Bringing financial and business analysis to the tidyverse
Our short introduction to
tidyquant integrates the best resources for collecting and analyzing
PerformanceAnalytics, with the tidy data infrastructure of the
tidyverse allowing for seamless interaction between each. You can now
perform complete financial analyses in the
TTR, and now
tidyversetools in R for Data Science
ggplot2functionality for beautiful and meaningful financial visualizations
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:
Integration for many financial functions from
is used to add a column to the data frame, and
used to return a new data frame which is necessary for periodicity
Performance Analysis and Portfolio Analysis:
tq_portfolio(). The newest additions to the
tq_performance() converts investment returns into performance
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
This just scratches the surface of
tidyquant. Here’s how to install to
Development Version with Latest Features:
# install.packages("devtools") devtools::install_github("business-science/tidyquant")
CRAN Approved Version:
tidyquant package includes several vignettes to help users get up
to speed quickly:
tidyquant- A 1-hour course on
tidyquantin Learning Labs PRO
plumber- Build a stock optimization API with
tidyquantto calculate optimal minimum variance portfolios and develop an efficient frontier.
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