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Intro to algorithmic trading from programmers perspective?

Matt Ward

Joined
12/16/12
Messages
9
Points
13
I am a undergraduate software engineer and am looking to start studying the basics of algorithmic trading for my senior project. Having very little background in finance, I am assuming there will be a lot of studying just to understands the basics; however, I am hoping there is a book which looks at algorithmic trading from a programmer's point of view.

I plan to get my masters in computer science, and figure I can continue my work throughout the next few years. I don't expect to write a workable algorithm, but I am intersted in learning some of the basic algorithmic trading paradigms. Are there any books which come to mind which might be useful to me? Thanks for the help.
 
That book was already in my cart before I decided to come here for advise, I guess I will go ahead and grab it. It sounds like good background on the material and although it may be a little light on the code, it should be helpful.

The online course seems like it will have some useful projects, so I figure I can work through it over winter break and then delve into more advanced material shortly. As for it being in python, that isn't much of a concern to me as I expect most of the concepts can be easily translated to other languages.

R is one of the few languages I see people discussing here that I have not dealt with. Are there specific uses for it that make it useful? I always had the impression it was a less powerful than other languages and more comparable to something like matlab. As I am already a programmer, will I be best off just to continue using C++ paired with a scripting language or should I learn R?
 
R is a niche language. The comparison to Matlab is accurate. R is more for research statistics and Matlab is more for engineering and numerical stuff. By Googling around, you can see the types of things people do with R and try to decide whether you would be doing anything like that for your project. The advantage I see for you with R is that you can piggy back of work that others have done (there are a large number of good packages, or extensions, for R). However, if you are under mandate from your course or whatnot to only use your own work, that may not be helpful to you.

R is not powerful in the sense of handling very big data sets. It is also not powerful in terms of breadth of application (you couldn't use R for web programming, etc). R is pretty good at being what it is, though; a platform for research statisticians.

Honestly, if you are very comfortable with C++, I doubt learning R would pose a challenge to you in any case.
 
Honestly, if you are very comfortable with C++, I doubt learning R would pose a challenge to you in any case.

If you know C++, any _imperative_ language is easy.

For functional languages e.g. F# this is a different story.
 
Daniel Duffy said:
Honestly, if you are very comfortable with C++, I doubt learning R would pose a challenge to you in any case.

If you know C++, any _imperative_ language is easy.

For functional languages e.g. F# this is a different story.
Click to expand...

That being said, useful knowledge transfer may still occur:
http://bartoszmilewski.com/2009/09/08/template-metaprogramming-made-easy-huh/
http://bartoszmilewski.com/2009/10/21/what-does-haskell-have-to-do-with-c/
http://bartoszmilewski.com/2010/11/29/understanding-c-concepts-through-haskell-type-classes/
http://fpcomplete.com/the-functor-pattern-in-c/
http://fpcomplete.com/functional-patterns-in-c/
 
I agree. A smooth transition from to C to FP should be very doable.

Must say thay I like std::function<> big time in C++ 11. It allows me to do programming in the large.
 
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