I'm a CS student looking to get into Quantative Finance, and would appreciate if anyone could point me in the right direction.
Ask HN: What are the best resources for learning about algorithmic trading?
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Re: Ask HN: What are the best resources for learning about algorithmic trading?
#2The 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.
Re: Ask HN: What are the best resources for learning about algorithmic trading?
#3Check out https://www.quantopian.com and in particular their community forums.
Re: Ask HN: What are the best resources for learning about algorithmic trading?
#4Broadly 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...
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/.
And finally, for shit'n'giggles: http://www.zerohedge.com/ ;)
Re: Ask HN: What are the best resources for learning about algorithmic trading?
#5Broadly 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... It has a…
>> 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 :)
Re: Ask HN: What are the best resources for learning about algorithmic trading?
#6As 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/)
-QuantStart has great starter material and a new book, although I haven't read it (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.
Re: Ask HN: What are the best resources for learning about algorithmic trading?
#7Broadly 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... It has a…
>> 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 esse…
Also Man AHL.
Re: Ask HN: What are the best resources for learning about algorithmic trading?
#8Quantopian 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) and then start going through the 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.
Re: Ask HN: What are the best resources for learning about algorithmic trading?
#9Related 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)
Re: Ask HN: What are the best resources for learning about algorithmic trading?
#10I'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
And see what others have said about it here: https://www.quora.com/What-do-you-think-about-Quantiacs-com-...