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

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Speaker 2: This is Master's in Business with Barry rid Hoolds on

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Speaker 2: Bloomberg Radio.

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Speaker 1: This week on the podcast, I have another extra spectral guest.

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Speaker 1: I met Vince Aida at a panel of emerging managers

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Speaker 1: earlier this year, and I thought the work he did

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Speaker 1: and his background was really so unusual and so fascinating,

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Speaker 1: he would make for a great guest, and he absolutely did.

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Speaker 1: He comes out of a graduate background at Columbia stunning

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Speaker 1: genomics and biotech and decides I don't want to be

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Speaker 1: a research scientist the rest of my life. I want

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Speaker 1: to see how I can apply This ends up moving

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Speaker 1: to the Byside, eventually goes to Millennium and then Citadel

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Speaker 1: Capital before launching his own firm, Cutter Capital. You'll be

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Speaker 1: amused and you hear what that name is based on.

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Speaker 1: Really interesting. They run a market neutral, factor neutral book

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Speaker 1: of biotech of US and European stocks. Just a fascinating

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Speaker 1: process and a fascinating way to think about the massive

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Speaker 1: changes that are taking place in a space that not

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Speaker 1: only has the potential for explosive growth, but the ability

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Speaker 1: to change your life, the quality of life, and the

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Speaker 1: length of your life. Really amazing, fascinating stuff. I found

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Speaker 1: this conversation to be fascinating, and I think you will

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Speaker 1: also with no further ado my discussion with Cutter Capitals.

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Speaker 2: Vince Aida Barry, thanks a lot for the invitation. Then,

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Speaker 2: well looking forward.

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Speaker 1: To yees same here. We had you on a panel

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Speaker 1: back in June of Emerging Managers and I thought what

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Speaker 1: you did is so fascinating and you have such an

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Speaker 1: interesting background. Let's start with that. You're a post doctoral

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Speaker 1: fellowship candidate at Columbia in the early two thousands at

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Speaker 1: the Department of Genetics and Development. What was the career

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Speaker 1: plan were you? Were you going to be a doctor?

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Speaker 2: I had thought originally that I was going to be

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Speaker 2: an academic scientist. I did my PhD work at the

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Speaker 2: Columbia Genome Center at a time where we had one

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Speaker 2: of the chromosomes in the genome project, and so we

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Speaker 2: were involved in that first push to sequence the genome,

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Speaker 2: and I had thought that, you know, academics is what

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Speaker 2: going to carry me forward. My individual work was related

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Speaker 2: to the study of actually evolution on a molecular level.

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Speaker 2: There's a whole rabbit hole that you could go down,

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Speaker 2: you know, kind of chasing that but suffice to say

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Speaker 2: that I think that Darwin in his explanation of evolution

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Speaker 2: does not necessarily fully describe the phenomenon that you see

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Speaker 2: on a molecular genetic level. And we were much more

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Speaker 2: in the camp of I was much more in the

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Speaker 2: camp of following Moto Kimura's neutral theory of evolution, which

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Speaker 2: is a real let me go down yourself, so let.

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Speaker 1: Me make sure I'm following you. In broad strokes, adaptability, survival,

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Speaker 1: the fittest more or less right on a species by

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Speaker 1: species level. But when you get down to mitochondria and

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Speaker 1: what power sells and everything at that level, are you

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Speaker 1: going even further?

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Speaker 2: We're saying, you know, the idea is that Darwin was

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Speaker 2: right on a more obvious phenotypic level for some of

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Speaker 2: the things that are very easy to track. But if

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Speaker 2: you're talking about the actual fuel of evolution, what drive

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Speaker 2: it on a molecular genetic level, it's much more driven

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Speaker 2: by mutations that really don't have any impact on fitness

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Speaker 2: and random genetic drift and so, and there's a ton.

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Speaker 1: Of that out there. I mean, you think about all

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Speaker 1: the little things. We're still trying to figure out what

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Speaker 1: the appendix does at a cellular or even small moleculecular

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Speaker 1: level that's not really fascinating.

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Speaker 2: So that was, you know, an initial career path that

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Speaker 2: I was, you know, kind of really intrigued to study. Obviously,

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Speaker 2: I'm still excited to talk about that type of stuff,

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Speaker 2: but I realized at a certain point that science was

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Speaker 2: not going to be the path for me. It involved

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Speaker 2: further and further specialization and doing work in centers of

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Speaker 2: excellence that are not necessarily geographically where do you'd want

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Speaker 2: to spend your life? And so I wound up choosing

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Speaker 2: New York. And so then the thought was, if I

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Speaker 2: wasn't going to be academic, where could I take the

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Speaker 2: knowledge base that I had developed and find a passion

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Speaker 2: to apply it in a different direction.

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Speaker 1: So theater, media, real estate is a lot of things, sure, absolutely,

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Speaker 1: but you know, you said, finance.

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Speaker 2: I came to the conclusion that the knowledge base I

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Speaker 2: had that finance provided an opportunity for me. For me personally,

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Speaker 2: I am a lifelong learner, and one of the things

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Speaker 2: in finance that's fascinating to me me going even till today,

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Speaker 2: is that you never stop learning, You never stop trying

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Speaker 2: to become more of an expert at what you're doing,

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Speaker 2: but just more experience learning from the world, and it's

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Speaker 2: a constant, constant process, and that's fascinating to me.

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Speaker 1: I'm totally with you. Autodidactism is wildly underrated. But walk

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Speaker 1: me through this. So healthcare is your focus your entire career.

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Speaker 1: Describe what that transition is like, going from Hey, I'm

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Speaker 1: literally in a Columbia grad school fellowship to I want

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Speaker 1: to move into the world of finance. How does that happen?

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Speaker 1: I did the same thing. I was practicing attorney, miserable

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Speaker 1: and said, let's see if I can transition to something else.

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Speaker 1: So I'm always intrigued to hear other people's stories of.

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Speaker 2: Sure, absolutely for me, I thought the knowledge base that

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Speaker 2: I developed, this science itself was evolving so rapidly. You know,

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Speaker 2: the unlocking of the sequencing of the genome was going

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Speaker 2: to provide this, you know, the thought was going to

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Speaker 2: be a new golden era of drug development. And it

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Speaker 2: might have taken twenty years that come. But the genetic

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Speaker 2: medicines that are being developed now, and the whole approach

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Speaker 2: to medicine today is much more based on what I

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Speaker 2: describe as biology first, as opposed to chemistry. First, where

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Speaker 2: previous generations of drugs were really all oral pills that

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Speaker 2: were chemical compounds that by serendipity they found out a

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Speaker 2: way it might impact a disease. Now it's much more

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Speaker 2: biology driven. And so at that time, with the background

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Speaker 2: I had, I thought, you know, the world of finance

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Speaker 2: might appreciate the domain expertise I had coming out of

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Speaker 2: coming out of a scientific background, and I could learn

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Speaker 2: the finance side of it. So I went straight to

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Speaker 2: the buyside at that point.

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Speaker 1: So go for a doctor in economics, who'd you first

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Speaker 1: share your expertise with on the buyside.

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Speaker 2: Well, like in many things in life, there's serendipity to

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Speaker 2: finding opportunities. And one of the professors at Columbia who

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Speaker 2: was a mentor of mine and I had worked with

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Speaker 2: Izzy Edelman. His son, Joe Edelman, founded Perceptive, which is

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Speaker 2: a firm that has been tremendously successful as healthcare investors.

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Speaker 2: And so when I was trying to network and find

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Speaker 2: people in the world of finance, I spoke to Izzy

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Speaker 2: about it and he said, wy, don't you talk to

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Speaker 2: my son Joe. And then conversation with Joe, which he

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Speaker 2: was kind enough to give me a portion of his

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Speaker 2: time opened the door to other people to talk to

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Speaker 2: you in roads into the industry and then just knocking

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Speaker 2: on doors found an opportunity for me.

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Speaker 1: Huh, that's really interesting. So what was your first gig

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Speaker 1: in the world of investing.

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Speaker 2: My first gig was at Paramount Capital Asset Management. Paramount

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Speaker 2: was a small boutique biotech firm that had investments in

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Speaker 2: both private equity side and public They were crossover investors

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Speaker 2: in the early days of doing that.

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Speaker 1: Is that that's not Deb Solomon.

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Speaker 2: That was lind Lindsay Rosenwald was the founder there and actually, interestingly,

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Speaker 2: Joe was director of research there for a number of

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Speaker 2: years before I moved on to start present.

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Speaker 1: So you begin as what a junior animal.

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Speaker 2: So I came in as a junior analyst. My role

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Speaker 2: was just to like dig through business plans, dig through

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Speaker 2: drug development and try to handicap what would work, but

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Speaker 2: equally as interestingly, what's going to fail. And I got

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Speaker 2: a lot of reps at seeing different attempts at drug development,

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Speaker 2: rinse and repeat over a number of years to try

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Speaker 2: to get those initial you know, kind of training on

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Speaker 2: how the drug development process kind of really works and

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Speaker 2: how that interacts with the equity markets.

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Speaker 1: Huh really really interesting. So that's your first gig. How

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Speaker 1: long did you stay there?

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Speaker 2: I stayed there for about three years. I moved on

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Speaker 2: to another firm, Kilkenny Capital, which was a Chicago based

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Speaker 2: firm also focused mainly in biotech, but a smaller cap

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Speaker 2: healthcare investor, and and that was the next three years

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Speaker 2: of my career. From there, I really started to get

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Speaker 2: my first inkling of process and thinking about the drug

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Speaker 2: development world and a probabilistic lens. I think previously for commonly,

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Speaker 2: you know, you go about the investment world looking for

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Speaker 2: people who are tremendously successful because they find ideas and

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Speaker 2: they have maximum conviction and those ideas play out and

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Speaker 2: they look like heroes, which is terrific in those individual

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Speaker 2: success cases, but is littered with failure of people who

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Speaker 2: fail to find that opportu.

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Speaker 1: You're a little survivorship bias in what you actually say.

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Speaker 2: Absolutely so, I thought early on in my career and

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Speaker 2: it's been something that has carried through in my personal

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Speaker 2: style to really kind of look at the world under

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Speaker 2: a much more probabilistic lens, where you're just asking yourself

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Speaker 2: where their situations, where the herd is thinking one thing.

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Speaker 2: Consensus has one level of thought, but you've got to

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Speaker 2: good foundation to believe why. Reality has a much bigger

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Speaker 2: percentage chance of not playing out that way.

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Speaker 1: So let's stay with that. I love the idea of

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Speaker 1: probabilistic thinking. My prior bias with biotech, especially smaller biotech,

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Speaker 1: is it's not so much probabilistic as binary, which I

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Speaker 1: guess technically as probability, but it seems either the drug

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Speaker 1: works or it doesn't, the drug has side effects or

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Speaker 1: it doesn't, the FDA approves it or not. Like I've

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Speaker 1: always looked at, Hey, it's black and white. You're implying

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Speaker 1: there is some more nuance here.

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Speaker 2: There is, And I think what I'm trying to imply

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Speaker 2: is there's a lot of informational value that's already held

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Speaker 2: within the valuations the way these equities are trading, that

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Speaker 2: you can calculate, you know, a sense of the implied

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Speaker 2: market probability of success for an opportunity for a company,

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Speaker 2: whether it's a product embedded within a larger company or

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Speaker 2: whether it's as you're referring to as smaller cap. You know,

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Speaker 2: kind of much more udosyncratic binary event and by looking

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Speaker 2: at that information and contrasting that with you know, an

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Speaker 2: independently formulated view that you may have if there's an

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Speaker 2: opportunity that arises between the two, to play some sort

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Speaker 2: of kind of arbitrage and probabilities in your in your

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Speaker 2: portfolio construction. That's the goal of the style of investing

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Speaker 2: we do.

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Speaker 1: So you're at a series of relatively smallish boutique healthcare

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Speaker 1: focused shops and you start developing a sense of there

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Speaker 1: is a set of probability analyses to be had. A

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Speaker 1: lot of the industry or a lot of the crowd

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Speaker 1: isn't engaging in that. What led you to that approach?

