Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News.
Speaker 2: Hello and welcome to another episode of the Odd Thoughts podcast.
Speaker 2: I'm Tracy Alloway.
Speaker 3: And I'm Joe Wisenthal.
Speaker 2: Joe, I know we did one episode on pod shops, Yeah,
Speaker 2: on multi strategy hedge funds, but it was primarily focused
Speaker 2: on their impact on the market, and I have to
Speaker 2: say I still came away from that conversation sort of
Speaker 2: wondering if I worked at a pod shop, what is
Speaker 2: it exactly that I would be doing all day?
Speaker 3: I would love to know the exact same thing. I mean, like,
Speaker 3: I guess I have this very vague sense of sort
Speaker 3: of they have a bunch of people all focused on
Speaker 3: their specific areas in the sort of ever out, and
Speaker 3: they net out a bunch of stuff and it's capital
Speaker 3: efficient and you know, it's like market neutral and theory
Speaker 3: and et cetera. But beyond that, like, I still don't
Speaker 3: really like understand. The only thing I know is like
Speaker 3: they've done really well and many people are launching more
Speaker 3: of them.
Speaker 2: Yes, they seem to be all the rage. They seem
Speaker 2: to be where everyone kind of wants to go in
Speaker 2: the quantitative finance space. At least everyone's sort of aiming
Speaker 2: for these big names, you know, places like Citadel Millennium.
Speaker 2: Maybe yeah, But my question is like, why was it
Speaker 2: just that they're minting money they're expected to continue minting
Speaker 2: money in the future, or is there something that's like
Speaker 2: fundamentally intriguing and attractive about working in that space that
Speaker 2: means lots of people want to get in.
Speaker 3: I mean, I think that could be two ways of
Speaker 3: saying the same thing. If they're minting money, then that
Speaker 3: probably is fundamentally attractive to people in that space. But
Speaker 3: I do think like backing up the questions, like what
Speaker 3: we know is that many and including apparently even like
Speaker 3: B tier C tier funds have done like very well.
Speaker 3: So I'm just like curious like how and why? And
Speaker 3: then yeah to the question of like what does it
Speaker 3: take to succeed in them or who is the type
Speaker 3: of person who can succeed in this environment?
Speaker 2: All right, well, I'm glad you put it that way,
Speaker 2: because today we're going to be speaking with someone who
Speaker 2: has done exactly that succeeded in this particular environment. We
Speaker 2: have the perfect guest. We're going to be speaking with
Speaker 2: Giuseppe Palielogo aka Gappy. He describes himself as a constant gardener,
Speaker 2: someone who's on gardening leave quite a lot. He is
Speaker 2: also the author of Advanced Portfolio Management, a quant's guide
Speaker 2: for fundamental investors, and I have to say it is
Speaker 2: one of the funniest books that I've read in quant finance.
Speaker 2: I can't say it's the funniest because I did read
Speaker 2: My Life as a Quant from Emmanuel Derman, but it's
Speaker 2: definitely up there. And Joe, I know you enjoyed it too.
Speaker 3: I did you know, I like skipped over all the numbers.
Speaker 2: And equations and you just looked at the jokes.
Speaker 3: And Greek letters. But it's very breezily written for what
Speaker 3: it is, and I did. Actually, I think maybe I
Speaker 3: learned a little bit even in my sort of basic
Speaker 3: reading of it. Extremely well written. I'm extremely excited about
Speaker 3: this conversation. You know, you mentioned that our guest is
Speaker 3: the king of gardening leave. If you look in his LinkedIn,
Speaker 3: it really is many different roles. Well.
Speaker 2: I also have to say he is the only person
Speaker 2: I know who has both an alpha and a beta
Speaker 2: tattoo on his shoulder.
Speaker 3: Oh wow.
Speaker 2: You know, some people do get the alpha symbol, but
Speaker 2: he has both. So you know, a well balanced portfolio
Speaker 2: of tattoos all around. Yeah, so gappy. Thank you so
Speaker 2: much for coming on all thoughts.
Speaker 4: Hi Tracy, Hi Joe.
Speaker 2: So maybe to begin with, I'm going to let you
Speaker 2: explain your previous job history because there is quite a lot.
Speaker 2: What is it that you've been doing in this industry.
Speaker 4: I'm not sure, I'm not sure, Okay, good question. Well,
Speaker 4: I got into this industry almost accidentally. I was for
Speaker 4: a few years a researcher in the math department at
Speaker 4: IBM Research, and then I got a little bit bored.
Speaker 4: So the only place that you can the only industry
Speaker 4: you can work in New York other than you know,
Speaker 4: IBM or tech, is finance. So I got into finance
Speaker 4: almost accidentally. And then again, there is no major plan
Speaker 4: to you know, to to my career choices. When I
Speaker 4: was getting bored for some reason, somebody called me and
Speaker 4: offered me a more interesting job. And so I have
Speaker 4: been working mostly on the so called buyside of the industry,
Speaker 4: so the part of the industry that invests, actively invests
Speaker 4: and takes risks. So I've worked for Citadel twice for
Speaker 4: a small edge fund as a portfolio manager, and then
Speaker 4: Millennium and Hudson River Trading, and I've kind of taken
Speaker 4: turns between doing quantitative research and risk management. So most
Speaker 4: recently I was at Hudson River Trading until the beginning
Speaker 4: of November.
Speaker 3: I think when people think about like multi strategy hedge
Speaker 3: fund or shop or whatever, maybe sort of Millennium is
Speaker 3: the first one that would come to mind for people.
Speaker 3: If someone asks you, how does Millennium make money? And
Speaker 3: they seem to have made a lot of money over
Speaker 3: the years, what's the answer?
Speaker 4: Okay, I hope without saying anything that is proprietary, but
Speaker 4: I think.
Speaker 3: That like the business model of Millennium, Yeah.
Speaker 4: I think that what Millennium has excelled at has been
Speaker 4: the ability to scale up, so to adapt its existing
Speaker 4: platform to accommodate new strategies and new portfolio managers and
Speaker 4: so sometimes actually in some of their marketing material they
Speaker 4: called it something like an investment operating system. So it's
Speaker 4: a system that is a firm that is willing to
Speaker 4: absorb some relatively new strategy and create an environment for
Speaker 4: that strategy to succeed. And so because of that, I
Speaker 4: think they might be having right now the highest number
Speaker 4: of individual pods maybe close to three hundred and hovering
Speaker 4: around sixty billion dollars of AUM of assets under management.
