Bringing financial analysis to the tidyverse
tidyquant
integrates the best resources for collecting and analyzing financial data, zoo
, xts
, quantmod
, TTR
, and PerformanceAnalytics
, with the tidy data infrastructure of the tidyverse
allowing for seamless interaction between each. You can now perform complete financial analyses in the tidyverse
.
- A few core functions with a lot of power
- Integrates the quantitative analysis functionality of
zoo
,xts
,quantmod
,TTR
, and nowPerformanceAnalytics
- Designed for modeling and scaling analyses using the the
tidyverse
tools in R for Data Science - Implements
ggplot2
functionality for beautiful and meaningful financial visualizations - User-friendly documentation to get you up to speed quickly!
With tidyquant
all the benefits add up to one thing: a one-stop shop for serious financial analysis!
-
Getting Financial Data from the web:
tq_get()
. This is a one-stop shop for getting web-based financial data in a "tidy" data frame format. Get data for daily stock prices (historical), key statistics (real-time), key ratios (historical), financial statements, dividends, splits, economic data from the FRED, FOREX rates from Oanda. -
Manipulating Financial Data:
tq_transmute()
andtq_mutate()
. Integration for many financial functions fromxts
,zoo
,quantmod
,TTR
andPerformanceAnalytics
packages.tq_mutate()
is used to add a column to the data frame, andtq_transmute()
is used to return a new data frame which is necessary for periodicity changes. -
Performance Analysis and Portfolio Analysis:
tq_performance()
andtq_portfolio()
. The newest additions to thetidyquant
family integratePerformanceAnalytics
functions.tq_performance()
converts investment returns into performance metrics.tq_portfolio()
aggregates a group (or multiple groups) of asset returns into one or more portfolios.
Visualizing the stock price volatility of four stocks side-by-side is quick and easy...
What about stock performance? Quickly visualize how a $10,000 investment in various stocks would perform.
Ok, stocks are too easy. What about portfolios? With the PerformanceAnalytics
integration, visualizing blended portfolios are easy too!
- Portfolio 1: 50% FB, 25% AMZN, 25% NFLX, 0% GOOG
- Portfolio 2: 0% FB, 50% AMZN, 25% NFLX, 25% GOOG
- Portfolio 3: 25% FB, 0% AMZN, 50% NFLX, 25% GOOG
- Portfolio 4: 25% FB, 25% AMZN, 0% NFLX, 50% GOOG
This just scratches the surface of tidyquant
. Here's how to install to get started.
Development Version with Latest Features:
# install.packages("devtools")
devtools::install_github("business-science/tidyquant")
CRAN Approved Version:
install.packages("tidyquant")
The tidyquant
package includes several vignettes to help users get up to speed quickly:
- TQ00 - Introduction to
tidyquant
- TQ01 - Core Functions in
tidyquant
- TQ02 - R Quantitative Analysis Package Integrations in
tidyquant
- TQ03 - Scaling and Modeling with
tidyquant
- TQ04 - Charting with
tidyquant
- TQ05 - Performance Analysis with
tidyquant
See the tidyquant
vignettes for further details on the package.