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Speaker 1: And then where did that approach take you?

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Speaker 2: Well, I think where the second part of it is

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Speaker 2: kind of easy to kind of start off with. Here.

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Speaker 2: Where it took me was the idea that there's you know,

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Speaker 2: mispricings to be found on either long or short opportunities,

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Speaker 2: depending on where you know, what kind of market view

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Speaker 2: is on a lot of these names. For my own

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Speaker 2: personal style and satisfaction, I didn't want to have part

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Speaker 2: of the performance that I was measured against dictated by

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Speaker 2: what the market did, and so I just kind of

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Speaker 2: almost intuitively gravitated towards a market neutral style of investing,

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Speaker 2: where I thought, any year, year in, year out, regardless

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Speaker 2: of what macroeconomic conditions are, regardless of what the stock

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Speaker 2: market does, if I'm successful at trying to identify idiosyncratic

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Speaker 2: stock opportunities, we could generate returns irrespective of market conditions.

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Speaker 2: And so that was very appealing to me, and so

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Speaker 2: that's what had me pivot back in two thousand and

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Speaker 2: seven to the first market neutral hedge fund that I

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Speaker 2: worked at, and I've been in market neutral investing ever since.

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Speaker 1: Let's talk a little bit about the next phase of

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Speaker 1: your career. After spending time at various healthcare boutiques, you

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Speaker 1: join Millennium in twenty eleven. They are a giant and

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Speaker 1: highly reguarded hedge funds. You join as an analyst. Tell

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Speaker 1: us what you did over your three years at Millennium.

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Speaker 2: Sure, Millennium was intriguing as an opportunity for me because

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Speaker 2: I had been through the earlier part of my career

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Speaker 2: at a few, as you mentioned, smaller hedge funds, and

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Speaker 2: I wanted to have an experience of what was already

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Speaker 2: at that time. This is twenty ten, twenty eleven, we're

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Speaker 2: talking about the emergence of a few of these larger

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Speaker 2: hedge funds as really centers of excellence, as really kind

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Speaker 2: of these multistrats that were already starting to dominate the landscape,

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Speaker 2: and I wanted to experience, you know what it is

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Speaker 2: about those places that allow them to kind of consistently outperform.

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Speaker 2: And so Millennium, to me, was another opportunity for me

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Speaker 2: to expand out of the small cap biotech universe that

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Speaker 2: I had been predominantly involved with for the first you know,

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Speaker 2: call it portion of my career and move into broader healthcare.

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Speaker 2: So it was my first time covering your peace in healthcare.

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Speaker 2: I moved into larger cap pharma, generic spec pharma, the

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Speaker 2: whole landscape of drug development. It really opened up the

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Speaker 2: opportunity set for me.

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Speaker 1: Let's talk about some of the other sectors you focus on.

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Speaker 1: You start with small cap pharma or small cap biotech,

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Speaker 1: get more granular, where do you go from there?

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Speaker 2: At Millennium, So what's really interesting, I started off, as

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Speaker 2: I kind of mentioned before, focused on trying to come

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Speaker 2: up with identification of opportunities in biotech where I felt

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Speaker 2: like risk was mispriced at its heart. That's what we're

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Speaker 2: talking about here from a probablistic lens of asking, you know,

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Speaker 2: what the market is pricing into an equity for an

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Speaker 2: event versus what I think the view is of that

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Speaker 2: particular event. What's really interesting when you get into the larger,

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Speaker 2: more complicated companies that have robust operating businesses, moving into

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Speaker 2: big pharma, moving into especially farmer companies, Investors at the

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Speaker 2: same time have to hold views of the cash flow

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Speaker 2: generative potential of the operating business and the scientific complexity

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Speaker 2: of the pipeline. And depending where they are in the narrative,

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Speaker 2: there's oftentimes one part of that story might prevail over

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Speaker 2: the other part of the story and lead to a

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Speaker 2: skew in the pricing of that other aspect of the business.

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Speaker 2: And so while the moves are maybe not as flashy

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Speaker 2: as what you'll see in small cap biotech when a

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Speaker 2: piece of news comes out and stocks up one hundred percent,

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Speaker 2: they're definitely idiosyncratic moves in nature and often have a

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Speaker 2: bit of an asymmetry to them in terms of upside

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Speaker 2: versus downside when that event happens, And so there's a

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Speaker 2: lot of fuel for investment opportunities throughout the kind of

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Speaker 2: story arc of larger companies in shorter time intervals. And

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Speaker 2: that's really kind of what we rinse and repeat and

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Speaker 2: did a lot of when we're at Millennium.

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Speaker 1: So all the science is fascinating. You're doing all this

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Speaker 1: at Millennium, which is really known as a very hard

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Speaker 1: charging trading shop. I'm curious your time at Millennium. You're

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Speaker 1: there for a couple of years, do you start to

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Speaker 1: get the bug, do you start saying to yourself, Hey,

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Speaker 1: I can manage a portfolio. I want to be involved

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Speaker 1: long store. I want to start training some of my

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Speaker 1: high conviction names. How long does it take before you're

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Speaker 1: an analyst at Millennium before you say I really need

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Speaker 1: to start managing money?

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Speaker 2: Well, I mean that is that was definitely a big

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Speaker 2: part of the motivation for coming, for going in there,

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Speaker 2: and also for eventually for leaving. For going in there,

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Speaker 2: I thought to be a well rounded investor, I needed

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Speaker 2: to have a wider aperture than just covering smaller cat

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Speaker 2: biotech names. So I moved there to expand my coverage universe.

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Speaker 2: After a few years of following that world, I really

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Speaker 2: felt like I was ready to take the next step

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Speaker 2: and to find an opportunity where I would be given

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Speaker 2: that opportunity to prove myself and start to manage money.

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Speaker 1: Huh. Really interesting, And so you depart Millennium to go

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Speaker 1: to survey or Capital part of investing giants Citadel tell

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Speaker 1: us without So.

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Speaker 2: Again, you know, serendipity plays an interesting role in this.

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Speaker 2: I had a colleague of mine from my Healthcore days,

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Speaker 2: Jeff Green, who was brought on to start a new

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Speaker 2: team at Citadel, and I knew that Citadel has and

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Speaker 2: I could tell you from having been there for seven years,

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Speaker 2: it's absolutely true. You know, a culture that tries for

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Speaker 2: an organization that large to really lean into being a meritocracy,

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Speaker 2: to evaluate the performance of analysts at various steps of

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Speaker 2: their career, and to promote internally people who are strong performers.

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Speaker 2: And so I thought it is a bet on myself

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Speaker 2: to go there that if I could be, you know,

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Speaker 2: just as strong as analysts as I could be for

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Speaker 2: the first year or two, that there would be an

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Speaker 2: opportunity that opened up to grow there. And in fact,

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Speaker 2: that's exactly how it played out. I was an analyst

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Speaker 2: there for two years, and then when an opportunity opened

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Speaker 2: up for an internal promotion, to portfolio manager. In the

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Speaker 2: beginning of twenty seventeen, they promoted me to that seat.

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Speaker 1: So talk to us about what that transition was like

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Speaker 1: from being almost you know, I think of analysts as

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Speaker 1: almost academic researchers, to actually running money, having real capital

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Speaker 1: at risk. Tell us about the transition and what were

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Speaker 1: some of the highlights and pitfalls.

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Speaker 2: Sure. Well, Again, one of the things I'd fall back

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Speaker 2: on in terms of the culture of Citadel and how

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Speaker 2: they develop people is at every step of the way

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Speaker 2: when you're on your journey, when you're an associate, they're

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Speaker 2: training you to do the analyst job. When you're an analyst,

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Speaker 2: they're training you to do the portfolio manager's job. So

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Speaker 2: as an analyst there for a year of my tenure,

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Speaker 2: I actually had a carve out of a smaller sub

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Speaker 2: sector book that I was able to manage on my

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Speaker 2: own under the watchful supervision of my portfolio manager. But

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Speaker 2: I had the opportunity to start taking risk on my

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Speaker 2: own in step with that. Citadel has you know, reputational

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Speaker 2: that's pretty well known, a risk framework that I think

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Speaker 2: is probably second to none in terms of how they

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Speaker 2: put guidance in place for you to understand the various

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Speaker 2: risks your portfolio carries, and if you lean into learning

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Speaker 2: that kind of system of investing, it really helps in

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Speaker 2: the transition from going to analysts to portfolio manager.

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Speaker 1: I'm really intrigued by the concept at some of the

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Speaker 1: big farm of the big pharmaceutical companies and their pipeline.

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Speaker 1: How does anyone have any clarity to the dozens of

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Speaker 1: compounds and endless potential drugs that A fives or or

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Speaker 1: you know, Johnson and Johnson are any of the big

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Speaker 1: shops are working on. It's got to be fairly difficult

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Speaker 1: to look into the future must much less what's going

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Speaker 1: on right now.

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Speaker 2: Well, what's actually really interesting about healthcare as a sector

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Speaker 2: of the market is I would argue you have more

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Speaker 2: visibility and a longer time period to evaluate the future

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Speaker 2: cash flow generative drivers of those businesses than any other sector.

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Speaker 2: I mean, sure, Apple every year might give you a

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Speaker 2: look what they're launching that year, but you don't really

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Speaker 2: have a couple of years look into their R and D.

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Speaker 2: You really don't have look into R and D for

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Speaker 2: you know, utilities companies or you know what other whatever

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Speaker 2: hotail or energy consumers what they're working on but the

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Speaker 2: nature of the drug development process mandates that the clinical

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Speaker 2: research for these drugs at various phases of development, starting

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Speaker 2: when the drug is first put into man gets published

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Speaker 2: and gets presented at medical conferences, and even the conduct

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Speaker 2: of future studies is publicly posted, so you're able to

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Speaker 2: then have a lot of information that can help you

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Speaker 2: formulate a view on the probabilities of success or failure

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Speaker 2: and the ultimate end user markets for those products that

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Speaker 2: you can't really have in other sectors. And it also

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Speaker 2: provides a big opportunity for investors to misprice those assets

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Speaker 2: because they're taking, you know, kind of behaviorally driven bets

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Speaker 2: on things they love, things they hate, and since you're

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Speaker 2: years away from ultimately being proven right or wrong, there

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Speaker 2: are a lot of ups and downs along the way.

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Speaker 2: So it's a really fascinating sub sector to be delving

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Speaker 2: into from an event driven perspective.

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Speaker 1: Really interesting. Giving your background at Columbia, I'm kind of

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Speaker 1: intrigued by what's been going on with genomics and the

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Speaker 1: concept of custom tailoring a sort of set of treatments

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Speaker 1: to your specific genome and whatever specific type of issue

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Speaker 1: is ailing you. How do you have any visibility down

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Speaker 1: that route? It seems like it's such an immense opportunity set.

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Speaker 1: Obviously I'm not in that space, but I can't wrap

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Speaker 1: my head around just the vast opportunities that have to

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Speaker 1: be coming in.

