
How to Get a Job in Algorithmic Trading - simonflynn
https://www.financejobs.co/development/how-to-get-a-job-in-algorithmic-trading.html
======
chollida1
To be honest, I was a bit disappointed with this article. I'm aware of the
author, I own two of his books, and he certainly knows what he's talking
about.

However, there wasn't really too much actionable advice in it. I don't think I
actually saw any advice as to how to become an algorithmic trader in the post.

I think I actually wrote a better answer in a previous post here:

[https://news.ycombinator.com/item?id=8699260](https://news.ycombinator.com/item?id=8699260)

The sad fact is that if you want to get into algorithmic trading you really
have 3 choices.

1) got to MIT, get an undergrad in math/engineering, apply to TradeBot, Virtu,
Getco, Jane Street.

This provably works as this is how these firms hire, sadly its not very
applicable for most people.

2) Get into a small and successful fund that was previously a prop shop(
traders without any algorithmic tooling and then start to build it out
yourself.

This can work, but its a very hard and long slog. You'll be creating
everything from scratch and wont' have alot of people to bounce technical
ideas off of. This might be the hardest way to break into the industry, as
you'll essentially be creating a new company inside of an existing one, but it
is possible, as this is how I did it.

3) Get hired in a technical capacity with a major algorithmic trading firm and
move up.

The key here is to not be in a strictly technical capacity for more than a few
years. The industry has a tendency to box people into their current roles.

You have to make people aware of what your goals are. Shadow the best traders
you can find. Be mentored by the technical talent who writes the strategies.
Get as close to the money as possible!

I lied there is actually a secret option 4)

You can go it alone and trade your own money. I really don't recommend this to
people as you need a minimum of $50,000 to $100,000 to do this well. Its hard
as you won't have anyone to bounce ideas off of or to lean on when times are
tough.

The biggest problem I've seen with going it on your own is that since 2009
we've been in a huge bull market. Everyone is making money. We haven't had a
challenging market for 5 years so if you've been trading for less its hard to
know if its you who is making money(alpha) or if its the market(beta).

I really don't try to time the market but I have a feeling that late next year
people who have been trading their own strategies will start to find out what
its like to trade in a bear market.

Someone privately messaged me about math. For each of these options, I find
math, specifically stats, to be very important. The hard part is getting
programmers to learn stats. There is an old Simpsons episode where Homer is
trying to learn about marketing. He starts with a huge book on marketing reads
it for a few minutes and then goes to a beginners guid to marketing before
finally looking the definition of marketing up on the internet.

Don't be afraid to learn math this way. I usually recommend people read
chapters 2-5 of Introduction to Statistically learning

[http://www-bcf.usc.edu/~gareth/ISL/](http://www-bcf.usc.edu/~gareth/ISL/)

If you are flying through it then graduate to Elements of statistical learning
[http://statweb.stanford.edu/~tibs/ElemStatLearn/](http://statweb.stanford.edu/~tibs/ElemStatLearn/)

If you are working hard to understand Intro to statistical learning then go to
Kahn Academy and spend 2 weeks doing all their stats lessons.

I feel like I'm repeating my self but there are no free lunches. You need to
work to learn the material. Don't be afraid to go back to basics.

On his book recommendations, Trading and Exchanges is awesome. Michael Lewis'
Flash boys is not, read Scott Patterson's DarkPools instead
[http://www.amazon.com/Dark-Pools-Machine-Traders-
Rigging/dp/...](http://www.amazon.com/Dark-Pools-Machine-Traders-
Rigging/dp/0307887189)

If you are determined to read Flash Boys then atleast read the counter
argument by a HFT
[https://news.ycombinator.com/item?id=8577237](https://news.ycombinator.com/item?id=8577237)

Its a much more enlightening read and is only a few dollars:)

~~~
zeeshanm
>> got to MIT, get an undergrad in math/engineering, apply to TradeBot, Virtu,
Getco, Jane Street.

Regarding Tradebot, they are known to hire from local schools out in Kansas.
In fact, Dave Cummings once said it's like half-way to India strategy. You
don't have to get an MIT kid and pay them loads of money when you can get a
local school kid pretty much do the same.

I used to be in this field, so I can say from my experience, at least, such
jobs come out of relationship building with the men of influence. Sometimes it
means being ruthless about following up until the right moment comes (e.g.
they have a headcount).

But I hear you on that. Having gone to MIT may help.

