What's a Pod Shop? Understanding Multi-Strategy Hedge Funds


Multi-strategy hedge funds are all the rage right now. But there's also a lot of confusion about what exactly they do, and how the the so-called "pod shops" differ from more traditional hedge funds. On this episode of the podcast, we speak with Giuseppe 'Gappy' Paleologo, a long-time veteran of the space. In addition to writing books about quantitative finance, Gappy was formerly the director of risk and quantitative analysis at Citadel and the head of enterprise risk at Millennium, among many other jobs. He walks us through what multi-strat traders actually do all day, what makes for a good multi-strat candidate, and how to win in the pod shop game. This transcript has been lightly edited for clarity.

Key insights from the pod:
Gappy’s many jobs in the hedge fund industry — 3:51
How do pod shops make money? — 5:18
What are the benefits of working within a trading platform — 7:41
How 300 pods in one organization can stay diversified — 9:32
How pod shops manage risk — 14:56
The average lifespan of a portfolio manager — 20:25
Why the world belongs to the “obsessed” — 27:24
The two ways to create alpha — 29:05
Why assets still get mispriced in the age of Big Data — 33:31
What will be the next big innovation for hedge funds — 38:29

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Tracy Alloway (00:20):
Hello, and welcome to another episode of the Odd Lots podcast. I'm Tracy Alloway.

Joe Weisenthal (00:25):
And I'm Joe Weisenthal.

Tracy (00:26):
Joe, I know we did one episode on pod shops, on multi-strategy hedge funds. But it was primarily focused on their impact on the market. And I have to say, I still came away from that conversation sort of wondering, if I worked at a pod shop, what is it exactly that I would be doing all day?

Joe (00:49):
I would love to know the exact same thing. I mean, I guess I have this like very vague sense of, sort of, they have a bunch of people all focused on their specific areas and they sort of average out and they net out a bunch of stuff and it's capital efficient and you know, it's like market neutral in theory, and etc. But beyond that, like, I still don't really understand. The only thing I know is they've done really well and many people are launching more of them.

Tracy (01:16):
Yes, they seem to be all the rage. They seem to be where everyone kind of wants to go in the quantitative finance space, at least. Everyone's sort of aiming for these big names, you know, places like Citadel, Millennium, maybe. But my question is like, why?

Joe (1:35):
It's my question, too.

Tracy (1:36):
Is it that they're minting money, they're expected to continue minting money in the future? Or is there something that's fundamentally intriguing and attractive about working in that space, that means lots of people want to get in?

Joe (01:47):
I mean, I think that could be two ways of saying the same thing. If they're minting money, then that probably is fundamentally attractive to people in that space. But I do think, backing up the questions, what we know is that many funds, including apparently, even B-tier or C-tier funds, have done very well. So I'm just curious how and why. And then, yeah, to the question of what does it take to succeed in them or who is the type of person who can succeed in this environment?

Tracy (02:16):
Alright, well I'm glad you put it that way, because today we are going to be speaking with someone who has done exactly that: succeeded in this particular environment. We have the perfect guest. We're going to be speaking with Giuseppe Paleologo, a.k.a. Gappy.

He describes himself as a “constant gardener,” someone who's on gardening leave quite a lot. He is also the author of Advanced Portfolio Management: A Quant’s Guide for Fundamental Investors. And I have to say it is one of the funniest books that I've read in quant finance. I can't say it's the funniest, because I did read My Life As a Quant, from Emanuel Derman, but it's definitely up there. And Joe, I know, I know you enjoyed it too.

Joe (02:54):
I did. You know, I skipped over all the numbers and equations and Greek letters.

Tracy (02:58):
You just looked at the jokes

Joe (02:58):
But it's very breezily written for what it is. And I did actually, I think maybe I learned a little bit even, in my sort of basic reading of it. Extremely well-written. I'm extremely excited about this conversation. You know, you mentioned that our guest is the king of gardening leave. If you look in his LinkedIn, it really is many different roles.

Tracy (03:19):
Well, I also have to say he is the only person I know who has both an alpha and a beta tattoo on his shoulder.

Joe (03:27):
Oh wow.

Tracy (03:28):
You know, some people do get the alpha symbol, but he has both, so you know, a well-balanced portfolio of tattoos all around.

Joe (03:36):
The yin-yang.

Tracy (03:36):
Yeah. So Gappy, thank you so much for coming on Odd Lots!

Giuseppe “Gappy” Paleologo (03:40):
Hi Tracy. Hi Joe.

Tracy (03:42):
So maybe to begin with, I'm going to let you explain your previous job history, because there is quite a lot. What is it that you've been doing in this industry?

Gappy (03:51):
Yeah, I'm not sure. I'm not sure. Okay, good question. Well, I got into this industry almost accidentally. I was for a few years a researcher in the math department at IBM Research, and then I got a little bit bored. So the only place that you can work in New York, other than you know, IBM or tech, is finance. So I got into finance almost accidentally.