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Speaker 2: Well, what's amazing now is we're finally seeing the realization

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Speaker 2: twenty thirty years later of a lot of the work

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Speaker 2: that was done at the turn of the century to

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Speaker 2: provide those insights into the genetic underpinnings of a lot

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Speaker 2: of human disease. And today, more and more we're no

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Speaker 2: longer seeing diseases defined by what tissue that they affect

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Speaker 2: or what you know organ system is involved, but they're

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Speaker 2: more and more being defined by the genetic underpinnings of

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Speaker 2: those diseases. Even in cancer these days, before you used

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Speaker 2: to have two types of lung cancer, it was either

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Speaker 2: small cell or non small cell, and maybe you've got

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Speaker 2: granule enough to ask if it was squamous or add

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Speaker 2: no carcinoma. In pistology today we're asking, you know, are

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Speaker 2: you alkpositive, are you EGFR positive? You know, are you

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Speaker 2: ross positive? Genetic yes, And that's allowing for the creation

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Speaker 2: of much more precise, targeted therapies that are not only

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Speaker 2: delivering better efficacy, than your former mainly chemistry driven medicines,

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Speaker 2: but also having a better side effect profile because they're

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Speaker 2: more targeted to what's wrong with it is. So it

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Speaker 2: is tremendously fascinating that this is going on. It continues

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Speaker 2: to emerge, it's starting to move into cardiology, it's starting

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Speaker 2: to move into other areas of medicine. The medicines themselves

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Speaker 2: are becoming more genetic in nature. Whether we're starting to

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Speaker 2: utilize i mean even coming out of the pandemic and

402
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Speaker 2: mRNA based therapeutics, but you're starting to use you know,

403
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Speaker 2: target anti by therapeutics. Gene therapy is being approved now

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Speaker 2: at rates that we've never seen previously, even if they're

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Speaker 2: freniche diseases. It's a proof of concept that that's all

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Speaker 2: on the com So it's very exciting time and healthcare

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Speaker 2: for innovation.

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Speaker 1: So I want to make sure I'm hearing this correctly

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Speaker 1: from you because it's really so fascinating. It was chemistry

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Speaker 1: for a long time, Hey, this chemical seems to have

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Speaker 1: this reaction in the body and maybe it helps this disease.

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Speaker 1: Then it becomes biology, which is a little more focused

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Speaker 1: and then ultimately down to the genomic level.

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Speaker 2: Yeah, genetic medicines being being the next wave of innovation

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Speaker 2: and healthcare.

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Speaker 1: And what does this mean for managing future diseases, what

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Speaker 1: does this mean for fighting cancer, and what does this

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Speaker 1: mean for longevity.

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Speaker 2: Longevity is still an open question because of so many

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Speaker 2: different things you've got to tackle all together, and that

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Speaker 2: that pulls into it a lot of other lifestyle related

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Speaker 2: and more you know, kind of metabolically related issues, and

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Speaker 2: so that's almost delving more into the world of nutrition

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Speaker 2: and health. So it's it's hard to go down that route.

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Speaker 1: Wait, I'm waiting for the little nano robots to take

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Speaker 1: care of my cholesterol or.

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Speaker 2: Whatever, shooting them with lasers.

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Speaker 1: Right, that's right, even better, Oh, that's phase two. That's

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Speaker 1: science fiction. I'm right there with you.

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Speaker 2: Yeah, I think that's a little bit far afield. But

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Speaker 2: in terms of healthcare innovations impact near term, it's driven

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Speaker 2: more so by taking what was previously viewed as you know,

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Speaker 2: kind of kind of very loosely defined conditions and narrowing

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Speaker 2: the definitions of them based on the underlying biology of

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Speaker 2: that disease and a tighter, more well defined, biologically defined

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Speaker 2: subgroup of patients, and then developing therapeutics that target that,

437
00:25:04,400 --> 00:25:08,080
Speaker 2: and that's where we're headed. And it's fascinating to be,

438
00:25:08,359 --> 00:25:10,679
Speaker 2: you know, a witness to that and get to invest

439
00:25:10,720 --> 00:25:11,200
Speaker 2: along the way.

440
00:25:11,240 --> 00:25:14,440
Speaker 1: So we've been fighting the war on cancer since Nixon

441
00:25:14,520 --> 00:25:19,440
Speaker 1: was president. It sounds like the tide is really beginning

442
00:25:19,440 --> 00:25:22,560
Speaker 1: to turn. I know survival rates have gone way up

443
00:25:22,600 --> 00:25:25,919
Speaker 1: for very specific types of cancer, and I know things

444
00:25:25,960 --> 00:25:30,280
Speaker 1: that used to be fatal are now very treatable. Where

445
00:25:30,359 --> 00:25:31,520
Speaker 1: are we in this process.

446
00:25:32,359 --> 00:25:35,159
Speaker 2: I think it's going to be very variable based on

447
00:25:35,200 --> 00:25:38,040
Speaker 2: the underlying type of cancer, because some of them are

448
00:25:38,080 --> 00:25:43,320
Speaker 2: still much much more amenable to intervention than others. So,

449
00:25:43,440 --> 00:25:47,120
Speaker 2: for example, pancreatic cancer, which is slow to really kind

450
00:25:47,160 --> 00:25:51,600
Speaker 2: of have improved outcomes on it's really because the ability

451
00:25:51,640 --> 00:25:54,840
Speaker 2: to diagnose it early is so difficult. Ovarian's another one

452
00:25:54,880 --> 00:25:59,280
Speaker 2: where it's so difficult to diagnose early. Whereas cancers that

453
00:25:59,400 --> 00:26:02,840
Speaker 2: kind of show up a little bit more readily, breast cancer,

454
00:26:03,560 --> 00:26:06,679
Speaker 2: a lot of different forms of blood cancers, we've had

455
00:26:06,800 --> 00:26:09,240
Speaker 2: much more of a head start in trying to develop

456
00:26:09,400 --> 00:26:13,879
Speaker 2: new therapeutics for. And so I think, you know, CLL

457
00:26:13,960 --> 00:26:16,760
Speaker 2: might be on the verge of chronic lymphysifical leukemia, might

458
00:26:16,800 --> 00:26:18,280
Speaker 2: be on the verge of becoming one of the first

459
00:26:19,160 --> 00:26:23,639
Speaker 2: diseases that's no longer you know, actually different in your

460
00:26:23,920 --> 00:26:27,520
Speaker 2: death prognosis than an age matched, unaffective person. So in

461
00:26:27,560 --> 00:26:29,639
Speaker 2: other words, you're no longer dying of that disease.

462
00:26:29,320 --> 00:26:31,720
Speaker 1: And that's like lymphoma and related.

463
00:26:32,040 --> 00:26:34,400
Speaker 2: And so this is starting to happen where you're seeing

464
00:26:35,000 --> 00:26:38,160
Speaker 2: you know, survival rates pushed out so far that it's

465
00:26:38,320 --> 00:26:41,440
Speaker 2: converting them into livable diagnoses.

466
00:26:41,960 --> 00:26:45,400
Speaker 1: So let's talk a little bit about launching Cutter Capital

467
00:26:46,000 --> 00:26:49,240
Speaker 1: right in November twenty twenty two, not a bad time

468
00:26:49,280 --> 00:26:53,600
Speaker 1: to launch post pandemic stocks which had just bottomed after

469
00:26:53,760 --> 00:26:57,639
Speaker 1: an awful twenty twenty two How fortunate was that? Was

470
00:26:57,680 --> 00:26:58,280
Speaker 1: that timing?

471
00:26:58,920 --> 00:27:01,200
Speaker 2: Well? I I would like to try to take more

472
00:27:01,200 --> 00:27:03,080
Speaker 2: credit for the timing than maybe I can. A lot

473
00:27:03,080 --> 00:27:05,800
Speaker 2: of it was dictated by the timing of my decision

474
00:27:05,840 --> 00:27:08,600
Speaker 2: to leave Citadel. But at the same point, you know,

475
00:27:09,480 --> 00:27:11,639
Speaker 2: when I left Citadel, I hadn't escaped my attention that

476
00:27:11,680 --> 00:27:14,879
Speaker 2: we were in the midst of a significant regime change

477
00:27:14,880 --> 00:27:16,960
Speaker 2: in the market. And it's not a bad time to

478
00:27:16,960 --> 00:27:18,600
Speaker 2: sit it out if you're going to pick a time

479
00:27:18,600 --> 00:27:19,119
Speaker 2: to sit it out.

480
00:27:19,200 --> 00:27:21,800
Speaker 1: Yeah, to say the very least was it a challenge

481
00:27:21,880 --> 00:27:24,800
Speaker 1: raising money during twenty twenty two. That was a pretty

482
00:27:24,880 --> 00:27:27,439
Speaker 1: rough bear market, even though it only lasted, you know,

483
00:27:27,560 --> 00:27:28,240
Speaker 1: less than a year.

484
00:27:28,920 --> 00:27:34,240
Speaker 2: So I think it's hard to necessarily speak for, you know,

485
00:27:34,359 --> 00:27:39,840
Speaker 2: kind of the broader fundraising environment at large. I think

486
00:27:39,880 --> 00:27:44,400
Speaker 2: for myself, I had the benefit of an experience set

487
00:27:44,800 --> 00:27:48,320
Speaker 2: that was very attractive to the market on the heels

488
00:27:48,359 --> 00:27:52,880
Speaker 2: of significant outperformance that Citadel and Millennium were having relative

489
00:27:52,920 --> 00:27:56,520
Speaker 2: to other peers at that time. I am willing to

490
00:27:56,520 --> 00:28:00,000
Speaker 2: admit that Pedigree probably helped start the at least open

491
00:28:00,080 --> 00:28:03,919
Speaker 2: the doors, and then the conversation is what follows. But

492
00:28:04,280 --> 00:28:07,760
Speaker 2: you know, that allowed to have the initial conversations get started,

493
00:28:08,320 --> 00:28:11,240
Speaker 2: so I think I probably benefited from their performance in retrospect.

494
00:28:12,040 --> 00:28:14,920
Speaker 1: So, speaking broadly about the healthcare industry, a lot of

495
00:28:15,040 --> 00:28:19,160
Speaker 1: interesting things going on coming out of COVID. You mentioned

496
00:28:19,359 --> 00:28:21,880
Speaker 1: mRNA tell us a little bit about what you were

497
00:28:21,920 --> 00:28:25,879
Speaker 1: seeing in that space at the time as a pandemic

498
00:28:26,000 --> 00:28:27,600
Speaker 1: was kind of lifting well.

499
00:28:27,640 --> 00:28:30,960
Speaker 2: I think one of the unique attributes of healthcare, among

500
00:28:31,000 --> 00:28:33,560
Speaker 2: the others that we've kind of discussed here, is that

501
00:28:33,600 --> 00:28:37,680
Speaker 2: there's never want of newsflow, and so you know, the

502
00:28:37,800 --> 00:28:41,120
Speaker 2: strategy that I'd been running for a while previously and

503
00:28:41,480 --> 00:28:44,600
Speaker 2: look to emulate at the start of Cutter is really

504
00:28:44,640 --> 00:28:49,080
Speaker 2: the harvest thing of volatility around the healthcare drug development

505
00:28:49,120 --> 00:28:52,880
Speaker 2: process on both along and the short side. And so

506
00:28:53,280 --> 00:28:57,480
Speaker 2: I'm not really necessarily looking to take a bet that

507
00:28:57,600 --> 00:29:01,800
Speaker 2: innovation in general is at a certain you know peak

508
00:29:01,880 --> 00:29:05,440
Speaker 2: or nader. I'm just happy that it's happening so that

509
00:29:05,480 --> 00:29:07,880
Speaker 2: there's an opportunity set for us to get involved with.

510
00:29:08,240 --> 00:29:10,920
Speaker 1: Well, if we look at the pandemic era, there were

511
00:29:10,960 --> 00:29:15,080
Speaker 1: a lot of you know, remote work work from home stocks,

512
00:29:15,120 --> 00:29:20,080
Speaker 1: everything from docu sign to teledoc to Peloton that all

513
00:29:20,120 --> 00:29:23,200
Speaker 1: had these huge moves. What is Peloton ninety seven percent off?

514
00:29:23,240 --> 00:29:27,480
Speaker 1: It's you know, highs And I always assume something similar

515
00:29:27,600 --> 00:29:31,320
Speaker 1: was happening with all the companies that got those giant

516
00:29:31,360 --> 00:29:38,000
Speaker 1: contracts to manufacture the COVID vaccine or the variations of them.

517
00:29:38,160 --> 00:29:40,920
Speaker 1: What did that space look like to you at that point?

