# RQuantLib 0.3.9

[This article was first published on

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

A minor feature release RQuantLib 0.3.9
is now on CRAN and
in Debian.
RQuantLib
combines (some of) the quantitative analytics of
QuantLib with the
R statistical computing environment and language.
**Thinking inside the box**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Bryan Lewis had suggested to enable
another pricing engine for American Options in order to get (at least some)
*Greeks*. This is now supported by picking
`engine="CrankNicolson"`

as shown in the default example for the
`AmericanOption`

function:

R> library(RQuantLib) R> example(AmericanOption) AmrcnOR> # simple call with unnamed parameters AmrcnOR> AmericanOption("call", 100, 100, 0.02, 0.03, 0.5, 0.4) Concise summary of valuation for AmericanOption value delta gamma vega theta rho divRho 11.3648 NA NA NA NA NA NA AmrcnOR> # simple call with some explicit parameters AmrcnOR> AmericanOption("put", strike=100, volatility=0.4, 100, 0.02, 0.03, 0.5) Concise summary of valuation for AmericanOption value delta gamma vega theta rho divRho 10.9174 NA NA NA NA NA NA AmrcnOR> # simple call with unnamed parameters, using Crank-Nicolons AmrcnOR> AmericanOption("put", strike=100, volatility=0.4, 100, 0.02, 0.03, 0.5, engine="CrankNicolson") Concise summary of valuation for AmericanOption value delta gamma vega theta rho divRho 10.9173 -0.4358 0.0140 NA NA NA NA R>

Thanks to CRANberries, there is also a diff to the previous release 0.3.8. Full changelog details, examples and more details about this package are at my RQuantLib page.

To

**leave a comment**for the author, please follow the link and comment on their blog:**Thinking inside the box**.R-bloggers.com offers

**daily e-mail updates**about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.