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Podcasts, Radio, News.
Hello and welcome to another episode of the Odd Lots Podcast.
I'm Tracy Alloway.
And I'm Joe Weisenthal.
Joe, I know we did one episode on pod shops.
Yeah.
On multi-strategy hedge funds.
But it was primarily focused on their impact on the market.
Yeah.
And I have to say I still came away from that conversation,
sort of wondering if I worked at a pod shop.
Yeah.
What is it exactly that I would be doing all day?
I would love to know the exact same thing.
I mean, I guess I have this very vague sense of sort of
they have a bunch of people all focused on their specific areas
and the sort of average out.
And they net out a bunch of stuff.
And it's capital efficient.
And it's market neutral and theory and etc.
But beyond that, 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.
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.
Yeah.
But my question is like, why?
Is it just that they're minting money,
they're expected to continue minting money in the future?
Or is there something that's like fundamentally
intriguing and attractive about working in that space
that means lots of people want to get in?
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 like backing up the question is like,
what we know is that many funds,
including apparently even like B tier,
C tier funds have done like very well.
So I'm just like curious like how and why.
And then yeah, to the question of like,
what does it take to succeed in them?
Or who is the type of person who can succeed in this environment?
All right, well, I'm glad you put it that way.
Because today we're 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 Palia Logo,
aka Gappy.
He describes himself as a constant gardener,
someone who's on gardening leave quite a lot.
He's also the author of Advanced Portfolio Management,
a quants 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 a manual German, but it's definitely up there.
And Joe, I know you enjoyed it too.
I did, you know, I like skipped over all the numbers
and equations and you just looked at the jokes.
And Greek letters, but it's very easily 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.
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.
Oh, wow.
You know, some people do get the alpha symbol,
but he has both.
So, you know, a well-balanced portfolio of tattoos
all around the Union Yang.
Yeah, so Gappy, thank you so much for coming on all thoughts.
Hi, Trissy.
Hi, Joe.
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?
Yeah, I'm not sure.
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,
the only industry 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.
I think when people think about like multi-strategy hedge fund
or pot shop or whatever, maybe sort of 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?
Okay, I hope without, you know, saying anything
that is proprietary.
But I think that. Like the business model of Millennium.
Yeah, I think that what Millennium has excelled
that has been the ability to scale up.
So to adapt its existing platform
to accommodate new new strategies
and new portfolio managers.
And so sometimes actually in some of their marketing material
they call it something like an investment operating system.
So it's a system that is 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 dollars of AUM
of assets under management.
But I would say what is their superpower
is really their ability to scale in number of pods?
So you mentioned creating an environment for success there.
What does that look like at an organization like that?
What are the sort of like conduits that allow trades
in that particular organization to be successful?
So I would give a sort of idiosyncratic maybe a story round.
Please.
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
or volume 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.
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 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 pass through 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-Show.
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 PNL.
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 mode around a platform
that makes it successful.
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If a 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, because there's a right, 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 whatever, by the
VTI ETF or something like that.
Why doesn't it work out that way?
A simplest explanation for this is actually just to look at what a retail investor would
hold in their portfolio.
Let's say that they are long, Apple, and IBM.
They have a little bit of an imperfect version of the market, but what makes their skill
is how different are the weights of their Apple and IBM holdings compared to the market.
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.
They run purely market neutral and factor neutral portfolios.
There is diversification, but this 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.
I still see some platform heads describe the overall tilt as market neutral.
What do they mean by that, exactly?
The typically run wide range of strategies.
Let's focus on discretion or long short equities and systematic equities, because everybody
knows what the stock is.
I love that you think systematic equities is related.
Relatively to treasury bases or selling vaults.
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.
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.
How do they know that?
Someone up there at the center, there's all that 300 pods, the data gets 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?
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 this various
systematic, or let's call them pervasive, market-wide factors, and instead it is in
critics.
You buy them off the shelves, they're really expensive, and they do a job, and so once
you've 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 your body in real time.
You can see, oh, well, my portfolio is a little bit short, the market is 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, they're not buying microstocks or investing in crazy stuff.
Or just going along in video.
Or along in video?
Yeah, if their idea is going along in video, probably that's not an ideal portfolio manager.
The other thing I've been wondering is how much visibility are 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 use of capital,
most efficient, and that's where a lot of the edge comes from.
But also, if you're 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?
All 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.
The rationale for this is you probably prefer having independent bets to having maybe
correlated bets that could be like 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 am having, what I'm holding.
Talk to us more about the risk management component, and again, I don't know very much.
