and have you know, maybe modest growth.

703
00:32:57,560 --> 00:32:58,520
Speaker 6: So if we get.

704
00:32:58,360 --> 00:33:00,560
Speaker 2: Clear, once we get clearity on the US election and

705
00:33:00,600 --> 00:33:03,160
Speaker 2: we get clarity on FED rate cuts, what does that

706
00:33:03,280 --> 00:33:04,320
Speaker 2: IPO market look like?

707
00:33:04,400 --> 00:33:07,400
Speaker 6: Is it like a flood like? How how do you

708
00:33:07,440 --> 00:33:08,080
Speaker 6: think about that?

709
00:33:08,440 --> 00:33:11,880
Speaker 11: I think that there are I think we'll have a

710
00:33:11,920 --> 00:33:14,280
Speaker 11: lot more companies that are willing to move forward with

711
00:33:14,280 --> 00:33:16,440
Speaker 11: an IPO once we have that behind us, because there's

712
00:33:16,440 --> 00:33:20,200
Speaker 11: not there aren't a lot of other alternatives at that point.

713
00:33:20,240 --> 00:33:23,280
Speaker 11: It's like either you sell to a strategic or you

714
00:33:23,320 --> 00:33:25,600
Speaker 11: take the company public and they've gotten to scale where

715
00:33:25,680 --> 00:33:29,640
Speaker 11: actually the visibility of being public companies helpful sometimes with

716
00:33:29,680 --> 00:33:33,200
Speaker 11: their customers, it's help helpful with employees. It helps provide

717
00:33:33,200 --> 00:33:36,120
Speaker 11: you know, liquidity for companies that have been private for eight.

718
00:33:35,960 --> 00:33:38,200
Speaker 6: Ten millars floodpo, I hope.

719
00:33:38,200 --> 00:33:41,920
Speaker 7: So, you know, are we going to have an AI

720
00:33:42,160 --> 00:33:46,880
Speaker 7: IPO aha moment? Like Google was for search, Facebook was

721
00:33:47,000 --> 00:33:50,760
Speaker 7: for social? Are there AI specific companies that are going

722
00:33:50,800 --> 00:33:52,920
Speaker 7: to come out and boom that's going to be the

723
00:33:52,960 --> 00:33:54,120
Speaker 7: IPO event of the year.

724
00:33:54,440 --> 00:33:57,200
Speaker 11: Well, the ones that have so far have been related

725
00:33:57,280 --> 00:34:00,520
Speaker 11: chips related. Right in the last two years. I would

726
00:34:00,560 --> 00:34:02,920
Speaker 11: say that there will be at some point, but it's

727
00:34:02,960 --> 00:34:04,720
Speaker 11: just too early to tell who those winners are going

728
00:34:04,800 --> 00:34:04,960
Speaker 11: to be.

729
00:34:05,480 --> 00:34:08,680
Speaker 2: You talk about people in your world talk about digital infrastructure,

730
00:34:09,000 --> 00:34:11,560
Speaker 2: like what is that? What is a digital infrastructure and

731
00:34:11,600 --> 00:34:13,879
Speaker 2: how does that change and progress?

732
00:34:14,200 --> 00:34:18,000
Speaker 11: Yeah, so there's a massive transformation happening within a number

733
00:34:18,040 --> 00:34:21,160
Speaker 11: of industries not that's being enabled by tech, and that's

734
00:34:21,200 --> 00:34:25,560
Speaker 11: the transition from things like on premise to cloud based

735
00:34:27,000 --> 00:34:30,560
Speaker 11: technologies and just changing the way that we've done things

736
00:34:30,560 --> 00:34:32,920
Speaker 11: that you know is from historically to moving things from

737
00:34:32,920 --> 00:34:36,880
Speaker 11: more to tech enabled. That's true in like healthcare sector, insurance,

738
00:34:36,920 --> 00:34:39,400
Speaker 11: financial sectors, you know, banks for example.

739
00:34:39,960 --> 00:34:43,000
Speaker 7: So for you guys at Barclays in your franchise these days,

740
00:34:43,040 --> 00:34:45,239
Speaker 7: where's the most activity here?

741
00:34:45,239 --> 00:34:47,960
Speaker 4: Where do they where? What do you guys really focus

742
00:34:48,040 --> 00:34:48,439
Speaker 4: on here?

743
00:34:49,080 --> 00:34:52,200
Speaker 11: I think back to the question around private equity pressure.

744
00:34:52,239 --> 00:34:55,480
Speaker 11: I think there's a lot of sponsor backed assets that

745
00:34:55,560 --> 00:34:58,520
Speaker 11: are either you know, the private equity firms are under

746
00:34:58,520 --> 00:35:01,399
Speaker 11: pressure to return capital to LP and so there will

747
00:35:01,440 --> 00:35:03,560
Speaker 11: be more sales. I think there will be minority stake

748
00:35:03,600 --> 00:35:07,480
Speaker 11: sales as well to get you know, some liquidity back,

749
00:35:07,520 --> 00:35:13,520
Speaker 11: but also to provide a mark and then I think

750
00:35:13,560 --> 00:35:16,600
Speaker 11: after that comes the kind of more large scale, large cat,

751
00:35:16,760 --> 00:35:22,200
Speaker 11: larger cap larger scaled businesses that have profitability and so growth.

