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

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Speaker 2: Hello and welcome to another episode of the Odd Lots podcast.

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Speaker 2: I'm Jill Wisenthal and I'm Tracy Alloway. Tracy, there's a

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Speaker 2: lot we've discussed about multi strategy hedge funds, but there's

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Speaker 2: still a lot we don't know. And specifically, although I've

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Speaker 2: come to learn things about comp and alignment and the

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Speaker 2: importance of risk management and risk models and all that stuff,

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Speaker 2: I actually don't know, like how how the pods make

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Speaker 2: good trade.

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Speaker 3: This is part two hundred and ninety eight of our

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Speaker 3: attempt to understand multi strat hedge funds.

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Speaker 2: That's what it is.

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Speaker 3: But you're right, we haven't really looked at it from

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Speaker 3: the I guess the perspective of a PM who is

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Speaker 3: actually working there, and what it takes to get hot fired,

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Speaker 3: what it takes to avoid getting fired, and things like that.

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Speaker 2: I have a feeling that like avoiding getting fired is

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Speaker 2: a really big part of the story, Like you want

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Speaker 2: to do well right, you want to make money and

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Speaker 2: all that, but I also get the impression that you

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Speaker 2: just want to hang onto that seat for a really

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Speaker 2: long time, and that a big part of I don't

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Speaker 2: know if the game is the word. But a big

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Speaker 2: part of the game is yeah, holding onto that seat,

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Speaker 2: avoiding being part of any given call, Avoiding having your

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Speaker 2: name show up on Bloomberg in a story that gets

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Speaker 2: read spiked about so and so out after losing two

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Speaker 2: hundred and sixty million or whatever in the trade.

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Speaker 3: This is exactly what I was wondering, like, how do

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Speaker 3: the drawdowns actually impact a bunch of pms. Is it

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Speaker 3: like really embarrassing and does it have like an actual

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Speaker 3: effect on their trading? I imagine it does, and it

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Speaker 3: must have an effect on their confidence as well. But

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Speaker 3: I am very interested in this subject, and we have

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Speaker 3: joked a number of times about, you know, if we

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Speaker 3: were at a multistrat hedge fund things like that. So

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Speaker 3: maybe we'll get a better idea.

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Speaker 2: We definitely have to learn more about the pod level,

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Speaker 2: because I do get the pressure from talking to some people.

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Speaker 2: We talked to Running Cosgrave recently. It's like, oh, you

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Speaker 2: just put a bunch of people in a room and

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Speaker 2: if you have the risk management right, it kind of

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Speaker 2: works out. Anyway, We're going to continue our journey of

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Speaker 2: learning more about these big out.

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Speaker 3: There's a natural affinity between podcasts and pod shops.

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Speaker 2: Oh, it's pretty sad. God, wouldn't you hate it if,

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Speaker 2: like if we screwed up or like we had like

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Speaker 2: an episode that didn't do very well and our traffic

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Speaker 2: was down or something, and there was like a big

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Speaker 2: article on It's like Joey Tracy out after you know,

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Speaker 2: after one month of underperformance of the podcast.

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Speaker 3: Oh yeah, Well, this is the other thing, Like what

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Speaker 3: happens if you outperform for like half the year and

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Speaker 3: then you underperform for the second half of the year,

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Speaker 3: And how is that actually calculated in terms of your comp.

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Speaker 2: Totally And this came up before, which is that people

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Speaker 2: who have really good starts the fund at the fund level,

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Speaker 2: you don't want them taking off risk just to lock

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Speaker 2: in their annual bonuses. These are important questions. Anyway, let's

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Speaker 2: dive right into it. We have the perfect guest, someone

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Speaker 2: with a long track record and experience across many as

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Speaker 2: spects of this space. We're going to be speaking with

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Speaker 2: Brian Yelvington. He's currently a consultant for executive search firm

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Speaker 2: Carrington Fox, but he's been a former analyst in PM

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Speaker 2: at several large multi strat funds, Millennium or Capital et cetera,

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Speaker 2: A few others in there, and so up. Brian, thank

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Speaker 2: you so much for coming on odd lots.

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Speaker 4: Thank you for having me. Great to be here. I

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Speaker 4: always enjoy the podcast and enjoy hearing the very subject

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Speaker 4: you guys come up with.

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Speaker 2: Oh, thank you, we'd love to hear it. We're gonna

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Speaker 2: clip that and put it in the mix before we

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Speaker 2: go on, like why do you just give us the

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Speaker 2: real brief version of like who are you? And why

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Speaker 2: are we talking to you? Other than the fact that

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Speaker 2: if I go to your LinkedIn page there are a

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Speaker 2: bunch of famous companies listed on it.

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Speaker 4: Yeah, probably a few too many for my taste, to

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Speaker 4: be honest, I've kind of been one of the few

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Speaker 4: people who've been both a pod PM as well as

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Speaker 4: kind of helped bring those people into a large multi strat.

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Speaker 4: I left the risk taking world and went to work

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Speaker 4: in the business development area. Business development is just to

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Speaker 4: badly disguise you from this for manager selection, although it

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Speaker 4: means very different things at very different firms. So I've

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Speaker 4: seen it both from junior analysts side to a senior

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Speaker 4: PM to the person who's the necessary, if not sufficient

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Speaker 4: gatekeeper at a hedge fund.

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Speaker 3: I'm trying to think where to start because there's so

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Speaker 3: much for us to talk about. But if I'm a

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Speaker 3: PM and I am applying to a multi strat, what

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Speaker 3: would my CV or resume actually look like? And then

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Speaker 3: b would I even be applying to a multi strat?

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Speaker 3: Or would I be headhunted and they would find me?

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Speaker 4: The chances are generally better that if you're an established PM,

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Speaker 4: you would probably come either through direct from the BD

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Speaker 4: team who said, we need somebody who represents the same

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Speaker 4: risk that Tracy represents. We hear she's great, We'd love

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Speaker 4: to speak to her, or through an executive search firm

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Speaker 4: who's there's a lot of turnover in this industry and

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Speaker 4: they do a lot of business as a result.

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Speaker 2: So how do you know if someone is actually good?

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Speaker 2: Because this seems to be like one of the core

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Speaker 2: challenges in really all investing, right, like past results are

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Speaker 2: no guarantee of future returns. Everything always says that you

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Speaker 2: don't know what's just a lucky streak, et cetera. So

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Speaker 2: let's go through this process you want to establish if

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Speaker 2: someone is actually a good investor or trader or portfolio

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Speaker 2: manager or whatever. Walk us through the steps of like

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Speaker 2: how you actually would identify if Tracy is good at

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Speaker 2: her job exactly.

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Speaker 4: Well, first to caveat, you're never going to know, Okay.

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Speaker 4: The reason that past performance is not indicative of future

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Speaker 4: returns is because it's the future and we never know

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Speaker 4: how somebody's going to act. So what I'm going to

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Speaker 4: do during our first conversation Tracy is I'm going to

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Speaker 4: ask sort of like you guys did a little bit

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Speaker 4: about your background. I'm going to be looking for things

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Speaker 4: like where we might know people in common, where you

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Speaker 4: might have worked through a really good group or something

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Speaker 4: like that that had a great reputation. And then we're

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Speaker 4: going to get into the nitty gritty of the conversation

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Speaker 4: where I asked you in great detail, you know, what

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Speaker 4: is your edge? That part's actually not too detailed. You

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Speaker 4: should be able to elucidate that sort of standing on

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Speaker 4: one foot. Then I'm going to go into wait.

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Speaker 2: Yeah, can you pause, just give me if that's an

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Speaker 2: easy part, what is it? Because this is actually something

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Speaker 2: that I'm completely in the dark about. How does someone

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Speaker 2: go about articulating an edge in plan English during an interview?

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Speaker 2: Like what does that actually sound like? You say? Okay,

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Speaker 2: Like Brian, what's your edge. You used to trade fixed

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Speaker 2: income at where and where? Brian, what was your age?

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Speaker 4: Well, I probably didn't have a very good one, but

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Speaker 4: my edge was usually from the research side. What I

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Speaker 4: will tell you is pms who are extremely good at

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Speaker 4: their jobs, have boiled down what their edge is to

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Speaker 4: a very well defined two or three sentence elevator pitch

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Speaker 4: style answer. And the reason that they're able to do

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Speaker 4: that is because this is something they've been doing a

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Speaker 4: long time, and they've made a huge number of mistakes,

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Speaker 4: and they know exactly the alpha that they want to identify,

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Speaker 4: are good at identifying and what they go after. So

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Speaker 4: it's going to sound different for everybody. For you know,

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Speaker 4: a macro RV type of fund, it may be that

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Speaker 4: they really anticipate the the shifts and monetary policy. For

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Speaker 4: a credit fund, it's that maybe they understand, you know,

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Speaker 4: corporate actions and they're really good at reading between the

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Speaker 4: lines of maybe even a specific niche of companies. So

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Speaker 4: it's going to differ, but you can usually tell by

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Speaker 4: someone's answer there how much they thought of it. The

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Speaker 4: bad answers tend to be something that relies on experience.

