The goal of rwRtools is to make it easy to access The Lab’s datasets and get started with research.

The Lab is Robot Wealth’s portal for collaborative research.

It is organized around Research Pods, which contain data, ideas, research and peer-reviewed edges for a given market question.

For example:

• in the Equity Factor Research Pod we look at the question: "What factors predict the relative performance of stocks in the Russell 1000 index?"
• In the Global Risk Premia Research Pod we look at the question: “What is the most effective way to get paid for taking on global market risks?”

The Lab serves three purposes:

1. It gets you hands-on with the research effort. As well as contributing, you’ll learn a ton in the process.
2. It scales the research effort by enabling community contribution.
3. It makes the fruits of that scaled research effort available to the entire Robot Wealth community.

The easiest way to install and load rwRtools and its dependencies is via the pacman library:

if(!require("pacman")) install.packages("pacman")
#> Loading required package: pacman
pacman::p_load_current_gh("RWLab/rwRtools", dependencies = TRUE)
#> tibble (3.0.3 -> 3.0.4) [CRAN]
#> package 'tibble' successfully unpacked and MD5 sums checked
#> 
#> The downloaded binary packages are in
#>  C:\Users\Kris\AppData\Local\Temp\RtmpKurQPb\downloaded_packages
#>          checking for file 'C:\Users\Kris\AppData\Local\Temp\RtmpKurQPb\remotes7d6017485573\RWLab-rwRtools-3fc66b9/DESCRIPTION' ...  v  checking for file 'C:\Users\Kris\AppData\Local\Temp\RtmpKurQPb\remotes7d6017485573\RWLab-rwRtools-3fc66b9/DESCRIPTION' (489ms)
#>       -  preparing 'rwRtools':
#>    checking DESCRIPTION meta-information ...     checking DESCRIPTION meta-information ...   v  checking DESCRIPTION meta-information
#>       -  checking for LF line-endings in source and make files and shell scripts
#>       -  checking for empty or unneeded directories
#>       -  building 'rwRtools_0.0.0.9001.tar.gz'
#>      
#> 

After installing and loading rwRtools, the quickest way to set up a session for working on a particular Research Pod is:

rwlab_data_auth(oauth_email = "[email protected]")

oauth_email is the email address you use to log in to Robot Wealth’s resources.

If called in an interactive session, you will be prompted in a browser to select a Google Identity and copy and paste an authentication code back at the call site.

list_pods()
#> [1] "EquityFactors"

This transfers price data from the data library to path and loads it into the Global Environment as the prices object.

IMPORTANT: It overwrites any object you might have in your Global Environment with that variable name, or locally at path with the Research Pod prices file name.

Requires that you have authorised to the data library prior.

quicksetup(pod = "EquityFactors", path = ".")

prices %>% 
  head()

This transfers the essential data that you always need to path (ohlc, metadata), overwriting any existing local Pod objects.

Requires that you’ve already authorised to the relevant GCS bucket.

get_pod_meta(pod = "EquityFactors")
#> $bucket
#> [1] "equity_factors_research_pod"
#> 
#> $datasets
#> [1] "R1000_ohlc_1d.feather"         "R1000_fundamentals_1d.feather"
#> 
#> $essentials
#> [1] "R1000_ohlc_1d.feather"
#> 
#> $prices
#> [1] "R1000_ohlc_1d.feather"

This outputs a list of all the data objects you can transfer for a Pod.

load_lab_object(pod = "EquityFactors", object = "R1000_ohlc_1d.feather", path = ".")

This transfers a specifc object to path, overwriting any existing local instance of that object.

Requires that you’ve already authorised to the relevant data library

See the examples for more.