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 now PerformanceAnalytics
• 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() and tq_mutate(). Integration for many financial functions from xts, zoo, quantmod,TTR and PerformanceAnalytics packages. 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.

• Coercing Data To and From xts and tibble: as_tibble()and as_xts(). There are a ton of Stack Overflow articles on converting data frames to and from xts. These two functions can be used to answer 99% of these questions.

• Performance Analysis and Portfolio Analysis: tq_performance() and tq_portfolio(). The newest additions to the tidyquant family integrate PerformanceAnalytics 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.