And then again, there is no major plan to, you know, to my career choices. When I was getting bored, for some reason somebody called me and offered me a more interesting job. And so I have been working mostly on the so-called buy side of the industry. So the part of the industry that invests actively invests and takes risks. So I've worked for Citadel twice, for a small hedge fund as a portfolio manager, and then Millennium and Hudson River Trading. And I've kind of taken turns between doing quantitative research and risk management. So most recently I was at Hudson River Trading until the beginning of November.

Joe (04:55):
I think when people think about like multi-strategy hedge fund or pod shops or whatever, maybe Millennium is the first one that would come to mind for people. If someone asks you ‘How does Millennium make money?’ — and they seem to have made a lot of money over the years — what's the answer?

Gappy (05:12):
Okay. I hope without, you know, saying anything that is proprietary...

Joe (05:18):
Sure, like the business model of Millennium?

Gappy (05:19):
Yeah. I think that what Millennium has excelled at has been the ability to scale up. So to adapt its existing platform to accommodate new strategies and new portfolio managers. And so sometimes actually in some of their marketing material, they called it something like an ‘investment operating system.’

So it's a system that, as a firm, that is willing to absorb some relatively new strategy and create an environment for that strategy to succeed. And so because of that, I think they might be having, right now the highest number of individual pods. Maybe close to 300. And hovering around $60 billion of AUM, of assets under management. But I would say what is their superpower is really their ability to scale in number of pods.

Tracy (06:16):
So you mentioned creating an environment for success there. What does that look like at an organization like that? What are the conduits that allow trades in that particular organization to be successful?

Gappy (06:32):
So I would give a sort of a idiosyncratic, maybe a story around the rationale for success of platforms. So I see platforms a little bit like managing an arbitrage or some kind of gap between the single platform, the single manager or the small hedge funds, and the fund of funds. So if you are a fund of funds, you do have the scale, but you do not have the ability to observe from a close distance the performance of your vehicles for investment.

And let's say that they don't perform well, you have to wait a year in order to take your money back. In the case of a hedge fund platform, you could actually, not only observe the performance of PMs, portfolio managers, their skill, from a very close distance, but you can also help them perform better. So you can centralize some of the functions that make them better. You know, capital access, corporate access, risk management. If they perform well, to give them more capital. If they don't perform well, to take capital away from them or let them go.

And at the same time, you also solve for two other problems. So one is, there is a risk transfer happening, because a platform almost by design, otherwise it's not really a platform, has a passthrough fee structure that's fundamental for the existence of a platform. That makes really a platform what it is, instead of a just multi-manager hedge fund, like a D.E. Shaw.

So this means that a portfolio manager is not paid with the incentive fee that the hedge fund as a whole receives from the limited partners, but instead the portfolio managers are paid a percentage of their P&L. This payment is passed through directly to the limited partners, to the investors. And this basically transfers the risk directly, basically from the PM into the limited partner. And so this makes the system more robust in a sense, right? And combine this with the diversification across investment styles and the number of PMs, and now you start having a moat around a platform that makes it successful.

Joe (09:04):
If an entity has 300 pods and everyone's doing their own thing, etc., why doesn't the return just become the market return? It seems like one intuition could be that this model wouldn't scale – I mean I know it does – but one intuition could be that this model wouldn't scale, that the more you add, you over-diversify and then you just end up with, you know, ‘Buy the VTI ETF’ or something like that. Why doesn't it work out that way?

Gappy (09:32):
A simplistic explanation for this is actually just to look at what a retail investor would hold in their portfolio. So let's say that they are, you know, long Apple and IBM. Okay, they have a little bit of an imperfect version of the market, right? But what makes their skill is how different are the weights of their Apple and IBM holdings compared to the market, okay?

So you can decompose your performance in your personal account into the sum of, let's say, the market and your idiosyncratic bets into these stocks. Now what the hedge funds do is, they do the same, but they completely eliminate, as much as they can, their exposure or their investment in the market. So they run purely market neutral and factor neutral portfolios.

So there is diversification, but these idiosyncratic bets don't get diversified away into a big market, but they actually become essentially a bunch of independent bets that by the law of large numbers, they tend to have better and better risk adjusted profiles.

Tracy (10:39):
So I still see some platform heads describe the overall tilt as market neutral, but what do they mean by that exactly?

Gappy (10:49):
I mean, they typically run a wide range of strategies. So let's focus, because it's more relatable, let's focus on discretionary long-short equities and systematic equities, because everybody knows what the stuff is.

Tracy (11:00):
Great. I love that you think systematic equities is relatable.

