For the past several years, Diethelm Würtz and his group at the Econophysics Group at the Institute of Theoretical Physics of ETH Zurich has been implementing tools in R for financial and econometric analysis. The Rmetrics project has now swelled to more than 30 packages for R, all available for free download.
Despite the fact Rmetrics is used in an industry which uses it to generate untold wealth (most of the time, at least), the Rmetrics Association which produces and supports Rmetrics is run as a non-profit enterprise. An affiliated organization, Finance Online, does generate financial support for Rmetrics through consulting to financial firms, but otherwise funding comes through donations.
Now, there's new way to contribute to the project by purchasing an E-book describing how to use Rmetrics. A series of E-books is planned, but the first is available now: Portfolio Analysis with R/Rmetrics. At around $85 (US) it's competitively priced with printed volumes that cover similar topics, and comes in a convenient PDF format. There's no copy-protection associated with the PDF (other than your name printed on each page to discourage unpaid distribution), and your purchase price includes all updates to the volume for a year. The PDF itself is very well produced, thanks to the talents of producer and co-author Andrew Ellis. The examples and output are all automatically generated from R and integrated with the written content to ensure accuracy, and the text is extensively bookmarked and hyperlinked making it easy to skip from section to section on-screen.
At over 450 pages it's a comprehensive study of all aspects of portfolio optimization with Rmetrics. If you're new to the domain (but have a good grounding in statistics and analysis), the theory sections provide a welcome and concise overview to the methods implemented. It does assume some familiarity with R, but all examples all start from first principles and include clear and well-commented code. Data sets are provided for the examples, and instructions are also provided on how to download financial data from public sources like Yahoo, the Swiss Exchange, and the Federal Reserve Bank in St Louis if you want to work with up-to-the-minute data sets.
There's a detailed review of the contents of the book after the break, but if you're doing any kind of financial analysis with R and haven't yet looked at Rmetrics, this book is a great place to start.
Rmetrics Association: Portfolio Analysis with R/Rmetrics
Contents of Portfolio Analysis with R/Rmetrics