Speaker 4: But I would say, what is their superpower is really
Speaker 4: their ability to scale in number of pods.
Speaker 2: So you mentioned creating an environment for success there, what
Speaker 2: does that look like at an organization like that? What
Speaker 2: are the sort of like conduits that allow trades in
Speaker 2: that particular organization to be successful?
Speaker 4: So I would give a sort of an idiosyncratic maybe
Speaker 4: a story around, please the rationale for success of platforms.
Speaker 4: So I see platforms a little bit like managing an
Speaker 4: arbitrage or some kind of gap between the single platform,
Speaker 4: the single manager, or the small hedge funds and the
Speaker 4: fund of funds. So if you're a fund of funds,
Speaker 4: you do have the scale, but you do not have
Speaker 4: the ability to observe from a close distance the performance
Speaker 4: of your vehicles for investment. And let's say that they
Speaker 4: don't perform well, you have to wait a year in
Speaker 4: order to take your money back. In the case of
Speaker 4: a hedge fund platform, you could actually not only observe
Speaker 4: the performance of pms or volume managers their skill from
Speaker 4: a very close distance, but you can also help them
Speaker 4: perform better. So you can centralize some of the functions
Speaker 4: that make them better capital access, corporate access, risk management.
Speaker 4: If they perform well, to give them more capital. If
Speaker 4: they don't perform well, to take capital away from them
Speaker 4: or let them go. And at the same time you
Speaker 4: also solve two for two other problems. So one is
Speaker 4: there is a risk transfer happening because a platform almost
Speaker 4: by design otherwise is not really a platform, has a
Speaker 4: pass through fee structure that's fundamental for the existence of
Speaker 4: a platform that makes really a platform what it is
Speaker 4: instead of a just multi manager hedge fund like the show.
Speaker 4: So this means that a portfolio manager is not paid
Speaker 4: with the incentive fee that the hedge fund as a
Speaker 4: whole receives from the limited partners, but instead the portfolio
Speaker 4: managers are paid a percentage of their p and L.
Speaker 4: This payment is passed through directly to the limited partners
Speaker 4: to the investors, and this basically transfers the risk directly
Speaker 4: basically from the PM into the limited partner, And so
Speaker 4: this makes the system more robust in a sense, right,
Speaker 4: And combine this with the diversification across investment styles and
Speaker 4: the number of pms, and now you start having a
Speaker 4: mote around a platform that makes it successful.
Speaker 3: If a entity has three hundred pods and everyone's doing
Speaker 3: their own thing, et cetera, why doesn't the return just
Speaker 3: become the market return like it seems like because there's
Speaker 3: a right Like, one intuition could be that this model
Speaker 3: wouldn't scale. I mean, I know it does, but one
Speaker 3: intuition could be that this model wouldn't scale that the
Speaker 3: more you add, you overdiversify and then you just end
Speaker 3: up with like whatever, like you know, like buy the
Speaker 3: VTI ETF or something like that. Why doesn't it work
Speaker 3: out that.
Speaker 4: A simplest explanation for this is actually just to look
Speaker 4: at what a retail investor right would hold in their portfolio.
Speaker 4: So let's say that they are, you know, long Apple
Speaker 4: and IBM. Okay, they have a little bit of an
Speaker 4: imperfect version of the market, right, But what makes their
Speaker 4: skill is how different are the weights of their Apple
Speaker 4: and IBM holdings compared to the market. Okay, So you
Speaker 4: can decompose your performance in your personal account into the
Speaker 4: sum of let's say the market and your idiosyncratic bets
Speaker 4: into these stocks. Now, what the hedge funds do is
Speaker 4: they do the same, but they completely eliminate as much
Speaker 4: as they can their exposure or their investment in the market,
Speaker 4: So they run purely market neutral and factor neutral portfolios.
Speaker 4: So there is diversification, but these indiosyncratic bets don't get
Speaker 4: diversified away into a big market, but they actually become
Speaker 4: essentially a bunch of independent bets that by the law
Speaker 4: of large numbers, they tend to have better and better
Speaker 4: risk adjusted profiles.
Speaker 2: So I still see some platform heads describe like the
Speaker 2: overall tilt as market neutral. So what do they mean
Speaker 2: by that? Exactly?
Speaker 4: I mean they typically run a wide range of strategies,
Speaker 4: so let's focus because it's more relatable. Let's focus on
Speaker 4: discretion ory long short equities and systematic equities because everybody
Speaker 4: knows star.
Speaker 2: I've love that you think systematic equities is relatable.
Speaker 4: Yeah, yeah, I mean relatively to I don't know, treasury
Speaker 4: basis or sell involved. So they mean that typically they
Speaker 4: do have a so called factor model, and a factor
Speaker 4: model is a little bit like having a market model
Speaker 4: on steroids, So you have a market term, so you
Speaker 4: can see your portfolio as having exposure to the market,
Speaker 4: so behaving a little bit like a market. And then
Speaker 4: it's also behaving a little bit like a portfolio that
Speaker 4: has momentum okay, and then it also has maybe a
Speaker 4: tilt in terms of value. The platforms tend to run
Speaker 4: portfolios that have no market exposure whatsoever, and then they
Speaker 4: also tend to have controlled exposure in these more exotic factors.
Speaker 3: How do they know that? I mean, so there's someone
Speaker 3: up there at the center, there's all that three hundred pods.
Speaker 3: The data gets probably aggregated and sliced in various ways,
Speaker 3: but what is the job or how do they actually
Speaker 3: sure that on that their portfolio managers don't have that
Speaker 3: market beta.
Speaker 4: Yeah, they typically have at the very minimum. They will
Speaker 4: buy some commercial factor model, which is a model of
Speaker 4: the market, like of your investment universe, how the how
Speaker 4: a stock behaves. How can you decompose the performance of
Speaker 4: the stock in this various systematic or let's call them
Speaker 4: pervasive market wide factors and instead idiosyncratics. So you buy
Speaker 4: them off the shelves. I mean, they're really expensive and
Speaker 4: they do a job. And so once you've bought them,
Speaker 4: you create some kind of user friendly interface so that
Speaker 4: a portfolio manager can always see how the portfolio looks
Speaker 4: like at any point in time. It's a little bit
Speaker 4: like having an X ray of you know, your body
Speaker 4: in real time. You know, you can see, oh, well,
Speaker 4: my portfolio is is a little bit short, the market
Speaker 4: is a little bit long momentum, maybe there is some crowding, exposure, whatever,
Speaker 4: And so this is in the hands of the portfolio manager.