~~~
busterarm
With some places (DE Shaw & similar), having gone to MIT or an Ivy is just
about the only way to get your foot in the door if you're new to the industry.

Also, having a Ph.D. helps, and if somebody wants to go this route I would
steer them towards Two Sigma over the competition.

~~~
jeffreyrogers
Even then it's still really hard. I'm at one of those schools and many of my
friends don't even get interviews with the best firms. My impression is that
the supply of capable people for these jobs is much higher than the capacity
to absorb everyone who is capable of doing the job.

~~~
busterarm
Yeah, it's hard to really pin down. They're all really image-conscious and
they're looking for specific things -- I don't even know what sometimes. It
also really helps to meet with their recruiters that come around your campus
and get feedback from them on this. They have a difficult job that they'd love
to make easier.

Also keep in mind that they have an image to maintain and some of them are
really hurting right now. They may have to look like they're hiring when
really they aren't.

(looking over your profile) You might be better off at some of the smaller,
specialized HFT shops out there (I hope you like Chicago) if you really know
your way around linux kernel programming. That's a really small industry
though.

~~~
jeffreyrogers
Thanks for the advice :)

------
Fede_V
Even with the high pay and the intellectually challenging work, I've never
found finance the slightest bit appealing.

Somehow, in finance, the impression I always got was that the
engineers/algorithm guys were always second fiddle to the traders, and the
traders were an incredibly aggressive group of people with a mean competitive
streak (part of it I'm sure was the subset of people I met).

It's hard to explain, but I very much enjoy being a nerd among nerds. Being a
nerd among finance people always made me feel highly alienated.

~~~
reverend_gonzo
On top of what Michael O'Church is saying, which I agree with entirely,
there's a huge different in the types of traders and types of trading firms
there are.

At small, purely algo shops (ala Jane Street), the traders are your nerds.
They're programmers, engineers, mathmeticians, physicists, but they just
happen to trade.

The incredibly aggressive people that you're talking about is mostly floor
traders, brokers, etc, because they need to be that way, and they're generally
on their way out, as algos will be smarter and faster.

I've worked in a variety of industries (in software development), and am
currently at an HFT shop, and I've found this to be the first place I feel
actually values my abilities.

~~~
PublicEnemy111
Would you say that, as a HFT shop, you are only competing with other HFT
shops? I've heard that HFTs use nearly identical algorithms, so now its
basically a competition for real estate near the exchanges.

~~~
kasey_junk
Real estate near exchanges has essentially been standardized and is no longer
a significant strategic advantage.

------
gozmike
If you're in Canada, it's worth noting that when you do trade with other
people's money you really need to be certified with the relevant authorities
in addition to having the skills.

I interned with a hedge fund for a year early on in my career building algo
trading models (circa 2002). Since then the fund has gone under and I was
contacted by an investigator from the OSC (more or less our SEC) about the
exact nature of my work. Thankfully no charges came of it but I learned that I
did expose myself to personal liability due to the fact that I had never
gained regulatory certification.

In short, don't overlook the laws in this space. They can really bite!

------
jordigh
I've always found the whole prospect of algorithmic trading morally dubious.
Is algorithmic trading overall a good thing? Is it something we should be
encouraging? Can I do good in the world by working in algorithmic trading?
Would people become algorithmic traders out of a belief that they're improving
the world, and would gladly do it even if the pay was slightly lower than
other software developer jobs?

I really don't know. The only reasons I've ever been marginally enticed to do
it is that it looks like a fun problem and people make a lot of money off it.
But it's hard to beat the job satisfaction at my current workplace. Right now
I can release free software, which helps diagnosing and treating neurological
diseases.

~~~
aurelius
Algorithmic trading is intrinsically neither good nor bad. It's kind of just a
natural progression in the markets once easily programmable computers and
high-speed networks came along.

How algorithmic trading is used, however, is another story. Humans are still
the ones who bring the intent to technology, using it for good or evil. But it
may interest you to know that a lot of malicious trading in the markets is not
done by algorithmic traders, but by teams of manual traders working in concert
to place manipulative trades that cause the market making algorithms to move
the market in certain ways. (Source: I work at an exchange, and this is what
our regulatory and compliance dept. says all the time.)

