Bringing financial and business analysis to the tidyverse
Our short introduction to
tidyquant on YouTube.
tidyquant integrates the best resources for collecting and analyzing financial data,
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 1.0.0 is the “R for Excel Users” release. My aim is to build functionality that helps users coming from an Excel Background (background I came from). It’s important to have these users feel at home. I have a full suite of functionality to accomplish your Excel-to-R transition.
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_mutate(). Integration for many financial functions from
tq_mutate() is used to add a column to the data frame, and
tq_transmute() is used to return a new data frame which is necessary for periodicity changes.
Performance Analysis and Portfolio Analysis:
tq_portfolio(). The newest additions to the
tidyquant family integrate
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!
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:
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.