I understand that 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 is reduced, if you're doing well, I guess
you get more, and if you do more, you get more and so on, but from how would you describe
the essence of risk management at the hedge fund level?
So there are maybe two or three core functions that can be described in a qualitative way,
but I think pretty comprehensively, and then there is something that is a little bit more
esoteric or like domain-specific, so let's talk about the general principles, okay?
So you mentioned stop losses, so this is very important, 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, okay?
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 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 sort of self-enforcing is 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 risk management organization needs to
get that right, the third thing is making sure that people stay in scope, okay?
So seems trivial, but actually that requires a lot of domain expertise, so understanding
the trades, what can go wrong from an operational standpoint, to microstructure standpoint?
Is this factor drift risk as well, or is that correct?
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 maybe the head of the hedge
fund, because it's not an expert in that area, it's 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, and. Can you give us concrete examples from your experience of the kind of things that would
set off alarm bells?
So is there like, I guess you don't have to give us specific examples, but you know,
the kind of thing that. The types of examples.
Yeah, the types of examples that would catch your eye in a risk management position.
So we covered a little bit the easy stuff, right?
So these stuff is people taking care of.
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.
So like value at risk, those kind of values?
Kind of value at risk, yes. I mean, most people think in terms of all 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, okay, 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 the things, it's a little bit like in merger R,
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.
Two managers, like how much do they, I mean, I'm sure they're sort of, I don't know if it's
accidental style 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 is a working, I know this is not
quite my mandate, this is not quite what I was made 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? Okay, 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've been educated to control their risks, to understand them,
with occasional screw ups, and so that's why you need to verify. Got it.
Okay, on the opposite side of screw ups, I'm curious how capital gets kind of doled out,
and if I'm running a massively profitable successful trading strategy, do I automatically
start being given more money to, you know, 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,
the most successful trader. Also popular. I'm both the most popular trader and most successful
trader at Citadel. What is the process for Tracey getting more money to trade? How do I get more
popular and successful? Probably not popular. Okay, assume that you're popular and successful.
Okay, 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
are driven, is driven by a single strategy. Okay, and maybe that's justified, right? But there is
a point where there is 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,
and so there is just a hard size for your strategy. So you cannot scale high frequency,
you cannot scale to infinity, even in industry balancing, or if you're a consumer PM,
your costs increase faster than the size of your portfolio. So your P&L in the absence of costs
goes more or less linearly, but your costs grow faster than linearly, so there is a point where
you just don't want to grow. All right, 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? And what would cause her,
what would be the threshold at which she gets fired? I don't have the statistics on the average
tenure of a PM. Okay, if I had them probably, I shouldn't say, well, and also depend 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. Okay, 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 every 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 and a platform is an instrument for exploration. Okay, so I'm not saying how long
they last or whatever, right? But okay, how good need do you need to be? I think that if you have a
market neutral sharp ratio, which for those who are not used to this number, this basically is a
risk adjusted measure of profits. So it's you take your PNL and you divide by some measure of
risk and you get the sharp ratio. If you don't have this kind of market exposures, you call it
information ratio. If you have an information ratio of one and you're managing your left tail
sufficiently wisely, you you can survive. Okay, so you know, start practicing. Okay. 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?
To an amazing extent, I think that platforms are shaped by the personalities of their founders.
So is the englander as a personality and a personal history can griffen as a different one
the founders of Hudson River Trading, not a platform, you know, strict to sense, but you know,
to some extent multi-strategy. And so 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 as 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 H1 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 U.S.
is you know, it's messy and inefficient, but it's very robust. And in a sense, you know, Millennium
has these features of robustness of it's like an organic creature. It does change a lot. So other,
some firms are more collaborative. I think Balinese, for example, tends to be more collaborative
than these other two firms. But by the way, and your mileage made vary between different teams,
like depending on where you work, you can, you know, it can be heaven or it can be hell.
All right. 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? Okay. So first of all, I would like to dissuade everybody who's
listening from starting a career in finance. Okay. Okay. So everyone's going to take that as a
challenge, but keep going. Of course. And so I wrote a small document because I got a lot of
questions like this from from students. And the brutal answer is that is 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 that's for sure.
There are coding tests that make the admission a little bit more democratic nowadays,
but still still it's very selective. I am not particularly qualified to give advice on how to
get food in the industry. I think I have a better view of how to succeed in how to be happy,
not succeed, how to be happy in the industry. So let's find more important. Let's hear this.
Yeah. 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 being able not to think
about a problem. So I think obsession helps. Okay, so
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 obsessions into this stuff is good, otherwise, at some point,
you leave the industry perfectly fine, by the way.
