the whole platform, actually. Allows for visual programming (a la Reaktor style)
price: DELTIX CLOUD SERVICES (DCS): http://www.deltixlab.com/dcs/ $200 / month
CQG: http://www.cqg.com/Products.aspx, https://en.wikipedia.org/wiki/CQG
data: CQG Data Factory offers traders more than twenty years of end-of-day market data and more than seven years of intraday data, including time & sales (tick data), intraday bar, and trade volume. Traders can also access additional data from as far back as the 1930s.
analytics: CQG’s TFlow charts and studies give traders an exclusive way to see the inside market, showing whether traders are hitting bids or lifting offers to generate the last price. With TFlow charts, you know who the agressors are: the buyers or the sellers. TFlow gives traders the edge they need.
Multicharts: use this if the two above are too expensive
R: http://www.r-project.org/, http://www.rinfinance.com/, http://cran.r-project.org/doc/manuals/R-lang.html, http://www.r-project.org/
RStudio: http://www.rstudio.com/ide/ RStudio is a free and open source integrated development environment for R. You can run it on your desktop (Windows, Mac, or Linux) or even over the web using RStudio Server.
Use this for quant analysis
StatET: R in Eclipse: http://navisan.com/Articles/EclipseRHTML.aspx, http://www.eclipse4you.com/?q=en/eclipse_plugins/statet
The R Journal: http://journal.r-project.org/archive/2013-1/
my reasoning tells me this will get better than R (why do prototyping in R and then reprogram in C when Julia is at worst 2 times slower than C ? Programmers’ time is expensive and Moore’s law takes care of the unnecessary optimization (which is in fact, pessimization, this is a programming philosophy from the book “The Art of Unix Programming”).
Comparison to R: https://en.wikipedia.org/wiki/R_(programming_language)#Speed-up_and_memory_efficiency Speed-up and memory efficiency, The package jit provides JIT-compilation, and the package compiler offers a byte-code compiler for R. The packages snow, multicore, and parallel provide parallelism for R. The package ff saves memory by storing data on disk. The data structures behave as if they were in RAM. The package ffbase provides basic statistical functions for ‘ff’.
[comparison of the R & Julia]: http://strata.oreilly.com/2012/10/matlab-r-julia-languages-for-data-analysis.html