About

TTR is an R package that provides the most popular technical analysis functions for financial market data. Many of these functions are used as components of systematic trading strategies and financial charts.

TTR for enterprise

Available as part of the Tidelift Subscription.

The maintainers of TTR and thousands of other packages are working with Tidelift to deliver commercial support and maintenance for the open source dependencies you use to build your applications. Save time, reduce risk, and improve code health, while paying the maintainers of the exact dependencies you use. Learn more.

Supporting TTR development

If you are interested in supporting the ongoing development and maintenance of TTR, please consider becoming a sponsor.

Installation

The current release is available on CRAN, which you can install via:

install.packages("TTR")

To install the development version, you need to clone the repository and build from source, or run one of:

# lightweight
remotes::install_github("joshuaulrich/TTR")
# or
devtools::install_github("joshuaulrich/TTR")

You will need tools to compile C, C++, and Fortran code. See the relevant appendix in the R Installation and Administration manual for your operating system:

• Windows
• MacOS (the R for Mac OS X Developer's Page might also be helpful)
• Unix-alike

Getting Started

Here are a few examples of some of the more well-known indicators:

# "TTR Composite" (simulated data)
data(ttrc)

# Bollinger Bands
bbands <- BBands( ttrc[,c("High","Low","Close")] )

# Directional Movement Index
adx <- ADX(ttrc[,c("High","Low","Close")])

# Moving Averages
ema <- EMA(ttrc[,"Close"], n=20)
sma <- SMA(ttrc[,"Close"], n=20)

# MACD
macd <- MACD( ttrc[,"Close"] )

# RSI
rsi <- RSI(ttrc[,"Close"])

# Stochastics
stochOsc <- stoch(ttrc[,c("High","Low","Close")])

TTR works with the chartSeries() function in quantmod. Here's an example that uses chartSeries() and adds TTR-calculated indicators and overlays to the chart.

# "TTR Composite" (simulated data)
data(ttrc)

# Use quantmod's OHLCV extractor function to help create an xts object
xttrc <- xts(OHLCV(ttrc), ttrc[["Date"]])

chartSeries(xttrc, subset = "2006-09/", theme = "white")
addBBands()
addRSI()

Have a question?

Ask your question on Stack Overflow or the R-SIG-Finance mailing list (you must subscribe to post).

Contributing

Please see the Contributing Guide.

See Also

• quantmod: quantitative financial modeling framework
• xts: eXtensible Time Series based

on zoo

Author

Joshua Ulrich