A new release of quantmod is now on CRAN! The only change was to address changes to Yahoo! Finance and their effects on getSymbols.yahoo(). GitHub issue #157 contains some details about the fix implementation. Unfortunately, the URL wasn’t the only thing that changed. The actual data available for download changed as well. The most noticeable difference is that the adjusted close column is no longer dividend-adjusted (i.e. it’s only split-adjusted). Also, only the close price is unadjusted; the open, high, and low are split-adjusted.
I pushed a bug-fix release of quantmod to CRAN last night. The major changes were to getSymbols.FRED() (#141) getSymbols.oanda() (#144) getSymbols.yahoo() (#149) All three providers made breaking changes to their URLs/interfaces. getSymbols.google() also got some love. It now honors all arguments set via setSymbolLookup() (#138), and it correctly parses the date column in non-English locales (#140). There’s a handy new argument to getDividends(): split.adjust. It allows you to request dividends unadjusted for splits (#128).
CRAN just accepted a bugfix release of quantmod. The most pertinent changes were to fix getSymbols.oanda (#36) and getOptionChain.yahoo (#92). It also includes a fix to addTRIX (#72). Oanda changed their URL format from http to https, and getSymbols.oanda did not follow the redirect. Yahoo Finance changed the HTML for displaying options data, which broke getOptionChain.yahoo. The fix downloads JSON instead of scraping HTML, so hopefully it will be less likely to break.
I just sent quantmod_0.4-5 to CRAN, and TTR_0.23-0 has been there for a couple weeks. I’d like to thank Ivan Popivanov for many useful reports and patches to TTR. He provided patches to add HMA() (Hull MA), ALMA(), and ultimateOscillator() functions. James Toll provided a patch to the volatility() function that uses a zero mean (instead of the sample mean) in close-to-close volatility. The other big change is that moving average functions no longer return objects with column names based on the input object column names.
We have been working on a new charting engine for xts::plot.xts for the past couple years. It started with Michael Weylandt’s work during the 2012 Google Summer of Code, and Ross Bennett took up the torch during the 2014 GSoC. This new engine improves the functionality, modularity, and flexibility of plot.xts by building off the framework Jeff Ryan began with quantmod::chart_Series. The modular framework allows users to plot an xts object and incrementally build custom charts by adding panels of new data (including transformations of the original xts object).
I pushed quantmod 0.4-4 to CRAN this weekend. It adds a getSymbols.yahooj function to pull stock data from Yahoo Finance Japan, and fixes issues in getOptionChain.yahoo and getSymbols.oanda. Changes to the Yahoo Finance and Oanda websites broke the getOptionChain.yahoo and getSymbols.oanda functions, respectively. I didn’t use getOptionChain.yahoo much, so I’m not certain I restored all the prior functionality. Let me know if there’s something I missed. I’d be glad to add a test case for that, or to add a test you’ve written.
An updated version of quantmod has just been released on CRAN. This is my first submission as the new maintainer. The major change was removing the dependency on the now-archived Defaults package. End-users shouldn’t notice a difference, since I basically copied the necessary functionality from Defaults and added it to quantmod. There are also several bug fixes. A few worth noting are: getSplits adjustOHLC getSymbols (when adjust=TRUE) saveSymbols newTA findValleys
An updated version of TTR is now on CRAN. The biggest changes to be aware of are that all moving averages attempt to set colnames, CCI() returns an object with colnames, and the initial gap for SAR() is not hard-coded at 0.01. There are also some much-needed bug fixes - most notably to Yang Zhang volatility, MACD(), SAR(), EMA()/EVWMA(), and adjRatios(). There are some exciting new features, including a rolling single-factor model function (rollSFM(), based on a prototype from James Toll), a runPercentRank() function from Charlie Friedemann, stoch() and WPR() return 0.
Running DEoptim in parallel has been on the development team’s wishlist for awhile. It had not been a priority though, because none of us have personally needed it. An opportunity arose when Kris Boudt approached me about collaborating to add this functionality as part of a consultancy project for a financial services firm. We were able to add and test the functionality within a week. The latest revision of DEoptim on R-Forge has the capability to evaluate the objective function on multiple cores using foreach.
An updated version of TTR is now on CRAN. It contains some much-needed bug fixes (most notably to stockSymbols()), some small changes, and a few new functions. Note that the change to wilderSum() will affect functions that use it (e.g. ADX()). Here are the full contents of the CHANGES file: TTR version 0.21-0 Changes from version 0.20-2 NEW FEATURES: Added variable moving average function, VMA(). Added Brian Peterson’s price bands function, PBands().