
Ask HN: What are the best resources for learning about algorithmic trading? - whiskers08xmt
I&#x27;m a CS student looking to get into Quantative Finance, and would appreciate if anyone could point me in the right direction.
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1o0ko
Broadly speaking I think that you are speaking about two things: derivatives
pricing (this is what people think when thy talk about quantitative finance)
and algorithmic trading (which can be either pure market making or alpha
seeking speculation ;).

To better understand the difference between the different branches of QF
world, visit this site:[https://www.quantstart.com/articles/Quantitative-
Finance-Rea...](https://www.quantstart.com/articles/Quantitative-Finance-
Reading-List)

It has a comprehensive list of references and articles describing in details
what to expect in different jobs.

It won't harm if you occasionally visit
[https://forum.wilmott.com/](https://forum.wilmott.com/).

And finally, for shit'n'giggles:
[http://www.zerohedge.com/](http://www.zerohedge.com/) ;)

~~~
dsacco
>> _Broadly speaking I think that you are speaking about two things:
derivatives pricing (this is what people think when thy talk about
quantitative finance) and algorithmic trading (which can be either pure market
making or alpha seeking speculation ;)._

"Quantitative finance" was mostly associated with derivatives pricing in the
mid-late aughts, but nowadays I see a pretty loose classification tossed
around that essentially makes it shorthand for "we're doing something data
science-y to forecast things." It's more of a marketing/cultural term, and has
sort of lost a lot of the meaning and precision it used to have. Handy to sort
of succinctly sum up where on the Street you vaguely work (or at least which
ingroup you'd like to signal therein), but not so handy for trying to e.g.
Google around for what to learn. QuantStart is probably helpful there though.

Not a criticism of your point, just wanted to add some color to it for other
readers. I agree with Wilmott forums being a great starting point at the very
least, though it's going to be a little esoteric for someone totally new to
finance.

To the OP: pick up _Heard on the Street: Quantitative Questions From Wall
Street Job Interviews._ It's not perfect, but it's a good start. There aren't
any textbooks that will take you all of the way in algorithmic trading (from
finding alpha, to strategy implementation, to risk management, to portfolio
theory, etc). If you're a CS student and looking for quantitative finance,
core computer science (not just programming) is what you want to drill down
on. You'll want to invest in your math skills quite a bit too, and especially
statistics.

Research firms like Two Sigma, RenTec (good luck), AQR, D.E. Shaw and
Bridgewater, which are wholly or in part devoted to what you might call
"financial engineering." Learn about their processes and talk to as many
people in the industry as you can to learn about what they do and network.

Finally, chollida1 does this better than I can, but please don't trade with
your own money. It's an expensive tuition :)

~~~
osullivj
Also Man AHL.

------
neuronsguy
Depends what your goals are.

If you want to get a job at an HFT e.g. Jump: as a student you're not expected
to know much about finance or trading, the prerequisite knowledge is similar
to getting hired at eg Google. I work at one of these firms, when we hire
people we have them come in and code in an IDE of their choice on a problem of
our choice for about 2 hours, and we watch them do it and discuss it after. We
also do algorithm interviews, and try to find people who are demonstrably
smart and also excited to work with us (note this is for dev roles. If you
want to work on trading roles you need to have a strong intuitive grasp of
probability, games and asymmetric payoff situations, these will come up in
interviews).

If you want to get a job as a quant: other comments here have addressed this.

If you want to learn about algorithmic trading from a tech perspective: go
read some exchange specs (BATS, CME, Eurex tech specs and market model).
That's the nitty gritty and you'll learn more about trading from that than
anything else you can do if you're not employed in trading.

If you want to learn about machine learning in the context of finance: get a
job at one of the quant hedge funds like Two Sigma. You do not have access to
the data you would need to learn on your own, and you cannot afford to get it
yourself.

In general to learn about modern algorithmic trading you have to work in the
industry, there is almost no public information of any value (maybe read the
Sniper in Mahwah blog if you haven't, he's pretty smart).