518
00:29:41,000 --> 00:29:44,920
Speaker 2: Yeah, absolutely, I think that it was probably driven by

519
00:29:45,080 --> 00:29:48,720
Speaker 2: a search for you know, any sort of thematic lens

520
00:29:48,800 --> 00:29:55,320
Speaker 2: that could drive returns that had investors crowding into anybody

521
00:29:55,400 --> 00:30:01,200
Speaker 2: who was helping while everybody else was being hurt. Difficulty

522
00:30:01,240 --> 00:30:05,000
Speaker 2: in that investing at the time was people putting, you know,

523
00:30:05,200 --> 00:30:11,720
Speaker 2: multiples of value longer term on what was inherently a

524
00:30:11,800 --> 00:30:16,080
Speaker 2: short term stop gap contracting. I mean, you know, realistically,

525
00:30:16,280 --> 00:30:19,160
Speaker 2: those contracts were really only worth the profit they generated

526
00:30:19,160 --> 00:30:21,800
Speaker 2: a near term, and putting a multiple on them didn't

527
00:30:21,840 --> 00:30:23,880
Speaker 2: make sense because there's no annuity value.

528
00:30:24,200 --> 00:30:27,480
Speaker 1: It's not once the picture of the python that's.

529
00:30:27,280 --> 00:30:30,840
Speaker 2: It, exactly, And so I think there was a lot

530
00:30:30,880 --> 00:30:33,320
Speaker 2: of that taking place at the time, driving companies like

531
00:30:33,360 --> 00:30:36,360
Speaker 2: Maderna and Bio went to and even Pfizer at that point.

532
00:30:36,960 --> 00:30:40,960
Speaker 2: Pfizer trading off for multiple that is derived from a

533
00:30:41,080 --> 00:30:45,560
Speaker 2: huge proportion of its revenue coming from COVID just didn't make,

534
00:30:45,960 --> 00:30:47,800
Speaker 2: you know, valuation sense either.

535
00:30:47,840 --> 00:30:49,959
Speaker 1: Your banning COVID was going to stick around in a

536
00:30:50,080 --> 00:30:53,880
Speaker 1: much broader way than it did and continue to drive profits.

537
00:30:54,120 --> 00:30:56,520
Speaker 1: But then the rest of your portfolio has other issues,

538
00:30:56,640 --> 00:30:58,800
Speaker 1: and it was sort of either we come out of

539
00:30:58,840 --> 00:31:01,400
Speaker 1: it and everybody can get back to normal. But that

540
00:31:01,560 --> 00:31:05,440
Speaker 1: means the pharmaceutical companies that did so well, and a

541
00:31:05,480 --> 00:31:09,120
Speaker 1: lot of them began rolling over before that was obvious.

542
00:31:08,840 --> 00:31:10,840
Speaker 2: Right, sure, I think there was a little bit of

543
00:31:10,880 --> 00:31:13,080
Speaker 2: a realization ahead of time that this was its own

544
00:31:13,160 --> 00:31:15,240
Speaker 2: type of bubble and that that was going to wind

545
00:31:15,320 --> 00:31:15,840
Speaker 2: up passing.

546
00:31:16,240 --> 00:31:19,520
Speaker 1: So since that point in time, we've seen all of

547
00:31:19,560 --> 00:31:24,400
Speaker 1: these new weight loss drugs, the GLP one drugs, that

548
00:31:24,760 --> 00:31:28,160
Speaker 1: not only are people talking about these as treatments for

549
00:31:28,240 --> 00:31:31,240
Speaker 1: diabetes and weight loss, but it seems every day I

550
00:31:31,320 --> 00:31:34,440
Speaker 1: read a different headline this is good for alcoholism or

551
00:31:34,520 --> 00:31:37,280
Speaker 1: drug addiction, or you know, go down the list of

552
00:31:37,360 --> 00:31:40,120
Speaker 1: all of these things that you wouldn't have thought were

553
00:31:40,160 --> 00:31:45,160
Speaker 1: somehow related to diabetes. But the biochemical mechanism that's being

554
00:31:45,360 --> 00:31:48,640
Speaker 1: used to, I guess, feed more dopamine. If you can

555
00:31:48,680 --> 00:31:53,640
Speaker 1: interrupt that, you create a reduction of demand for whatever

556
00:31:53,720 --> 00:31:56,360
Speaker 1: that addictive substance is tell us a little bit about

557
00:31:56,360 --> 00:31:58,480
Speaker 1: what you're seeing in the GLP space.

558
00:31:58,920 --> 00:32:00,960
Speaker 2: So I think that that's correct. I think that there's

559
00:32:01,440 --> 00:32:05,880
Speaker 2: two phenomenon that are going on there. One is an

560
00:32:06,000 --> 00:32:11,400
Speaker 2: understanding that obesity itself is such an integral risk factor

561
00:32:11,440 --> 00:32:16,200
Speaker 2: to a number of different, seemingly potentially unrelated conditions that

562
00:32:16,240 --> 00:32:21,120
Speaker 2: when you reduce that burden of obesity, you're reducing its

563
00:32:21,160 --> 00:32:23,280
Speaker 2: impact in a number of ancillary diseases.

564
00:32:23,360 --> 00:32:24,480
Speaker 1: When you say unreal.

565
00:32:24,240 --> 00:32:28,280
Speaker 2: Apnea, you know I mean, there's always thought that obesity

566
00:32:28,440 --> 00:32:30,720
Speaker 2: was a risk factor that might have an increase the

567
00:32:30,800 --> 00:32:33,880
Speaker 2: currens of sleep apnea. Oh really, but it's now demonstrated

568
00:32:33,880 --> 00:32:38,360
Speaker 2: that by reducing obesity you're actually improving sleep apnea outcomes.

569
00:32:38,600 --> 00:32:40,120
Speaker 2: As one vignette, like.

570
00:32:40,040 --> 00:32:44,840
Speaker 1: I immediately when I hear OBESID, I immediately think blood pressure, cholesterol,

571
00:32:44,960 --> 00:32:50,560
Speaker 1: cardiac diabetes. Hey, that should be enough to do damage

572
00:32:50,600 --> 00:32:53,040
Speaker 1: to most people. You're saying it goes far beyond that.

573
00:32:53,240 --> 00:32:58,040
Speaker 2: There are definitely other elements of related. They call it

574
00:32:58,080 --> 00:33:00,840
Speaker 2: a metabolic disorder, and it's a broader of things that

575
00:33:00,880 --> 00:33:04,160
Speaker 2: can be that could be positively impacted by this. I

576
00:33:04,200 --> 00:33:07,440
Speaker 2: should say it's not necessarily clear that they're impacted because

577
00:33:07,480 --> 00:33:11,320
Speaker 2: of clip one versus being impacted because you're losing weight,

578
00:33:11,360 --> 00:33:13,120
Speaker 2: but the net of it is still a positive.

579
00:33:14,160 --> 00:33:18,400
Speaker 1: So when you look at the GLP drugs, what are

580
00:33:18,400 --> 00:33:22,320
Speaker 1: you looking at? What companies do you find interesting? What's

581
00:33:22,320 --> 00:33:24,880
Speaker 1: happening in that space? Has this gotten ahead of itself

582
00:33:25,000 --> 00:33:27,320
Speaker 1: or is there still plenty and runway for this to

583
00:33:27,440 --> 00:33:28,280
Speaker 1: keep ramping up?

584
00:33:28,840 --> 00:33:33,680
Speaker 2: So I think that by and large, for the incumbents ELI,

585
00:33:33,720 --> 00:33:36,560
Speaker 2: Lilly and Novo Nordisk, you know, a lot of the

586
00:33:36,720 --> 00:33:39,840
Speaker 2: easy money on this is done. You know, they've already

587
00:33:39,880 --> 00:33:42,560
Speaker 2: reached levels that you know, in terms of both multiples

588
00:33:42,560 --> 00:33:45,680
Speaker 2: and market cap that you haven't seen. You know, I

589
00:33:45,680 --> 00:33:48,600
Speaker 2: think there was a portion of time this year where

590
00:33:48,680 --> 00:33:51,840
Speaker 2: Novo Nordisk had a larger market cap than the GDP

591
00:33:51,960 --> 00:33:55,200
Speaker 2: of its host country. So you know, it's it's impressive.

592
00:33:55,280 --> 00:33:58,719
Speaker 2: It's impressive, and a lot of that's already kind of

593
00:33:58,760 --> 00:34:03,000
Speaker 2: baked into the expectation there. What's fascinating now if pharma

594
00:34:03,240 --> 00:34:07,880
Speaker 2: does absolutely nothing else, well, they're very good at being copycats,

595
00:34:08,600 --> 00:34:11,800
Speaker 2: and knowing that this mechanism works and has this potential

596
00:34:11,840 --> 00:34:16,600
Speaker 2: has everybody chasing a better version. And what's really interesting

597
00:34:17,080 --> 00:34:19,600
Speaker 2: right now in terms of the investment world are the

598
00:34:19,680 --> 00:34:24,480
Speaker 2: second generation obesity drugs that can look at how the

599
00:34:24,520 --> 00:34:28,879
Speaker 2: successes of Novo and Lily and iterate on it. And

600
00:34:29,080 --> 00:34:32,200
Speaker 2: there's a wealth of that in development now and those

601
00:34:32,239 --> 00:34:36,720
Speaker 2: are really fascinating. One example of that is a company,

602
00:34:36,760 --> 00:34:41,280
Speaker 2: another Danish company, Zeeland Pharma, who are developing a amlin

603
00:34:41,360 --> 00:34:46,920
Speaker 2: based therapeutic which is related in overall biology but not

604
00:34:47,000 --> 00:34:50,720
Speaker 2: quite the same target as glip one, and they've shown

605
00:34:50,760 --> 00:34:53,520
Speaker 2: some of the first data over this past summer of

606
00:34:53,560 --> 00:34:55,959
Speaker 2: weight loss levels that are comparable, but with a better

607
00:34:56,000 --> 00:34:58,719
Speaker 2: tolerability profile. And the goal here is going to be

608
00:34:58,760 --> 00:35:03,359
Speaker 2: able to make these drugs experientially better for patients. And

609
00:35:03,560 --> 00:35:06,640
Speaker 2: that's not just the vanity perspective or convenience perspective. It's

610
00:35:06,640 --> 00:35:09,400
Speaker 2: going to help patients stay on these drugs longer and

611
00:35:09,520 --> 00:35:10,800
Speaker 2: tolerate the whole therapy.

612
00:35:10,880 --> 00:35:14,200
Speaker 1: You know, I recall it wasn't that long ago, I

613
00:35:14,200 --> 00:35:17,160
Speaker 1: want to say a decade ago. There was sort of

614
00:35:17,200 --> 00:35:20,920
Speaker 1: this sense, hey, all these big farmer companies, you know,

615
00:35:21,160 --> 00:35:25,160
Speaker 1: they've shot there. Well, their best days are behind them.

616
00:35:25,360 --> 00:35:28,759
Speaker 1: They're not developing new drugs, they don't have the new technologies.

617
00:35:28,760 --> 00:35:32,840
Speaker 1: They don't they're not into the genomics aspect. They really

618
00:35:33,120 --> 00:35:37,839
Speaker 1: are being left behind by what's happening. That turned out

619
00:35:37,960 --> 00:35:41,480
Speaker 1: not to be all that accurate. It seems like the

620
00:35:41,520 --> 00:35:44,400
Speaker 1: big farmers still have more than a few tricks up

621
00:35:44,400 --> 00:35:45,040
Speaker 1: their sleeps.