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Speaker 4: I'll note that there are too many octagenarian PMS or

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Speaker 4: something that relies on well, I'm just really good at this.

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Speaker 4: You kind of have to be able to identify it

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Speaker 4: to be good at it.

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Speaker 3: So going back to performance metrics, like what figures or

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Speaker 3: numbers are actually available? Well, here, you know, does a

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Speaker 3: potential PM come bearing sharp ratios? And then how does

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Speaker 3: the potential hiring firm actually do due diligence on some

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Speaker 3: of those numbers.

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Speaker 4: It's difficult. And the reality is that you know P

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Speaker 4: and L even within a firm as a BD person,

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Speaker 4: and again BD is very different from firm to firm.

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Speaker 4: But if I were to hire Tracy as PM.

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Speaker 3: I'm regretted using myself as an example, by the way.

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Speaker 4: No, we're going to have you do well, okay, right,

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Speaker 4: we'll flunk out somebody else. But if we were to

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Speaker 4: hire Tracy in some places, I might not even be

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Speaker 4: aware of how she's doing six months after we hired,

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Speaker 4: and others I would have kind of perfect inside p

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Speaker 4: and ls are extremely closely guarded secrets and usually they're

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Speaker 4: not discussed within the firm except for a very few

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Speaker 4: select group of people. And nobody's going to attest to

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Speaker 4: that P and L. Right, you of your own accord, Tracy,

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Speaker 4: might provide some assurance to somebody. Maybe it's because your

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Speaker 4: past cap or something. They can't ask, but you can

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Speaker 4: certainly say, hey, by the way, there's proof that I

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Speaker 4: did what I did. That's your priority.

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Speaker 2: Wait why can't they ask?

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Speaker 4: I believe that's the employment law. Yeah, you're allowed to ask.

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Speaker 4: It might not been designed to protect hedge fund pms,

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Speaker 4: but I believe it does cover them somewhat.

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Speaker 2: Tracy, I've brought up a bunch of chodes. I told you.

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Speaker 2: I have talked about the time that I interviewed at

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Speaker 2: a prop trading firm, right many many times.

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Speaker 3: Joe, Yes, are you going to tell the story again?

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Speaker 3: You can if you want.

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Speaker 2: I'll just tell the brief one, which is that when

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Speaker 2: I was living in Austin, which you are, Brian, you're

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Speaker 2: there now, I interviewed at a prop trading firm when

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Speaker 2: I was right out of college. There were two hundred interviews,

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Speaker 2: and they asked me about my own trading when I

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Speaker 2: used to date trade on each trade by myself, and

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Speaker 2: I told them a little about my trades. They made

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Speaker 2: me play a video game to test my hand and

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Speaker 2: I coordination, and then they made me play ping pong

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Speaker 2: against the CEO. I'm not really sure what that was

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Speaker 2: all about, but then I was one of I was one.

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Speaker 2: I was one of four people who got to offer

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Speaker 2: the job, and then for some reason I didn't take it.

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Speaker 3: Didn't you work at a sandwich shop?

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Speaker 2: To the now, I'm making sandwiches at the Wheatsville food

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Speaker 2: co Op at the time, and all my friends were

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Speaker 2: working there. I was like, I don't really feel like

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Speaker 2: working the corporate life just yet. And everything worked out

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Speaker 2: and it was fine. That's still one of the stranger

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Speaker 2: times in my life. But it was kind of like

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Speaker 2: this where they asked me specifics. All right, here's a

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Speaker 2: more important question. It's great to say, like, if you're

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Speaker 2: a PM, then you show, but the first you got

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Speaker 2: to become a PM. What does an analyst do? So

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Speaker 2: so a PM has a pod and they have analysts

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Speaker 2: in their pod, what does an analyst actually do?

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Speaker 4: Just as with the street, you know how they're analysts

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Speaker 4: and function and analysts and rank as you will, pods

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Speaker 4: will generally have analysts covering, you know, specific areas. Basically

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Speaker 4: at most firms, it's sort of a euphemism. If you

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Speaker 4: have trading authority you're either a trader, a SUBPM, or

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Speaker 4: a PM. If you do not have trading authority, but

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Speaker 4: you're still committing or contributing to investment decisions, you're an analyst.

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Speaker 4: It's just a generic catch all term. But you are

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Speaker 4: generally in charge of building the you know, specific type

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Speaker 4: of surveillance that the pod needs. You may have names

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Speaker 4: or industries or specific areas of a specific market to cover,

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Speaker 4: and you're being eyes and ears, and you will have

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Speaker 4: specific projects. Yeah, in our current environment, there's no no

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Speaker 4: shortage of things to test out and look into as

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Speaker 4: to how policies may change. So if you're in a macropod,

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Speaker 4: you're probably pretty busy right now.

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Speaker 3: Presumably you don't have to make perfect PowerPoint presentations for

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Speaker 3: potential deals and things like that. It's much more idea

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Speaker 3: generation and I guess like back testing.

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Speaker 4: There's you know there. Again, it kind of depends on

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Speaker 4: the type of pod that you're in. If you're in

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Speaker 4: a very directional macropod, you're probably looking for a lot

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Speaker 4: of historical analogs, you know, house pods, he responded in

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Speaker 4: the past. If you are in a more quantitatively oriented pod,

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Speaker 4: maybe something that does some form of arbitrage. He has

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Speaker 4: lots of back testing, lots of mathematical confetency. But it's

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Speaker 4: interesting who I've seen make the jump. I've seen a salesperson.

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Speaker 4: We basically just sent out a weekly commentary with a

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Speaker 4: model portfolio in it, and people loved it, and PM said, Hey,

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Speaker 4: we want to talk to this person. Who you go

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Speaker 4: talk to him? For US analysts public machine analysts. Joey

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Speaker 4: and I actually have a mutual friend that you've had

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Speaker 4: on the show before who was kind of writing for

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Speaker 4: a newsletter, and it was a newsletter. I can tell

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Speaker 4: you that most every PM I knew in macro was

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Speaker 4: reading and he built his audience on Twitter or X. Sorry,

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Speaker 4: that doesn't make a very good verb.

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Speaker 3: All right? And then if I am running a pod shop,

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Speaker 3: what exactly am I looking for in terms of potential PM?

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Speaker 3: So I get probably past performance, even though as we discussed,

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Speaker 3: it's not a perfect indicator of future performance. But am

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Speaker 3: I looking at personality like would I hire a complete

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Speaker 3: jerk who happens to be a star trader because it

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Speaker 3: doesn't really matter how he works with other people because

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Speaker 3: he's going to be completely independent, Or would I be

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Speaker 3: looking at it very holistically and taking a sort of

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Speaker 3: moneyball approach where I'm trying to fill in or plug

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Speaker 3: specific gaps in my overall business with maybe players or

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Speaker 3: traders that are undervalued by the market.

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Speaker 4: I think you're always trying to play the moneyball approach. However,

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Speaker 4: most puge funds differ a lot in how internally they communicate.

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Speaker 4: There are some hedge funds where you're really not allowed

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Speaker 4: to talk to people from other pods, Like I might

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Speaker 4: say something to you Tracy, like I like the market here,

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Speaker 4: I don't like it here, But I would never say,

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Speaker 4: you know, I'm shorting the two year versus the three year.

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Speaker 4: DBO one weighted something specific, and that's to avoid kind

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Speaker 4: of cross contamination of the pods. Whereas there are others

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Speaker 4: who really value the esprie de corps and they like

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Speaker 4: to have people collaborate and those places. Not only are

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Speaker 4: you going to have the typical meetings with BD and

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Speaker 4: risk and the CIO, but you're also going to meet

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Speaker 4: a lot of other pms to make sure that you

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Speaker 4: know you're not a jerk.

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Speaker 2: Let's talk more about getting a job as an analyst.

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Speaker 2: There are probably a lot of people, maybe they're in

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Speaker 2: college listening to this episode right now. I think that

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Speaker 2: if I were young and in college and didn't have

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Speaker 2: any obligations, I would like, Oh, this sounds really fun

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Speaker 2: working for a multi strategy hedge funds. I would love

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Speaker 2: to get my door in one. What would be like?

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Speaker 2: What should I do to get that first role.

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Speaker 4: There are a few firms that hire direct from college,

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Speaker 4: direct from university. Those are very very small programs. Normally,

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Speaker 4: there's only a few of them at scale. I would

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Speaker 4: say typically people who first move into a pod as

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Speaker 4: an analyst or perhaps a sub PM generally come from

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Speaker 4: the cell side or maybe prop but they generally have

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Speaker 4: spent a couple of years on the cell side, have

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Speaker 4: a lot of the great training that the street can provide,

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Speaker 4: and have advanced themselves to where they are saying, you know,

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Speaker 4: I no longer just want to make markets. I actually

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Speaker 4: want to trade my own risk.

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Speaker 2: So you get a job on the cell side, and

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Speaker 2: you establish yourself as someone who knows something, who people

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Speaker 2: like reading from, and who people like reading their You

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Speaker 2: know their takes and their models and have interesting insights

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Speaker 2: to say about whatever asset classes is being traded.

