R For Quantitative Finance

[NYConsultant]

I was wondering if anyone here is currently using R for financial engineering applications, or has any input or resources about it's applicability; thanks in advance-

 

[alain]

we are using it. It is widely used in the industry. There is even an annual conference about R in Finance in Chicago. Check REvolution Computing for a company that has a business around R.

 

[Joy Pathak]

R is utilized quite a bit in algorithmic trading desks (e.g Stat Arb) at big investment banks and hedge funds especially in the research/strategy development phase. I personally prefer MATLAB along with my Stat Arb professor and several places use MATLAB as the preferred analytics package, but R is free and there is a push to use it more it seems.

 

[alain]

the only issue is MATLAB is not cheap, far from it.

 

[Joy Pathak]

the only issue is MATLAB is not cheap, far from it.

Yes. I definitely agree with that.

 

[NYConsultant]

R is a pretty impressive piece of software. I'm surprised as to why people would spend large sums of money on SAS or S+ solutions.

 

[dstefan]

Legacy code, force of habit, previous knowledge.

 

[emsfeld]

We are slowly phasing out R and Matlab as analysis tools, even in research, and 'replace' them via strongly typed languages (mainly C# and some C++). Reason being that integration into production is quicker and they also seem to be more suitable for crunching through large(r) amounts of data.
<o:p> </o:p>
Most of the numerical algos you need, can be found within open-source libraries. If any specific functions are not available through these you can interface to R via the statconnector or go through the trouble of either marshalling or translating the C source (which doesn’t take very long anyway).

Personally, I find the arrival of linq a real blessing for preparing/ aligning data. Sure, it can be done in R/ Matlab as well, but I find linq much more convenient to use. We are dealing with quite massive datasets, so relational databases don’t cut it in terms of reading/ query speeds. Objects (de-)serialization from/into binary files to cope with the size and achieve better processing performance is the only alternative. Other than specialized, commercial databases, of course, which are not feasible economically at this stage (for us).
<o:p> </o:p>
The only overhead in terms of time and additional code you have from using C# is that you have to (a) format the output and (b) take care of stuff like charting yourself. You do the latter once, in an easily extensible framework and the additional overhead reduces to almost nothing. Also, the gain from VS’s debugger vs R’s, outweighs any overhead incurred otherwise.

 

[Christophe]

Anyone knows about good ressources related to R and financial engineering? There is a lot for MATLAB, but I find it hard to find material related to R for FE.

Thanks

 

[IlyaKEightSix]

I am surprised that people say they use R extensively. I haven't been able to find a single job posting that values R above C++/C#/Java (I feel far more comfortable in R).

Is there a certain way I can find out about these heavy R using positions, because I'd love to apply to them.

 

[Andy D.]

Coming from a non-Quant Software Engineering background where we had a team of Mathematicians doing number crunching, the common tool was Stata.
I downloaded a copy of the R environment and it seems like a impressive tool, if anyone has any recommended resources I'd be interested in checking them out.

 

[alain]

I am surprised that people say they use R extensively. I haven't been able to find a single job posting that values R above C++/C#/Java (I feel far more comfortable in R).

Is there a certain way I can find out about these heavy R using positions, because I'd love to apply to them.

we never ask for experience with R when looking for candidates. I think the prop desk does the same thing. R can be picked up if you know the math and know how to code.

Most of the people using R in finance subscribe to the R Finance mailing list. They also interact in the R Finance conferences.