~~~
jsprogrammer
Why are the market making algorithms so easily exploited?

~~~
throwaway283719
Most market making algorithms work like -

    
    
      Market state                                     -> price forecast
      Price forecast + other factors (risk, liquidity) -> trading decision
    

If you know (or have a good guess) how the algorithm works, you can work out
what state of the market would lead to a price forecast in your favour, i.e.
would lead to the algorithm offering liquidity at a price favourable to you.

You then manipulate the state of the market to look like that (generally this
is "spoofing" or "layering"), wait for the algorithm to respond, and then take
advantage of the favourable liquidity it offers.

When people calibrate their algorithms, they use real market data. Most of the
time, someone isn't actively manipulating the market, so the model is not
calibrated to handle those situations.

~~~
aurelius
I know someone who used to work at an algorithm trading firm and did
electronic market making. He said they used to go to great lengths to program
their algorithms to try to spot this sort of manipulation, but it's a hard
problem because you're fighting against a cloud of bad traders who are
coordinating their efforts across multiple market centers.

I have to say, the regulatory dept. at the exchange I work for does an
excellent job of monitoring for any funny business. They have some nifty real-
time tools that are scriptable and can replay the state of the market at any
point. It's really cool stuff!

------
dpweb
It's good to note too that if you really have the skills, you can work for
yourself. You don't need to impress someone enough to have them hire you on.
Real ability is rare and very valuable so if you can learn that you'll be
fine.

What a shop will gain you is a larger pool of capital to work with, so you're
open to safer strategies that may only net say 1-5%/mo. (the higher the return
the higher the risk, so if you're doing a high risk/reward strategy, the only
way to not completely bankrupt is to quit at some point before you blow up,
which almost everyone cannot do).

There are a number of ways to pull 1-5% mo. out of capital, which doesn't make
it worth the time unless you're well capitalized, so it can make sense to get
with a firm, but keep in mind if you have the skills, you don't need to go
impress anyone. Your record will speak for itself.

~~~
michaelochurch
_It 's good to note too that if you really have the skills, you can work for
yourself. You don't need to impress someone enough to have them hire you on.
Real ability is rare and very valuable so if you can learn that you'll be
fine._

I don't agree. If you trade $25k of your personal capital up to $35k, that's
not going to impress a fund enough to hire you if it otherwise wouldn't. You
could have gotten lucky. It doesn't prove that you understand markets or the
effects of large trades ("slippage") or the game theory and microstructure. If
you lose that money, well now you're out by an amount that would be a fair
chunk of change for most people.

 _What a shop will gain you is a larger pool of capital to work with_

And relationships and experts that make transaction costs and taxes low, and
the ability to colocate and shave milliseconds off your execution time
(milliseconds matter; even _micro_ seconds matter, these days), and smart
people to learn from.

~~~
tptacek
Did you work for a trading firm? In what capacity?

~~~
michaelochurch
Yes, as a quant.

~~~
tptacek
At Jane Street, you mean, right? There might be a selection effect here.

Or I could just be wrong. More than just possible.

------
simonflynn
If anyone is interested in getting into algo trading, other books not
mentioned but are highly regarded are:

\- "The Evaluation and Optimization of Trading Strategies" by Pardo

\- "The Elements of Statistical Learning" by Hastie et al

~~~
EC1
Is there a way to get into any of this without any math background whatsoever,
just programming skills?

~~~
coldnebo
Programming skills are math skills. For example, how would you prove that your
code is the fastest possible for a given task? A hunch? A stopwatch? Would it
make a difference if you used a different language or machine? What if you
could objectively compare the algorithm performance itself without conflating
factors? What if you could prove it to others without having to simply trust
that you are right? This is math. This is why you can't solve the halting
problem or lossless compress past the Shannon limit no matter how hard you
try. But it's also why a simple fractal contains an infinite universe of
complexity. Don't be afraid of math, embrace it! Find some good teachers/books
and maybe you'll find that math isn't some arcane priesthood setup by
mathematicans, but that it's the language of nature, the most practical and
precise way we have of explaining and understanding these things.

~~~
django_dev__
At least I have always found (most) math to be highly theoretical with little
applicability.

Any suggestions on applied math? I suspect I just haven't been exposed to
enough of it to really connect the theory to the real world.

~~~
coldnebo
I had to laugh when I saw my response next to @getsat's. Both are valid
viewpoints. In other words, not everyone who uses tools has to know how to
make tools.