Speaker 4: And then there is another layer on top of that,
Speaker 4: which is very important risk management, which ensures that pms
Speaker 4: are behaving well, that they're not going out of scope.
Speaker 4: You know, they're not buying microstocks or you know, investing
Speaker 4: in crazy stuff just.
Speaker 3: Going or just going along in video.
Speaker 4: Or long in Vidia. Yeah, if their idea is going
Speaker 4: long in Vidia, probably that's not an ideal portfolio manager. Yeah.
Speaker 2: So the other thing I've been wondering is how much
Speaker 2: visibility are there between the different pods within one shop. Yeah,
Speaker 2: And I mean that like, I assume there's a centralized
Speaker 2: risk management system of some sort that is like netting
Speaker 2: out positions and trying to make use of capital most efficient,
Speaker 2: and that's where a lot of the edge comes from.
Speaker 2: But also, if you're just a trader pursuing your own strategy,
Speaker 2: do you know what the guy next to you is doing?
Speaker 2: Do you have that kind of vision ability or is
Speaker 2: the idea to keep everyone sort of intellectually separated so
Speaker 2: that they're not influenced by each other.
Speaker 4: Right, that's a good question. So there is no really
Speaker 4: black and white answer to this, because historically there was
Speaker 4: a time when platforms had more visibility and more collaboration
Speaker 4: among pods or at least pods in the same sector,
Speaker 4: for example. But I would say that the historical trend
Speaker 4: has been more and more to give them the tools
Speaker 4: to succeed, but not give them the ability to see
Speaker 4: into each other's portfolios for example. And the rationale for
Speaker 4: this is you probably prefer having independent bets to having
Speaker 4: maybe corredated bets that could be like maybe a little
Speaker 4: bit more informed. So that's the trade off. Let's if
Speaker 4: we talk, maybe we can come up with slightly better ideas. Sure,
Speaker 4: but yeah, I think that the trend is more and
Speaker 4: more towards you are not seeing what I am, what
Speaker 4: I'm having, what I'm holding.
Speaker 3: Talk to us more about the risk management component, and
Speaker 3: again I don't know very much. I understand that you know,
Speaker 3: stop losses are very tight and you don't get a
Speaker 3: long leash to lose money, and if you're not doing well,
Speaker 3: your capitals reduced. If you're doing well, I guess you
Speaker 3: get more, and if you do more, you get more,
Speaker 3: et cetera. But from how would you describe the sort
Speaker 3: of the essence of risk management at the hedge fund level.
Speaker 4: So there are maybe two or three core functions that
Speaker 4: can be described in a qualitative way, but you know,
Speaker 4: I think pretty comprehensively. And then there there is something
Speaker 4: that is a little bit more esoteric or like domain specific.
Speaker 4: So let's talk about the general principles. Okay, So you
Speaker 4: mentioned stop losses, so this is very important. You know,
Speaker 4: there are always stop losses, the ones that you know
Speaker 4: you have and the ones you don't know you have,
Speaker 4: but everybody has stop losses in life. Okay, So those
Speaker 4: are very important because you could imagine that a PM
Speaker 4: is a little bit like somebody who's holding a coll
Speaker 4: option and you you know, the PM who's losing money
Speaker 4: has kind of a incentive to go for broke maybe sometimes.
Speaker 4: But the stop laws is effectively at a sort of
Speaker 4: a primitive tail insurance TAE risk management tool on the
Speaker 4: left tail of a PM. So that's very important. The
Speaker 4: second principle is sort of self enforcing, is true diversification.
Speaker 4: So this is where you want to have some kind
Speaker 4: of risk model that tells you what are the hidden
Speaker 4: bets that kind of overlap and maybe compound at the
Speaker 4: aggregate level, so that if everybody takes a little bit
Speaker 4: of a factor exposure in the same direction and then
Speaker 4: you sum this across three hundred pms, it becomes a
Speaker 4: big factor exposure. So a risk management organization needs to
Speaker 4: get that right. The third thing is making sure that
Speaker 4: people stay in scope. Okay, so seems trivial, but actually
Speaker 4: that requires a lot of domain expertise. So understanding the trades,
Speaker 4: what can go wrong from an operational standpoint macrostructure standpoint.
Speaker 2: Is this factor drift risk as well?
Speaker 4: Or said that scope is more like factor drift or
Speaker 4: in general strategy drift, not only factor but whereas being
Speaker 4: in scope is more of a pure strategy drift or
Speaker 4: just taking risks that a portfolio manager would be possibly
Speaker 4: aware of, but that maybe the head of the hedge fund,
Speaker 4: because it's not an expert in that area, is not
Speaker 4: so aware of. So the risk manager has to know
Speaker 4: very well what's going on and an alert. Talk to
Speaker 4: the PM, talk to the business head and.
Speaker 2: Can you give us concrete examples from your experience of
Speaker 2: the kind of things that would set off alarm belts.
Speaker 2: So is there like, I guess you don't have to
Speaker 2: give us specific examples, but you know the kind of thing,
Speaker 2: the types of examples, Yeah, the types of examples that
Speaker 2: would catch your eye in a risk management position.
Speaker 4: So we covered a little bit the easy stuff, right,
Speaker 4: So the easy stuff is people taking too much risk.
Speaker 4: First of all, it simple, but you know, we think
Speaker 4: in terms of dollar volatility. Dollar volatility is a little
Speaker 4: bit like how much you can make or lose in
Speaker 4: one year for it.
Speaker 2: So like value at risk, those kind of kind of
Speaker 2: value risk.