752
00:35:22,600 --> 00:35:24,799
Speaker 2: Paul's really into the msment banking part, and I'm into

753
00:35:24,800 --> 00:35:26,520
Speaker 2: the tech part. Like he wants to be like, Okay,

754
00:35:26,560 --> 00:35:28,560
Speaker 2: when did things open? What are your what are sponsors

755
00:35:28,560 --> 00:35:31,120
Speaker 2: talking about? And I'm like, what's the disruptive cool technology?

756
00:35:31,480 --> 00:35:34,439
Speaker 2: How does digital infrastructure wind up changing? Like what what's

757
00:35:34,480 --> 00:35:38,080
Speaker 2: the cool thing that we totally don't know about? Oh god,

758
00:35:38,280 --> 00:35:40,640
Speaker 2: we mean Paul, yeah a lot?

759
00:35:40,360 --> 00:35:43,360
Speaker 11: So yeah, well, right now, I think the focus for

760
00:35:43,440 --> 00:35:47,080
Speaker 11: most companies is how do we use AI to generate efficiency?

761
00:35:47,200 --> 00:35:49,280
Speaker 11: That's the first part, right, and that's an easy sale.

762
00:35:49,360 --> 00:35:50,840
Speaker 2: That's like how do I like go through my email

763
00:35:50,840 --> 00:35:51,880
Speaker 2: more efficiently that yeah thing?

764
00:35:51,960 --> 00:35:54,720
Speaker 11: Yeah well, or how do yeah, and how do you

765
00:35:54,760 --> 00:35:57,799
Speaker 11: cut costs with call centers or fraud protection or things

766
00:35:57,840 --> 00:35:59,759
Speaker 11: like this that you're maybe doing in a way that

767
00:35:59,800 --> 00:36:03,640
Speaker 11: has it requires more people or you know, including together

768
00:36:03,680 --> 00:36:06,680
Speaker 11: different technologies. Here's a way we can There are solutions

769
00:36:06,719 --> 00:36:09,200
Speaker 11: now that can make that easier, and that's going to

770
00:36:09,280 --> 00:36:14,960
Speaker 11: create profitability, you know, more profitability, and so that's the

771
00:36:15,000 --> 00:36:18,280
Speaker 11: first step. I think the next question is which AI

772
00:36:18,760 --> 00:36:23,000
Speaker 11: solutions are going to enhance innovation, And that's really where

773
00:36:23,000 --> 00:36:26,560
Speaker 11: it starts to get interesting, and that's that's probably where

774
00:36:26,640 --> 00:36:30,359
Speaker 11: you see the biggest threat to the large cap tech

775
00:36:30,400 --> 00:36:33,319
Speaker 11: companies is the new incumbents or the new entrants that

776
00:36:33,480 --> 00:36:37,880
Speaker 11: have some sort of they can scale much quicker because

777
00:36:37,880 --> 00:36:41,400
Speaker 11: of the technology that they have around innovation fintech.

778
00:36:41,440 --> 00:36:42,880
Speaker 4: Where are we in that evolution?

779
00:36:43,000 --> 00:36:46,520
Speaker 7: I think during a pandemic, everybody I do a lot

780
00:36:46,560 --> 00:36:50,800
Speaker 7: more of my financial services just on the phone, which.

781
00:36:50,560 --> 00:36:52,879
Speaker 2: Which which was a big moment for Post. So let's

782
00:36:53,000 --> 00:36:54,879
Speaker 2: be very clear on that point. He's gray cash.

783
00:36:54,920 --> 00:36:57,120
Speaker 4: But still exactly where are we on that kind of

784
00:36:57,120 --> 00:37:00,600
Speaker 4: that pendulum? Where do you see that? Look?

785
00:37:00,640 --> 00:37:02,880
Speaker 11: I think there was a period where I mean I

786
00:37:02,800 --> 00:37:05,200
Speaker 11: I remember spending time in Asia and they you know,

787
00:37:05,480 --> 00:37:07,719
Speaker 11: I was in Hangzhou where you could not use a

788
00:37:07,760 --> 00:37:09,880
Speaker 11: credit card. It went straight to mobile, right, it went

789
00:37:09,880 --> 00:37:14,239
Speaker 11: from cash to mobile. Here we've gone, you know, we

790
00:37:14,280 --> 00:37:16,920
Speaker 11: had credit cards. We're now very much in the mobile world.

