I am happy to announce a long-overdue update to the TTR package (version 0.2) is now on CRAN.
This update represents a major milestone, as TTR useRs are no longer restricted to using matrix objects. TTR 0.2 uses xts internally, so all major time series classes are now supported.
- Added the zig zag indicator:
- Added volatility estimators/indicators:
volatility(), with the following calculations
- Garman Klass
- Rogers Satchell
- Added Money Flow Index:
- Added Donchian channel:
- All functions now use xts internally, adding support for all major time series classes. If
try.xts()fails on the input object(s), they will be converted to a matrix and a matrix object will be returned.
SMI(), which includes the current period in the calculation.
naCheck()and implemented it in the moving average functions.
maTypeargument default values from function formals to function body for the following functions:
CMO()no longer sets
TDI(), allowing more user control
getYahooData()now returns an xts object
- Added colnames to output for
- Added unit tests using the RUnit package
checkEquals()on object attributes as well as values
.First.libfunction and added
.onLoad()with package version.
- Corrected NaN replacement in
williamsAD(): AD=0 if C(t)=C(t-1)
runMAD(). The argument controlling which type of median to calculate for even-numbered samples wasn’t being passed to the Fortran routine.
aroon()calculation starts at period
n+1, instead of
NAto first element of
rowMeans()use on xts objects
- Made changes to Rd files to pass
R CMD checkon R-devel (2.9.0)
Please do contact me with any questions, concerns, bug reports, etc.
If you love using my open-source work (e.g. quantmod, TTR, xts, IBrokers, microbenchmark, etc.), you can give back by sponsoring me on GitHub. I truly appreciate anything you’re willing and able to give!
I look forward to your questions and feedback! If you have a question, please ask on Stack Overflow and use the [r] and [ttr] tags. Or you can send an email to the R-SIG-Finance mailing list (you must subscribe to post). Open an issue on GitHub if you find a bug or want to request a feature. Please read the contributing guide first! It will help save time for both of us. ;-)