So this actually reminds me of something else I wanted to ask you.
So you said the world belongs to the obsessed, which 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 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?
So I think that there are two dimensions to your question.
So the first one is, how objectively do you create alpha?
And so there are only a certain finite number of ways to go about alpha.
So there are structural, structural imbalances that are not adaptively filled because the
market is poorly designed because we don't live in a new classical world.
Okay.
So 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
it 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 drive, tolerance, risk tolerance.
So when you, I was actually having lunch with a former 0.72 PM now and his biggest drawdown
was 90 million dollars which is by the way not crazy, crazy high.
If you are down half a billion dollars you are literally losing your marbles, your face
looks different.
So.
Have you seen that?
Oh, sure.
Yeah.
I remember in a flood by randomness to live talks about watching all of like the hormones
of someone who just lost a lot of money like pour out and how pale they look.
Right.
He had a specific comment about that.
If there are least so many geniuses, if there isn't an infinite supply of alpha, if the
structural forces, the physical forces as you described them, there's only so many sort
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?
Yes.
Cool.
Yeah.
Yeah.
Wait.
Why?
Well, because everything has a finite capacity.
That's it.
I mean, and as you say Joe, right, there is, there are only that many opportunities.
And each opportunity has a finite capacity.
And so at some point, everybody is 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?
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This is Matt Rodgers from Lost Culture East, that's with Matt Rodgers and Bowen Yang.
This is Bowen Yang from Lost Culture East, that's Matt Rodgers and Bowen Yang.
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You've probably seen it in the grocery store before.
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Because this mayo is different.
With mayonnaise uses whole eggs, QB only uses egg yolks, which gives it this rich umami
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It's smoother, deeper, and almost buttery.
Once people try it, they start putting it on everything.
Egg sandwiches, fries, burgers, some fans even swear by dipping pizza crust in it.
And once you notice it, you start seeing it everywhere.
Chefs use it, restaurants use it, people who really care about flavor use it.
Never try it, grab the bottle with the red cap next time you're out of the store.
Put it on just about anything, then you'll understand.
QB, the original Japanese mayonnaise.
You mentioned earlier that systematic equities are more relatable than other things like
the treasury basis trade.
And I kind of, 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.
Because the day-to-day of being in equities versus fixed income in this kind of world,
is it very different or do you similar principles apply?
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.
And the case of a lot of fixed income 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.
This management, the way you think about investment is different, it's more scenario-based,
it's less diversified.
Fundamentally you have relatively correlated bets.
Why isn't the world actually mapped to the new classical 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.
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?
In theory, everything should get arbred out.
Yeah, but not in practice.
But that's why.
Why not in practice?
Why does it even with all the professionals and money trying to do this, did there still
persist in these anomalies or dislocations, what everyone would call them?
I'm not really qualified to answer, but I just see there is only a finite number of
professionals.
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 Schlafer and
Vishni, but that's kind of a funding arbitrage and the mechanism, by the way, it's wrong for
that paper.
And 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.
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 it's, 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 their devaluing the UN.
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 nut out trading positions?
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 in your fixed income portfolio or in your equities portfolio.
If you capture those well, so it's a risk that you know you're taking and you can hedge,
you should see the factor moving, but not your portfolio moving.
Okay.
And by the way, you can also not have these factors, but you may have factors that are
proxy.
seeing 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 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, when rates went up, a lot of equity portfolios moved. And they really
didn't know why. And there was no interest rates sensitivity in commercial factor models.
So there you go. In theory, on a day of some sort of unexpected event, Tracey mentioned,
the China UN devaluation, if everything is working perfectly and you truly do have like
completely eliminated your market exposure. Does that show up at that level? Like, does
it still show up somehow? It still can show up in weird ways, right? So, for example,
you can be market neutral. Yeah. The market has a big drawdown. And you still lose money.
Yeah. Why? Because the market, the drawdown starts weird processes of the risking that
affect your portfolio. So even if I'm market neutral, somebody is selling my stock to reduce
the 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. You mentioned crowding in multi strap and the idea that maybe, you know,
eventually you would reach a limit for the efficacy of some of this type of trading.
That's next for hedge funds. So we went from fund to funds to pod shops. They became the
hot new thing. What comes after pod shops? What's exciting? I'd love to know. It's for the
next guest to answer. I don't know. This is where you reveal where you're gardening,
your current gardening leave ends and where you're going to wind up next. Yeah. My best job
is always the next. I don't know. But so what's next? In terms of business model 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 alpha external cell side alpha capture. That's
historically like kind of a creation of martial ways. An English hedge fund that in 2003 or
2004 studied a programmable tops where they gathered ideas from the cell 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 arbitrage doubt. Now there is a similar concept of by side external
alpha capture. So there are firms that are trying to get ideas from hedge funds, small
hedge funds. They 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
scale or zero visibility into the stuff. So that's really another question for somebody else.
