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https://github.com/business-science/tidyquant

Bringing financial analysis to the tidyverse
https://github.com/business-science/tidyquant

dplyr financial-analysis financial-data financial-statements multiple-stocks performance-analysis performanceanalytics quantmod r-package stock stock-exchanges stock-indexes stock-lists stock-performance stock-prices stock-symbol tidyverse time-series timeseries xts

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Bringing financial analysis to the tidyverse

Awesome Lists containing this project

README 

        
---

output: github_document

---



```{r, echo = FALSE, message = FALSE, warning=F}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "man/figures/README-",

  out.width = "100%",

  dpi = 300,

  message = F,

  warning = F

)

```



# tidyquant 



[![R-CMD-check](https://github.com/business-science/tidyquant/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/business-science/tidyquant/actions/workflows/R-CMD-check.yaml)

[![Codecov](https://codecov.io/gh/business-science/tidyquant/branch/master/graph/badge.svg)](https://app.codecov.io/gh/business-science/tidyquant)

[![CRAN_Status_Badge](http://www.r-pkg.org/badges/version/tidyquant)](https://cran.r-project.org/package=tidyquant)

![](http://cranlogs.r-pkg.org/badges/tidyquant?color=brightgreen)

![](http://cranlogs.r-pkg.org/badges/grand-total/tidyquant?color=brightgreen)



> Bringing financial and business analysis to the `tidyverse` in R.



Mission: Our number 1 goal is to make financial analysis easier in R. We've designed `tidyquant` to give you the flexibility of the tidyverse with the performance of the R `xts` system. The result: easier, faster, and more scalable financial analysis. 



## Start: 2-Minutes To tidyquant



Our short introduction to `tidyquant` on

[YouTube](https://www.youtube.com/embed/woxJZTL2hok).



Anomalize



# Features of tidyquant



`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 `tidyverse` tools in [_R for Data Science_](https://r4ds.hadley.nz/)__

* __Implements `ggplot2` functionality for beautiful and meaningful financial visualizations__

* __User-friendly documentation to get you up to speed quickly!__



### New Excel Functionality in tidyquant 



 - [__Excel in R - Pivot Tables, VLOOKUPs, and more__](https://www.business-science.io/finance/2020/02/26/r-for-excel-users.html): Details on the __Excel integrations__ are covered in the blog article.



## 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.  



* __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...



```{r echo=FALSE, out.width='100%'}

knitr::include_graphics("man/figures/sample_img_1_volatility.png")

```



### Evaluating Stock Performance



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



```{r echo=FALSE, out.width='100%'}

knitr::include_graphics("man/figures/sample_img_2_stock_returns.png")

```



### 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



```{r echo=FALSE, out.width='100%'}

knitr::include_graphics("man/figures/sample_img_3_portfolio_returns.png")

```



This just scratches the surface of `tidyquant`. Here's how to install to get started.



## Installation



Development Version with Latest Features:



``` {r, eval = FALSE}

# install.packages("devtools")

devtools::install_github("business-science/tidyquant")

```



CRAN Approved Version: 



```{r, eval = FALSE}

install.packages("tidyquant")

```



## Further Information



The `tidyquant` package includes several vignettes to help users get up to speed quickly:



* [TQ00 - Introduction to `tidyquant`](https://business-science.github.io/tidyquant/articles/TQ00-introduction-to-tidyquant.html)

* [TQ01 - Core Functions in `tidyquant`](https://business-science.github.io/tidyquant/articles/TQ01-core-functions-in-tidyquant.html)

* [TQ02 - R Quantitative Analysis Package Integrations in `tidyquant`](https://business-science.github.io/tidyquant/articles/TQ02-quant-integrations-in-tidyquant.html)

* [TQ03 - Scaling and Modeling with `tidyquant`](https://business-science.github.io/tidyquant/articles/TQ03-scaling-and-modeling-with-tidyquant.html)

* [TQ04 - Charting with `tidyquant`](https://business-science.github.io/tidyquant/articles/TQ04-charting-with-tidyquant.html)

* [TQ05 - Performance Analysis with `tidyquant`](https://business-science.github.io/tidyquant/articles/TQ05-performance-analysis-with-tidyquant.html)

* [Blog Article: Excel in R - Pivot Tables, VLOOKUPs, and more!](https://www.business-science.io/finance/2020/02/26/r-for-excel-users.html)



# Want to Learn tidyquant?



- [Learning Lab #9:](https://university.business-science.io/p/learning-labs-pro) 

  

  - __Performance Analysis & Portfolio Optimization with `tidyquant`__ - A 1-hour course on `tidyquant` in Learning Labs PRO



- [Learning Lab #10:](https://university.business-science.io/p/learning-labs-pro) 

  

  - __Building an API with `plumber`__ - Build a stock optimization API with `plumber` and `tidyquant`

  

- [Learning Lab #16:](https://university.business-science.io/p/learning-labs-pro) 

  

  - __Stock Portfolio Optimization and Nonlinear Programming__ - Use the `ROI` package with `tidyquant` to calculate optimal minimum variance portfolios and develop an efficient frontier.  

  

- [Learning Lab #30:](https://university.business-science.io/courses/learning-labs-pro/lectures/14630075)

  - __Shiny Financial Analysis with Tidyquant API & Excel Pivot Tables__ - Learn how to use the new Excel Functionality to make Pivot Tables, VLOOKUPs, Sum-If's, and more!