622
00:35:45,200 --> 00:35:49,600
Speaker 2: They do. And I think that the pharmaceutical industry right

623
00:35:49,640 --> 00:35:54,600
Speaker 2: now in general, has reached a really good balance of sourcing,

624
00:35:54,880 --> 00:36:00,799
Speaker 2: of having competition for sourcing products internally and extern and

625
00:36:00,880 --> 00:36:03,440
Speaker 2: they're targeting their R and D efforts more and more

626
00:36:04,080 --> 00:36:09,360
Speaker 2: in specific areas of expertise where they have previously shown

627
00:36:09,480 --> 00:36:12,000
Speaker 2: successes and they have the infrastructure built and are no

628
00:36:12,080 --> 00:36:14,960
Speaker 2: longer trying to be one stop shops that do research

629
00:36:15,040 --> 00:36:18,399
Speaker 2: on everything. They have internal R and DA what they're

630
00:36:18,440 --> 00:36:22,120
Speaker 2: good at, and then they look externally at bringing in

631
00:36:22,920 --> 00:36:27,040
Speaker 2: other products that could have the benefit of helping their

632
00:36:27,040 --> 00:36:29,799
Speaker 2: growth rate and long term value creation for their shareholders,

633
00:36:30,120 --> 00:36:34,239
Speaker 2: but also really leverage their internal commercial capabilities and regulatory

634
00:36:34,239 --> 00:36:37,400
Speaker 2: capabilities to aid these smaller companies and getting over the

635
00:36:37,440 --> 00:36:40,200
Speaker 2: finish line. So it's a really good symbiotic relationship that's

636
00:36:40,239 --> 00:36:40,480
Speaker 2: going on.

637
00:36:40,520 --> 00:36:44,480
Speaker 1: So either through acquisitions or licensing, they can find new molecules,

638
00:36:44,520 --> 00:36:47,719
Speaker 1: new drugs, new whatever and building on it. So you

639
00:36:47,800 --> 00:36:52,040
Speaker 1: run a long short portfolio. I'm kind of curious given

640
00:36:52,560 --> 00:36:56,960
Speaker 1: this wide birth of new technologies and companies and drugs

641
00:36:56,960 --> 00:36:59,440
Speaker 1: that are coming along. First of all, do you run

642
00:36:59,719 --> 00:37:02,640
Speaker 1: you know, a one twenty twenty or one thirty thirty

643
00:37:03,160 --> 00:37:07,160
Speaker 1: or is it more opportunistic? How do you structure your book?

644
00:37:07,560 --> 00:37:10,600
Speaker 2: So the goal at Cutter when we came out was

645
00:37:11,400 --> 00:37:15,120
Speaker 2: looking at, if you take the experience base that I

646
00:37:15,120 --> 00:37:18,480
Speaker 2: had had previously at the multi strategy funds that I

647
00:37:18,520 --> 00:37:21,160
Speaker 2: had worked at and the industry in general. If you

648
00:37:21,200 --> 00:37:23,840
Speaker 2: expanded to the ballyasn, The's in point seventy twos and

649
00:37:23,920 --> 00:37:28,920
Speaker 2: everybody else. There is this convergent evolution of interaction with

650
00:37:29,000 --> 00:37:31,920
Speaker 2: the market that these firms have all developed to have

651
00:37:32,000 --> 00:37:36,520
Speaker 2: teams of a certain size sector specialist managing certain amount

652
00:37:36,560 --> 00:37:39,680
Speaker 2: of capital in that sub sector in a market in

653
00:37:39,719 --> 00:37:45,719
Speaker 2: factor aware type approach, And we thought it cutter. Why

654
00:37:45,760 --> 00:37:49,560
Speaker 2: not democratize that a bit and allow the broader investor

655
00:37:49,600 --> 00:37:52,840
Speaker 2: community to plug and play in their portfolios one of

656
00:37:52,840 --> 00:37:55,680
Speaker 2: those high performing teams and be able to take that

657
00:37:55,760 --> 00:37:59,520
Speaker 2: expertise in house to their own personal portfolios if you will.

658
00:37:59,560 --> 00:38:01,120
Speaker 2: You may not be able to get a spot as

659
00:38:01,120 --> 00:38:03,160
Speaker 2: an allocation in Citadel, but you could get a spot

660
00:38:03,200 --> 00:38:07,400
Speaker 2: an allocation in someone who runs a Citadel style equities portfolio,

661
00:38:07,680 --> 00:38:10,080
Speaker 2: which is the what we do. So our risk parameters

662
00:38:10,719 --> 00:38:14,239
Speaker 2: market neutral and factor neutral are very similar to what

663
00:38:14,280 --> 00:38:17,120
Speaker 2: you would have inside one of those other firms, such

664
00:38:17,160 --> 00:38:19,360
Speaker 2: that if you kind of dropped our strategy into one

665
00:38:19,400 --> 00:38:21,480
Speaker 2: of those firms, we wouldn't have to change what we're doing.

666
00:38:21,719 --> 00:38:24,080
Speaker 1: Right, So let's define some of those terms for some

667
00:38:24,160 --> 00:38:27,160
Speaker 1: of the lay people may not be familiar market neutral

668
00:38:27,200 --> 00:38:31,240
Speaker 1: means your long half your book or some percentage your short,

669
00:38:31,520 --> 00:38:33,840
Speaker 1: and it doesn't matter what the market does. If the

670
00:38:33,880 --> 00:38:36,160
Speaker 1: market goes up, your lungs go up. If the market

671
00:38:36,200 --> 00:38:40,960
Speaker 1: goes down, your shorts do better. And the expectation is

672
00:38:41,320 --> 00:38:45,480
Speaker 1: over the fullness of times, your lungs will outperform the

673
00:38:45,920 --> 00:38:50,880
Speaker 1: equity market, while your shorts will ultimately go in the

674
00:38:50,920 --> 00:38:54,040
Speaker 1: right direction, even if it's not down as much as

675
00:38:54,480 --> 00:38:55,560
Speaker 1: the market has gone up.

676
00:38:55,840 --> 00:38:57,480
Speaker 2: I think that's a good description of it. I mean,

677
00:38:57,520 --> 00:39:02,000
Speaker 2: what we're trying to do is really focus on this

678
00:39:02,200 --> 00:39:06,280
Speaker 2: thematic style of investing that is really trying to harvest

679
00:39:07,360 --> 00:39:10,719
Speaker 2: the inflection points in innovation and medicine and how that

680
00:39:10,840 --> 00:39:14,279
Speaker 2: impacts the related equities to that, and take kind of

681
00:39:14,360 --> 00:39:19,000
Speaker 2: market dynamics out of the mix, take exposures to different

682
00:39:20,040 --> 00:39:23,319
Speaker 2: style factors in the portfolio out of the mix, so

683
00:39:23,440 --> 00:39:26,520
Speaker 2: things like momentum, things like a growth verst value bias,

684
00:39:27,440 --> 00:39:30,640
Speaker 2: and et cetera, et cetera, pulling their exposures out of

685
00:39:30,680 --> 00:39:33,840
Speaker 2: the portfolio and really leaning into the bets you're making

686
00:39:33,840 --> 00:39:37,120
Speaker 2: on a scientific basis. So we ask the question at

687
00:39:37,160 --> 00:39:41,440
Speaker 2: Cutter over the next three, six, nine months, what are

688
00:39:41,520 --> 00:39:46,120
Speaker 2: the inflection points in the practice of medicine and who

689
00:39:46,160 --> 00:39:49,040
Speaker 2: are the winners and losers in that, and we try

690
00:39:49,040 --> 00:39:53,320
Speaker 2: to build thematic trades that will be constellations of winners

691
00:39:53,320 --> 00:39:56,719
Speaker 2: and losers that allow us to kind of hedge some

692
00:39:56,800 --> 00:40:00,960
Speaker 2: of those other exposures and really extend our exposure to

693
00:40:01,000 --> 00:40:04,280
Speaker 2: the scientific driver of performance in those names.

694
00:40:04,520 --> 00:40:07,760
Speaker 1: So let's talk about the difference between the long half

695
00:40:07,800 --> 00:40:09,880
Speaker 1: of your book and the short half of your book.

696
00:40:10,600 --> 00:40:13,120
Speaker 1: My assumption, or let me just ask you this way.

697
00:40:13,520 --> 00:40:18,160
Speaker 1: On the longside, you're looking for companies that are potentially

698
00:40:18,160 --> 00:40:21,680
Speaker 1: putting out a new product that you think the rest

699
00:40:21,840 --> 00:40:26,880
Speaker 1: of the marketplace hasn't recognized, either the likelihood of success

700
00:40:26,960 --> 00:40:30,320
Speaker 1: or the potential upside. I'm reluctant to use the word

701
00:40:30,480 --> 00:40:34,080
Speaker 1: value play because it really is less of a Hey,

702
00:40:34,120 --> 00:40:39,600
Speaker 1: we think this drug, this technology, this new approach has

703
00:40:39,800 --> 00:40:42,440
Speaker 1: this sort of commercial application and it's not reflected in

704
00:40:42,480 --> 00:40:45,160
Speaker 1: stock price. Is that a fair way to describe how

705
00:40:45,200 --> 00:40:45,759
Speaker 1: you think about it.

706
00:40:45,800 --> 00:40:49,680
Speaker 2: I think so, it's pretty close. The one thing that

707
00:40:49,680 --> 00:40:51,920
Speaker 2: I'd layer on top is it's not so much I

708
00:40:51,960 --> 00:40:55,520
Speaker 2: wouldn't say that we're so much solely driven by a

709
00:40:55,640 --> 00:41:00,200
Speaker 2: value mindset so much as we're driven by recognizing the

710
00:41:00,200 --> 00:41:04,680
Speaker 2: potential for upside optionality. So sometimes companies that in their

711
00:41:04,719 --> 00:41:08,680
Speaker 2: current market conditions you wouldn't call cheap, right, but they

712
00:41:08,719 --> 00:41:13,200
Speaker 2: have additional accelerators on performance, They have additional upside in

713
00:41:13,280 --> 00:41:18,279
Speaker 2: their pipelines that could continue to have them outperform that

714
00:41:18,360 --> 00:41:20,919
Speaker 2: might not be fully appreciated by the market. We'll still

715
00:41:20,920 --> 00:41:22,000
Speaker 2: be interested in those names.

716
00:41:22,080 --> 00:41:24,520
Speaker 1: Right, Just because something's expensive doesn't mean it can't get

717
00:41:24,520 --> 00:41:28,000
Speaker 1: more more right, And I'm always fascinated. People seem to

718
00:41:28,000 --> 00:41:31,360
Speaker 1: think shorting is a mirror image of going long, but

719
00:41:31,440 --> 00:41:34,560
Speaker 1: it really isn't. It's a very different sort of experience.

720
00:41:35,080 --> 00:41:37,399
Speaker 1: Tell us what sort of screens you do to make

721
00:41:37,520 --> 00:41:39,960
Speaker 1: downside bets. I mean, how much of it is hedging

722
00:41:40,040 --> 00:41:43,319
Speaker 1: the long book and how much of it is just Hey,

723
00:41:43,360 --> 00:41:47,279
Speaker 1: we think the stock is wildly misunderstood and there's a

724
00:41:47,320 --> 00:41:49,400
Speaker 1: lot more downside than upside.

725
00:41:49,000 --> 00:41:52,280
Speaker 2: If you'll indulge me for a moment. Cutter Capital itself

726
00:41:52,320 --> 00:41:55,160
Speaker 2: is a baseball reference. I'm a big sports fan. That

727
00:41:55,239 --> 00:42:00,280
Speaker 2: cut fastball is a pitch that Mariano perfected that's equally

728
00:42:00,320 --> 00:42:03,000
Speaker 2: effective on left hand hitters and right hand hitters, depending

729
00:42:03,040 --> 00:42:06,200
Speaker 2: on how we delivered it. For us, that represents our

730
00:42:06,239 --> 00:42:10,280
Speaker 2: research process, which by doing the same type of analysis

731
00:42:10,320 --> 00:42:14,239
Speaker 2: over and over. Emerging from that are opportunities where we

732
00:42:14,400 --> 00:42:18,759
Speaker 2: find events as they are reflected in the underlying equities

733
00:42:18,920 --> 00:42:23,759
Speaker 2: to be either indexed to over enthusiasm or underappreciated. And

734
00:42:23,800 --> 00:42:26,480
Speaker 2: when there's over enthusiasm in a situation, when you know

735
00:42:26,640 --> 00:42:30,600
Speaker 2: equities are reflecting fully an expectation that this innovation is

736
00:42:30,640 --> 00:42:34,280
Speaker 2: going to work, that provides you an opportunity to find shorts.