And then there is always product innovation. Every strategy is continuously innovating.
It has to has to change. So just look at where fundamental equities was a hundred years
ago, right? The recommendation was investing a railway single stock and you know, be happy.
And now we have, you know, and now we spend hundreds of millions of dollars in alternative
data and there are tools and stuff. So what is it in 10 years? I don't know. But it will
be very different than it is today. I remember, you know, when I was over 20 years ago and
I first got interested in markets picking up the intelligent investor because of course,
you know, Buffett and Munger into it. And like reading is like, so if you buy the Brooklyn
rail bond yielding 8% I was like, what is this? I just thought it seemed so disconnected
from it. I mean, I'm sure there's a lot of deep wisdom and I probably should have like
internalized it. But just in terms of like what they were talking about, it seemed so funny
because of how antique it all seems. Yeah, totally. Yeah. And so now PMs are, 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. 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. 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 either worked in healthcare companies. They have never practiced, but they are 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 manager portfolio. And that's very difficult. So that's not
sufficient, but it's definitely necessary. How important are the data sets? Like what
if I'm just really good at finding original and alternative data sets?
Someone's analyst. Yeah. 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. I have just one more question, which is, what
do you find most satisfying about your job? What gives you the most pleasure on a day-to-day
basis? Do you feel fantastic if China devalues the UN and you look at, you know, positioning
across the firm and you're not going under? Do you feel great if you identify a particular
strategy or something like that? Now, 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. 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, you come up with an idea after multiple failures
and it works, you implement it and somebody else uses it to find some volume to this and
everybody is happier and we get drunk together. That's great.
All right. Giuseppe Palia Logo, aka Gaffy. Thank you so much for coming on AllBots. Really
appreciate it. Thank you. Thank you. That was fantastic.
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. Yeah. Never mind.
But sometimes it's great. Sometimes it's good. I love that line. I feel like the world
belongs to the obsessed. It's 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, I want to talk about hedge funds one day and then
the next day I want to talk about like how energy works. Yeah, I was going to say it's
not really like us.
But obsessed. It's just you flip a session to it. Yeah. So it's not real obsessions kind
of delatante. Well, Tracy, have I told you about when I got a job offer at a prop trading
shop? This vaguely rings a bell. So can I tell a quick story? Go for it. So I had traded
stocks in college just because it was like the dog com era was fun. It was very easy.
Everything was going up. I managed to sell for XNL reasons a good time and I didn't lose
all my money.
It was always 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
one it had at a prop trading shop in Austin, Texas. And it didn't seem like they have 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.
It seems weird. And I did this other thing where I like typed without like too many typos
and stuff like that. And they're like 200 people applied. And I second round. I got
one of the four spots that they offered. And for reasons that still allude me to this
day, I didn't take the job. I was enjoying making minimum wage at the deli. All my friends
work there is 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 is my life look like if
I took that job, the strangest most inexplicable career decision I could ever imagine not take
a trading job from a five dollar minimum wage job or whatever it is at the time. Anyway,
I'll never know.
Okay. Well, I once got offered a specialty sales position in bank equities at a Swiss
bank. And I never question what my future would have 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 like moving joysticks as well?
part of the job?
- That was fun.
And I didn't even beat the CEO in PingPong.
She beat me, but she still hired me.
I don't, no, I don't know why.
The only thing I could explain 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.
- 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 Multistrat 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.
- 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.
- Yeah, and everyone should definitely check out
Gapby's byside quant job advice.
It's nine pages and it actually,
it goes into some detail on the structure of the industry
itself of how quantitative hedge funds actually work
and like who are the big names and things like that.
So anyone's interested in the space?
Definitely check it out.
Shall we leave it there?
- Let's leave it there.
- This has been another episode of the All Thoughts podcast.
I'm Tracy Alloway.
You can follow me at Tracy Alloway.
- And I'm Jill Wyzenthal.
You can follow me at the stoward.
Follow our guest Giuseppe Palliola Go aka Gapby.
He's double underscore Palliola Go on Twitter.
Follow our producers, Carmen Rodriguez,
Ed Kerman, Arman Dash,
she'll be in a Dashbot and kill Brooks at Kill Brooks.
Thank you to our producer Moses Andam.
For more AdLots content, go to Bloomberg.com/AdLots
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