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Speaker 4: Either that or you have a business that actually would

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Speaker 4: work good on the buy side happens to be in

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Speaker 4: the cell side. But in terms of how you get

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Speaker 4: that first job, I would say, be useful. I think

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Speaker 4: that everybody is kind of concentrated on the you know,

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Speaker 4: I want to be coming up with the ideas that

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Speaker 4: go into the book, and you sort of grow into

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Speaker 4: that slowly. But if you're somebody who you know has

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Speaker 4: read the history or done the work or researched, you

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Speaker 4: know what happens when on the first bed cut, what

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Speaker 4: happens on the last what happened in the dollar the

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Speaker 4: last time we had tariffs. Those sorts of analogs in

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Speaker 4: the macro world are very good. If you understand restructurings,

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Speaker 4: you're probably going to be pretty valuable to high yield

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Speaker 4: or distress pod. You're not going to get that. You know,

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Speaker 4: I've got the con kind of job right away, So

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Speaker 4: you need to be useful in the job you're applying for.

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Speaker 1: And then you.

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Speaker 3: Kind of touched on this before, but I would love

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Speaker 3: to hear more what are the pools that multistraats are

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Speaker 3: actually drawing from and have those changed over time, Like

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Speaker 3: you know, when they first started popping up, were they

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Speaker 3: hiring from fund of funds? And the cell side, and

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Speaker 3: then as they progress, maybe get a little bit more

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Speaker 3: experimental and start diversifying into other industries to draw pms from.

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Speaker 4: Yeah, I mean, for instance, we've seen a lot of

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Speaker 4: interesting commodities pms over the past few years, and a

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Speaker 4: lot of those are at trade houses, or perhaps they worn't.

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Speaker 4: For large boiling gas companies, a lot of which are

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Speaker 4: really more engineering than trading, they'll look anywhere if there's

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Speaker 4: sort of, you know, a definable edge. And we were

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Speaker 4: talking a little bit about the process of interviewing. Part

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Speaker 4: of what somebody is looking for is, you know, can

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Speaker 4: we do what you do? I'll give you an example.

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Speaker 4: Funds really want to expand their balance sheet and be

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Speaker 4: as efficient with it as possible. If we look at

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Speaker 4: gross notional exposure to net assets for multistrats, we hovered

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Speaker 4: around ten ten x through about twenty twenty, and since

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Speaker 4: then now we're between fourteen and sixteen and that's grossing

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Speaker 4: sets up as a multiple of their investible assets. So

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Speaker 4: that tells you they're looking for things that are a

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Speaker 4: little bit more highly leverageable. But any edge they will

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Speaker 4: look at. You know, fifteen years ago, no multistrap traded

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Speaker 4: munis most all of them do. Now, you know, there

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Speaker 4: were certain businesses like index rebounel, things of that nature

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Speaker 4: basis type trades that once were the exclusive province of

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Speaker 4: the street and now because in the ability of a

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Speaker 4: lot of these multi strats to effectively lose use their

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Speaker 4: balance sheet, they can engage in those businesses. Right.

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Speaker 2: This is run of the themes that's come up as

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Speaker 2: the sort of like post dog frank era or a

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Speaker 2: lot of certain types of trades that used to exist

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Speaker 2: in house at the major banks are now have now

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Speaker 2: effectively been outsourced in some manner to buyside entities where

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Speaker 2: it's more appropriate to take these risks. Let's talk about

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Speaker 2: your time when you were a PM. We talked about

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Speaker 2: the value of the seat and not getting fired. And

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Speaker 2: I also get the impression that on a sort of

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Speaker 2: day to day or week to week or trade to

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Speaker 2: trade basis, there's a lot of constraints from the risk manager.

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Speaker 2: Talk about the incentives of the PM to survive and

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Speaker 2: make it to the next year and make it to

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Speaker 2: the next bonus season.

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Speaker 4: I mean, you can essentially think of working for a

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Speaker 4: multistrat is you're running your own business. Okay, you're sort

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Speaker 4: of running your own fund. But you only have one client,

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Speaker 4: so you have to make very sure that that client's happy.

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Speaker 4: Your constraints are usually put in, you know, two terms.

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Speaker 4: You'll often hear the term capital thrown around. You know,

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Speaker 4: Tracy manages seven hundred million in XYZ and Joe has

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Speaker 4: fifty million in ABC, that sort of thing. The truth is,

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Speaker 4: those aren't really easily comparable numbers, right. The hedge fund

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Speaker 4: itself is inherently leveraged. They'll typically allocate somewhere between three

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Speaker 4: and four times their notional value, maybe even more in

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Speaker 4: terms of allocations to traders a billion dollars, you're allocating

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Speaker 4: out theoretically three or four billion. But there are two

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Speaker 4: numbers that are going to matter a lot to a PM.

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Speaker 4: The first one is how much can I lose? That's

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Speaker 4: your draw down, and there are two ways to measure that.

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Speaker 4: Most hedge funds are going to measure it on a

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Speaker 4: peak to trough basis, meaning even if you're up five,

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Speaker 4: if you give back suppose you're stopped is seven. If

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Speaker 4: you give back seven, then that's going to be your

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Speaker 4: draw down, even though you really weren't down from zero

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Speaker 4: much at all. The other way to measure that is

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Speaker 4: from zero from flat. So you can actually be fired

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Speaker 4: from one of these places and be up money on

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Speaker 4: the year. When it happens, you just gave back too

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Speaker 4: much of your sort of new money.

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Speaker 2: So actually explain that further a why would you fire

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Speaker 2: someone who's managed money profitably? But then here's another related

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Speaker 2: question to that is, like you hear about, Okay, someone

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Speaker 2: gets fired from place X, and then they go get

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Speaker 2: a new job at place y. But if there objectively talented,

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Speaker 2: and maybe they're not, but if by some measure that

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Speaker 2: it can be established that they're talented, why are the

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Speaker 2: pods so quick to fire them? I mean, I get, yeah,

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Speaker 2: you lose money, that's not good. But if you know

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Speaker 2: losing money happens if the person has talent, why the

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Speaker 2: quick fires.

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Speaker 4: It helps if you think of the multistraat itself as

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Speaker 4: managing a portfolio themselves, but it's a portfolio of risk takers.

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Speaker 4: Not to be reductive, but generally most of those types

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Speaker 4: of decisions are made on a fund by fund basis.

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Speaker 4: In other words, you know, maybe this person is not

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Speaker 4: as uncorrelated to what we have as we already thought.

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Speaker 4: They are not really making a lot of money. They

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Speaker 4: just exceeded their draw down, because it's not like they

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Speaker 4: don't know that it's a picatrough number. They're perfectly aware

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Speaker 4: of it. Or perhaps there's another opportunity in the market

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Speaker 4: to replace them with someone better. They're always looking to

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Speaker 4: optimize their portfolio of risk takers as far as the

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Speaker 4: other firm. They could be thinking, this person does fit

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Speaker 4: what we need and we really like their risk profile.

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Speaker 4: Even a really great PM is going to have a

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Speaker 4: significant draw down every two to five years, and there

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Speaker 4: aren't too many who've gone ten plus years with no

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Speaker 4: losing gears. You know, you just don't want to be

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Speaker 4: that person who experiences that five percent of the time

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Speaker 4: broad down in your first few months. And a new thought.

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Speaker 3: I used to know a credit guy who always said, like,

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Speaker 3: you're not a proper credit trader until you've had at

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Speaker 3: least one major blow up. Maybe maybe that's true. But

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Speaker 3: on this note, Okay, if I get a big draw down,

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Speaker 3: I understand maybe it depends on where I am with

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Speaker 3: my career, and if I get it in the first

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Speaker 3: six months of working at a shop, that would be

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Speaker 3: very bad. But if it's in you know, year six

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Speaker 3: or something, maybe it doesn't matter so much, But how

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Speaker 3: embarrassed am I when that happens? And am I like

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Speaker 3: publicly shamed within the organization for this happening? Or how

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Speaker 3: does it work exactly?

435
00:23:01,520 --> 00:23:04,040
Speaker 4: You know, it's sort of funny because obviously we had

436
00:23:04,440 --> 00:23:06,719
Speaker 4: a period just a few months back where there were

437
00:23:06,720 --> 00:23:11,359
Speaker 4: a lot of headlines about large losses. Is the marketplace

438
00:23:11,600 --> 00:23:14,680
Speaker 4: views it, it's going to feel awful to the PM, right,

439
00:23:14,800 --> 00:23:16,959
Speaker 4: you never want to be on the screen for a loss.

440
00:23:17,280 --> 00:23:19,680
Speaker 4: But whenever you see somebody up there with one hundred

441
00:23:19,720 --> 00:23:22,520
Speaker 4: million dollar loss, that means they had one hundred million

442
00:23:22,600 --> 00:23:26,040
Speaker 4: to lose, which means that they were managing a large

443
00:23:26,040 --> 00:23:28,919
Speaker 4: book and they were taking a lot of risk. And

444
00:23:29,000 --> 00:23:31,160
Speaker 4: if you'll notice, some of those pms from a few

445
00:23:31,160 --> 00:23:34,320
Speaker 4: months ago are still exactly where they were. You are

446
00:23:34,480 --> 00:23:39,440
Speaker 4: really generally better off getting bounced for a large loss

447
00:23:39,800 --> 00:23:41,040
Speaker 4: than you are a small one.

