8 bear signs for potential correction coming

# Tag Archives: potential

# Examples of Java Virtual Machine JVM for FPGA uses for potential HFT including open source options

Examples of Java Virtual Machine JVM for FPGA uses for potential HFT including open source options

# Video of R, RCPP, RInside makes use of C++ so much easier than Matlab Builder NE for high frequency trading aka HFT potential

Video of R, RCPP, RInside makes use of C++ so much easier than Matlab Builder NE for high frequency trading aka HFT potential

So I am going from trying out an open source C# application trading platform to an open source C++ ‘platform’ using Interactive Brokers. I also switched from Matlab to R. Lastly; I am looking at more open source projects including Linux where Ubuntu is becoming my preferred distribution. As you can tell, I am straying away from expensive options like Matlab. Being a developer, I can quickly debug most applications if need be.

The benefit I am finding switching to R as compared to using Matlab with something like Matlab’s Builder JA (for Java) or Builder NE (for .NET languages like C#) toolboxes. When I tried out the combination of R packages RCpp and RInside, I was pleasantly surprised for a number of things. Installing any R package is quite easy. Building or ‘making’ the provided C++ examples for RInside was flawless and easy to execute. The most impressive were samples of parallelization of C++ which was jaw dropping.

Now I am hoping I can see my newer open source C++ trading solution Trading Shim (http://www.tradingshim.org/) will work at some point as well. Hey…it is C++ so leave it alone. But the speed and scalability of it should be impressive. I just wish there was a complete open source trading platform in Java that could connect to my chosen broker Interactive Brokers.

Anyhow, back to the R packages of RCpp and Rinside. I need to give a shout out to the contributors for making these packages happen in a quick and easy way. The provided C++ examples really do make a difference to showcase how a C++ application can call the R shell processor and execute individual R functions directly. You could not do that with the Matlab NE Builder as you could only call M scripts with their archaic programming structure. The C++ code within RInside as compared to Matlab NE is much simpler, tighter, and smaller. The Matlab NE Builder is really meant for C# so trying it in Visual C++ would have been ‘interesting.’ I am just glad I found this deadly combination of R, RCpp/Rinside, with C++. It may work well for my hopeful high frequency trading platform with R for prototyping and analytics.

[youtube_sc url=”http://www.youtube.com/watch?v=wIzrJFy-VCA” playlist=”Calling R from a C application for HFT development with MPI parallelzation ” title=”Calling%20R%20from%20a%20C%20application%20for%20HFT%20development%20with%20MPI%20parallelzation%20″]

# The mother load of R packages for financial trading, quant, and potential high frequency trading (HFT) needs

The mother load of R packages for financial trading, quant, and potential high frequency trading (HFT) needs

So there seems to be this endless supply of what look to be a decent list of R finance packages. Some of these include quant based ones. This is my first day researching so I cannot vouch for any of these yet. I do know some R packages can be duds but I am not sure if these ones will be either but are part of CRAN which says positive things. Here we go:

Extreme value analysis:

http://cran.r-project.org/web/packages/evir/evir.pdf

Refer to p 39 for parameter use in Gvt:

http://www.stat.colostate.edu/

Potential fat tail analysis which lead to the ones below:

http://braverock.com/brian/R/

PerformanceAnalytics package is quite amazing and easy to use for the amount of analysis it has: i.e. VaR

http://r.789695.n4.nabble.com/

Overview and demo of PerformanceAnalytics (PA):

http://www.rinfinance.com/

How read profitable data and convert to PA package

http://quant.stackexchange.

How to back test strategies with PA:

http://blog.fosstrading.com/

A technical package:

http://cran.r-project.org/web/

TradeAnalytics packages which includes quantstrat:

http://cran.r-project.org/web/

Intro to quantstrat:

http://blog.fosstrading.com/

General list of R packages for quant trading:

http://blog.fosstrading.com/

The motherload of all financial trading packages in CRAN:

http://cran.wustl.edu/web/views/Finance.html

I feel like a kid a candy factory with all this. Makes me wonder how Matlab is going to keep up. Wow! Thanks to all contributors above for all these. Now I have to start digging and play with everything. I will also keep reporting through this blog for those interested.