Speaker 4: Yes, I mean most people think in terms of all
Speaker 4: value risk too. Okay, yeah, choose your risk metric you
Speaker 4: want to stay within that. Then factor exposures. Okay, that's
Speaker 4: also easy concentration. So if you take a mega bet
Speaker 4: in Nvidia, it has to surface. Okay. So these are
Speaker 4: relatively simple. There are things that are a little bit
Speaker 4: more complicated, like, for example, you take some true arbitrage
Speaker 4: positions where you think that something is running cheap versus
Speaker 4: rich in say bond versus futures, or you do some
Speaker 4: kind of funding arbitrage trade where different agents in the
Speaker 4: investing world have different funding rates for their assets, and
Speaker 4: those can break, like in a dislocation, that can break.
Speaker 4: And so the way that typically you manage these things
Speaker 4: a little it's a little bit like in merger arm.
Speaker 4: You give it a max size and you want to
Speaker 4: make sure that this is correct, that this size is correct,
Speaker 4: and it's monitored. So this is stuff that can go wrong.
Speaker 3: Two managers like, how much do they I mean, I'm
Speaker 3: sure there's sort of I don't know if it's accidental
Speaker 3: style drift or you know, drift is sort of a
Speaker 3: neutral term. How much does the risk manager have to
Speaker 3: watch out for I guess intentional drift or this is
Speaker 3: a working I know this is not quite my mandate,
Speaker 3: this is not quite what I was made to trade.
Speaker 3: But I could sort of justify it this way, or
Speaker 3: I just see all these lines up over here going up,
Speaker 3: I need to how much of a risk management concern
Speaker 3: is that?
Speaker 4: Okay, I think that in general the principle should be trust,
Speaker 4: but verify. I would say that the vast majority of
Speaker 4: portfolio managers are very responsible, and because they're in that role,
Speaker 4: they have been educated to control their risks, to understand
Speaker 4: them with occasional screw ups, and so that's why you
Speaker 4: need very fie got it?
Speaker 3: Okay.
Speaker 2: On the opposite side of screw ups, I'm curious how
Speaker 2: capital gets kind of doled out. And if I'm running
Speaker 2: a massively profitable, successful training strategy, do I automatically start
Speaker 2: giving start being given more money to you know, play
Speaker 2: around with or is there some amount of discipline here
Speaker 2: where you don't want people to be bumping up against
Speaker 2: you know, sizing positions or additional trading costs and things
Speaker 2: like that. Imagine I am the most popular trader, the
Speaker 2: most successful popular also popular, I'm both the most popular
Speaker 2: trader and most successful trader at Citadel.
Speaker 3: What is the process for traces getting more money to trade?
Speaker 2: How do I get more popular and successful? Probably not popular?
Speaker 4: Okay, assume that you're popular and successful, okay, So do
Speaker 4: you get more capital? You do get more capital up
Speaker 4: to a point. So there are a couple of factors.
Speaker 4: The first one is there is like a natural limit
Speaker 4: where somebody can be too successful. And without giving examples,
Speaker 4: but there are large funds whose daily p and l
Speaker 4: sometimes at points are driven is driven by a single
Speaker 4: strategy Okay, and maybe that's justified, right, But there is
Speaker 4: a point where there could be just too much because
Speaker 4: the concentration across strategies. Or think of pods as stocks, right,
Speaker 4: you don't want to have ninety percent of your savings
Speaker 4: in Nvidia, So okay, so that's number one. So there
Speaker 4: is some kind of basic heuristics. Then there is just
Speaker 4: a natural limit to growth for strategies, like there is
Speaker 4: a trade off because your market impact is very high
Speaker 4: and so, or there is just a hard size for
Speaker 4: your strategy, so you cannot scale high frequency, you cannot
Speaker 4: scale to infinity even index rebalancing. Or if you're a
Speaker 4: consumer PM, your costs increase faster than the size of
Speaker 4: your portfolio, so your P and L in the absence
Speaker 4: of costs goes more or less lilenar linearly, but your
Speaker 4: costs grow faster than linearly. So there is a point
Speaker 4: where you just don't want to grow all Right.
Speaker 3: On the flip side, Let's say Tracy comes in and
Speaker 3: she is a PM and she has her pod. How
Speaker 3: long is she likely to last and what would cause
Speaker 3: her what would be the threshold at which she gets fired.
Speaker 4: I don't have the statistics on the average tenure of
Speaker 4: a PM, Okay, if I had them, probably I shouldn't say. Well,
Speaker 4: and also depends a lot on the place. Okay, so
Speaker 4: how long I would say that it's like everything in life, right,
Speaker 4: So like ninety percent of everything is of poor quality,
Speaker 4: I'm sorry to say, but the same applies to pms.
Speaker 4: But this is another beautiful aspect of platforms, by the way. Okay,
Speaker 4: so let me take a quick ditchure about this again,
Speaker 4: because like a beautiful and under appreciated aspect of platforms
Speaker 4: is that they act like sieves. So you go through
Speaker 4: basically every possible PM on the market, and there is
Speaker 4: a turnover, let's say, of twenty percent, So twenty percent
Speaker 4: of pms more or less are let go every or
Speaker 4: leave every year, but you keep the good ones right,
Speaker 4: and so eventually you have a sufficient number of pms
Speaker 4: who really can carry make the business sustainable. And a
Speaker 4: platform is an instrument for exploration. Okay. So I'm not
Speaker 4: saying how long they last or whatever, right, but okay,
Speaker 4: how good do you need to be? I think that
Speaker 4: if you have a market neutral sharp RAI show which
Speaker 4: for those who are not used to this number, this
Speaker 4: basically is a risk adjusted measure of profits. So you
Speaker 4: take your P and L and you divide by some
Speaker 4: measure of risk, and you get the sharp pray show.
Speaker 4: If you don't have these kind of market exposures, you
Speaker 4: call it information race show. If you have an information
Speaker 4: ratio of one, and you are managing your left tail
Speaker 4: sufficiently wisely, you can survive. Okay, So you know, start practicing.
Speaker 2: Okay, okay. But on this note, the other thing I
Speaker 2: wanted to ask you was, you know, we tend to
Speaker 2: talk about these things platforms, pod shops, multi strat as
Speaker 2: like this one big blob basically doing a similar thing.
Speaker 2: But my impression is that the culture varies quite substantially
Speaker 2: across firms. And again there aren't that many that are
Speaker 2: doing this, although as Joe said and the intro, the
Speaker 2: number is growing. But when we talk about that kind
Speaker 2: of cultural variation, what do we mean exactly?