Gappy (11:03):
Yeah. I mean relative to, I don’t know, Treasury basis or selling vol. So they mean that typically they do have a so-called factor model. And a factor model is a little bit like having a market model on steroids. So you have a market term, so you can see your portfolio as having exposure to the market. So behaving a little bit like a market. And then it's also behaving a little bit like a portfolio that has momentum. And then it also has maybe a tilt in terms of value. The platforms tend to run portfolios that have no market exposure whatsoever, and then they also tend to have controlled exposure in these more exotic factors.

Joe (11:47):
How do they know that? I mean, so someone up there at the center, there's all the 300 pods, the data gets probably aggregated and sliced in various ways, but what is the job or how do they actually ensure that on net their portfolio managers don't have that market beta exposure?

Gappy (12:05):
Yeah, they typically have, at the very minimum, they will buy some commercial factor model, which is a model of the market, like of your investment universe: how a stock behaves, how can you decompose the performance of the stock in these various systematic, or let's call them, pervasive market-wide factors, and instead idiosyncratic.

So you buy them off the shelves. I mean they're really expensive and they do a job. And so once you have bought them, you create some kind of user-friendly interface so that a portfolio manager can always see how the portfolio looks like at any point in time. It's a little bit like having an X-ray of, you know, your body in real time.

You know, you can see ‘Oh, well my portfolio is a little bit short the market, a little bit long momentum, maybe there is some crowding, exposure.’ Whatever. And so this is in the hands of the portfolio manager. And then there is another layer on top of that, which is very important: risk management, which ensures that PMs are behaving well, that they're not going out of scope. You know, they're not buying micro stocks or, you know, investing in crazy stuff.

Joe (13:17):
Or just going long Nvidia.

Gappy (13:19):
Or long Nvidia. Yeah. If their idea is going long Nvidia, probably that's not an ideal portfolio manager.

Tracy (13:27):
So the other thing I've been wondering is how much visibility is there between the different pods within one shop? And I mean that, I assume, there's a centralized risk management system of some sort that is like netting out positions and trying to make the use of capital most efficient. And that's where a lot of the edge comes from. But also if you are just a trader pursuing your own strategy, do you know what the guy next to you is doing? Do you have that kind of visibility? Or is the idea to keep everyone sort of intellectually separated so that they're not influenced by each other?

Gappy (14:06):
Right. That's a good question. So there is no really black and white answer to this because, historically, there was a time when platforms had more visibility and more collaboration among pods, or at least pods in the same sector, for example. But I would say that the historical trend has been more and more to give them the tools to succeed, but not give them the ability to see into each other's portfolios, for example.

And the rationale for this is you probably prefer having independent bets to having correlated bets that could be, maybe a little bit more informed. So that's the trade off. If we talk, maybe we can come up with slightly better ideas. But yeah, I think that the trend is more and more toward, ‘No, you are not seeing what I'm having, what I'm holding.’

Joe (14:56):
Talk to us more about the risk management component. And again, I don't know very much, I understand that, you know, stop-losses are very tight and you don't get a long leash to lose money. And if you're not doing well, your capital's reduced. If you're doing well, I guess you get more, and if you do [well], you get more, etc. But how would you describe, the sort of, the essence of risk management at the hedge fund level?

Gappy (15:20):
So there are maybe two or three core functions that can be described in a qualitative way, but you know, I think pretty comprehensively. And then there is something that is a little bit more esoteric or domain-specific.

So let's talk about the general principles. So you mentioned stop-losses. So this is very important. You know, there are always stop-losses. The ones that you know you have and the ones you don't know you have, but everybody has stop-losses in life. So those are very important, because you could imagine that a PM is a little bit like somebody who's holding a call option, and you know, the PM who's losing money has kind of an incentive to go for broke, maybe sometimes. But a stop-loss is effectively a sort of a primitive tail insurance, tail risk management tool, on the left tail of a PM. So that's very important.

The second principle is, it’s sort of self enforcing, true diversification. So this is where you want to have some kind of risk model that tells you what are the hidden bets that kind of overlap and maybe compound at the aggregate level, so that if everybody takes a little bit of factor exposure in the same direction, and then you sum this across 300 PMs, it becomes a big factor exposure. So a PA risk management organization needs to get that right. The third thing is making sure that people stay in scope. Okay, so it seems trivial, but actually that requires a lot of domain expertise. So understanding the trades, what can go wrong from an operational standpoint, microstructure standpoint…

Tracy (16:56):
Is this factor drift risk as well?

Gappy (17:00):
I would say that scope is more like factor drift. Or in general, strategy drift, not only factor. But whereas being in scope is more of a pure strategy drift or just taking risks that a portfolio manager would be possibly aware of, but that may be the head of the hedge fund, because it's not an expert in that area, is not so aware of. So the risk manager has to know very well what's going on, and alert, talk to the PM, talk to the business head.

Tracy (17:33):
Can you give us concrete examples, from your experience, of the kind of things that would set off alarm bells? So is there, I guess you don't have to give us specific examples, but you know, the kind of thing that…

Joe (17:48):
The types of examples.

