tidyquant v0.5.1

0

Monthly downloads

0th

Percentile

by Matt Dancho

Tidy Quantitative Financial Analysis

Bringing financial analysis to the 'tidyverse'. The 'tidyquant' package provides a convenient wrapper to various 'xts', 'zoo', 'quantmod', 'TTR' and 'PerformanceAnalytics' package functions and returns the objects in the tidy 'tibble' format. The main advantage is being able to use quantitative functions with the 'tidyverse' functions including 'purrr', 'dplyr', 'tidyr', 'ggplot2', 'lubridate', etc. See the 'tidyquant' website for more information, documentation and examples.

Readme

tidyquant

Travis-CI Build Status codecov CRAN\_Status\_Badge

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.

Benefits

  • 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!

One-Stop Shop for Serious Financial Analysis

With tidyquant all the benefits add up to one thing: a one-stop shop for serious financial analysis!

Core Functions

  • 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.

Comparing Stock Prices

Visualizing the stock price volatility of four stocks side-by-side is quick and easy...

Evaluating Stock Performance

What about stock performance? Quickly visualize how a $10,000 investment in various stocks would perform.

Evaluating Portfolio Performance

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.

Installation

Development Version with Latest Features:

# install.packages("devtools")
devtools::install_github("business-science/tidyquant")

CRAN Approved Version:

install.packages("tidyquant")

Further Information

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.

Functions in tidyquant

Name Description
palette_tq tidyquant palettes for use with scales
quandl_api_key Query or set Quandl API Key
as_xts Coerce objects to xts, designed to work with tibble and data.frame objects
coord_x_date Zoom in on plot regions using date ranges or date-time ranges
geom_chart Plot Financial Charts in ggplot2
geom_ma Plot moving averages
FANG Stock prices for the "FANG" stocks.
as_tibble Coerce to tibble. Enable preserving row names when coercing matrix
deprecated Deprecated functions
geom_bbands Plot Bollinger Bands using Moving Averages
tq_index Get all stocks in a stock index or stock exchange in
tq_get Get quantitative data in
tq_mutate Mutates quantitative data
tq_performance Computes a wide variety of summary performance metrics from stock or portfolio returns
tq_portfolio Aggregates a group of returns by asset into portfolio returns
theme_tq tidyquant themes for ggplot2.
tidyquant tidyquant: Integrating quantitative financial analysis tools with the tidyverse
quandl_search Search the Quandl database
scale_manual tidyquant colors and fills for ggplot2.
No Results!

Last month downloads

Details

Include our badge in your README

[![Rdoc](http://www.rdocumentation.org/badges/version/tidyquant)](http://www.rdocumentation.org/packages/tidyquant)