Speaker 4: To an amazing extent, I think that platforms are shaped
Speaker 4: by the personalities of their founders. So is Englander as
Speaker 4: a personality, and a personal history can grief in as
Speaker 4: a different one, So of wads and river trading not
Speaker 4: a platform, you know, strict to censu but you know,
Speaker 4: to some extent, multi strategy, and so and so the
Speaker 4: cultures are very affected by this. So if you are
Speaker 4: a trader like Ken Griffin, it's more likely that the
Speaker 4: fund that you work in it's as more of a
Speaker 4: trading as opposed to maybe a pure technology culture. Millennium
Speaker 4: is very decentralized. Citadel tends to run more like a
Speaker 4: centralized and efficient organization. So in the words of a
Speaker 4: of a Hedgehund manager, you know, Citadel is like Singapore
Speaker 4: and Millennium is like the United States. Right, Singapore very efficient,
Speaker 4: efficiently run technocratic to some extent, and the US is
Speaker 4: messy and inefficient, but it's very robust. And in a sense,
Speaker 4: you know, Millennium has these features of robustness of it's
Speaker 4: like an organic creature. It does change a lot. So
Speaker 4: other some firms are more collaborative. I think Ballyasni for example,
Speaker 4: tends to be more collaborative than these other two firms.
Speaker 4: But by the way, and your marriage may vary between
Speaker 4: different teams, like depending on where you work, you know,
Speaker 4: it can be heaven or it can be hell.
Speaker 3: All Right, someone hears this podcast, maybe they're in college
Speaker 3: studying finance or maybe something in tech or something engineering
Speaker 3: or whatever. They're like oh, this sounds really cool. I
Speaker 3: want to work, for one, what is sort of the
Speaker 3: basic path that one winds up maybe first in a
Speaker 3: pod and then running a pod.
Speaker 4: Okay, So first of all, I would like to dissuade
Speaker 4: everybody who's listening from studying a career in finance.
Speaker 3: Okay, okay, So everyone's going to take that as a challenge,
Speaker 3: but keep going.
Speaker 4: Of course. And so I wrote a small document because
Speaker 4: I got a lot of questions like this from students,
Speaker 4: and the brutal answer is that it's very difficult and
Speaker 4: there is some luck involved. So it does help to
Speaker 4: go to schools with a brand name, for sure. It
Speaker 4: definitely does help if you want to do quantitative stuff
Speaker 4: to be a very good programmer, and you know, you
Speaker 4: need to have the ability to think quantitatively. So that's
Speaker 4: that's for sure. There are couting tests that make the
Speaker 4: admission a little bit more democratic nowadays, but still still
Speaker 4: it's very selective. I am not particularly qualified to give
Speaker 4: advice on how to get food in the industry. I
Speaker 4: think I have a better view of how to succeed
Speaker 4: in how to be happy, not succeed how to be
Speaker 4: happy in the industry.
Speaker 3: So that's probably more important, let's hear this.
Speaker 4: Yeah, yeah, So I mean how to be happy in
Speaker 4: the industry. I think that I ask a lot the
Speaker 4: question of what makes a good analyst or a good
Speaker 4: quantitative researcher to people, and I get very often the
Speaker 4: same answer, which is people who are curious do well
Speaker 4: and seem to be happy. So as usual, you need
Speaker 4: to have passion, you need to go, you know, to
Speaker 4: get into the weekend, and not being able not to
Speaker 4: think about a problem. So I think obsession helps. Okay,
Speaker 4: So I think the belongs to the obsessed, for good
Speaker 4: or worse in the future. Like you can see this,
Speaker 4: it's a heavy tailed world. So if you want to
Speaker 4: have a more stable job and less absorbing, I think
Speaker 4: being a dentisty is a better career path. But having
Speaker 4: some level of obsessions into this stuff it's good. Otherwise
Speaker 4: at some point, you know, you leave the industry. It's
Speaker 4: perfectly fine.
Speaker 2: By the way, So this actually reminds me of something
Speaker 2: else I wanted to ask you. So you said the
Speaker 2: world belongs to the obsessed, which great line is a
Speaker 2: very good line. But when I read books on quantitative finance,
Speaker 2: so much of it seems to be about Greek letters
Speaker 2: for a start, but basically sizing and managing risk and
Speaker 2: how to look at your positions and all of that,
Speaker 2: how do you actually generate trade ideas? Like where does
Speaker 2: the strategy come from? Am I just looking for you know,
Speaker 2: mathematical dislocations in the market and arbitrary opportunities? Or am
Speaker 2: I thinking like I want to go big on something
Speaker 2: like AI or clean energy or whatever.
Speaker 4: So I think that there are two dimensions to your question.
Speaker 4: So the first one is how objectively do you create alpha? Okay?
Speaker 4: And so there are only a certain finite number of
Speaker 4: ways to go about alpha okay. So there are structural,
Speaker 4: structural imbalances that are not adaptively filled because the market
Speaker 4: is poorly designed, because we don't live in a neoclassical world, okay,
Speaker 4: and so these imbalances persist. And how do you exploit
Speaker 4: this physical alpha? Is two ways. The first one is
Speaker 4: you're a freaking genius and you face a wall for
Speaker 4: two years, do research, and you come up with an
Speaker 4: originally okay, there are people like this, very few. The
Speaker 4: other is simpler. It's like a Renaissance style. You are
Speaker 4: an apprentice in a famous painter's shop and you learn
Speaker 4: the trade, and then you strike it on your own
Speaker 4: and you make it a little bit better, and even
Speaker 4: making it a little bit better can make a huge difference.
Speaker 4: So I would say imitation plays a big role. And
Speaker 4: then maybe there is another characteristic, which is you just
Speaker 4: have to have the right makeup in terms of you know,
Speaker 4: drive tolerance, risk tolerance, so you know when you I
Speaker 4: was actually having lunch with a former zero point seventy
Speaker 4: two pm now and his biggest jordan was ninety million dollars,
Speaker 4: which is, by the way, not crazy crazy high. If
Speaker 4: you're down half a billion dollars, you're literally losing your marbles. Okay,
Speaker 4: your you know, your face looks different.
Speaker 3: So have you seen that?
Speaker 4: Oh sure, yeah, yeah, yeah.
Speaker 3: I remember in a flowed by randomness to Lev talks
Speaker 3: about watching all of like the hormones of someone who
Speaker 3: just lost a lot of money, like pour out, and
Speaker 3: how pale they look.