Tracy (17:48):
Yeah. The types of examples that would catch your eye in a risk management position?

Gappy (17:54):
So we covered a little bit. The easy stuff, right? So the easy stuff is people taking too much risk, first of all. It's simple, but you know, we think in terms of dollar volatility. Dollar volatility is a little bit like how much you can make or lose in one year, for example.

Tracy (18:09):
So like value at risk, those kind of calculations?

Gappy (18:11):
Kind of value at risk. Yes. I mean, most people think in terms of value at risk too, but okay. Yeah. I mean, choose your risk metric. You want to stay within that. Then factor exposures, okay? That's also easy. Concentration. So if you take a mega bet in Nvidia, it has to surface. So these are relatively simple.

There are things that are a little bit more complicated. Like, for example, you take some true arbitrage positions where you think that something is running cheap versus rich, in say, bond versus futures. Or you do some kind of funding arbitrage trade where different agents in the investing world have different funding rates for their assets. And those can break. Like, in a dislocation, they can break. And so the way that typically you manage these things, it's a little bit like in merger arb. You give it a max size and you want to make sure that this is correct, that this size is correct and it's monitored. So this is stuff that can go wrong.

Joe (19:11):
Do managers, how much do they, I mean, I'm sure there's sort of, I don't know if it's accidental drift or, you know, drift is sort of a neutral term. How much does the risk manager have to watch out for, I guess, intentional drift? Or ‘This isn't working, I know this is not quite my mandate, this is not quite what I was meant to trade, but I could sort of justify it this way, or I just see all these lines up over here going up, I need to…’ How much of a risk management concern is that?

Gappy (19:39):
I think that in general the principle should be trust, but verify. I would say that the vast majority of portfolio managers are very responsible and because they're in that role, they have been educated to control their risks, to understand them. With occasional, uhhhh, screw ups. And so that's why you need to, to verify.

Tracy (20:01):
Okay. On the opposite side of screw ups, I'm curious how capital gets kind of doled out. And if I am running a massively profitable, successful trading strategy, do I automatically start being given more money to play around with? Or is there some amount of discipline here where you don't want people to be bumping up against, you know, sizing positions or additional trading costs and things like that? Imagine I am the most popular trader...

Joe (20:37):
Successful.

Tracy (20:37):
The most successful trader...

Joe (20:38):
I don't think popularity should matter.

Tracy (20:38):
Also popular!

Joe (20:39):
But successful.

Tracy (20:40):
I'm both the most popular trader and most successful trader at Citadel.

Joe (20:44):
What is the process for Tracy getting more money to trade?

Tracy (20:47):
How do I get more popular and successful? Probably, not [more] popular.

Gappy (20:50):
Okay. Assume that you're popular and successful. So do you get more capital? You do get more capital up to a point. So there are a couple of factors. The first one is, there is like a natural limit where somebody can be too successful and without giving examples, but there are large hedge funds whose daily P&L sometimes, at points, is driven by a single strategy, okay?

And maybe that's justified, right? But there is a point where the risk could be just too much because the concentration across strategies are — think of pods as stocks, right? You don't want to have 90% of your savings in Nvidia. So, okay, so that's number one. So there is some kind of basic heuristics.

Then there is just a natural limit to growth for strategies. Like, there is a trade off, because your market impact is very high. Or there is just a hard size for your strategy. So you cannot scale high frequency, you cannot scale to infinity, even, index rebalancing. Or if you are a consumer PM, your costs increase faster than the size of your portfolio. So your P&L in the absence of costs, grows more or less linearly, but your costs grow faster than linearly. So there is a point where you just don't want to grow.

Joe (22:13):
Alright. On the flip side, let's say Tracy comes in and she is a PM and she has her pod – how long is she likely to last?

Tracy (20:14):
How dare you, Joe!

Joe (20:15):
And what would cause her, what would be the threshold at which she gets fired?

Gappy (22:31):
I don't have the statistics on the average tenure of a PM. If I had them, probably, I shouldn't say. Well, and also it depends a lot on the place. Okay, so how long? I would say that it's like everything in life, right? So like 90% of everything is of poor quality. I'm sorry to say, but the same applies to PMs.

But this is another beautiful aspect of platforms, by the way. So let me take a quick detour about this. Because like a beautiful and underappreciated aspect of platforms is that they act like sieves. So you go through basically every possible PM on the market. And there is a turnover, let's say, of 20%. So 20% of PMs more or less are let go or leave every year, but you keep the good ones, right? And so eventually you have a sufficient number of PMs who really can carry, make the business sustainable. And a platform is an instrument for exploration. So I'm not saying how long they last or whatever, right?