Tool makers have more insight into the assumptions behind the tools they
create -- they might know how a tool was meant to be used and what its limits
are. That being said, there are times when using a screwdriver as a hammer is
expedient and does no harm. Of course, there are other times where using
Black-Scholes to model a high-volatility market outside of the 'smoothly
differentiable' market assumptions it was built on can crash a large part of
the economy. It can be a dangerous game to use someone else's tools without
knowing their assumptions.

As for applied math suggestions:

1) Watch Feynman's take on applied math in physics:
[https://www.youtube.com/watch?v=obCjODeoLVw](https://www.youtube.com/watch?v=obCjODeoLVw)

2) Read this essay "A Mathematician's Lament" which points out the math
learned in school is likely not really mathematics and that surprisingly math
is not practical but aesthetic -- mathematics is closer to art than we are
taught:
[http://www.maa.org/external_archive/devlin/LockhartsLament.p...](http://www.maa.org/external_archive/devlin/LockhartsLament.pdf)

------
wehadfun
How does pay work in this field? It is commission or salery?

Do these programmers have a short career span. (lose x amount of dollars and
you need to leave.)

How much could someone make in this field. Software engineers regularly make
100K so do these guys make more to justify the risk?

~~~
michaelochurch
_How does pay work in this field? It is commission or salery?_

Salaries in finance are low compared to comparable jobs. Bonuses can be very
high. A senior programmer who'd make $150k in tech will probably get $130k in
a hedge fund, but the bonuses... can be anywhere from 0 to 1000%. Median is
probably 30%. Market conditions play a role.

Sadly, compensation has been getting worse for quants over the years. It used
to be that you could take a $500k all-in for granted just for knowing college-
level math and programming. That's no longer true.

 _Do these programmers have a short career span. (lose x amount of dollars and
you need to leave.)_

No worse than startups. It's probably better, to be honest. The age
discrimination isn't nearly as bad as in the VC-funded world, people are less-
often fired for stupid reasons in hedge funds, and the ethics are generally
better in finance than in the VC-funded world. Finally, the lower status of
programmers may be more visible in finance (i.e. you're clearly second-rate
compared to traders) but less onerous. Engineers are _third_ -class citizens
in the Valley, with their 0.01% equity slices of post-A startups, and because
the VC-funded startups aren't very selective and a third of the programmers
are incompetent, they feel a need to use "Agile" micromanagement that you
wouldn't see at a hedge fund.

If you lose serious money (meaning hundreds of thousands) doing something
stupid, you'll get fired. If you're unluckym good funds won't fire you. A lot
of statistical arbitrage is taking "51/49" bets.

 _How much could someone make in this field._

The upside is very high. That said, typically it's not going to be more than
25-50% more than you'd make elsewhere. You need to manage your career
aggressively and become someone's protege if you want to get above $300k...
but it can be done, and some people make 10-50 times that.

~~~
tptacek
Wait, let me see if I understand the logic here. Engineers are second-class
citizens in finance, but _third-class_ citizens in "the VC-funded world".
Evidence: engineers get "0.01% equity slices of post-A startups".

What percentage of a hedge fund does a typical engineer get?

~~~
kasey_junk
I get what you are trying to say, and don't agree with the either the
second/third class citizen descriptions, but in hedge funds/prop trading shops
compensation is typically not equity based, but is very typically profit
sharing based, with the _engineers_ getting a pretty hefty share of any
trading profits.

In fact, when you hear about giant bonuses in finance what you are often
really hearing about are groups that traded salary for profit sharing and it
paid off. In the context of finance, this comes off as shady or outrageous but
in the context of startup hits it doesn't.

Lets just say, having worked under option based equity arrangements and profit
sharing arrangements, they both had their positives and negatives, but only
ever felt like a system was stacked against me, as an employee, when
equity/options were on the table.

~~~
tptacek
Sure, but let me go a little further out on this limb and challenge you, too:
in established trading firms --- DRW, Two Sigma, that sort of place --- what
percentage of the returns do you think go to non-founding engineers?

~~~
kasey_junk
I obviously have no way of knowing, but I suspect the compensation package at
those places is much more dependent on the amount of impact you have to those
returns than to when you joined the firm (for better or worse) and that people
that impact those returns in dramatic ways will get compensated in a similar
manner to early stage employees at startups.

The big issue I think with the equity based model, is the golden handcuffs it
applies to early employees. Not only do they frequently forego market based
compensation for long periods of time, when they make the decision to stop
doing that, they are asked to take on more downside in order to keep any part
of their deferred compensation. For all it's downsides, the trading
environment would never ask someone to do that.