Speaker 4: Right.
Speaker 3: He had a specific comment about that if there are
Speaker 3: only so many geniuses, if there isn't an infinite supply
Speaker 3: of alpha, if the structural forces, the physical forces as
Speaker 3: you describe them, you know, there's only so many sort
Speaker 3: of these dislocations or reasons why reality is separate from
Speaker 3: the neoclassical world. Does it imply that as we see
Speaker 3: more of these launches, and as these hedgephones get bigger,
Speaker 3: that the opportunity diminishes. Yes? Cool?
Speaker 4: Wait, why, well, because everything has a finite capacity, that's it.
Speaker 4: I mean, And you know, as you say, Joe, right,
Speaker 4: there is there are only that many opportunities, and each
Speaker 4: opportunity has a finite capacity, and so at some point
Speaker 4: everybody is doing the same thing and you get to
Speaker 4: some kind of equilibrium which is not necessary that everybody
Speaker 4: makes the minimum rate of return. Right, But you know.
Speaker 2: You mentioned earlier the systematic equities are more relatable than
Speaker 2: other things like the treasury basis trade and I kind
Speaker 2: of my personal experience, I would beg to differ because
Speaker 2: I come from a sort of credit background. But it
Speaker 2: reminded me a lot of these firms are becoming bigger
Speaker 2: presences in the bond market, bigger market making roles and
Speaker 2: that sort of thing. Does the day to day of
Speaker 2: being in equities versus fixed income in this kind of world?
Speaker 2: Is it very different or do similar principles? Supply?
Speaker 4: I think it's very different, actually, you know, And why first,
Speaker 4: in fundamental equities, your edge is mostly informational, so you
Speaker 4: do have a model of the world that differs from consensus,
Speaker 4: and you monetize that. It's really informational. In the case
Speaker 4: of a lot of fixed income, is truly structural. You know,
Speaker 4: there are predictable flows, there are well known imbalances, there
Speaker 4: are different demands for liquidity. So it's more of a
Speaker 4: strategy or a class of strategies that has skew. So
Speaker 4: you could lose a lot of money, but to collect
Speaker 4: pennies on a regular basis, so you need to manage
Speaker 4: risk for that. You need to have more capital for that,
Speaker 4: and scenarios for that. So the risk management. The way
Speaker 4: you think about investment is different, is more scenario based,
Speaker 4: it's less diversified. Fundamentally, you have relatively correlated bets.
Speaker 3: Why isn't the world actually mapped to the neoclassical view
Speaker 3: of the world because there's so much money and there's
Speaker 3: so much investment and effort being put into spotting any
Speaker 3: price dislocation anywhere, So why is it with all the
Speaker 3: money and all of the professionals and the geniuses and
Speaker 3: the supercomputers and the AI that are like essentially attacking
Speaker 3: the question of finding mispriced securities. Why are there still
Speaker 3: mispriced securities?
Speaker 2: Theory everything should get arbed out.
Speaker 4: Yeah yeah, but not in practice.
Speaker 3: Well yeah, but that's why. Why not? Why does it
Speaker 3: even with all the professionals and money trying to do this,
Speaker 3: did there still persist in these anomalies or dislocations, whatever
Speaker 3: you want to call it.
Speaker 4: I don't I'm not really qualified to answer, but I
Speaker 4: just see, there is only a finite number of professionals,
Speaker 4: you know, and there is only a finite number of
Speaker 4: professionals with a certain risk tolerance. So and there are
Speaker 4: constraints all around their constraints on your balance sheet, there
Speaker 4: are constraints on how much money can you lose. So
Speaker 4: there are all sorts of limits to arbitrage that go
Speaker 4: beyond the toy model of you know, slife with AMBITIONI
Speaker 4: but they go So that's kind of a funding arbitrage.
Speaker 4: And the mechanism, by the way, it's wrong for that paper.
Speaker 4: I mean, it's not realistic, not wrong, it's like artificial.
Speaker 4: But wherever there is a constraint, independently of how many
Speaker 4: players you have, you have a potential inefficiency and it's
Speaker 4: not going to go away.
Speaker 2: I have a practical question, And I always wanted to
Speaker 2: ask this of someone, and I think you're the perfect
Speaker 2: person to perhaps answer this. But if you are a
Speaker 2: risk manager at this kind of firm, and I don't
Speaker 2: know you're you come into the office and it's let's
Speaker 2: say it's like the day of a FED meeting and
Speaker 2: Jerome Powell comes out and says something completely unexpected, or
Speaker 2: let's say it's twenty fifteen and China suddenly announces they're
Speaker 2: devaluing the un And you're looking at your computer screen
Speaker 2: and you're looking at the various risk metrics. How fast
Speaker 2: do those move and how much of it is calculated
Speaker 2: in real time versus all the numbers having to be
Speaker 2: run at the end of the day when you net
Speaker 2: out trading positions.
Speaker 4: If you have the right model, you should be able
Speaker 4: to either capture those risks directly in a sense, imagine
Speaker 4: you have a sensitivity to the various points in the
Speaker 4: Yell curve, either in your fixed income portfolio or in
Speaker 4: your equities portfolio. If you capture those well, so it's
Speaker 4: a risk that you you know you're taking and you
Speaker 4: can hedge. You should see the factor moving, but not
Speaker 4: your porfolio moving. Okay, And by the way. You can
Speaker 4: also not have these factors, but you may have factors
Speaker 4: that are proxying these microeconomic drivers, like say, for example,
Speaker 4: momentum is one, crowding is another. And so even if
Speaker 4: a portfolio manager doesn't think directly in terms of points
Speaker 4: on the ill curve, but they have other related ways
Speaker 4: of thinking, so they can still control for that. And
Speaker 4: then there is, unfortunately the case where well we never
Speaker 4: model this, we do not have a proxy for this,
Speaker 4: and then you're screwed, And yeah, you don't want to
Speaker 4: be in that situation. Typically, you know, you can see
Speaker 4: these effects like I mean, there was a big surprise
Speaker 4: when when rates went up a lot of equity portfolios
Speaker 4: moved and they didn't know why, and there was no
Speaker 4: interest rates sensitivity in commercial factor models.