448
00:23:41,640 --> 00:23:44,280
Speaker 2: This goes fits with something one of my beliefs that

449
00:23:44,400 --> 00:23:47,959
Speaker 2: a billionaire is someone who either has positive one billion

450
00:23:47,960 --> 00:23:50,800
Speaker 2: dollars in net worth or negative one billion in one

451
00:23:50,840 --> 00:23:53,240
Speaker 2: billion in debt, because you have to be like really

452
00:23:53,359 --> 00:23:55,919
Speaker 2: rich to have lost that much money. And anytime you

453
00:23:56,000 --> 00:23:59,160
Speaker 2: hear about like a former billionaire and they lost everything.

454
00:23:59,280 --> 00:24:02,440
Speaker 2: They're almost all as still somehow living large. So being

455
00:24:02,520 --> 00:24:06,119
Speaker 2: deeply deeply in debt is almost as good as having

456
00:24:06,640 --> 00:24:09,480
Speaker 2: tons of money. So I'm glad to hear this. How

457
00:24:09,480 --> 00:24:12,000
Speaker 2: does that constrain your actual trading? Okay, you know that

458
00:24:12,160 --> 00:24:14,240
Speaker 2: draw down number, you know at the point we're going

459
00:24:14,320 --> 00:24:16,159
Speaker 2: to get stopped out of the seat, How does that

460
00:24:16,240 --> 00:24:19,480
Speaker 2: actually translate into thinking about the trades that you put on?

461
00:24:20,160 --> 00:24:22,720
Speaker 4: I hate to do And it depends, But it sort

462
00:24:22,760 --> 00:24:26,160
Speaker 4: of depends on where you're at. Because even though common

463
00:24:26,240 --> 00:24:30,439
Speaker 4: draw down for limits are usually somewhere between seven and

464
00:24:30,520 --> 00:24:33,880
Speaker 4: ten percent for what's called a stop out, you might

465
00:24:33,960 --> 00:24:36,639
Speaker 4: end up getting your capital reduced well before that at

466
00:24:36,720 --> 00:24:39,280
Speaker 4: three and a half or five, and that makes it

467
00:24:39,440 --> 00:24:42,879
Speaker 4: really really hard to come back. The key is, you know,

468
00:24:42,960 --> 00:24:45,560
Speaker 4: do you have a process, do you have risk management

469
00:24:45,560 --> 00:24:50,720
Speaker 4: and portfolio construction where you are still applying your risk management.

470
00:24:50,760 --> 00:24:53,240
Speaker 4: I'm only going to risk as much my risk capital.

471
00:24:53,359 --> 00:24:56,240
Speaker 4: What is between me and a capital reduction or draw down?

472
00:24:57,080 --> 00:24:59,879
Speaker 4: I'm going to be pick here. I'm going to trade smaller.

473
00:25:00,400 --> 00:25:02,600
Speaker 4: There are a lot of funds that have you know,

474
00:25:02,720 --> 00:25:07,000
Speaker 4: internal coaches, psychologists like it's windy Rhodes is based on

475
00:25:07,240 --> 00:25:11,480
Speaker 4: real people who do real things. And you know, certain

476
00:25:11,520 --> 00:25:13,479
Speaker 4: firms will sit you down and talk to you, or

477
00:25:13,520 --> 00:25:16,320
Speaker 4: they'll make you take a time out. Other firms will

478
00:25:16,359 --> 00:25:19,920
Speaker 4: just say that's it, you're out. But psychologically it makes

479
00:25:19,960 --> 00:25:22,520
Speaker 4: you you want to get it back, which is not

480
00:25:22,560 --> 00:25:24,720
Speaker 4: a great feeling because even when you get there, you're

481
00:25:24,760 --> 00:25:30,240
Speaker 4: just at flat and it really impacts your risk taking tolerance.

482
00:25:31,000 --> 00:25:33,080
Speaker 4: I think one of the best things that you know,

483
00:25:33,280 --> 00:25:35,199
Speaker 4: I ever heard was if you're kind of in a

484
00:25:35,240 --> 00:25:38,400
Speaker 4: losing street, just get flat and go away. Don't keep

485
00:25:38,440 --> 00:25:41,240
Speaker 4: any marginal things. You can always buy it back later.

486
00:25:41,320 --> 00:25:43,960
Speaker 4: You can always sell it later. But get your mind right.

487
00:25:44,000 --> 00:25:47,679
Speaker 4: But it does negatively affect you and you kind of

488
00:25:47,840 --> 00:25:51,080
Speaker 4: stew your thinking either to I'm going to take more

489
00:25:51,119 --> 00:25:53,719
Speaker 4: bets to get it back faster, or I'm not going

490
00:25:53,800 --> 00:25:56,320
Speaker 4: to do anything because I'm going to be so picky.

491
00:25:57,080 --> 00:26:00,080
Speaker 4: Overtrading is really common. I'll give you a for example. Well,

492
00:26:00,520 --> 00:26:03,959
Speaker 4: people coming from the cell side almost always overtrade when

493
00:26:04,000 --> 00:26:06,760
Speaker 4: they first get to the buyside. The reason is trading

494
00:26:06,800 --> 00:26:09,320
Speaker 4: has a positive expected value for them. They are in

495
00:26:09,359 --> 00:26:13,720
Speaker 4: the bid ask. Not only that, but facilitation desk on

496
00:26:13,760 --> 00:26:18,199
Speaker 4: the cell side. They lose money if VALL explodes, but

497
00:26:18,240 --> 00:26:21,640
Speaker 4: they generally make a lot of more money after it subsides.

498
00:26:21,800 --> 00:26:24,600
Speaker 4: The bid ask widens out and they could collect a

499
00:26:24,600 --> 00:26:26,320
Speaker 4: lot of clients flow in the back end of that.

500
00:26:26,840 --> 00:26:29,159
Speaker 4: One of the questions that I always ask people is,

501
00:26:29,240 --> 00:26:31,359
Speaker 4: you know, tell me about your biggest draw down. What

502
00:26:31,440 --> 00:26:34,439
Speaker 4: did happen, When was it, what was going on? What happened?

503
00:26:34,480 --> 00:26:37,320
Speaker 4: Would you do? And the sell side traders will always

504
00:26:37,359 --> 00:26:40,679
Speaker 4: have very quick times to recovery, and they expected to

505
00:26:40,680 --> 00:26:43,960
Speaker 4: get it back, but that's not the positive expected value

506
00:26:44,080 --> 00:26:46,520
Speaker 4: you have on the buy side. It costs your money

507
00:26:46,600 --> 00:27:00,720
Speaker 4: to trade.

508
00:27:02,440 --> 00:27:05,440
Speaker 3: Brian, tell me about your biggest draw down and what

509
00:27:05,480 --> 00:27:07,720
Speaker 3: it was and what you did well.

510
00:27:07,760 --> 00:27:10,440
Speaker 4: My biggest drug I was losing my job. I can't

511
00:27:10,520 --> 00:27:14,399
Speaker 4: name numbers, but essentially I violated my own risk. I

512
00:27:14,480 --> 00:27:18,359
Speaker 4: usually never speculated on outright vault, and I had a

513
00:27:18,400 --> 00:27:23,240
Speaker 4: long VALL position, and I normally would have structured that

514
00:27:23,359 --> 00:27:26,320
Speaker 4: as a spread, and I didn't. And though I was

515
00:27:26,400 --> 00:27:31,240
Speaker 4: directionally right, I bought really expensive wall and therefore didn't

516
00:27:31,240 --> 00:27:34,760
Speaker 4: make much money. Got hit on volatility in a much

517
00:27:34,840 --> 00:27:37,840
Speaker 4: larger fashion than I thought I would, And I was

518
00:27:37,880 --> 00:27:40,320
Speaker 4: in that camp of not a big draw down, and

519
00:27:40,359 --> 00:27:43,560
Speaker 4: it was almost unreal to people that I knew, Like,

520
00:27:43,640 --> 00:27:46,760
Speaker 4: why would they let you go? Because there's not a

521
00:27:46,760 --> 00:27:50,640
Speaker 4: lot of verifiable information out there. That always sounds very

522
00:27:50,680 --> 00:27:54,000
Speaker 4: suspect to people. I wish I could be more colorful

523
00:27:54,000 --> 00:27:54,199
Speaker 4: for that.

524
00:27:54,400 --> 00:27:58,040
Speaker 3: No, no, no, then that's really helpful. But on this note,

525
00:27:58,240 --> 00:28:01,840
Speaker 3: I'm also curious. Do pms ever go to like risk

526
00:28:01,920 --> 00:28:05,199
Speaker 3: managers or the people above them and beg for like

527
00:28:05,680 --> 00:28:08,800
Speaker 3: either more money or more risk tolerance.