791
00:37:17,200 --> 00:37:19,440
Speaker 11: The next thing, I think is going to be biometrics,

792
00:37:19,600 --> 00:37:22,120
Speaker 11: and that's a trend that's already happening in Asia that

793
00:37:22,200 --> 00:37:23,640
Speaker 11: I think will make its way the rest of the

794
00:37:23,640 --> 00:37:24,720
Speaker 11: world over time.

795
00:37:24,640 --> 00:37:25,960
Speaker 6: Great dumb question. What does that mean?

796
00:37:26,239 --> 00:37:30,240
Speaker 11: Like so being able to pay with your eyeballs for example,

797
00:37:30,360 --> 00:37:32,040
Speaker 11: or some sort of you know, bigger prints.

798
00:37:32,280 --> 00:37:34,440
Speaker 7: So when Europeans come over here, they're like so amazed

799
00:37:34,440 --> 00:37:36,040
Speaker 7: that when you restaur on your hand your card to

800
00:37:36,160 --> 00:37:39,279
Speaker 7: the way to walk the West End. Yeah, come back

801
00:37:39,320 --> 00:37:40,920
Speaker 7: here because you know the rest of the world. They

802
00:37:41,000 --> 00:37:43,080
Speaker 7: just the carries around a little thing that you.

803
00:37:43,400 --> 00:37:45,120
Speaker 6: Or even like the tapping thing, like I mean.

804
00:37:45,360 --> 00:37:46,960
Speaker 4: We were two three years behind the tapping.

805
00:37:47,000 --> 00:37:49,080
Speaker 2: I mean even that, I don't think my credit card

806
00:37:49,080 --> 00:37:50,640
Speaker 2: does the tapping thing, Like I have to do my

807
00:37:50,680 --> 00:37:52,719
Speaker 2: phone do the tapping thing, but the credit card doesn't

808
00:37:52,760 --> 00:37:53,000
Speaker 2: do the tap.

809
00:37:53,320 --> 00:37:54,319
Speaker 4: Credit card taps it does.

810
00:37:54,360 --> 00:37:56,000
Speaker 6: Are you sure? Okay?

811
00:37:56,880 --> 00:37:57,640
Speaker 4: We got there?

812
00:37:58,600 --> 00:38:01,120
Speaker 2: My credit card tap. The questions he is, the pressing

813
00:38:01,200 --> 00:38:03,800
Speaker 2: questions we have. She's like, I don't know, all right, Christen,

814
00:38:03,800 --> 00:38:06,640
Speaker 2: thanks a lot. We appreciate thanks for stopping by Anton Clark.

815
00:38:06,680 --> 00:38:09,839
Speaker 2: She is a Global head of Technology Investment Banking over

816
00:38:09,920 --> 00:38:12,319
Speaker 2: at Barclay. Is talking about all the innovations that are

817
00:38:12,400 --> 00:38:14,040
Speaker 2: upcoming and then what do you do if you're a

818
00:38:14,080 --> 00:38:16,000
Speaker 2: company and you have cash flow and you can IPO

819
00:38:16,080 --> 00:38:18,399
Speaker 2: and sort of the like treading water until you can

820
00:38:18,480 --> 00:38:19,839
Speaker 2: in the market's really open up, and.

821
00:38:19,800 --> 00:38:22,560
Speaker 7: The companies are so much better now than like people

822
00:38:22,600 --> 00:38:24,759
Speaker 7: make that. Are we close to the nineteen ninety nine

823
00:38:24,800 --> 00:38:27,719
Speaker 7: and haven't been in that marketplace? Answers definitely know because

824
00:38:27,719 --> 00:38:30,319
Speaker 7: these companies are bigger, profitable, they have free cash flow.

825
00:38:30,520 --> 00:38:32,640
Speaker 7: The companies I were taking public, it was a thought

826
00:38:32,719 --> 00:38:34,319
Speaker 7: out there in the world. It was like pets and

827
00:38:34,400 --> 00:38:36,000
Speaker 7: we put a thirty yeah, and we put a thirty

828
00:38:36,040 --> 00:38:37,879
Speaker 7: multiple on it, and we're done. That's all we needed.

829
00:38:38,200 --> 00:38:39,759
Speaker 7: It's much harder for these people. They actually have to

830
00:38:39,800 --> 00:38:41,240
Speaker 7: have real businesses and real companies.

831
00:38:41,280 --> 00:38:41,759
Speaker 6: It's a good thing.

832
00:38:41,800 --> 00:38:42,279
Speaker 4: It's a good thing.

833
00:38:42,320 --> 00:38:43,160
Speaker 6: Ye, it's a good thing.

834
00:38:43,440 --> 00:38:47,960
Speaker 1: This is the Bloomberg Intelligence Podcast, available on Apples, Spotify,

835
00:38:48,160 --> 00:38:51,080
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836
00:38:51,160 --> 00:38:54,760
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837
00:38:54,880 --> 00:38:58,239
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838
00:38:58,400 --> 00:39:01,400
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839
00:39:01,600 --> 00:39:03,400
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840
00:39:06,960 --> 00:39:07,320
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