
Getting a Job in a Top Tier Quant Hedge Fund - shogunmike
http://quantstart.com/articles/Getting-a-Job-in-a-Top-Tier-Quant-Hedge-Fund
======
lutusp
Quote: "However, a financial crisis in the Western hemisphere coupled with
other macro/socioeconomic factors has lead to a reduction in scientific and
engineering budgets and later-stage investment in such technologies."

Translation: The recent worldwide economic meltdown was caused in part by
quants' inability to accurately assess investment risks, or to influence
decision-making, or both. The fallout was public distrust (justifed or not) of
quants and what they do for a living.

The bottom line is that reliable quantitative analysis hinges on the degree to
which economics is a science. Economics isn't a science. Any questions?

~~~
vijucat
Blaming quants for the economic crisis is like blaming programmers for the
2001 tech bubble. In both cases, there's a decision maker to whom the
quant/programmer reports, an executive who decides which boat the company
wants to float. The engineer's role is just to inform his/her manager that,
"Uh, boss, this boat will probably sink. We shouldn't be claiming otherwise".
The manager's response in both cases was to say, "Shut up and do your job,
we'll go to IPO with just a business plan / we'll sell so many CDOs just the
commission is going to make us millionaires. Fuck consequences". If you want
to blame someone, I believe you need to look at the executives who took the
decisions. This meme of "the quants did it" is a bit ridiculous, and it
irritates me because it successfully removes attention from the real culprits.

Be honest : you have never worked on Wall Street. This is just some opinion
that you picked up from your favourite newspaper or conspiracy web site.

~~~
lutusp
> Blaming quants for the economic crisis is like blaming programmers for the
> 2001 tech bubble.

I should have blamed trust in quantitative analysis. That would have been more
fair, and it was the point I was trying to make. My shorthand way of saying it
may have given the impression that I was speaking of the analysts, not the
idea of analysis.

> Be honest : you have never worked on Wall Street.

Be honest -- where I have worked isn't the topic. And if I had worked on Wall
Street, that would represent a much better justification for doubting the
merit of my views.

------
lpage
"A great way to get into such a fund is to apply as a software developer, with
aspirations of becoming a portfolio manager"

That's not a path well traveled, especially at banks. At good hedge funds
roles are well delineated, and chances are that you'll be working hard enough
at your day job that you'll have little chance to explore on your own. Policy
may prevent you access to the interesting data sets (execution data and
historical P&L is sensitive to reverse engineering, and market data is often
subject to expensive licensing). For banks the issue is far more bureaucratic
- different teams with different hiring budgets and lines of business yada
yada. There are relatively few managers high enough to wall cross between back
office (technology) and front office (trading) so there's a stochastic
component to your success at moving internally based on what group you end up
in and how well connected your MD is. It doesn't help that coders are usually
the limiting reagent (and paid less than traders) so the firm's interests
aren't necessarily aligned with your own.

If you're passionate about trading and coding, HFT is a great way to go. Money
makers come from all backgrounds (grad/undergrad/super technical/creative
coder) and you'll likely have better control over your coding/research ratio.

~~~
shogunmike
I think I may have suffered somewhat from selection bias when writing that, in
that a lot of my friends/colleagues work at smaller shops, where they
initially started as technology infrastructure developers and worked very hard
to move over to the research side.

For instance, these were the guys -running- the data infrastructure so they
were looking at it all day, every day. After a while it was probably
straightforward to test out intuition on patterns they may have seen.

Thanks for pointing out that the difficulties in doing so at a larger firm.

------
spot
Two Sigma (where I work) is hiring for a variety of positions, not just
Math/Physics types but security, systems, UI, networking, etc. anyone with a
serious love of and talent for technology should consider it. i left google
for two sigma and am loving it, especially the people and culture. feel free
to ask me about it either in this forum or by email.

[http://www.twosigma.com/careers.html](http://www.twosigma.com/careers.html)

~~~
canttestthis
I understand if you can't answer this, but how does the pay for software
engineers at Two Sigma compare to pay at top tech companies, like Google?
Glassdoor is ambiguous.

~~~
spot
I got a raise, but salary is only part of compensation. In the end it will
depend on how the stock does (at a tech company) or what your bonus is (in
finance).

~~~
canttestthis
I've read elsewhere that unless you're in a role that directly generates
revenue (traders, etc.), you shouldn't rely on bonuses in finance, and should
instead maximize the cash portion of your compensation. I assume this would be
true for software engineers at Two Sigma too.

~~~
jchendy
Two Sigma, more than most other companies (financial or otherwise),
understands that innovation and success is largely driven by technology. The
content of twosigma.com is designed to communicate this, and it's absolutely
true. Anything you've heard about how other companies are structured is
unlikely to apply here.

------
anonu
The article makes a good point about MFE degrees. They're a dime a dozen these
days and most of them can't answer simple interview questions about linear
regression. Its pretty shameful, not so much on the student's part, but on the
universities that graduate these kids fully unprepared for the jobs that they
think they can get...