528
00:28:09,440 --> 00:28:13,600
Speaker 4: Oh? Absolutely, And a lot of firms actually have, you know,

529
00:28:13,760 --> 00:28:16,960
Speaker 4: programs where if you have something that's really scalable that

530
00:28:17,040 --> 00:28:19,280
Speaker 4: you think is very functional, they may give you sort

531
00:28:19,280 --> 00:28:21,720
Speaker 4: of a side account and you get paid on that,

532
00:28:21,880 --> 00:28:24,840
Speaker 4: but it's not part of your regular book. Once you

533
00:28:24,880 --> 00:28:27,359
Speaker 4: work in BD, a lot of the people who you

534
00:28:27,440 --> 00:28:30,000
Speaker 4: bring in sort of ask you questions like, Hey, I

535
00:28:30,040 --> 00:28:31,960
Speaker 4: want to do this, Who should I ask? When should

536
00:28:31,960 --> 00:28:35,560
Speaker 4: I ask? I generally tell pms, unless it's an actual

537
00:28:35,600 --> 00:28:39,280
Speaker 4: trade idea, don't just ask for more capital unless it's

538
00:28:39,320 --> 00:28:42,680
Speaker 4: one of two situations. Number One, you just got there

539
00:28:42,720 --> 00:28:44,920
Speaker 4: because they love you, you haven't done anything wrong, and

540
00:28:44,960 --> 00:28:47,440
Speaker 4: they just probably paid up to get you. Number Two,

541
00:28:47,520 --> 00:28:50,400
Speaker 4: you've just made a hundred million bucks. Other than those

542
00:28:50,400 --> 00:28:52,480
Speaker 4: two situations, don't ask for things.

543
00:28:53,400 --> 00:28:56,680
Speaker 2: Wait, let's learn more about violating your own risk book.

544
00:28:56,760 --> 00:29:01,000
Speaker 2: There's a famous story from Stan Druckenmiller. He apparently like

545
00:29:01,080 --> 00:29:04,400
Speaker 2: bought the very top of the internet bubble, and he says,

546
00:29:04,480 --> 00:29:06,960
Speaker 2: you asked me what I learned. I didn't learn anything.

547
00:29:07,080 --> 00:29:08,760
Speaker 2: I already knew that I wasn't supposed to do that.

548
00:29:08,800 --> 00:29:11,480
Speaker 2: I was just an emotional basket case and couldn't help myself.

549
00:29:11,680 --> 00:29:13,520
Speaker 2: So maybe I learned not to do it again, but

550
00:29:13,600 --> 00:29:16,280
Speaker 2: I already knew that. When a fund manager is sort

551
00:29:16,280 --> 00:29:18,640
Speaker 2: of like violate or a PM is violating some of

552
00:29:18,680 --> 00:29:22,040
Speaker 2: their own things, do they know it? Do they feel differently?

553
00:29:22,040 --> 00:29:24,120
Speaker 2: Do they get like some sort of acidic taste in

554
00:29:24,160 --> 00:29:27,200
Speaker 2: their mouth? When I like go on tilt when I

555
00:29:27,240 --> 00:29:29,160
Speaker 2: play poker, I always sort of know it, but I

556
00:29:29,200 --> 00:29:31,760
Speaker 2: can't help myself anyway. Like I just do it and

557
00:29:31,800 --> 00:29:33,280
Speaker 2: I go all in and I know I hadn't then

558
00:29:33,320 --> 00:29:35,400
Speaker 2: I have to embarrassingly walk out of the table. Like

559
00:29:35,640 --> 00:29:37,920
Speaker 2: what does that feel like? Talk about like what's going

560
00:29:37,960 --> 00:29:40,440
Speaker 2: on in someone's brain when they're like taking these risks

561
00:29:40,560 --> 00:29:41,760
Speaker 2: that on paper they shouldn't be.

562
00:29:42,000 --> 00:29:45,160
Speaker 4: Well, usually you only recognize in the rear view. If

563
00:29:45,200 --> 00:29:47,440
Speaker 4: you slow down and think through the trade, you know,

564
00:29:47,520 --> 00:29:50,680
Speaker 4: you sort of realize that, hey, you probably shouldn't do this.

565
00:29:51,600 --> 00:29:54,320
Speaker 4: But I think you're parallel with being on tilt at

566
00:29:54,320 --> 00:29:57,120
Speaker 4: a poker table. It's it's that knowledge, you know, as

567
00:29:57,120 --> 00:30:00,000
Speaker 4: can you call somebody or after you raise that instant

568
00:30:00,160 --> 00:30:04,520
Speaker 4: feeling that man, I just leaped up. It's that feeling,

569
00:30:04,560 --> 00:30:06,440
Speaker 4: only you're going to feel it for a few days,

570
00:30:06,600 --> 00:30:08,800
Speaker 4: and you're going to get a little email or call

571
00:30:08,880 --> 00:30:11,760
Speaker 4: from your risk manager, and then you're not going to

572
00:30:11,840 --> 00:30:13,440
Speaker 4: know what that sit down is going to be like.

573
00:30:13,560 --> 00:30:16,520
Speaker 4: It might be, Hey, no big deal, get back out there,

574
00:30:17,120 --> 00:30:20,400
Speaker 4: you know, don't worry about it. It may be an

575
00:30:20,520 --> 00:30:23,640
Speaker 4: entirely different conversation. You may be told to go to

576
00:30:23,760 --> 00:30:26,880
Speaker 4: HR don't take your jacket, or take your jacket, I

577
00:30:26,920 --> 00:30:29,400
Speaker 4: should say. But it isn't a bad feeling. And I

578
00:30:29,440 --> 00:30:32,600
Speaker 4: think some of the better mentors that I've had through

579
00:30:32,600 --> 00:30:34,520
Speaker 4: the years have kind of taught me like that mental

580
00:30:34,560 --> 00:30:37,760
Speaker 4: health thing and where you're at is very important. And

581
00:30:37,800 --> 00:30:41,520
Speaker 4: I think it's even worse when you're at a multistraat

582
00:30:41,680 --> 00:30:46,160
Speaker 4: or a situation where you have a single plot that's

583
00:30:46,240 --> 00:30:49,840
Speaker 4: it if that one client isn't happy, you are probably

584
00:30:50,120 --> 00:30:54,480
Speaker 4: out for at least six months and potentially much longer.

585
00:30:54,640 --> 00:30:57,680
Speaker 4: The BD process to bring a new PM on board

586
00:30:57,800 --> 00:30:59,960
Speaker 4: is somewhere around three months on its own.

587
00:31:00,560 --> 00:31:03,200
Speaker 2: Do you do post mortems on winning and losing trades?

588
00:31:03,280 --> 00:31:03,520
Speaker 3: Kind of?

589
00:31:03,680 --> 00:31:06,360
Speaker 2: You know, like after I forget talk about poker, you

590
00:31:06,440 --> 00:31:08,960
Speaker 2: go back and you run the poker hand through a

591
00:31:09,040 --> 00:31:11,240
Speaker 2: solver and you see if you played it correctly, often

592
00:31:11,280 --> 00:31:13,720
Speaker 2: whether you made money or lose money. Is there an

593
00:31:13,720 --> 00:31:16,880
Speaker 2: equivalent process that's done in the trading world.

594
00:31:17,240 --> 00:31:19,840
Speaker 4: N hundred percent. As a matter of fact, if you

595
00:31:19,920 --> 00:31:22,840
Speaker 4: guys have never had Brent Donnelly on, he wrote a

596
00:31:22,840 --> 00:31:25,160
Speaker 4: book called Alfit Trader, and I've probably never seen that

597
00:31:25,200 --> 00:31:27,400
Speaker 4: information written down in one place before.

598
00:31:27,520 --> 00:31:29,760
Speaker 2: But right, yeah, we should have them back on or

599
00:31:29,800 --> 00:31:31,479
Speaker 2: something to talk about just now, but keep tell us

600
00:31:31,480 --> 00:31:33,640
Speaker 2: more about it from your perspective, Yes.

601
00:31:33,520 --> 00:31:36,520
Speaker 4: You know, and that is part of the other process,

602
00:31:36,600 --> 00:31:39,440
Speaker 4: like we mentioned edge, like the other parts of the

603
00:31:39,440 --> 00:31:41,760
Speaker 4: beating process that I want to know the process by

604
00:31:41,760 --> 00:31:44,680
Speaker 4: which somebody selects trades. I want to know about their

605
00:31:44,840 --> 00:31:47,760
Speaker 4: portfolio construction, and I want to know their approach to risk,

606
00:31:48,560 --> 00:31:52,440
Speaker 4: Especially on risk, you'll find that very good pms, and

607
00:31:52,600 --> 00:31:56,280
Speaker 4: especially these firms, the firms themselves, even though the PM

608
00:31:56,360 --> 00:31:59,080
Speaker 4: may not see it, they know exactly how many bets

609
00:31:59,120 --> 00:32:01,760
Speaker 4: you've taken. They know about your hit rate, they understand

610
00:32:01,800 --> 00:32:04,960
Speaker 4: your skew. They can sort of tell when you're deviating

611
00:32:05,000 --> 00:32:08,120
Speaker 4: from your wrist mandate. They have a lot of analytics.