But, okay, how good do you need to be? I think that if you have a market neutral Sharpe ratio, which for those who are not used to this basically is a risk-adjusted measure of profits. So you take your P&L and you divide by some measure of risk and you get the Sharpe ratio. If you don't have these kind of market exposures, you call it information ratio. If you have an information ratio of one, and you are managing your left tail sufficiently wisely, you can survive. So, you know, start practicing.

Tracy (24:12):
Okay. But on this note, the other thing I wanted to ask you was, you know, we tend to talk about these things – platforms, pod shops, multi-strat – as like this one big blob basically doing a similar thing. But my impression is that the culture varies quite substantially across firms. And again, there aren't that many that are doing this, although, as Joe said in the intro, the number is growing. But when we talk about that kind of cultural variation, what do we mean exactly?

Gappy (24:43):
To an amazing extent, I think that platforms are shaped by the personalities of their founders. So Izzy Englander has a personality and a personal history. Ken Griffin has a different one. The founders of Hudson River Trading – not a platform, you know, in a strict sense, but you know, to some extent multi-strategy. And so the cultures are very affected by this.

So if you are a trader like Ken Griffin, it's more likely that the fund that you work in, it's more of a trading, as opposed to maybe a pure technology culture. Millennium is very decentralized. Citadel tends to run more like a centralized and efficient organization. So in the words of a hedge fund manager, you know, Citadel is like Singapore and Millennium is like the United States, right? Singapore: very efficient, efficiently run. Technocratic to some extent. And the US, you know, it’s messy and inefficient, but it's very robust.

And in a sense, you know, Millennium has these features of robustness. It's like an organic creature. It does change a lot. So other, some firms are more collaborative. I think Balyasny, for example, tends to be more collaborative than these other two firms, by the way. And your mileage may vary between different teams. Like depending on where you work, you know, it can be heaven or it can be hell.

Joe (26:10):
Alright, someone hears this podcast, maybe they're in college studying finance, or maybe something in tech or something. Engineering or whatever. They're like ‘Oh, this sounds really cool, I want to work for one.’ What is sort of the basic path that one winds up, maybe first in a pod, and then running a pod?

Gappy (26:25):
Okay, so first of all, I would like to dissuade everybody who's listening from studying a career in finance. Okay?

Joe (26:32):
Everyone's going to take that as a challenge, but keep going,

Gappy (26:34):
Of course. And so I wrote a small document because I got a lot of questions like this from students. And the brutal answer is that it's very difficult and there is some luck involved. So it does help to go to schools with a brand name for sure. It definitely does help if you want to do quantitative stuff to be a very good programmer.

And, you know, you need to have the ability to think quantitatively. So that's for sure. There are coding tests that make the admission a little bit more democratic nowadays, but still it's very selective. I am not particularly qualified to give advice on how to get a foot in the industry. I think I have a better view of how to succeed and — how to be happy, not succeed — how to be happy in the industry.

Joe (27:22):
That's probably more important. Let's hear this.

Gappy (27:24):
Yeah. So I mean, how to be happy in the industry. I think that, I ask a lot the question of what makes a good analyst or a good quantitative researcher to people? And I get very often the same answer, which is, people who are curious do well and seem to be happy.

So, as usual, you need to have passion. You need to go, you know, to get into the weekend and not be able not to think about a problem. So I think obsession helps. So I think the world belongs to the obsessed, for good or worse, in the future. Like, you can see this, it's a heavy tailed world. So if you want to have a more stable job and less absorbing, I think being a dentist is a better career path. But having some level of obsession into this stuff is good. Otherwise, at some point, you know, you leave the industry. It's perfectly fine, by the way.

Tracy (28:23):
So this actually reminds me of something else I wanted to ask you. So you said the world belongs to the obsessed, which…

Joe (28:30):
Great line

Tracy (28:31):
… is a very good line. But when I read books on quantitative finance, so much of it seems to be about Greek letters for a start. But basically sizing and managing risk and how to look at your positions and all of that. How do you actually generate trade ideas? Like, where does the strategy come from? Am I just looking for, you know, mathematical dislocations in the market and arbitrage opportunities? Or am I thinking like ‘I want to go big on something like AI or clean energy,’ or whatever?

Gappy (29:05):
So I think that there are two dimensions to your question. So the first one is how objectively do you create alpha? Okay. And so there are only a certain finite number of ways to go about alpha, okay? So there are structural imbalances that are not adaptively filled, because the market is poorly designed, because we don't live in a neoclassical world. And so these imbalances persist.

And how do you exploit this physical alpha is two ways. The first one is you're a freaking genius and you face a wall for two years, do research, and you come up with an original idea. Okay. There are people like this. Very few. The other is simpler. It's like a Renaissance style. You are an apprentice in a famous painter's shop, and you learn the trade, and then you strike out on your own and you make it a little bit better.