If you want to get a job you do not need to learn about this, you just need to
be worth teaching it to.

~~~
ryanx435
is this the right link to the blog? I can't imagine more than one blogger
using that name:

[https://sniperinmahwah.wordpress.com/](https://sniperinmahwah.wordpress.com/)

edit: this blog needs to be organized: best post, recommended posts, etc for
new readers. What a waste of writing if your new readers can't find good
articles.

double edit: interesting investigation into HFT companies building microwave
towers to cut transmission times to milliseconds from chicago to japan
[https://sniperinmahwah.wordpress.com/2016/09/23/once-
upon-a-...](https://sniperinmahwah.wordpress.com/2016/09/23/once-upon-a-time-
in-the-west/)

~~~
jackbrian
Yeah, that's the right one. He talks about HFT microwave towers and things

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dunster
Quantopian is home to 120,000 people learning algorithmic trading, including
students, data scientists, academic researchers, developers, and finance
professionals.

We provide a research platform, market simulation, and data for free. We also
provide tutorials, community, and lectures to teach you how to get good at it.
I recommend you take a look at the Getting Started Guide
([https://www.quantopian.com/tutorials/getting-
started](https://www.quantopian.com/tutorials/getting-started)) and then start
going through the Lectures
([https://www.quantopian.com/lectures](https://www.quantopian.com/lectures)).
The lectures cover some important statistical topics, and they get into how to
apply those concepts to algorithmic trading.

disclosure: I work for Quantopian.

~~~
boniface316
I recently started to explore quantopian. Do you plan on integrating R lang?

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jackbrian
As a CS student, I'd really make sure your stats knowledge is solid. Perhaps
take a class that covers stochastic finance (Black-Scholes, etc.) if
available.

I learned the hard way that it is quite difficult to break into finance as a
non-student, so do everything you can now to land that first gig. Good luck!

Some starting resources:

-Ernie Chan's books and blog ([https://epchan.blogspot.com/](https://epchan.blogspot.com/))

-QuantStart has great starter material and a new book, although I haven't read it ([https://www.quantstart.com/](https://www.quantstart.com/))

-"Inside the Black Box" (Narang) I've seen referenced a good bit but felt as though it leaned toward order execution and rather boring

-"Dark Pools" (Scott Patterson) a great story about the rise of algorithmic trading

-"Flash Boys' (Michael Lewis) offers a nice follow up (HFT), but considered a bit sensationalist

EDIT: If you're planning on using Python (a solid bet)...

-Python for Data Analysis (Wes McKinney) - Great, quick book for Pandas by former AQR (and now Two Sigma?) guy.

-Yves Hilpisch books: "Python for Finance" is introductory while "Derivative Analytics in Python" is quite math heavy.

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matheweis
Check out [https://www.quantopian.com](https://www.quantopian.com) and in
particular their community forums.

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baccredited
Related question: after creating a successful quant trading strategy - how
would you publicize it?

I've created a fund that tracks my strategy at motifinvesting.com and am
posting the trades at instavest.com. Where else should I go? Are there any
contests I can enter? (Quantopian requires too much turnover I only do 50
trades/yr)

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brudgers
The first company that comes to mind in terms of publicly discussing its
programming and computer science type engineering is JaneStreet. There are
episodes of Software Engineering Daily and YouTube talks and blog posts. Many
of them related to the OCaml language and system design.

Good luck.

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proquant
I'd recommend that you get good at stochastic processes and time series
analysis, machine learning, and neural networking on the tech side, and
managed futures and commodities trading as opposed to stocks.

Quantiacs is the best place to learn. They are the world's 1st and only
crowdsourced hedge fund actively trading with institutional capital, you can
contribute your algo to their marketplace and get matched with millions in
investment allocations and you keep 10% of the profits and retain 100% of your
IP, and they also run the world's largest quantitative finance competitions --
giving out $2.2M in allocations per Quarter.

Unlike Quantopian, Quantiacs focuses on managed futures as opposed to
equities. This is important because managed futures are uncorrelated with the
stock market and are the most liquid markets in the world -- it's where the
professional quants play. So if you want to be successful with quantitative
finance and algorithmic trading -- you should focus on managed futures more
than equities. So even though there are more users on Quantopian, the best
quants in the world are on Quantiacs.

Also on Quantiacs you can use either Python or Matlab so it's more flexible,
and the learning curve is not as steep as with Quantopian.

I'd recommend that you take a look here for tutorials:
[https://quantiacs.com/GetStarted](https://quantiacs.com/GetStarted)

And see what others have said about it here: [https://www.quora.com/What-do-
you-think-about-Quantiacs-com-...](https://www.quora.com/What-do-you-think-
about-Quantiacs-com-for-quantitative-finance-algorithmic-trading-and-
quantitative-managed-futures)

~~~
dsacco
Any affiliations you'd like to disclose?