612
00:32:08,800 --> 00:32:11,280
Speaker 4: But it's been my experience that the best pms look

613
00:32:11,320 --> 00:32:14,080
Speaker 4: at it themselves. They're almost religious with it. You know,

614
00:32:14,160 --> 00:32:16,640
Speaker 4: how did I do today? It's very similar to an

615
00:32:16,680 --> 00:32:20,920
Speaker 4: athlete watching tape or a dancer. My daughters loves dance.

616
00:32:21,000 --> 00:32:23,160
Speaker 4: You know, she'll watch tape of herselves. This is what

617
00:32:23,200 --> 00:32:25,600
Speaker 4: I missed, this is what I didn't do. And the

618
00:32:25,720 --> 00:32:28,640
Speaker 4: great benefit of doing it in a statistical fashion is

619
00:32:28,680 --> 00:32:31,200
Speaker 4: you can remove, oh, I won't count that because it

620
00:32:31,320 --> 00:32:34,280
Speaker 4: was a Tuesday and a full moon. Any excuse you

621
00:32:34,360 --> 00:32:37,840
Speaker 4: have goes out the window. Those are the numbers on

622
00:32:37,880 --> 00:32:38,400
Speaker 4: this note.

623
00:32:38,440 --> 00:32:41,840
Speaker 3: And since Joe brought up poker earlier, are there like

624
00:32:42,040 --> 00:32:47,760
Speaker 3: popular ways to become a better better better? Does that

625
00:32:47,800 --> 00:32:48,320
Speaker 3: work for all?

626
00:32:48,560 --> 00:32:49,040
Speaker 2: Better?

627
00:32:49,160 --> 00:32:52,000
Speaker 3: A better better better? And I'm thinking, you know, I'm

628
00:32:52,000 --> 00:32:55,200
Speaker 3: thinking back to Liar's Poker. That's a famous example. And

629
00:32:55,280 --> 00:32:58,680
Speaker 3: then wasn't there something at Jane Street that Sam Bankman

630
00:32:58,760 --> 00:33:02,200
Speaker 3: Freed was doing a bunch of different like gambling games

631
00:33:02,600 --> 00:33:03,240
Speaker 3: things like that.

632
00:33:03,400 --> 00:33:03,720
Speaker 4: Yeah.

633
00:33:04,040 --> 00:33:07,480
Speaker 3: Like what is popular in terms of I guess building

634
00:33:07,600 --> 00:33:09,760
Speaker 3: up your risk returnals.

635
00:33:10,240 --> 00:33:14,800
Speaker 4: Well, I think anything where you have some element of strategy,

636
00:33:14,880 --> 00:33:16,640
Speaker 4: And I think one of the reasons that poker is

637
00:33:16,680 --> 00:33:21,400
Speaker 4: so popular is that it combines not only strict strategy

638
00:33:21,560 --> 00:33:24,120
Speaker 4: like you might see in chess, but also a fair

639
00:33:24,160 --> 00:33:27,400
Speaker 4: degree of complete randomness and you're going to take some

640
00:33:27,520 --> 00:33:30,720
Speaker 4: bad beats and that's going to happen in trading. It's

641
00:33:30,720 --> 00:33:33,400
Speaker 4: easy to forget, but a really good PM might have

642
00:33:33,440 --> 00:33:36,680
Speaker 4: a fifty two fifty three percent hit rate on their trades.

643
00:33:37,000 --> 00:33:39,480
Speaker 4: It becomes what their skew is how much they make

644
00:33:39,520 --> 00:33:42,080
Speaker 4: on their winners versus how much they lose on their losers.

645
00:33:42,720 --> 00:33:45,680
Speaker 4: So anything where you're actually becoming more in tune to

646
00:33:45,960 --> 00:33:49,320
Speaker 4: your own risk taking, your ability to think in what

647
00:33:49,800 --> 00:33:53,240
Speaker 4: most people call probabilistic terms, or thinking in bets after

648
00:33:53,280 --> 00:33:56,280
Speaker 4: they any Duke book, any exercise like that, and I

649
00:33:56,280 --> 00:33:58,920
Speaker 4: think poker is probably just the most popular. It's also

650
00:33:58,960 --> 00:34:01,520
Speaker 4: a great fun I don't know whether i'd say team

651
00:34:01,520 --> 00:34:04,920
Speaker 4: building game, but it's a fun social game that people

652
00:34:04,960 --> 00:34:08,440
Speaker 4: play often around hedge funds, and it fits with the

653
00:34:08,480 --> 00:34:10,880
Speaker 4: gambling mentality, so we hear about it a lot, but

654
00:34:10,920 --> 00:34:13,400
Speaker 4: there are a lot of different internal games that people

655
00:34:14,239 --> 00:34:14,919
Speaker 4: engage in.

656
00:34:15,800 --> 00:34:18,120
Speaker 2: I just have one last question, and it goes back

657
00:34:18,120 --> 00:34:19,920
Speaker 2: to the role of the analyst, and you mentioned, oh,

658
00:34:19,920 --> 00:34:22,040
Speaker 2: maybe you know, an analyst could be valuable if they

659
00:34:22,080 --> 00:34:24,279
Speaker 2: really know the history of what happens, if they're X

660
00:34:24,400 --> 00:34:28,000
Speaker 2: or Y. I can just look that up on three

661
00:34:28,120 --> 00:34:32,719
Speaker 2: on chagbtr perplexity these days, like, how realistic is it

662
00:34:32,960 --> 00:34:38,120
Speaker 2: in your view that firms could meaningfully reduce analyst headcount

663
00:34:38,600 --> 00:34:42,279
Speaker 2: by using artificial intelligence, or if they save money on

664
00:34:42,440 --> 00:34:46,280
Speaker 2: by using artificial intelligence, would that just create new roles

665
00:34:46,480 --> 00:34:49,000
Speaker 2: for more sort of advanced research. Where are we at

666
00:34:49,000 --> 00:34:51,319
Speaker 2: with this? You must talk to people about what they're

667
00:34:51,320 --> 00:34:51,759
Speaker 2: doing with this.

668
00:34:52,239 --> 00:34:55,600
Speaker 4: I think there's lots of things they can do. And obviously,

669
00:34:55,840 --> 00:34:58,839
Speaker 4: you know you're talking about pret secretive organizations, so there's

670
00:34:58,840 --> 00:35:02,800
Speaker 4: an enterprise sharing issue there to deal with. But yeah,

671
00:35:02,880 --> 00:35:07,239
Speaker 4: a lot of things could be really computerized. But you're

672
00:35:07,280 --> 00:35:10,959
Speaker 4: also looking for people who are going to be able

673
00:35:10,960 --> 00:35:13,560
Speaker 4: to tie the story and the narrative and with what

674
00:35:13,719 --> 00:35:16,120
Speaker 4: was going on with the instruments, and it's probably not

675
00:35:16,280 --> 00:35:19,239
Speaker 4: something so simple as you know, what did the dollar

676
00:35:19,440 --> 00:35:22,000
Speaker 4: in do the last time the FED hiked? It might

677
00:35:22,040 --> 00:35:25,320
Speaker 4: be something more like what was a red screens puts

678
00:35:25,360 --> 00:35:28,800
Speaker 4: foot steepener doing the last time the FED hiked, which

679
00:35:29,440 --> 00:35:32,640
Speaker 4: you're going to require a lot of modifications to those

680
00:35:32,680 --> 00:35:36,280
Speaker 4: AI models. I'm always hesitant to talk about this because

681
00:35:36,400 --> 00:35:38,520
Speaker 4: I can remember we were told that all the paper

682
00:35:38,520 --> 00:35:40,760
Speaker 4: companies were going to go out of business because everybody

683
00:35:40,800 --> 00:35:42,759
Speaker 4: was going to read everything online. And what happened. We

684
00:35:42,880 --> 00:35:43,759
Speaker 4: just all printed it.

685
00:35:44,520 --> 00:35:47,200
Speaker 2: Oh, yeah, that's true. And they and they a lot

686
00:35:47,239 --> 00:35:50,440
Speaker 2: of them also sell cardboard boxes and so they benefited

687
00:35:50,440 --> 00:35:53,520
Speaker 2: from e commerce. Those same companies actually absolutely.