737
00:42:34,960 --> 00:42:36,719
Speaker 2: Because if that doesn't work out and everybody's got to

738
00:42:36,800 --> 00:42:39,920
Speaker 2: change their view on the opportunity, you know those equities

739
00:42:39,920 --> 00:42:41,000
Speaker 2: are are going to suffer.

740
00:42:41,120 --> 00:42:43,000
Speaker 1: So how do you deal with the timing and the

741
00:42:43,080 --> 00:42:46,480
Speaker 1: technicals of shorts because you could be right and a

742
00:42:46,480 --> 00:42:48,920
Speaker 1: little early, and it's very painful on the short side.

743
00:42:49,040 --> 00:42:53,760
Speaker 2: No, absolutely, That's why I think part of the style

744
00:42:53,800 --> 00:42:59,239
Speaker 2: of investing we have looks at individual investment opportunities through

745
00:42:59,280 --> 00:43:02,319
Speaker 2: more of a thematic lens, where we will then look

746
00:43:02,360 --> 00:43:06,680
Speaker 2: at constellations of winners and losers and put them together

747
00:43:06,880 --> 00:43:09,399
Speaker 2: in one trade. So our trades are often three four

748
00:43:09,960 --> 00:43:16,680
Speaker 2: positions that are combinations in a particular therapeutic class, incumbents, innovators,

749
00:43:16,760 --> 00:43:20,280
Speaker 2: fast followers that are all going to have different varying

750
00:43:20,400 --> 00:43:25,520
Speaker 2: levels of their value influenced by these news events, and

751
00:43:25,680 --> 00:43:28,480
Speaker 2: by pairing them up long and short, you're hoping that

752
00:43:28,600 --> 00:43:31,000
Speaker 2: why you're waiting for that event to play out, you're

753
00:43:31,040 --> 00:43:33,320
Speaker 2: hedging some of your market exposures. So to put it

754
00:43:33,400 --> 00:43:36,080
Speaker 2: your way, if that's short, is the short which is

755
00:43:36,120 --> 00:43:38,840
Speaker 2: the key to the trade is going up with the market.

756
00:43:38,920 --> 00:43:42,160
Speaker 2: Hopefully your lungs are protecting you and making enough on

757
00:43:42,200 --> 00:43:44,200
Speaker 2: the upside while you wait to get paid for the short.

758
00:43:44,840 --> 00:43:48,880
Speaker 1: Are you restricted to only the healthcare sector? Or Like

759
00:43:48,960 --> 00:43:53,160
Speaker 1: when I first started reading about glps, what immediately came

760
00:43:53,200 --> 00:43:57,120
Speaker 1: to mind was young brands and McDonald's and Dunkin Donuts,

761
00:43:57,160 --> 00:43:59,879
Speaker 1: and Hey, how are supermarkets going to deal with this?

762
00:44:00,600 --> 00:44:06,840
Speaker 1: You know, the food in the perimeter of the supermarket, meat, poultry, fish, fruit, vegetables, dairy,

763
00:44:07,680 --> 00:44:10,839
Speaker 1: their lowest profit margin stuff, all the junk in the

764
00:44:10,880 --> 00:44:16,680
Speaker 1: middle that GLP users are not going to be consuming. Hey,

765
00:44:16,719 --> 00:44:21,279
Speaker 1: does this mean Kroger's is a GLP downside play? And

766
00:44:21,360 --> 00:44:23,719
Speaker 1: I have no idea, but it just it's a fascinating

767
00:44:23,840 --> 00:44:24,520
Speaker 1: thought process.

768
00:44:24,560 --> 00:44:28,680
Speaker 2: So I would say we stick to our domain expertise

769
00:44:29,160 --> 00:44:32,040
Speaker 2: and we have a team that's highly specialized and focused

770
00:44:32,040 --> 00:44:36,000
Speaker 2: in their career history and path to be healthcare specialists,

771
00:44:36,040 --> 00:44:38,680
Speaker 2: and so we prefer to kind of kind of stick

772
00:44:38,680 --> 00:44:41,239
Speaker 2: to where we have that level of domain expertise, and

773
00:44:41,280 --> 00:44:43,759
Speaker 2: then beyond that for a second, I would just say

774
00:44:43,840 --> 00:44:49,319
Speaker 2: that the glip ones are an exciting introduction to the

775
00:44:49,360 --> 00:44:53,040
Speaker 2: broader investment world into what we do in healthcare every day.

776
00:44:53,640 --> 00:44:55,960
Speaker 2: But it's relatively few and far between the type of

777
00:44:56,000 --> 00:44:59,440
Speaker 2: drugs that have such an impact on a macro level

778
00:44:59,440 --> 00:45:02,000
Speaker 2: that you could think madically bet outside the sector on

779
00:45:02,040 --> 00:45:04,960
Speaker 2: their impacts. So you know, we have a preference to

780
00:45:05,000 --> 00:45:06,480
Speaker 2: remain in the healthcare.

781
00:45:06,160 --> 00:45:10,760
Speaker 1: World, So you also like to play in European pharmaceutical

782
00:45:10,800 --> 00:45:15,240
Speaker 1: and healthcare stocks. Generally speaking, over the past couple of years,

783
00:45:15,880 --> 00:45:20,480
Speaker 1: European values were much cheaper in the United States, and hey,

784
00:45:20,520 --> 00:45:23,080
Speaker 1: if you were betting on that mean reversion ten fifteen

785
00:45:23,160 --> 00:45:26,239
Speaker 1: years ago, we're still waiting. How do you look at

786
00:45:26,280 --> 00:45:30,040
Speaker 1: the way things are priced in Europe and are the

787
00:45:30,080 --> 00:45:34,240
Speaker 1: same discounts that we see in banking and other areas

788
00:45:34,280 --> 00:45:37,280
Speaker 1: in Europe are they taking place in the healthcare sector.

789
00:45:37,560 --> 00:45:42,000
Speaker 2: So I think what's interesting about investing in Europe for

790
00:45:42,239 --> 00:45:46,799
Speaker 2: US might not necessarily be directly related to a view

791
00:45:46,840 --> 00:45:50,680
Speaker 2: we have on the discounted valuations there, although what I

792
00:45:50,680 --> 00:45:56,600
Speaker 2: would say about that is, by and large, US investors

793
00:45:57,000 --> 00:46:01,560
Speaker 2: tend to be more speculative at earlier stages of development,

794
00:46:01,640 --> 00:46:05,800
Speaker 2: being more willing to credit companies for future cash flows

795
00:46:05,920 --> 00:46:09,520
Speaker 2: well in advance of the realization of whether those products

796
00:46:09,560 --> 00:46:10,640
Speaker 2: will come to market or not.

797
00:46:11,000 --> 00:46:15,200
Speaker 1: Meaning American investors tend to be more speculators and gamblers

798
00:46:15,520 --> 00:46:16,719
Speaker 1: than their European counterpart.

799
00:46:16,840 --> 00:46:19,440
Speaker 2: They tend to be more aggressive in their willingness to

800
00:46:19,560 --> 00:46:24,359
Speaker 2: price in early data as proof of concept. I mean,

801
00:46:24,400 --> 00:46:27,920
Speaker 2: there was even a time period during the height of

802
00:46:28,000 --> 00:46:31,000
Speaker 2: the you know, kind of low rate biotech boom where

803
00:46:31,440 --> 00:46:33,759
Speaker 2: you know, we used to sometimes joke that, you know,

804
00:46:33,840 --> 00:46:36,959
Speaker 2: proof of concept was having a concept. You know, these

805
00:46:37,000 --> 00:46:39,600
Speaker 2: things just ran as soon as companies announced they were

806
00:46:39,640 --> 00:46:44,320
Speaker 2: working on things. European investors buyinglizes a generalization, but European

807
00:46:44,320 --> 00:46:48,120
Speaker 2: investors generally want to have a more solid proof of

808
00:46:48,200 --> 00:46:52,719
Speaker 2: concept before they start pricing in those opportunities to those equities,

809
00:46:53,040 --> 00:46:55,600
Speaker 2: and so there is interesting opportunity there for you to

810
00:46:55,640 --> 00:46:58,160
Speaker 2: get ahead of that curve and bring a little bit

811
00:46:58,200 --> 00:47:01,920
Speaker 2: of US style speculation into European biotech and look at

812
00:47:01,920 --> 00:47:05,520
Speaker 2: some of those those names. So that's an interesting reason

813
00:47:05,560 --> 00:47:08,359
Speaker 2: to be in Europe. Another quick vignette and why it's

814
00:47:08,360 --> 00:47:12,719
Speaker 2: interesting to be in Europe is in US, particularly for

815
00:47:12,840 --> 00:47:15,080
Speaker 2: you know, kind of the market neutral world where we're living,

816
00:47:15,880 --> 00:47:19,680
Speaker 2: there are times where, whether you want to call it

817
00:47:19,719 --> 00:47:24,120
Speaker 2: positioning or crowding in names, or unwind regime, however you

818
00:47:24,160 --> 00:47:27,840
Speaker 2: want to describe it, where US equities tend to act

819
00:47:28,200 --> 00:47:31,120
Speaker 2: together in a de risking, you know, kind of mode,

820
00:47:31,200 --> 00:47:34,160
Speaker 2: and it's based on what's popularly owned by the major

821
00:47:34,200 --> 00:47:38,040
Speaker 2: hedge funds and they're de risking themselves. Europe in general

822
00:47:38,800 --> 00:47:42,879
Speaker 2: doesn't behave in the exact same lockstep with the US.

823
00:47:42,960 --> 00:47:45,759
Speaker 2: So if you have a relatively robust European book, it

824
00:47:45,800 --> 00:47:47,880
Speaker 2: allows you to head yourself from some of the US

825
00:47:47,960 --> 00:47:51,400
Speaker 2: crowding exposure because you're in a different world of investors,

826
00:47:51,400 --> 00:47:54,920
Speaker 2: in a different mindset and different you know, drivers of

827
00:47:54,960 --> 00:47:57,520
Speaker 2: those equity markets. So it provides a little bit of

828
00:47:57,560 --> 00:47:59,480
Speaker 2: diversity to the approach and portfolio.

829
00:48:00,040 --> 00:48:03,680
Speaker 1: Let's talk about another difference. What is the regulatory environment

830
00:48:03,880 --> 00:48:10,600
Speaker 1: for new drugs, new procedures, new ways of applying the

831
00:48:10,640 --> 00:48:14,160
Speaker 1: science to healthcare in Europe VERSUS the US, how do

832
00:48:14,200 --> 00:48:15,000
Speaker 1: they compare contes.

833
00:48:15,040 --> 00:48:19,720
Speaker 2: So it's interesting the way I described the US equity

834
00:48:19,760 --> 00:48:23,320
Speaker 2: markets and the earlier speculation and success that we see here.

835
00:48:24,120 --> 00:48:27,640
Speaker 2: I almost see an analogy in the way the regulators

836
00:48:27,680 --> 00:48:33,400
Speaker 2: think on a drug approval process, because the US FDA

837
00:48:34,239 --> 00:48:40,200
Speaker 2: in recent years has become much more active in allowing

838
00:48:40,280 --> 00:48:45,439
Speaker 2: drugs to get approved based on so called surrogate markers

839
00:48:45,480 --> 00:48:49,000
Speaker 2: of efficacy. In the past, for drug to be approved,

840
00:48:49,040 --> 00:48:53,440
Speaker 2: you had to demonstrate against a tangible clinical endpoint that

841
00:48:53,520 --> 00:48:56,680
Speaker 2: your drug worked. And now we're moving more and more

842
00:48:56,719 --> 00:49:00,560
Speaker 2: in the interest of getting drugs to patients faster, to

843
00:49:00,680 --> 00:49:05,640
Speaker 2: approve drugs based on predictive markers of efficacy and confirming

844
00:49:05,680 --> 00:49:10,000
Speaker 2: they work later in follow up studies, whereas Europe is

845
00:49:10,040 --> 00:49:13,160
Speaker 2: still kind of old school and wants to see more

846
00:49:13,480 --> 00:49:17,480
Speaker 2: proof of clinical benefit before you know the government payer

847
00:49:17,600 --> 00:49:20,279
Speaker 2: starts doling out cash to pay for these things. So

848
00:49:20,840 --> 00:49:23,680
Speaker 2: there's actually, I think a little bit more willingness to

849
00:49:23,719 --> 00:49:29,479
Speaker 2: be speculative in the approval process here in the US

850
00:49:29,480 --> 00:49:30,360
Speaker 2: than there is in Europe.

