tidyquant.Rmd

# Stock data with tidyquant {#tidyquant}

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*This chapter originated as a community contribution created by [	naotominakawa](https://github.com/naotominakawa){target="_blank"}*

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```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

## Overview
This section covers how to use the `tidyquant` package to conduct timeseries analysis.

## What is tidyquant?

`tidyquant` is an one-stop shop for financial analysis. It is suitable for analyzing timeseries data, such as financial and economic data. `tidyquant` connects to various data sources such as Yahoo! Finance, Morning Star, Bloomberg market data, etc. It also behaves well with other `Tidyverse` packages.

## Installing tidyquant
You can install **tidyquant** from CRAN:

```
install.packages("tidyquant")
```

If you want to see which functions are available, you can run the following:
```{r, eval = FALSE}
# to see which functions are available (not run)
library(tidyquant)
tq_transmute_fun_options()
```

## Single timeseries
Obtain historical data for single stock (for example, Google):
```{r, message=FALSE}
# get historical data for single stock. e.g. google
library(tidyquant)
tq_get("GOOGL", get="stock.prices")
```

Calculate monthly return of single stock:
```{r, message = FALSE}
library(dplyr)
# calculate monthly return of single stock
tq_get(c("GOOGL"), get="stock.prices") %>%
  tq_transmute(select=adjusted,
               mutate_fun=periodReturn,
               period="monthly",
               col_rename = "monthly_return")
```

Create a line chart of the *closing price* for single stock:
```{r, message=FALSE}
# showing closing price for single stock
library(ggplot2)
tq_get(c("GOOGL"), get="stock.prices") %>%
  ggplot(aes(date, close)) +
  geom_line()
```

Create a line chart of the *monthly return* for single stock:
```{r}
# showing monthly return for single stock
tq_get(c("GOOGL"), get="stock.prices") %>%
  tq_transmute(select=adjusted,
               mutate_fun=periodReturn,
               period="monthly",
               col_rename = "monthly_return") %>%
  ggplot(aes(date, monthly_return)) +
  geom_line()
```

## Multiple timeseries
Obtain historical data for multiple stocks (for example, GAFA):
```{r}
# get historical data for multiple stocks. e.g. GAFA
tq_get(c("GOOGL","AMZN","FB","AAPL"), get="stock.prices")
```

Create a multiple line chart of the closing prices of multiple stocks (again, GAFA). We can show each stock in a different color on the same graph:
```{r}
# Create a multiple line chart of the closing prices of the four stocks,
# showing each stock in a different color on the same graph.
tq_get(c("GOOGL","AMZN","FB","AAPL"), get="stock.prices") %>%
  ggplot(aes(date, close, color=symbol)) +
  geom_line()
```

Transform the data so each stock begins at 100 and replot (Standardize the data so that we can compare timeseries):
```{r}
# Create a multiple line chart of the closing prices of the four stocks,
# showing each stock in a different color on the same graph.
# Transform the data so each stock begins at 100 and replot.
tq_get(c("GOOGL","AMZN","FB","AAPL"), get="stock.prices") %>%
  group_by(symbol) %>%
  mutate(close = 100*close/first(close)) %>%
  ggplot(aes(date, close, color=symbol)) +
  geom_line()
```

Calculate *monthly return* of multiple stocks (again, GAFA):
```{r}
# calculate monthly return of multiple stocks
tq_get(c("GOOGL","AMZN","FB","AAPL"), get="stock.prices") %>%
  group_by(symbol) %>%
  tq_transmute(select=adjusted,
               mutate_fun=periodReturn,
               period="monthly",
               col_rename = "monthly_return")
```

Create a multiple line chart of monthly return of the four stocks. Again, we can show each stock in a different color on the same graph:
```{r}
# Create a multiple line chart of monthly return of the four stocks,
# showing each stock in a different color on the same graph
tq_get(c("GOOGL","AMZN","FB","AAPL"), get="stock.prices") %>%
  group_by(symbol) %>%
  tq_transmute(select=adjusted,
               mutate_fun=periodReturn,
               period="monthly",
               col_rename = "monthly_return") %>%
  ggplot(aes(date, monthly_return, color=symbol)) +
  geom_line()
```

## External Resources
- [tidyquant CRAN doc](https://cran.r-project.org/web/packages/tidyquant/vignettes/TQ00-introduction-to-tidyquant.html){target="_blank"}: formal documentation on the package
- [tidyquant Github repo](https://github.com/business-science/tidyquant){target="_blank"}: Github repository for the `tidyquant` package with a great README