688
00:35:53,600 --> 00:35:58,719
Speaker 4: Georgia Pacific is probably huge in Amazon's warehouse. But I

689
00:35:58,760 --> 00:36:02,440
Speaker 4: think that there will always people who because this industry

690
00:36:02,480 --> 00:36:04,960
Speaker 4: thrives on you know, I can do this even though

691
00:36:05,000 --> 00:36:07,960
Speaker 4: the odds are very much against me, and they will

692
00:36:07,960 --> 00:36:11,359
Speaker 4: definitely use any edge they can get informationally as far

693
00:36:11,360 --> 00:36:15,960
Speaker 4: as analytics or anything like that. But usually there's something

694
00:36:16,680 --> 00:36:19,400
Speaker 4: that you're going to have to ask that maybe not

695
00:36:19,520 --> 00:36:23,160
Speaker 4: everybody understands or nos. I think everybody who's in this

696
00:36:23,239 --> 00:36:25,239
Speaker 4: business got into it in one way or another, and

697
00:36:25,320 --> 00:36:29,520
Speaker 4: somebody handed them what I just generically call, you know,

698
00:36:29,680 --> 00:36:33,120
Speaker 4: street born, which is the market Wizard's books or any

699
00:36:33,200 --> 00:36:35,640
Speaker 4: of those types of things, and they're fantastic because what

700
00:36:35,760 --> 00:36:37,560
Speaker 4: I got out of reading those types of books is

701
00:36:37,600 --> 00:36:40,360
Speaker 4: there's a lot of different ways to make money. You

702
00:36:40,520 --> 00:36:43,040
Speaker 4: just have to find out what you're good at and

703
00:36:43,320 --> 00:36:46,400
Speaker 4: how you can apply your particular set of skills and

704
00:36:46,480 --> 00:36:49,440
Speaker 4: attributes to doing it. And I think that there's going

705
00:36:49,520 --> 00:36:52,400
Speaker 4: to be somebody who gets really good at asking you

706
00:36:52,560 --> 00:36:55,319
Speaker 4: one of these am models market questions, and that person

707
00:36:55,320 --> 00:36:58,680
Speaker 4: who's going to get built up. We're already seeing increase

708
00:36:58,800 --> 00:37:02,319
Speaker 4: for heads of AI at several different funds, and I

709
00:37:02,320 --> 00:37:04,600
Speaker 4: think that that's going to continue as they explore more

710
00:37:04,640 --> 00:37:07,120
Speaker 4: and more, you know, what they can actually do with it.

711
00:37:07,600 --> 00:37:09,759
Speaker 4: They have no problem spending money on the either the

712
00:37:09,760 --> 00:37:12,239
Speaker 4: AI or the human being. It will ultimately come up

713
00:37:12,280 --> 00:37:14,080
Speaker 4: to who can perform.

714
00:37:14,719 --> 00:37:18,720
Speaker 3: So how do you avoid I guess group think among

715
00:37:18,760 --> 00:37:22,479
Speaker 3: your pms, because the whole point of multistrats is those

716
00:37:22,719 --> 00:37:26,399
Speaker 3: uncorrelated returns, and you don't want everyone just putting on

717
00:37:26,800 --> 00:37:31,480
Speaker 3: the same trades, either literally or maybe through another angle.

718
00:37:31,920 --> 00:37:36,759
Speaker 3: And I'm thinking specifically about journalism. So some newspapers used

719
00:37:36,800 --> 00:37:40,160
Speaker 3: to always move reporters from a certain beat after they'd

720
00:37:40,200 --> 00:37:42,640
Speaker 3: been there for like ten years or something, and the

721
00:37:42,719 --> 00:37:45,160
Speaker 3: idea was just to shake it up a little bit

722
00:37:45,280 --> 00:37:48,120
Speaker 3: and make sure that they're not getting like too cozy

723
00:37:48,200 --> 00:37:51,799
Speaker 3: or too comfortable with that particular industry. The downside of

724
00:37:51,840 --> 00:37:55,360
Speaker 3: doing that, of course, is that you lose expertise. But

725
00:37:55,560 --> 00:37:58,279
Speaker 3: I'm just wondering, like, how do people, yeah, how do

726
00:37:58,360 --> 00:38:01,839
Speaker 3: people avoid that group think aspect and make sure that

727
00:38:01,960 --> 00:38:05,040
Speaker 3: everyone's doing you know, new stuff kind of independently.

728
00:38:05,600 --> 00:38:10,160
Speaker 4: Well. One way is limiting the communication between the pods.

729
00:38:10,200 --> 00:38:13,480
Speaker 4: Some places do not really allow their pods to communicate.

730
00:38:14,160 --> 00:38:19,640
Speaker 4: Another way is basically structurally, you don't want to see

731
00:38:19,680 --> 00:38:22,360
Speaker 4: people hang on to each other's trades. You're going to

732
00:38:22,400 --> 00:38:24,879
Speaker 4: be looking at this from you know, a macro view

733
00:38:24,920 --> 00:38:27,120
Speaker 4: within the firm. You're going to see this type of

734
00:38:27,160 --> 00:38:30,000
Speaker 4: trade that this person had on is increasing in size

735
00:38:30,000 --> 00:38:33,279
Speaker 4: in the firm. But by and large, if you've fired right,

736
00:38:33,360 --> 00:38:37,400
Speaker 4: you're going to hire independent thinkers, and a seasoned PM

737
00:38:37,440 --> 00:38:40,440
Speaker 4: will tell you I might like somebody else's idea, but

738
00:38:40,520 --> 00:38:44,719
Speaker 4: I can't really trade it properly unless it's my idea too,

739
00:38:44,840 --> 00:38:46,839
Speaker 4: I kind of have to adopt that as my own.

740
00:38:47,239 --> 00:38:50,000
Speaker 4: So group think is not as prevalent as you would

741
00:38:50,000 --> 00:38:53,000
Speaker 4: think because it's structurally prohibited in some places and the

742
00:38:53,000 --> 00:38:56,440
Speaker 4: places where it's not. You know, a seasoned PM is

743
00:38:56,480 --> 00:38:59,279
Speaker 4: like any I may love that trade that you pitched me, Joe,

744
00:38:59,320 --> 00:39:02,959
Speaker 4: but yours and I can't. I'm not doing my job

745
00:39:03,080 --> 00:39:04,840
Speaker 4: if I say, Joe, when are we getting out of this?

746
00:39:05,080 --> 00:39:08,080
Speaker 4: That's not what I'm paid to do. So part of

747
00:39:08,120 --> 00:39:09,800
Speaker 4: it is on the part of the PM internally, and

748
00:39:10,040 --> 00:39:11,640
Speaker 4: then the other part of it is on the fact

749
00:39:11,680 --> 00:39:13,640
Speaker 4: that they don't want to be seen as copying the

750
00:39:13,719 --> 00:39:14,880
Speaker 4: p next guy's trades.

751
00:39:15,120 --> 00:39:16,960
Speaker 2: All right, but just real quickly, maybe you don't want

752
00:39:16,960 --> 00:39:19,480
Speaker 2: to do groupthink or copy the next guy's trades. But

753
00:39:19,560 --> 00:39:22,200
Speaker 2: if there's a hot beta, right, you're always looking for alpha.

754
00:39:22,280 --> 00:39:25,560
Speaker 2: But if there's a hot beta like AI beta or whatever,

755
00:39:25,800 --> 00:39:29,560
Speaker 2: or falling inflation beta like some of these long term trends,

756
00:39:29,680 --> 00:39:32,520
Speaker 2: but that's not your thing. Do pms find ways to

757
00:39:32,640 --> 00:39:36,200
Speaker 2: backdoor their acid class into the hot trade in a

758
00:39:36,239 --> 00:39:40,040
Speaker 2: way that like may the fact to become trade crowding.

759
00:39:40,960 --> 00:39:43,600
Speaker 4: Yeah. A former boss of mine used to say, there's

760
00:39:43,640 --> 00:39:47,480
Speaker 4: never been a risk management framework the smart trader could outwit.

761
00:39:48,000 --> 00:39:49,879
Speaker 2: That's what I'm wondering. That's like, is it this cat

762
00:39:49,920 --> 00:39:52,120
Speaker 2: and mouse game where you're, in part trying to outwit

763
00:39:52,160 --> 00:39:54,439
Speaker 2: the person who could tap you on the shoulder by

764
00:39:54,480 --> 00:39:56,359
Speaker 2: trading something that looks like something else.

765
00:39:56,920 --> 00:39:59,759
Speaker 4: Yeah, there's a lot of downside to doing that, you know,

766
00:39:59,760 --> 00:40:02,239
Speaker 4: if you don't have a trade kind of properly thought out.

767
00:40:03,000 --> 00:40:06,239
Speaker 4: But you know, in general, if I hire one of

768
00:40:06,280 --> 00:40:09,280
Speaker 4: you to trade credit and the other one to trade

769
00:40:09,320 --> 00:40:12,600
Speaker 4: the front end of the yield curve, and you know,

770
00:40:12,719 --> 00:40:16,080
Speaker 4: all of a sudden, Brazil is very hot the real

771
00:40:16,719 --> 00:40:19,200
Speaker 4: and you're both asking me for limits on the real Like,

772
00:40:19,719 --> 00:40:23,360
Speaker 4: you won't have limits in something that you don't already trade,

773
00:40:23,760 --> 00:40:27,040
Speaker 4: so you can't really deviate for your mandate too much.

774
00:40:27,560 --> 00:40:29,560
Speaker 2: It's kind of a I'll just find a credit spread

775
00:40:29,600 --> 00:40:32,600
Speaker 2: that's correlated with the rail yeah.