Speaker 3: So there you go in theory, on a day of
Speaker 3: some sort of unexpected event. Tracy mentioned the China U
Speaker 3: end evaluation. If everything is working perfectly and you truly
Speaker 3: do have like completely eliminated your market exposure, does that
Speaker 3: show up at that level, like does it still show
Speaker 3: up somehow?
Speaker 4: It still can show up in weird ways, right, So
Speaker 4: for example, you can be market neutral. Yeah, the market
Speaker 4: has a big drowdown and you still lose money. Why
Speaker 4: because the market the drawdown starts weird processes of the
Speaker 4: risking that affect your portfolio. So even if I'm market neutral,
Speaker 4: somebody is selling my stock to reduce their risk and
Speaker 4: it's affecting even though I'm perfectly market neutral. So weird
Speaker 4: things can happen. Unfortunately, you know, so there is no
Speaker 4: perfect model, that's the short answer.
Speaker 2: Unfortunately, you mentioned crowding in multi strap and the idea
Speaker 2: that maybe you know, eventually you would reach a limit
Speaker 2: for the efficacy of some of this type of trading.
Speaker 2: What's next for hedge funds? So we went from fund
Speaker 2: of funds to pod shops. They became the hot new thing.
Speaker 2: What comes after pod shops?
Speaker 3: What's exciting?
Speaker 4: I'd love to know. It's for the next guest to answer,
Speaker 4: I don't know.
Speaker 2: This is where you reveal where you're gardening, your current
Speaker 2: gardening leave ends, and where you're gonna wind up next.
Speaker 4: Oh yeah, my best job is always the next I
Speaker 4: don't know. But so what's next in terms of business model?
Speaker 4: Would be very interesting to know what's next. So there
Speaker 4: are some interesting ideas. So there is the idea of
Speaker 4: alpha capture, which is kind of a big umbrella. And
Speaker 4: you know, alpha capture has has an interesting story. So
Speaker 4: there was external external sale set alpha capture. That's historically
Speaker 4: like kind of a creation of Martial Ways, an English
Speaker 4: hatch fund that in two thousand and three or four
Speaker 4: study at program called tops where they gathered ideas from
Speaker 4: the cell side, and that for a while was very
Speaker 4: profitable and also has lots of other byproducts that are great.
Speaker 4: Now I think it's kind of arbitraged out now there
Speaker 4: is a similar concept of byside external alpha capture. So
Speaker 4: there are firms that are trying to get ideas from
Speaker 4: hedge funds, small edge funds. They don't have scale, they
Speaker 4: can aggregate them and then they make into a portfolio.
Speaker 4: That's a new business model. I don't know how scalable
Speaker 4: it is, how sustainable it is, but that's an idea.
Speaker 4: There is definitely an expansion into privates. I have like
Speaker 4: zero skill or zero divisibility to this stuff, so that's
Speaker 4: really another question for somebody else. And then there is
Speaker 4: always product innovation. Every strategy is continuously innovating, has to change.
Speaker 4: So just look at where fundamental Equities was one hundred
Speaker 4: years ago. Go right, the recommendation was invest in a
Speaker 4: railway single stock and you know, be happy. And now
Speaker 4: we have, you know, and now we spend hundreds of
Speaker 4: millions of dollars in alternative data and there are tools
Speaker 4: and stuff. So what is it in ten years I
Speaker 4: don't know, but it will be very different than it
Speaker 4: is today.
Speaker 3: I remember, you know, when I was over twenty years
Speaker 3: ago and I first got interested in markets, picking up
Speaker 3: the Intelligent Investor because of course, you know, Buffett and
Speaker 3: Munger were into it and like reading is like and
Speaker 3: so if you buy the Brooklyn rail bond yielding eight percent,
Speaker 3: I was like, what is this?
Speaker 1: Yeah?
Speaker 3: I just thought it seems so disconnected from me. I mean,
Speaker 3: I'm sure there's a lot of deep wisdom and I
Speaker 3: probably would have like internalized it. Yeah, but just in
Speaker 3: terms of like what they were talking about, it seems
Speaker 3: so funny because of how antique it all seemed.
Speaker 4: Totally. Yeah. And so now pms are quantitative. Fundamental pms
Speaker 4: tend to be quantitatively quite literate. In the future they
Speaker 4: will be even different. Maybe they will be prompt experts.
Speaker 4: I don't know.
Speaker 3: Can you be a fundamental PM by just being a
Speaker 3: domain expert in a certain area, say like you're really
Speaker 3: understand biotech, or say you really understand the semiconductor industry
Speaker 3: and you want to trade chip stocks versus and not
Speaker 3: really have that sort of quant background but some other expertise.
Speaker 4: So being a domain expert is definitely a necessary condition.
Speaker 4: You absolutely need to be a domain expert. And since
Speaker 4: you make the example of healthcare super domain experts, so
Speaker 4: a lot of good healthcare pms have either worked in
Speaker 4: healthcare companies they have never practiced, but they are domain expert.
Speaker 4: Is is it sufficient to be just a domain expert.
Speaker 1: No.
Speaker 4: I think that you need to be able also to
Speaker 4: monetize and to risk manage your portfolio, and that's very difficult.
Speaker 4: So that's not sufficient, but it's definitely necessary.
Speaker 2: How important are the data sets? Like what if I'm
Speaker 2: just really good at finding original and alternative data someone's analysts.
Speaker 4: Yeah, it varies a lot, so some pms, well, okay,
Speaker 4: first of all, for systematic it matters a lot period Unconditionally,
Speaker 4: for discretionary pms, it varies a lot. So some pms
Speaker 4: will use alternative data, some will do deep research and
Speaker 4: think three months to a year ahead. And the reality
Speaker 4: is that there are not that many data that really
Speaker 4: help you think at that horizon. So we don't live
Speaker 4: in the world of really really big data for fundamental thinking.
Speaker 4: So I think that's interesting.
Speaker 2: I have just one more question, which is what do
Speaker 2: you find most satisfying about your job? What gives you
Speaker 2: the needs yeah or jobs? Yeah? What gives you the
Speaker 2: most pleasure on a data day basis? Do you feel
Speaker 2: fantastic if China devalues the un and you look at
Speaker 2: positioning across the firm and you're not going under, Or
Speaker 2: do you feel great if you identify a particular strategy
Speaker 2: or something like that.