And even making it a little bit better can make a huge difference. So I would say imitation plays a big role. And then maybe there is another characteristic, which is, you just have to have the right makeup in terms of, you know, drive tolerance, risk tolerance. So, you know, I was actually having lunch with a former Point72 PM. And his biggest drawdown was $90 million. Which is, by the way, not crazy high. If you are down half a billion dollars, you are literally losing your marbles, okay? You know, your face looks different.

Joe (30:39):
Have you seen that?

Gappy (30:40):
Oh, sure. Yeah, yeah.

Joe (30:42):
Yeah. I remember in Fooled by Randomness, [Nassim Nicholas] Taleb talks about watching all of the hormones of someone who just lost a lot of money, like pour out, and how pale they look. I remember he had a specific comment about that.

If there are only so many geniuses, if there isn't an infinite supply of alpha, if the structural forces, the physical forces as you described them, you know, there's only so many of these dislocations or reasons why reality is separate from the neoclassical world, does it imply that as we see more of these launches and as these hedge funds get bigger, that the opportunity diminishes?

Gappy (31:20):
Yes.

Joe (31:22):
Cool.

Tracy (31:23):
Wait, why?

Gappy (31:25):
Well, because everything has a finite capacity. That's it. I mean, you know, as you say, Joe, there are only that many opportunities. And each opportunity has a finite capacity. And so at some point everybody's doing the same thing and you get to some kind of equilibrium, which is not necessary that everybody makes the minimum rate of return, right? But, you know.

Tracy (32:02):
You mentioned earlier that systematic equities are more relatable than other things like the Treasury basis trade. And I kind of, [in] my personal experience, I would beg to differ, because I come from a sort of credit background, but it reminded me a lot of these firms are becoming bigger presences in the bond market. Bigger market-making roles and that sort of thing. Does the day-to-day of being in equities versus fixed income in this kind of world, is it very different? Or do similar principles apply?

Gappy (32:35):
I think it's very different, actually, you know. And why? First, in fundamental equities, your edge is mostly informational. So you do have a model of the world that differs from consensus and you monetize that. It's really informational.

In the case of a lot of fixed income, [it] is truly structural. You know, there are predictable flows, there are well-known imbalances, there are different demands for liquidity. So it's more of a strategy or a class of strategies that has skew. So you could lose a lot of money, but you collect pennies on a regular basis. So you need to manage risk for that. You need to have more capital for that and scenarios for that. So the risk management, the way you think about investment is different. It’s more scenario-based. It’s less diversified. Fundamentally, you have relatively correlated bets.

Joe (33:31):
Why isn't the world actually mapped to the neoclassical view of the world? Because there's so much money and there's so much investment and effort being put into spotting any price dislocation anywhere. And so why is it that with all the money and all of the professionals and the geniuses and the supercomputers and the AI that are like essentially attacking the question of finding mispriced securities? Why are there still mispriced securities?

Tracy (33:57):
In theory, everything should get arbed out.

Joe (33:59):
Yeah. And like instantly, right?

Gappy (34:01):
But not in practice.

Joe (34:02):
Well, yeah, but why not in practice? Why does it — even with all the professionals and money trying to do this — [does] there still persist these anomalies or dislocations, whatever you want to call them?

Gappy (34:13):
I don't, I am not really qualified to answer, but I just see there is only a finite number of professionals. You know, and there is only a finite number of professionals with a certain risk tolerance. And there are constraints all around. There are constraints on your balance sheet. There are constraints on how much money can you lose.

So there are all sorts of limits to arbitrage that go beyond the toy model of, you know, [Andrei] Shleifer and [Robert] Vishny. So that's kind of a funding arbitrage. And the mechanism, by the way, it's wrong for that paper. I mean, it's not realistic, not wrong. It's like, artificial. But wherever there is a constraint, independently of how many players you have, you have a potential inefficiency. Period. And it's not going to go away.

Tracy (35:01):
I have a practical question, and I always wanted to ask this of someone, and I think you are the perfect person to perhaps answer this, but if you are a risk manager at this kind of firm. And, I don't know, you come into the office and, let's say, it's like the day of a Fed meeting and Jerome Powell comes out and says something completely unexpected. Or, let's say it's 2015, and China suddenly announces they're devaluing the yuan.

And you're looking at your computer screen and you're looking at the various risk metrics, how fast do those move? And how much of it is calculated in real time versus all the numbers having to be run at like the end of the day when you net out trading positions?

Gappy (35:49):
If you have the right model, you should be able to either capture those risks directly, in a sense. Imagine you have a sensitivity to the various points in the yield curve, either you know, in your fixed income portfolio or in your equities portfolio. If you capture those well, so it's a risk that you know you are taking and you can hedge, you should see the factor moving, but not your portfolio moving.

And by the way, you can also not have these factors, but you may have factors that are proxying this, these macroeconomic drivers. Like, say for example, momentum is one, crowding is another. And so even if a portfolio manager doesn't think directly in terms of points on the yield curve, but they have other related ways of thinking, so they can still control for that.

