Algorithmic Trading in R: Available Information

After digging through different blogs and info on the web I found an amazingly strong and developing community supporting R for specific applications in algorithmic trading. Thereafter I present some of the major information that I believe are essential to the novice R algorithmic trader, hoping this will reduce the learning curves of the few following that path:

  1. QuantMod: development, testing, and deployment,
  2. TTR: technical trading rules,
  3. PerformanceAnalytics: econometric functions for performance and risk analysis of financial instruments or portfolios,
  4. XTS: extensible time-series,
  5. Blotter/QuantStrat: Transaction-oriented infrastructure for defining instruments, transactions, portfolios and accounts for trading systems and simulation – build, and back-test strategies
  6. R-QuantLib: R interface to the QuantLib library
  7. CRAN Finance & Econometrics packages

A nice summary can be found here.

Now I’m early in my project, which aims at using R to provide trading-signals to a Metatrader platform, but there is a specific information that I’m not yet able to find: Is R efficient enough (fast enough if you will) to allow live trading on a per-tick basis, per-second basis or per-? basis ? What is the ideal architecture to perform live trades: asynchrone R calculation for major analysis, combined to c++ functions and/or Metatrader functions to closely watch market opportunities? I was not able to find anyone detailing his/her Live trading set-up involving R which is a pity as a lack of design would result in basically restarting from scratch or living with inefficient set-ups. I guess I will have to experience the trial & error investigation.