851
00:49:30,520 --> 00:49:36,000
Speaker 1: So it sounds like you're suggesting private insurance is allowing

852
00:49:36,080 --> 00:49:39,359
Speaker 1: the FDA to be a little more aggressive in Hey,

853
00:49:39,400 --> 00:49:43,000
Speaker 1: maybe this safe some people, let's try it, versus you

854
00:49:43,040 --> 00:49:44,800
Speaker 1: have a government saying, we don't want to pay for

855
00:49:44,880 --> 00:49:47,520
Speaker 1: this unless we know it's safe and effective, and so

856
00:49:47,640 --> 00:49:48,719
Speaker 1: far you haven't demonstrated that.

857
00:49:48,680 --> 00:49:51,680
Speaker 2: One hundred percent. And in the past that was FDA's

858
00:49:51,680 --> 00:49:54,800
Speaker 2: mandate also, and I would imagine if you have FDA

859
00:49:55,040 --> 00:49:56,960
Speaker 2: you know, administrators in front of you, they would try

860
00:49:56,960 --> 00:50:00,759
Speaker 2: to insist that's still their mandate. But you know, as

861
00:50:00,760 --> 00:50:04,759
Speaker 2: a matter of just observation, there are more and more

862
00:50:04,800 --> 00:50:08,400
Speaker 2: drugs that are getting approved on the basis of predictions

863
00:50:08,440 --> 00:50:11,120
Speaker 2: of their efficacy rather than proof of their efficacs.

864
00:50:11,200 --> 00:50:13,879
Speaker 1: What about all of the off brand approvals we see

865
00:50:13,880 --> 00:50:17,400
Speaker 1: in the beginning, which really is what the GLP began, right,

866
00:50:17,680 --> 00:50:20,359
Speaker 1: The most famous example is Viagara was supposed to be

867
00:50:20,719 --> 00:50:24,440
Speaker 1: a cardiac medicine or a blood pressure medicine. How does

868
00:50:24,440 --> 00:50:27,879
Speaker 1: that play into what the FDA is doing in terms of, hey,

869
00:50:27,960 --> 00:50:30,160
Speaker 1: let's get it out there at least if it's safe.

870
00:50:30,520 --> 00:50:32,879
Speaker 1: We'll find out if it's effective only after it's out

871
00:50:32,880 --> 00:50:33,560
Speaker 1: there for a while.

872
00:50:33,640 --> 00:50:36,360
Speaker 2: Right. That's It's an interesting part of I think just

873
00:50:36,440 --> 00:50:39,680
Speaker 2: the you know, the cultural differences between America and Europe

874
00:50:39,719 --> 00:50:42,480
Speaker 2: and kind of how you know, we embrace, you know,

875
00:50:42,680 --> 00:50:45,920
Speaker 2: certain levels of freedoms here that we talk about as Americans,

876
00:50:46,239 --> 00:50:48,560
Speaker 2: and one of them is the concept that you know,

877
00:50:48,600 --> 00:50:52,520
Speaker 2: once drugs are approved by FDA, physicians have the ability

878
00:50:52,640 --> 00:50:55,839
Speaker 2: to use them in ways that they think are appropriate.

879
00:50:56,239 --> 00:50:58,680
Speaker 2: Whereas in Europe, you know, to really be able to

880
00:50:58,760 --> 00:51:03,799
Speaker 2: use a drug outside of its prescribed usage is going

881
00:51:03,840 --> 00:51:05,600
Speaker 2: to be difficult because the government's not going to pay

882
00:51:05,640 --> 00:51:05,839
Speaker 2: for it.

883
00:51:06,200 --> 00:51:10,439
Speaker 1: Question on Cutter. You know, when we look at out

884
00:51:10,440 --> 00:51:13,759
Speaker 1: in Hedge fund Lands, we know allocators tend to buy

885
00:51:13,920 --> 00:51:17,760
Speaker 1: brand their's safety in numbers. I'm looking at big shops

886
00:51:17,880 --> 00:51:20,759
Speaker 1: like not just Millennium in Citadel, but go down the

887
00:51:20,800 --> 00:51:24,440
Speaker 1: list of oak Tree or Bridgewater or you know whoever

888
00:51:24,480 --> 00:51:28,120
Speaker 1: you want to think of. That's a large, reputable shop.

889
00:51:28,440 --> 00:51:31,319
Speaker 1: You were previously at a multi manager shop. Now that

890
00:51:31,360 --> 00:51:36,000
Speaker 1: you're on the other side outside of Citadel, how are

891
00:51:36,000 --> 00:51:39,839
Speaker 1: you managing dealing with the consulting worlds and the institutional

892
00:51:39,840 --> 00:51:42,720
Speaker 1: investors as a single strategy manager.

893
00:51:43,239 --> 00:51:45,399
Speaker 2: One of the things I think when I embarked upon

894
00:51:45,440 --> 00:51:49,200
Speaker 2: that was an unknown to me that I've been somewhat

895
00:51:49,200 --> 00:51:52,840
Speaker 2: pleasantly surprised to the upside of. As now a launched

896
00:51:53,000 --> 00:51:59,000
Speaker 2: manager is there's a relatively robust infrastructure of support that

897
00:51:59,160 --> 00:52:04,440
Speaker 2: has developed around emerging managers such as us to provide

898
00:52:04,800 --> 00:52:07,640
Speaker 2: a lot of the tools, a lot of the operational

899
00:52:07,680 --> 00:52:10,480
Speaker 2: infrastructure that you're accustomed to at one of those larger

900
00:52:10,520 --> 00:52:15,960
Speaker 2: firms as third party vendored services. And so while we

901
00:52:16,080 --> 00:52:20,400
Speaker 2: are independent of what is a well developed infrastructure one

902
00:52:20,440 --> 00:52:25,000
Speaker 2: of those larger firms, we were able to replicate substantive

903
00:52:25,280 --> 00:52:28,840
Speaker 2: portion of that enough to have a robust investment process

904
00:52:29,480 --> 00:52:34,000
Speaker 2: through identification of other vendors who realize the value of

905
00:52:34,040 --> 00:52:36,600
Speaker 2: providing that service and provided to a much broader community.

906
00:52:36,719 --> 00:52:41,440
Speaker 2: So it hasn't been as bad as I first feared

907
00:52:41,440 --> 00:52:42,240
Speaker 2: when we came out.

908
00:52:42,400 --> 00:52:46,080
Speaker 1: Really fascinating stuff, Vince. Let's jump to our favorite questions

909
00:52:46,120 --> 00:52:49,640
Speaker 1: that we ask all of our guests, starting with what's

910
00:52:49,719 --> 00:52:52,320
Speaker 1: keeping you entertained these days? What are you either watching

911
00:52:52,520 --> 00:52:53,200
Speaker 1: or listening to?

912
00:52:53,640 --> 00:52:58,120
Speaker 2: In terms of streaming content. I just wrapped up season

913
00:52:58,160 --> 00:53:00,200
Speaker 2: three of The Bear, which is a terrific show. I

914
00:53:00,320 --> 00:53:02,200
Speaker 2: actually lived for a few years in Chicago, so that

915
00:53:02,280 --> 00:53:05,040
Speaker 2: kind of pulls at my you know, reminiscences of being there.

916
00:53:05,360 --> 00:53:07,400
Speaker 1: Even if it was season three wasn't as good as

917
00:53:07,400 --> 00:53:09,160
Speaker 1: season two, it was still it.

918
00:53:09,120 --> 00:53:11,480
Speaker 2: Was still terrific. Yeah, and now.

919
00:53:11,200 --> 00:53:13,239
Speaker 1: Some of the reviews kind of missed the point.

920
00:53:13,400 --> 00:53:14,839
Speaker 2: They missed the point of what it is. It really

921
00:53:14,920 --> 00:53:16,960
Speaker 2: was a year of just delving into the background of

922
00:53:17,000 --> 00:53:19,439
Speaker 2: these characters in a in a richer way than most

923
00:53:19,440 --> 00:53:23,040
Speaker 2: shows spend the time doing. And so right now working

924
00:53:23,040 --> 00:53:25,799
Speaker 2: our way through Bad Monkey, which is really you know,

925
00:53:25,840 --> 00:53:28,720
Speaker 2: I think sometimes you need a little bit of lightness

926
00:53:28,760 --> 00:53:31,279
Speaker 2: and levity in terms of what you're watching. Vince Vaughn

927
00:53:32,040 --> 00:53:35,320
Speaker 2: on Apple TV. And it's just a really easy watch.

928
00:53:35,520 --> 00:53:38,919
Speaker 2: I mean, there's nothing so amusing, there's nothing fascinating about it.

929
00:53:38,920 --> 00:53:41,560
Speaker 2: It's just a very easy watch. And I'm looking forward

930
00:53:41,560 --> 00:53:44,000
Speaker 2: to season two of Pachinko. It speaks a little bit

931
00:53:44,040 --> 00:53:47,840
Speaker 2: to my Korean heritage. Season one was just a fascinating

932
00:53:47,840 --> 00:53:51,520
Speaker 2: immigrant story of Korean family based on a terrific book.

933
00:53:51,920 --> 00:53:54,959
Speaker 1: I saw that go by in previews and I never

934
00:53:55,160 --> 00:53:58,200
Speaker 1: got around to seeing it. Strong endorsement, Yeah, worth the

935
00:53:58,239 --> 00:54:01,440
Speaker 1: watch for sure, really really interesting. I'm gonna definitely check

936
00:54:01,480 --> 00:54:04,920
Speaker 1: that out. You hinted but didn't really dive into a

937
00:54:04,960 --> 00:54:08,080
Speaker 1: lot about your early mentors. Tell us who were some

938
00:54:08,200 --> 00:54:10,480
Speaker 1: of the people who helped shape your career.

939
00:54:10,680 --> 00:54:13,960
Speaker 2: Sure, so I think that probably one of the most

940
00:54:14,040 --> 00:54:17,080
Speaker 2: talented healthcare investors the world hasn't heard of is Jeff Green,

941
00:54:17,280 --> 00:54:21,200
Speaker 2: who I spent years with at Healthcore and who was

942
00:54:21,200 --> 00:54:25,440
Speaker 2: my first portfolio manager at Citadel. And what Jeff brought

943
00:54:25,480 --> 00:54:30,160
Speaker 2: to me was this ability to really appreciate the power

944
00:54:30,640 --> 00:54:33,400
Speaker 2: of the rate of change in a story, the second

945
00:54:33,400 --> 00:54:38,440
Speaker 2: derivative of movement in a narrative. And he had the

946
00:54:38,440 --> 00:54:42,400
Speaker 2: ability to look at very very complicated stories, very complicated topics,

947
00:54:42,440 --> 00:54:47,520
Speaker 2: complicated drug development studies, and kind of point out if

948
00:54:47,520 --> 00:54:51,719
Speaker 2: you understand this, it's the key that unlocks the view

949
00:54:51,719 --> 00:54:55,120
Speaker 2: of the whole trade, if you understand this portion of

950
00:54:55,160 --> 00:54:57,480
Speaker 2: the income statement, this portion of the tamp And so

951
00:54:57,520 --> 00:54:59,520
Speaker 2: he was able to go from story to story and

952
00:54:59,600 --> 00:55:03,160
Speaker 2: really hone in on all other things being equal, this

953
00:55:03,320 --> 00:55:05,919
Speaker 2: is what you need to know. And so I learned

954
00:55:05,960 --> 00:55:09,840
Speaker 2: a lot from working with him. More recently in the

955
00:55:09,880 --> 00:55:13,200
Speaker 2: launch of Cutter, I have to say that a mentor

956
00:55:13,239 --> 00:55:17,200
Speaker 2: for me is actually my fiance, who runs her own

957
00:55:17,280 --> 00:55:21,680
Speaker 2: business and who in times where I faced a little

958
00:55:21,680 --> 00:55:24,279
Speaker 2: bit of self doubt or challenges about going down this path,

959
00:55:24,719 --> 00:55:27,120
Speaker 2: I had this relentless attitude of where failure was not

960
00:55:27,160 --> 00:55:29,960
Speaker 2: an option and you know, pick yourself up and carry

961
00:55:30,000 --> 00:55:31,839
Speaker 2: to the next day because you're going to do this,

962
00:55:32,440 --> 00:55:36,160
Speaker 2: no tapping out, no, yeah, and she's she's terrific at that.