776
00:40:32,320 --> 00:40:34,920
Speaker 4: Or you know, there are a lot of ETFs that

777
00:40:35,000 --> 00:40:39,160
Speaker 4: basically contain macro trades if you will, and I have

778
00:40:39,320 --> 00:40:41,880
Speaker 4: often wondered, you know, are those there so that mutual

779
00:40:41,920 --> 00:40:45,320
Speaker 4: fund managers can you know, and investigate equities, can speculate

780
00:40:45,360 --> 00:40:48,319
Speaker 4: on the yield curve. But there are always ways to

781
00:40:48,480 --> 00:40:51,080
Speaker 4: do it. You just have to kind of hire the

782
00:40:51,160 --> 00:40:54,480
Speaker 4: right people who aren't necessarily going to do that. And

783
00:40:54,520 --> 00:40:56,920
Speaker 4: if you get in trouble for something like that, I

784
00:40:57,000 --> 00:40:58,880
Speaker 4: sort of like to say that this is the second

785
00:40:58,880 --> 00:41:04,000
Speaker 4: most waryuristic streight in America. Word gets out is large

786
00:41:04,040 --> 00:41:06,040
Speaker 4: of an industry, it is, it's not that big in

787
00:41:06,080 --> 00:41:10,640
Speaker 4: an individual areas. And if somebody has really done something untoward,

788
00:41:11,000 --> 00:41:13,520
Speaker 4: then it's people are going to hear about it.

789
00:41:13,640 --> 00:41:16,759
Speaker 2: Brian Yelvington, thank you for coming on odd Lots and

790
00:41:16,800 --> 00:41:21,520
Speaker 2: talking about getting and keeping multistraat jobs. Our journey continues.

791
00:41:21,560 --> 00:41:23,840
Speaker 2: Thank you so much. Really appreciate chatting with you.

792
00:41:24,200 --> 00:41:26,120
Speaker 4: Thank you, thank you for having me. It's great to

793
00:41:26,120 --> 00:41:27,160
Speaker 4: get to talk to you guys.

794
00:41:39,960 --> 00:41:41,960
Speaker 2: Tracy, if I were like young, I think I or

795
00:41:42,000 --> 00:41:43,680
Speaker 2: if I were in college or something, I think I

796
00:41:43,680 --> 00:41:45,080
Speaker 2: would have taken that trading job.

797
00:41:45,120 --> 00:41:45,279
Speaker 4: Now.

798
00:41:45,320 --> 00:41:47,839
Speaker 2: I mean, I like the way my direction, life direction went.

799
00:41:47,880 --> 00:41:50,600
Speaker 2: But if I wanted to do over, I'm curious what

800
00:41:50,640 --> 00:41:51,839
Speaker 2: that fork in the road looks like.

801
00:41:51,920 --> 00:41:54,680
Speaker 3: There'ought Yeah, that's so sad will.

802
00:41:54,560 --> 00:41:56,799
Speaker 2: Be a different puck, you know, Like I feel like

803
00:41:57,160 --> 00:41:59,200
Speaker 2: I would I would trade you know what happened, there

804
00:41:59,200 --> 00:42:01,680
Speaker 2: would still be an odd one. I would trade for

805
00:42:01,719 --> 00:42:05,080
Speaker 2: a while, I would blow up. I would get a

806
00:42:05,160 --> 00:42:07,719
Speaker 2: job in journalism, and then I would be one of

807
00:42:07,760 --> 00:42:10,759
Speaker 2: those journalists who reminds all of their colleagues all of

808
00:42:10,800 --> 00:42:12,759
Speaker 2: the times that they used work and finance. You know,

809
00:42:12,880 --> 00:42:14,799
Speaker 2: I would find like the person on the call, they're like,

810
00:42:15,160 --> 00:42:17,200
Speaker 2: I just love the you know, It's like I was like, oh,

811
00:42:17,440 --> 00:42:20,120
Speaker 2: I used to work in a multi strategy hedge fun. Yeah, yeah, yeah, yeah,

812
00:42:20,120 --> 00:42:21,480
Speaker 2: well I used to be a trader. Anyway.

813
00:42:21,520 --> 00:42:23,919
Speaker 3: Sorry, keep going, Joe, how many times have you brought

814
00:42:24,040 --> 00:42:27,160
Speaker 3: up that interview with the trading company on this note?

815
00:42:27,200 --> 00:42:27,439
Speaker 4: Yeah?

816
00:42:27,480 --> 00:42:31,080
Speaker 3: Okay, that was really interesting. One thing that kind of

817
00:42:31,440 --> 00:42:35,680
Speaker 3: jumps out at me is the last discussion about you know,

818
00:42:35,760 --> 00:42:38,959
Speaker 3: how do you avoid everyone just taking on the same risk.

819
00:42:39,719 --> 00:42:44,800
Speaker 3: It really seems to me like it's correlation built on correlation,

820
00:42:44,960 --> 00:42:47,759
Speaker 3: built on correlation, right, And I often think correlation is

821
00:42:47,800 --> 00:42:51,279
Speaker 3: one of the hardest things to actually nail down on

822
00:42:51,360 --> 00:42:55,399
Speaker 3: Wall Street. So you know, you gotta wonder so far,

823
00:42:55,800 --> 00:42:59,960
Speaker 3: so far, you know, a bunch of multistrats survived April

824
00:43:00,080 --> 00:43:02,360
Speaker 3: pretty well, so I guess we'll see.

825
00:43:02,800 --> 00:43:05,160
Speaker 2: I think if I were a risk manager and I

826
00:43:05,239 --> 00:43:09,000
Speaker 2: had one person trading credit and the other person trading

827
00:43:09,040 --> 00:43:11,680
Speaker 2: the short end of the old curve, and suddenly there

828
00:43:11,680 --> 00:43:14,680
Speaker 2: are month to month return started looking identical, and it

829
00:43:14,760 --> 00:43:18,440
Speaker 2: happened to be identical with the person who traded Brazilian rayal.

830
00:43:18,920 --> 00:43:22,160
Speaker 2: That would set off a red flag for me. You know, like,

831
00:43:22,200 --> 00:43:26,560
Speaker 2: I feel like the return profile itself is probably part

832
00:43:26,600 --> 00:43:29,520
Speaker 2: of the hint, right that even if you can't really

833
00:43:29,640 --> 00:43:33,640
Speaker 2: articulate why this person's traded is secretly this person's trade

834
00:43:33,680 --> 00:43:36,680
Speaker 2: in disguise. If there re tuned profile looks too similar,

835
00:43:36,719 --> 00:43:38,680
Speaker 2: that probably sets off some red flags.

836
00:43:39,000 --> 00:43:42,600
Speaker 3: We got to talk to a risk manager, don't Yeah,

837
00:43:42,640 --> 00:43:43,359
Speaker 3: we should do that.

838
00:43:43,440 --> 00:43:46,000
Speaker 2: Okay, if you're a risk manager, you want to talk

839
00:43:46,040 --> 00:43:48,440
Speaker 2: about what that job is like or if you know,

840
00:43:48,480 --> 00:43:50,520
Speaker 2: one shoots a message.

841
00:43:50,239 --> 00:43:51,319
Speaker 3: All right, shall we leave it there.

842
00:43:51,400 --> 00:43:52,080
Speaker 2: Let's leave it there.

843
00:43:52,200 --> 00:43:54,600
Speaker 3: This has been another episode of the All Thoughts Podcast.

844
00:43:54,719 --> 00:43:58,000
Speaker 3: I'm Tracy Alloway. You can follow me at Tracy Alloway.

845
00:43:57,760 --> 00:44:00,600
Speaker 2: And I'm Jill Wisenthal. You can follow me at the Stalwart.

846
00:44:00,800 --> 00:44:04,040
Speaker 2: Follow our producers Carmen Rodriguez at Carman Arman dash Ol

847
00:44:04,080 --> 00:44:07,399
Speaker 2: Bennett at Dashbot and Kilbrooks at Kilbrooks. From our Odd

848
00:44:07,440 --> 00:44:10,000
Speaker 2: Lots content go to Bloomberg dot com slash od lots

849
00:44:10,000 --> 00:44:12,600
Speaker 2: were the daily newsletter and all of our episodes, and

850
00:44:12,640 --> 00:44:14,680
Speaker 2: you can chat about all of these topics twenty four

851
00:44:14,719 --> 00:44:18,839
Speaker 2: to seven in our discord Discord dot gg slash od lots.

852
00:44:18,680 --> 00:44:21,160
Speaker 3: And if you enjoy odd Lots, if you like our

853
00:44:21,400 --> 00:44:25,520
Speaker 3: ongoing exploration of multistrap funds, then please leave us a

854
00:44:25,520 --> 00:44:29,120
Speaker 3: positive review on your favorite podcast platform. And remember, if

855
00:44:29,160 --> 00:44:31,920
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856
00:44:31,960 --> 00:44:34,680
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857
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858
00:44:37,320 --> 00:45:05,200
Speaker 3: follow the instructions there. Thanks for listening, then, in the

859
00:45:05,560 --> 00:45:05,600
Speaker 3: e