~~~
hudibras
The article really buried the lead on this one. The bottom line is that it's
flat-out crazy for anyone to get an MFE these days. They cost as much as an
MBA and won't get you a job as a quant.

~~~
shogunmike
Indeed, I am considering actually writing an entire article on that whole
topic.

I haven't done an MFE personally, so I don't feel I can comment too much on
what they're like, although I have a few friends who have. A lot of them
simply went into research afterwards.

------
dunster
Another solution is to write the algorithm but avoid the hedge fund - lots of
suits, and they take most of the money. You're better off if you trade it
yourself.

People work for hedge funds because hedge funds provide mentorship and really
powerful tools and lots of data to sift through. We're trying to provide all
of those things, for free, at Quantopian.
[https://www.quantopian.com/](https://www.quantopian.com/) Check out our
community (for mentorship), our backtester (very powerful, and open source),
and our 11-years of minute-bar data - all for free.

------
Tycho
Sometimes I think of the HFT and quant trading industries are like the Formula
1 of tech. A way for extremely talented people to apply their skills and
compete with each other, with lots of money involved, but ultimately the
technologies developed for the 'race track' make their way onto 'main street'
in some shape or form.

I'm sure all this research into ultra low latency infrastructure and live data
mining is bound to come in useful somewhere else. Maybe this is off base but
why be cynical.

------
tom_b
Quantitative trading seems interesting because I would hazard that you need
strong math background along with solid hacking skills.

There are other problem domains with similar requirements, but I'm quite
curious to hear stories from other HN'ers who have tackled quantitative
trading either for themselves and in the day job. Specifically, if you can
share a bit on your technical work in such a role, that would be cool to hear
about.

~~~
alexkus
> Quantitative trading seems interesting because I would hazard that you need
> strong math background along with solid hacking skills.

Strong maths knowledge can be good for general developer roles anyway. It's
one (small) reason why I did a maths degree part time (Open University in the
UK) to complement my existing Comp Sci degree.

I'm sure you could get a better bang per buck picking and choosing specific
areas rather than an entire degree but that wasn't my motivation (I'm equally
interested in both in general).

A good number theory course (even just plowing through Crandall and Pomerance,
or Apostol) will definitely help with understanding/analysing asymmetric
encryption.

~~~
shogunmike
I completely agree with this.

While you may not be solving partial differential equations in your average
tech startup, there are plenty of instances where a maths degree can be
directly applicable. Statistics is one instance, for A/B testing. Another
example is the use of vector calculus in machine learning and "data science".

How did you find the OU degree?

~~~
alexkus
> How did you find the OU degree?

It was good. I took it almost as slowly as you can (typically one module per
year) so it was 8 years from start to finish. In that time I got married,
moved house twice and became a father so I wanted to avoid it taking over my
life. Tutorials were local to home or work (I was lucky in that respect) but
they did seem infrequent.

Tricky to recommend now the fees have quadrupled though (I paid about £4k in
total for my degree, it'd be closer to £15k now); unless it's your first
degree and you're considering the OU over a traditional university; then £5k a
year is quite cheap as you can be much more flexible with life and (part/full-
time) work.