~~~
tptacek
You'd know better than I would, and if I have a dog in this fight, it's
fighting on your side: the more prized engineers are in trading firms, the
better off I am. :)

My immediate reaction to this point, though, is:

* The downsides of equity comp are shared by all roles in a tech company, not just engineers; the exceptions are the very most senior management, and the tiny cohort of founders. Both of which are exceptional at _all_ firms.

* Dev jobs in finance are, I am pretty sure, a better deal than those in tech startups.

* But let's not move the goalposts: the argument is that engineers are _second-class_ in tech startups in a way that isn't true in finance companies. Most engineering jobs at finance companies are cost-center roles.

~~~
kasey_junk
"But let's not move the goalposts: the argument is that engineers are second-
class in tech startups in a way that isn't true in finance companies. Most
engineering jobs at finance companies are cost-center roles."

As I mentioned, I do not think it is a fair characterization to say that
engineers are more/less valued in either situation. I just think that using
equity distribution percentage to argue one way or the other is problematic in
that compensation is determined in 2 dramatically different ways.

That said, if I were going to argue anything, it would be that the equity
options based compensation packages in tech startups seem to have more
opportunity for abuse. So characterizing engineers as 3rd vs 2nd class isn't
interesting, but characterizing one compensation structure as more
exploitative than the other may be, and I think that is at the heart of what
the original post was about.

[edit] I'd also add that any characterizations about the methodologies used in
finance/trading vs tech startups is completely inaccurate. I've seen great
development process in both places and the converse as well.

~~~
tptacek
This makes too much sense for me to productively argue with, so instead I will
accept and wallow in my wrongness.

------
noname123
Not interested in job. Would love to hear and share some new strategies with
peeps on HN; specifically, what do you guys think are the new opportunities
for the new coming year.

Me personally, I think next year is going to be great. Vol should pick up with
the Fed actually tapering and VIX returning to its real median of 16-20. So I
think strategies that sell vol could be more effective. Here's a study on
Quantopian for that:
[http://papers.ssrn.com/sol3/papers.cfm?abstract_id=225532](http://papers.ssrn.com/sol3/papers.cfm?abstract_id=225532)

I'm curious about how the rising interest rate will affect things such as gold
and US treasuries; obviously, it should drive the yield/prices down as US
dollar becomes more attractive. But specifically, how to pair trade it; here's
some study on pair trading TLT and SPY:
[http://seekingalpha.com/article/2714185-the-spy-tlt-
universa...](http://seekingalpha.com/article/2714185-the-spy-tlt-universal-
investment-strategy)

Finally, pair trading GDX and GLD; and also oil futures and oil
refining/exploration companies. I'm not very familiar at all the dynamics
there, I was told that the correlation of producer to spot is like an option
being in the money, if oil or gold drops down or up to the threshold of break-
even for producers; that changes the pricing dynamics of these companies.
Anyways, let me know what you guys think. Thanks.

------
guiomie
The author mentions 2 backtesting platforms, which platform is better:
BattleFin or Quantopian?

~~~
wallstreetguy
I have used the BattleFin backtesting platform extensively but I always think
Quantopian has more better things.

------
michaelochurch
Perhaps surprisingly, the funds considered elite are biased _against_ people
with prior work experience, outside of academia. The best time to join the
elite firms is right out of a PhD program. That said, money is money, and I'd
honestly rather take a great position at an above-average hedge fund than an
entry-level spot at one with a gold-plated reputation. By the time you're in
your 30s, you evaluate the position rather than the company.

Some of these funds have a passionate hatred for "job hoppers" are are
inaccessible to almost anyone in tech. It's normal to change jobs every 2
years. Not getting promoted? Switch. Your manager left for greener pastures?
Follow him. Hedge funds do a better job of internal promotion, so you're more
likely to end up on a track that would merit a longer stay, but they tend to
view the average tech CV negatively, because they're extremely paranoid about
IP and changing jobs every 18-24 months until you get lucky and "click" with
someone powerful and are on a protege/leadership track (which is what you have
to do, in tech) is frowned upon.

Learning finance is important for showing an interest in the field (and not
just the money) but most of the hard effort is going to be in learning
statistics, computer science, microeconomics, and technology.