Speaker 4: Now, the thing that gives me most pleasure when I
Speaker 4: work is when I do something that is useful and
Speaker 4: it works for others. So I just love the social
Speaker 4: aspect of working, Like it's actually a job where you
Speaker 4: can be of some use to other people, and I
Speaker 4: just enjoy that. So when things work out, like you
Speaker 4: come up with an idea after multiple failures and it works,
Speaker 4: you implemented, and somebody else uses it or finds a
Speaker 4: value to this, and everybody is happier and like and
Speaker 4: we get drunk together. That's great, all right.
Speaker 2: Giuseppe Palia logo aka Gappy, Thank you, so much for
Speaker 2: coming on all blots. Really appreciate it.
Speaker 4: Thank you, thank you.
Speaker 3: That was fantastic, Joe.
Speaker 2: I feel like that's good life advice. If it all
Speaker 2: ends in people getting drunk, it's usually no, wait, that
Speaker 2: doesn't make sense. Sometimes it's really bad, yeah, say never mind.
Speaker 2: But sometimes it's great.
Speaker 3: Sometimes it's good. I love that line. I feel like
Speaker 3: the world belongs to the obsessed. It's just like a
Speaker 3: really good line. That's sort of ominous to me because
Speaker 3: I don't really get obsessed with anything besides country music.
Speaker 3: And then the rest of my time, I'm just like
Speaker 3: I want to talk about hedge funds one day, and
Speaker 3: then the next day I want to talk about like
Speaker 3: how energy.
Speaker 2: Yeah, I was going to say, it's not really like
Speaker 2: get obsessed. It's just you flip. Then I'm an obsession
Speaker 2: to obsession, so.
Speaker 3: It's not real obsession. It's kind of delet Wait, Tracy,
Speaker 3: have I told you about when I got a job
Speaker 3: offer at a prop trading shop?
Speaker 2: This vaguely rings a bell.
Speaker 3: So can I tell a quick story?
Speaker 2: Go for it?
Speaker 3: So I had traded stocks in college just because it
Speaker 3: was like the dog Come era. It was fun, it
Speaker 3: was very easy. Everything was going up. I managed to
Speaker 3: sell for excellent reasons a good time, and I didn't
Speaker 3: lose all my money anyway. I was always I got
Speaker 3: interested in markets. Then I graduated with my useless liberal
Speaker 3: arts degree and I had a job. I was making
Speaker 3: minimum wage working at a Delhi and I saw this
Speaker 3: help wanted ad at a prop trading shop and all Austin, Texas,
Speaker 3: and it didn't seem like they had many requirements, so
Speaker 3: I went. They asked me about my personal trading. I
Speaker 3: played ping pong against the CEO. I played this video
Speaker 3: game that involved me using two joysticks. One was to
Speaker 3: control the tilt of a triangle and the other one
Speaker 3: was to control the space and I kept it in
Speaker 3: the square already, its weird. And I did this other
Speaker 3: thing where I like typed without like too many typos
Speaker 3: and stuff like that. And there were like two hundred
Speaker 3: people applied and second round, I got one of the
Speaker 3: four spots that they offered, and for reasons that still
Speaker 3: allude me to this day, I didn't take the job.
Speaker 3: I was enjoying making minimum wage at the deli. All
Speaker 3: my friends worked there. It was like the cool place
Speaker 3: to work in Austin. I didn't feel like giving that up,
Speaker 3: and I didn't, and I just like, I always think
Speaker 3: about what if, what does my life look like if
Speaker 3: I took that job? The strangest most inexplicable career decision
Speaker 3: I could ever imagine, not taking a trading job from
Speaker 3: a five dollar minimum way job or whatever it is
Speaker 3: at the time. Anyway, I'll never know.
Speaker 2: Okay, Well, I once got offered a specialty sales position
Speaker 2: in bank equities at a Swiss bank, and I never
Speaker 2: question what my future would have been had I taken
Speaker 2: that job. I'm very satisfied, but I actually have a question.
Speaker 2: Do you think you were put off by the weirdness
Speaker 2: no interview process? Like did you think that you were
Speaker 2: going to be playing ping pong and like moving joysticks
Speaker 2: as part of the job.
Speaker 3: That was fun? And I didn't even beat the CEO
Speaker 3: in ping pong. She beat me, but she still hired me.
Speaker 3: I don't, no, I don't know why I can't. The
Speaker 3: only thing I could explain is that in my post
Speaker 3: college life, I had a cool job where I got
Speaker 3: to hang out with my friends in the back of
Speaker 3: this deli at a grocery store. I didn't really feel
Speaker 3: like giving it.
Speaker 2: Up, just yet all right, Well, I do feel like
Speaker 2: coming out of that conversation with Giesseppe, I feel like
Speaker 2: I have a much better conception of how multistrat actually
Speaker 2: works and what people are sort of doing on a
Speaker 2: day to day basis, and also just maybe a better
Speaker 2: understanding of some of the terminology around the industry totally.
Speaker 3: So now we'll probably do more episodes, but I feel
Speaker 3: like I'm now like roughly grounded in at least some
Speaker 3: core ideas here.
Speaker 2: Yeah, and everyone should definitely check out Gappy's Buyside quant
Speaker 2: Job Advice. It's nine pages and it actually it goes
Speaker 2: into some detail on the structure of the industry itself
Speaker 2: of how you know quantitative hedge funds actually work, and
Speaker 2: like who are the big names and things like that.
Speaker 2: So anyone's interested in the space, definitely check it out.
Speaker 2: Shall we leave it there?
Speaker 3: Let's leave it there.
Speaker 2: This has been another episode of the Odd Thoughts podcast.
Speaker 2: I'm Tracy Alloway. You can follow me at Tracy Alloway and.
Speaker 3: I'm Jill Wisenthal. You can follow me at The Stalwart.
Speaker 3: Follow our guest Joseppi Polyioligo aka Gappy. He's Double Underscore
Speaker 3: Palyioligo on Twitter Follow our producers Carmen Rodriguez at Kerman
Speaker 3: Ermann Dashil Bennett a Dashbot, Killed Brooks at kill Brooks.
Speaker 3: Thank you to our producer Moses on Them. For more
Speaker 3: odd Lots content, go to Bloomberg dot com slash odd Lots,
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