I was considering either continuing with the OU with Maths on some of the
Master's courses (those fees aren't subsidised in the same way that UG courses
are), or switching to languages (French, German, Spanish) but the prices put
me off those. For now I'll have a year or two off as a break.

~~~
bencollier49
I agree, the OU Maths degree is excellent, but it's been ruined by the new
pricing arrangements. None of the really interesting people I met on the
course would have been able to afford the new fees.

------
3327
Hi, I worked in both roles. I did an undergrad in theoretical Math and MFE.
Its particularly easy to get a risk management job. My first job was for 100k
+ bonus out of school for BNPP. It is a highly quantitative risk department
and was one of the best (if not THE best) institutional risk management gigs
on the street. I did not know this at them time but I started in 2007 and
after 2008-2009 I came to this conclusion.

Anyway back to main subject. Risk jobs are easy to land and you can learn TONS
or nothing interesting. Every shop has Risk integrated at different levels.
Some shops its a backoffice type job where the risk guys are in the back seat
(and this is the dominant case actually 8/10 I'd say). And rarely in places
like BNP will you sit on the trading floor and have more power than traders.
Yes traders will actually fear you... Rather than vice versa where Traders
that are making money are big swinging dicks doing whatever they want (this is
still the case at most shops).

I started quant trading by chance when some guys running an arb blackbox were
started constantly loosing money and were working late hours. I gave them a
hand fixed a few bugs and word quickly spread. Next opening they offered me a
position and I did an internal transfer...

After I went to managing a portfolio (2 years after). And successfully did
that for 4 more years.

The summary is this. Quant Trading roles actually come in tones of flavors.

Banks have option desks and in the recruiters will call these "quant trading
roles". Hell, for all they know there is complex math involved and 'quant'
sounds sophisticated. Truth is all option traders are proficient and calculus
and derivatives to the point good traders are able to calculate pretty
accurate 2nd orders in their head. And the tools available are also vast.

But this is not a 'quant trading role'.

A true 'quant' role is what some institutions have in house 'quant' teams that
manage all the pricing models and libs.

A 'true' quant trading role is stat-arb or some other arb strategy desk or
similar type of strategy. Most banks do not have them anymore so its
hedgefunds only. But even these vary vastly in quality. I know desks that
would make 2-3 million a day net with very shitty hardware and patchwork
system with lowlevel to mediocore guys working on it. And brilliant guys whom
struggled (talking tier 1 guys, PHd MIT, princeton).

So its a strange game and I would recommend going into a trading role into a
medium level shop. Whats important is a good team and having a good vibe with
the people you will work with.

Trading is high stress and high emotion business so for your sanity in the
long term its more important to work with good people rather than a top tier
shop in the beginning.

~~~
Sven7
I would rather work on porn or for the NSA, than on Wall Street.

~~~
conjecTech
Why is that?

~~~
gnarbarian
less drugs and STDs.

~~~
magicarp
Silicon Valley or Wall Street?

------
Sukotto

      Despite the intense competition, it is still possible to
      shine as a candidate, but you must be very well aware of
      what the funds are after, and then make sure you are
      providing it to them.
    

I think this is a truism for any role in any capacity in any organization.
Just replace "funds" with the organization/manager/client/whatever name.

------
bachback
RenTech assembled some of the brightest technical minds in the world to trade
purely quantitively. They did pretty well for themselves.

Jim Simons, famous mathematician, former MIT professor and DIA code cracker,
earned the following amounts according to Forbes: 2011: $2.1 Billion 2010:
$2.5 billion 2009: $2.8 billion 2008: $1.3 billion 2007: $1.5 billion

------
kenster07
Getting rich while play poker with others' pensions. And just like a casino,
the only sure winner is the house.

------
ruang
Does this mean that most MFE degrees lead to risk management instead of quant
trading?

~~~
shogunmike
I would say it's easier to get a job in risk management (likely in investment
banking) than quant trading coming out of an MFE degree. This is primarily a
consequence of how the MFE programs are set up, what they teach and the
network of the professors etc.

~~~
ruang
So quant funds don't use that much calculus? Primarily statistical techniques?

I would guess that might be the case since pure arbitrage no longer works and
thus quant funds have to delve into more probabilistic strategies like stat
arb.

~~~
shogunmike
Yeah, this is pretty much the case.

The quant derivatives pricing teams at banks are where the stochastic calculus
folk tend to head to. Their teams are generally highly respected in this area.
Also, banks are doing a different job to funds. Banks are generally interested
in assessing the risk or trading risk of these products, either on prop (i.e.
with their own funds) or to clients.

Funds tend to concentrate more on statistical/machine learning/econometrics
research approaches. The culture is generally more like a research institute
thank a bank. They tend to hire more PhDs from Comp Sci, whereas banks will
hire directly after MFE or straight out of undergrad.

~~~
ruang
Is that why physicists (vs computer scientists) are no longer recruited as
actively for quant trading roles?

It seems like all the low hanging fruit has been arbitraged away. I've worked
with a Math PhD from Princeton before in prop trading and he always lost
money.

~~~
shogunmike
Machine learning techniques are becoming more common. Hence a shifting trend
towards CompSci away from Physicists. The latter were often hired due to their
modelling/probability capabilities in PDEs for derivatives pricing.

Also CompSci comes with a (perceived) "built in" ability to carry out good
software development practices.

------
anoncowherd
Dear HN: Stop casually discussing working for a bunch of disgustingly greedy,
full-of-shit, and downright _evil_ sociopaths as if you hadn't noticed.

~~~
hudibras
The title of this submission was pretty clear. If you don't want to discuss
this topic, then don't click on the comments link.

That's what I do when I see, for example, the word "Haskell" in the submission
title...