And then there is unfortunately the case where ‘Oh, well, we never modeled this. We do not have a proxy for this.’ And then you're screwed. And yeah, you don't want to be in that situation. Typically, you know, you can see these effects. Like, I mean, there was a big surprise when rates went up. A lot of equity portfolios moved and they really didn't know why and there was no interest rate sensitivity in commercial factor models. So there you go.

Joe (37:04):
In theory, on a day of some sort of unexpected event – Tracy mentioned the China yuan devaluation – if everything is working perfectly and you truly have completely eliminated your market exposure, does that show up at that level? Like, does it still show up somehow?

Gappy (37:24):
It still can show up in weird ways, right? So, for example, you can be market neutral. The market has a big drawdown and you still lose money. Why? Because the market, the drawdown starts weird processes of derisking that affect your portfolio. So even if I'm market neutral, somebody is selling my stock to reduce their risk and it's affecting me even though I'm perfectly market neutral. So weird things can happen unfortunately, you know? So there is no perfect model. That's the short answer unfortunately.

Tracy (37:58):
You mentioned crowding in multi-strat and the idea that maybe, you know, eventually you would reach a limit for the efficacy of some of this type of trading. What's next for hedge funds? So we went from fund-of-funds to pod shops. They became the hot new thing. What comes after pod shops?

Joe (38:17):
What's exciting?

Gappy (38:18):
I'd love to know. It's for the next guest to answer. I don't know.

Tracy (38:23):
This is where you reveal where your current gardening leave ends and where you're going to wind up next.

Gappy (38:29):
Oh yeah. My best job is always the next. I don't know, but, so what's next? In terms of business model, it would be very interesting to know what's next. So there are some interesting ideas. So there is the idea of alpha capture, which is kind of a big umbrella.

And you know, alpha capture has an interesting story. So there was external sell-side alpha capture that's historically kind of a creation of Marshall Wace, an English hedge fund that in 2003 or ‘04, studied a program called Tops where they gathered ideas from the sell side. And that for a while was very profitable and also has lots of other byproducts that are great. Now I think it's kind of arbitraged out.

Now there is a similar concept of buyside external alpha capture. So there are firms that are trying to get ideas from hedge funds, small hedge funds that don't have scale. They can aggregate them and then they make into a portfolio that's a new business model. I don't know how scalable it is, how sustainable it is, but that's an idea

There is definitely an expansion into privates. I have like zero skill or zero visibility into this stuff. So that's really another question for somebody else. And then there is always product innovation. Every strategy is continuously innovating, has to change. So just look at where fundamental equities was a hundred years ago. Right? The recommendation was ‘Invest in a railway, single stock, and, you know, be happy.’ And now we have, now we spend hundreds of millions of dollars on alternative data and there are tools and stuff. So what is it in 10 years? I don’t know. But it'll be very different than it is today.

Joe (40:13):
I remember, you know, when I was — over 20 years ago when I first got interested in markets — picking up The Intelligent Investor. Because of course, you know, [Warren] Buffet and [Charlie] Munger were into it. And reading it is like, ‘So if you buy the Brooklyn rail bond yielding 8%,’ I was like ‘What is this?’ Just, yeah, I just thought, it seems so disconnected. I mean, I'm sure there's a lot of deep wisdom and I probably should have internalized it. But just in terms of what they were talking about, it seemed so funny, because of how antique it all seems.

Gappy (40:40):
Totally, yeah. And so now fundamental PMs tend to be quantitatively quite literate. In the future, they will be even different. Maybe they will be prompt experts. I don't know.

Joe (40:52):
Can you be a fundamental PM by just being a domain expert in a certain area? Say like, you really understand biotech or say you really understand the semiconductor industry and you want to trade chip stocks versus, and not really have that sort of quant background, but some other expertise.

Gappy (41:09):
So being a domain expert is definitely a necessary condition. You absolutely need to be a domain expert. And since you make the example of healthcare – super domain expert. So a lot of good healthcare PMs have worked in healthcare companies. They have never practiced, but they are a domain expert. Is it sufficient to be just a domain expert? No, I think that you need to be able also to monetize and to risk manage your portfolio. And that's very difficult. So that's not sufficient, but it's definitely necessary.

Tracy (41:40):
How important are the data sets? Like, what if I'm just really good at finding original and alternative data sets?

Joe (41:46):
You can be someone's analyst.

Gappy (41:49):
It varies a lot. So some PMs, well, okay, first of all, for systematic it matters a lot, period. Unconditionally. For discretionary PMs, it varies a lot. So some PMs will use alternative data, some will do deep research and think three months to a year ahead. And the reality is that there are not that many data that really help you think at that horizon. So we don't live in the world of really, really big data for fundamental thinking. So I think that's interesting.