963
00:55:36,560 --> 00:55:39,200
Speaker 1: Huh. Let's talk about books. What are some of your favorites?

964
00:55:39,200 --> 00:55:40,400
Speaker 1: What are you reading right now?

965
00:55:40,680 --> 00:55:46,080
Speaker 2: So right now reading Marshall Goldsmith has his book The

966
00:55:46,160 --> 00:55:50,360
Speaker 2: Earned Life. He is a life coach for a number

967
00:55:50,480 --> 00:55:53,719
Speaker 2: of executives. He's written a ton of books just kind

968
00:55:53,719 --> 00:55:57,120
Speaker 2: of about, you know, the whole self discovery process. I

969
00:55:57,160 --> 00:56:01,000
Speaker 2: think he incorporates some takes from buddhistfulosophy that I kind

970
00:56:01,040 --> 00:56:05,879
Speaker 2: of feel speak to me. And in particular, it's about

971
00:56:05,880 --> 00:56:09,480
Speaker 2: defining your own success. We're in a world where you

972
00:56:09,520 --> 00:56:12,799
Speaker 2: can get very very much focused on, you know what,

973
00:56:14,200 --> 00:56:17,759
Speaker 2: certainly what other people make, or what other people's performance are,

974
00:56:18,000 --> 00:56:20,879
Speaker 2: or just in general comparing yourself to other people in

975
00:56:20,880 --> 00:56:24,360
Speaker 2: this field, and I feel like it's important to have

976
00:56:24,440 --> 00:56:28,560
Speaker 2: perspective on the definition of success being something you define

977
00:56:28,560 --> 00:56:32,480
Speaker 2: for yourself and being satisfied, you know, in terms of

978
00:56:32,560 --> 00:56:36,160
Speaker 2: your own personal journey, which is unique to everyone. So

979
00:56:36,200 --> 00:56:38,799
Speaker 2: that's really fascinating. In terms of prior books that I

980
00:56:38,800 --> 00:56:42,040
Speaker 2: read that I have to discuss that are influential. Annie

981
00:56:42,080 --> 00:56:45,720
Speaker 2: Duke's Speaking Bets is really one that I think spoke

982
00:56:45,760 --> 00:56:49,520
Speaker 2: to me in terms of resonating with our investment process,

983
00:56:50,040 --> 00:56:54,000
Speaker 2: understanding that for her in her career in poker, there

984
00:56:54,080 --> 00:56:56,120
Speaker 2: was really nothing to be gained from just dwelling on

985
00:56:56,160 --> 00:56:59,320
Speaker 2: bad beat stories, and there's really nothing to be gained from,

986
00:56:59,400 --> 00:57:01,440
Speaker 2: you know, kind of worrying about success of failure of

987
00:57:01,440 --> 00:57:03,880
Speaker 2: an individual hand. It's really about the process.

988
00:57:03,680 --> 00:57:07,520
Speaker 1: Right, resulting is failure. You have to if you're only

989
00:57:07,520 --> 00:57:10,000
Speaker 1: looking at the outcome. She's great at that.

990
00:57:10,160 --> 00:57:13,040
Speaker 2: So that's taking in bets is really and yeah, thinking

991
00:57:13,040 --> 00:57:15,439
Speaker 2: in bets and and i'd have to say the last

992
00:57:15,440 --> 00:57:17,360
Speaker 2: book I would mention, which I know has been mentioned

993
00:57:17,400 --> 00:57:20,440
Speaker 2: numerous times in this podcast, but there's a reason for

994
00:57:20,480 --> 00:57:23,480
Speaker 2: that is if you're in this business, it's almost like

995
00:57:23,480 --> 00:57:26,040
Speaker 2: a cult need to read Reminiscences of a stock operator.

996
00:57:26,480 --> 00:57:28,160
Speaker 2: It comes up over and over, and there's a reason

997
00:57:28,200 --> 00:57:28,640
Speaker 2: for it.

998
00:57:28,640 --> 00:57:30,280
Speaker 1: It was one of the first things I read when

999
00:57:30,320 --> 00:57:33,760
Speaker 1: I began on a trading desk, and you it really

1000
00:57:34,560 --> 00:57:38,320
Speaker 1: arguably was the first behavioral book because it was not

1001
00:57:38,480 --> 00:57:41,200
Speaker 1: about by the cell that it was about here's how

1002
00:57:41,280 --> 00:57:43,920
Speaker 1: traders go wrong. It was it's really fascinating and it

1003
00:57:44,160 --> 00:57:46,000
Speaker 1: still holds up a century later.

1004
00:57:46,160 --> 00:57:46,680
Speaker 2: Absolutely.

1005
00:57:47,000 --> 00:57:49,880
Speaker 1: All right, our final two questions, what sort of advice

1006
00:57:49,880 --> 00:57:53,440
Speaker 1: would you give to a recent college grad interested in

1007
00:57:53,480 --> 00:57:56,080
Speaker 1: a career in healthcare investing?

1008
00:57:56,560 --> 00:57:59,560
Speaker 2: I would say, and I'd broaden this, you know, for

1009
00:57:59,640 --> 00:58:02,880
Speaker 2: a moment into whatever type of avenue you'd want to

1010
00:58:02,920 --> 00:58:06,400
Speaker 2: go down. It really helps to spend time at this

1011
00:58:06,560 --> 00:58:09,000
Speaker 2: point of your life speaking to a college grad to

1012
00:58:09,120 --> 00:58:12,040
Speaker 2: become more of a domain specialist in whatever area that

1013
00:58:12,120 --> 00:58:15,200
Speaker 2: really fascinates you. You can pivot into the finance world later.

1014
00:58:15,680 --> 00:58:18,680
Speaker 2: The finance skill sets are the basics you'll have to learn.

1015
00:58:18,760 --> 00:58:21,760
Speaker 2: Their training is very, very fungible, and it's almost commoditized

1016
00:58:21,800 --> 00:58:23,760
Speaker 2: to kind of know what it takes to be informed

1017
00:58:23,760 --> 00:58:27,160
Speaker 2: on the underpinnings of finance. But really, your expertise is

1018
00:58:27,200 --> 00:58:30,320
Speaker 2: going to come from finding something you're passionate about and

1019
00:58:30,400 --> 00:58:32,480
Speaker 2: learning as much as you can about it, immersing yourself

1020
00:58:32,480 --> 00:58:35,880
Speaker 2: in that world, and coming out of that you'll think

1021
00:58:35,920 --> 00:58:37,800
Speaker 2: better about how to make investments in something you have

1022
00:58:37,840 --> 00:58:39,720
Speaker 2: that level of domain expertise.

1023
00:58:39,760 --> 00:58:43,000
Speaker 1: And our final question, what do you know about the

1024
00:58:43,040 --> 00:58:46,320
Speaker 1: world of investing today? You wish you knew twenty twenty

1025
00:58:46,360 --> 00:58:48,880
Speaker 1: five years ago, when you were first getting started.

1026
00:58:48,760 --> 00:58:53,960
Speaker 2: I would say thirty years ago, I would tell myself

1027
00:58:55,040 --> 00:59:02,400
Speaker 2: that the idea that a good successful investor leans in

1028
00:59:02,520 --> 00:59:07,560
Speaker 2: on conviction and intuition as their guide posts is kind

1029
00:59:07,600 --> 00:59:10,720
Speaker 2: of like false idolatry. I think, you know, if you

1030
00:59:10,760 --> 00:59:12,760
Speaker 2: take any talented investor in general and you ask them

1031
00:59:12,800 --> 00:59:15,000
Speaker 2: to give you your ten best ideas for the next year,

1032
00:59:15,680 --> 00:59:18,240
Speaker 2: if they get seven, eight correct, terrific. But then if

1033
00:59:18,280 --> 00:59:20,439
Speaker 2: you tell them to rank order them, it's not eight,

1034
00:59:20,520 --> 00:59:23,440
Speaker 2: nine and ten that fail all up your conviction scale.

1035
00:59:23,440 --> 00:59:26,760
Speaker 2: You fail. So I think I would tell myself previously

1036
00:59:27,320 --> 00:59:31,240
Speaker 2: it's much more important to develop a robust set of

1037
00:59:31,280 --> 00:59:35,640
Speaker 2: guide posts in investing, a robust process of investing, rather

1038
00:59:35,800 --> 00:59:38,240
Speaker 2: than just worshiping this idol of like, look, I need

1039
00:59:38,280 --> 00:59:40,680
Speaker 2: max conviction on an idea that's going to be you know,

1040
00:59:41,080 --> 00:59:41,880
Speaker 2: career setting.

1041
00:59:42,280 --> 00:59:45,440
Speaker 1: Quite fascinating. Vince, thank you for being so generous with

1042
00:59:45,480 --> 00:59:48,560
Speaker 1: your time. We have been speaking with Vince Aida. He

1043
00:59:48,760 --> 00:59:54,040
Speaker 1: is the founder and chief investment officer of Cutter Capital Management.

1044
00:59:54,600 --> 00:59:58,040
Speaker 1: If you enjoy this conversation, well check out any of

1045
00:59:58,080 --> 01:00:00,960
Speaker 1: the previous five hundred or so we've done over the

1046
01:00:01,000 --> 01:00:06,640
Speaker 1: past ten years. You can find those at iTunes, Spotify, YouTube,

1047
01:00:07,000 --> 01:00:10,920
Speaker 1: wherever you find your favorite podcast, and be sure and

1048
01:00:11,000 --> 01:00:14,760
Speaker 1: check out my new podcast, At the Money, short ten

1049
01:00:14,800 --> 01:00:20,240
Speaker 1: minute discussions with experts about issues that directly affect your

1050
01:00:20,360 --> 01:00:23,840
Speaker 1: investing and your money, earning it, spending it, and most

1051
01:00:23,880 --> 01:00:27,560
Speaker 1: importantly investing it At the Money in the Master's in

1052
01:00:27,640 --> 01:00:32,120
Speaker 1: Business feed or wherever you find your favorite podcasts. I

1053
01:00:32,120 --> 01:00:34,240
Speaker 1: would be remiss if I did not thank the crack

1054
01:00:34,320 --> 01:00:37,680
Speaker 1: team that helps us put these conversations together each week.

1055
01:00:37,880 --> 01:00:42,760
Speaker 1: Stephen Gonzalez is my audio engineer. Anna Luke is my producer.

1056
01:00:42,880 --> 01:00:46,880
Speaker 1: Sean Russo is head of Research. Sage Bauman is head

1057
01:00:46,920 --> 01:00:51,080
Speaker 1: of Podcasts Here at Bloomberg, I'm Barry Richolts. You've been

1058
01:00:51,160 --> 01:00:54,880
Speaker 1: listening to Masters in Business on Bloomberg Radio.