https://github.com/cran/quantmod
Raw File
Tip revision: 1a9fc92bc6e0ae299209a23b446a37c48e5d3272 authored by Jeffrey A. Ryan on 07 January 2008, 00:00:00 UTC
version 0.3-1
Tip revision: 1a9fc92
WISHLIST
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quantmod wishlist: as of Jan 8, 2008

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  - Documentation (web and vignettes) :
    1. charting and indicator overlays!
    2. building models
    3. testing models
    4. extending quantmod
    5. package/inteface preferences
  
  - Move to R-forge for devel tools
  
  - getSymbols.skeleton, buildModel.skeleton, addTA.skeleton

  - convert to xts from zoo throughout.  Simplify data methods
  
  - try to remove dependence on fSeries and its (etc).  Through 'xts'???

FUNCTIONALITY:

  - getFundamentals.google and getFundamentals to download data
    from google.  Possibly add arbitrary downloads from finance.yahoo.com
    using http://www.gummy-stuff.org/Yahoo-data.htm formats

  - tradeRule and tradeLog

  - move all quantmod.OHLC to c('OHLC','xts','zoo') format - eventually move
    to new package all together


CHARTS:

  - add addHolidays/Weekends function to add in missing data with NA

  - liveChart function - used in conjunction with RT data feeds

  - dropTA function to remove TA indicators applied

  - add subset argument to chartSeries (et al) and buildModel function to pass
    along to underlying [.xts method

  - mask lagged indicator days - use full dataset for calculation and a
    seperate subset for actual plotting.  (using above [.xts method)

  - multiple series in one line chart, or in one window - possibly
    mchartSeries, mbarChart, mlineChart, mcandleChart plus multiple
    series normal command interpretation

  - HSV color schemes from vcd or colorbrewer

  - finish TA integration with TTR

  - additional charting tools, like seriesHi, seriesLo, lines, points,...

  - allow for indicators to be drawn under series - BBands, Envelopes...

  - performance charts:
    - periodReturn
    - modelResults
    - integrate with PerformanceAnalytics

TESTING:

  - regression testing suite, via RUnit.  See RQuantLib.
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