Tracy (42:22):
I have just one more question, which is, what do you find most satisfying about your job? What gives you the most…

Joe (42:31):
Your jobs.

Tracy (42:32):
Yeah, or jobs.

Gappy (42:33):
My jobs?

Tracy (42:34):
Yeah. What gives you the most pleasure on a day-to-day basis? Do you feel fantastic if China devalues the yuan and you look at, you know, positioning across the firm and you're not going under? Or do you feel great if you identify a particular strategy or something like that?

Gappy (42:49):
No, the thing that gives me most pleasure when I work is when I do something that is useful and it works for others. So I just love the social aspect of working. Like, it's actually a job where you can be of some use to other people and I just enjoy that. So when things work out, like you come up with an idea after multiple failures, and it works, you implement it and somebody else uses it or finds a value to this and everybody's happier and like, and we get drunk together. That's great.

Tracy (43:23):
All right. Giuseppe Paleologo. AKA Gappy. Thank you so much for coming on Odd Lots. Really appreciate it.

Gappy (43:29):
Thank you.

Joe (43:30):
Thank you. That was fantastic.

Tracy (43:47):
Joe, I feel like that's good life advice. If it all ends in people getting drunk, it's usually… No, wait, that doesn't make sense. Sometimes it's really bad.

Joe (43:54):
Yeah, don’t say that.

Tracy (43:54):
Okay. Nevermind. But sometimes it's great.

Joe (43:57):
Sometimes it's good. I love that line, I feel like “the world belongs to the obsessed” is just like a really good line. That's sort of ominous to me, because I don't really get obsessed with anything besides country music. And then the rest of my time I'm just like ‘Oh, I want to talk about hedge funds one day and then the next day I want to talk about how energy works.’

Tracy (44:15):
Yeah, I was going o say you do get obsessed. It's just you flit from obsession to obsession.

Joe (44:20):
Yeah, so it's not real obsession. It's kind of dilettantish. Wait, Tracy? Have I told you about when I got a job offer at a prop trading shop?

Tracy (44:30):
This vaguely rings a bell.

Joe (44:32):
So can I tell a quick story?

Tracy (44:33):
Go for it.

Joe (44:34):
So I had traded stocks in college, just because it was like the dotcom era. It was fun, it was very easy. Everything was going up. I managed to sell for accidental reasons at a good time. And I didn't lose all my money. Anyway, I got interested in markets. Then I graduated with my useless liberal arts degree and I had a job — I was making minimum wage working at a deli.

And I saw this ‘Help Wanted’ ad at a prop trading shop in Austin, Texas. And it didn't seem like they had many requirements. So I went. They asked me about my personal trading. I played ping pong against the CEO. I played this video game that involved me using two joysticks. One was to control the tilt of a triangle and the other one was to control the space. And I kept it in the square all right.

Tracy (45:17):
This seems weird.

Joe (45:18):
And I did this other thing where I like typed without too many typos and stuff like that. And there were like 200 people [who] applied. And the second round, I got one of the four spots that they offered. And for reasons that still elude me to this day, I didn't take the job. I was enjoying making minimum wage at the deli. All my friends worked there. It was like the cool place to work in Austin. I didn't feel like giving that up. And I didn't. And I just like, I always think about ‘What if?’ What does my life look like if I took that job? The strangest, most inexplicable career decision I could ever imagine [is] not taking a trading job from a $5 minimum wage job or whatever it is at the time. Anyway, I'll never know.

Tracy (46:00):
Okay. Well, I once got offered a specialty sales position in bank equities at a Swiss bank and I never questioned what my future would've been had I taken that job. I'm very satisfied. But I actually have a question, do you think you were put off by the weirdness of the interview process? Like, did you think that you were going to be playing ping pong and moving joysticks as part of the job?

Joe (46:23):
That was fun. And I didn't even beat the CEO at ping pong. She beat me, but she still hired me. I don't, no, I don't know why. The only thing that could explain [it] is that in my post-college life, I had a cool job where I got to hang out with my friends in the back of this deli in a grocery store, I didn't really feel like giving it up just yet.

Tracy (46:42):
All right. Well, I do feel like coming out of that conversation with Giuseppe, I feel like I have a much better conception of how multi-strat actually works and what people are sort of doing on a day-to-day basis. And also just maybe a better understanding of some of the terminology around the industry.

Joe (46:59):
Totally. So now we'll probably do more episodes, but I feel like I'm now roughly grounded in at least some core ideas here.

Tracy (47:06):
Yeah. And everyone should definitely check out Gappy's buy-side quant job advice. It's nine pages and it actually, it goes into some detail on the structure of the industry itself of how, you know, quantitative hedge funds actually work and who are the big names and things like that. So anyone who’s interested in the space, definitely check it out. Shall we leave it there?

Joe (47:27):
Let's leave it there.


You can follow Giuseppe Paleologo at

@__paleologo

.