Code Along 4: Reproducible Finance with R, Chapter 2

Import Stock Prices, Convert to Returns, Plot Returns

Step 1: Import Stock Prices

library(tidyverse)

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library(tidyquant)

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symbols <- c("SPY", "EFA", "IJS", "EEM", "AGG")

prices <- tq_get(
  x    = symbols,
  get  = "stock.prices",
  from = "2012-01-01",
  to   = "2017-01-01"
)

prices

## # A tibble: 6,290 × 8
##    symbol date        open  high   low close    volume adjusted
##    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>    <dbl>
##  1 SPY    2012-01-03  128.  128.  127.  128. 193697900     98.8
##  2 SPY    2012-01-04  127.  128.  127.  128. 127186500     99.0
##  3 SPY    2012-01-05  127.  128.  126.  128. 173895000     99.2
##  4 SPY    2012-01-06  128.  128.  127.  128. 148050000     99.0
##  5 SPY    2012-01-09  128   128.  127.  128.  99530200     99.2
##  6 SPY    2012-01-10  129.  130.  129.  129. 115282000    100. 
##  7 SPY    2012-01-11  129.  129.  129.  129. 111540700    100. 
##  8 SPY    2012-01-12  130.  130.  129.  130. 118983700    100. 
##  9 SPY    2012-01-13  129.  129.  128.  129. 179836200     99.9
## 10 SPY    2012-01-17  130.  130.  129.  129. 132209200    100. 
## # ℹ 6,280 more rows

Step 2: Convert Prices to Returns

asset_returns_tbl <- prices %>%
  group_by(symbol) %>%
  tq_transmute(
    select     = adjusted,
    mutate_fun = periodReturn,
    period     = "monthly",
    type       = "log"
  ) %>%
  set_names(c("asset", "date", "returns")) %>%
  ungroup()

asset_returns_tbl

## # A tibble: 300 × 3
##    asset date        returns
##    <chr> <date>        <dbl>
##  1 SPY   2012-01-31  0.0295 
##  2 SPY   2012-02-29  0.0425 
##  3 SPY   2012-03-30  0.0317 
##  4 SPY   2012-04-30 -0.00670
##  5 SPY   2012-05-31 -0.0619 
##  6 SPY   2012-06-29  0.0398 
##  7 SPY   2012-07-31  0.0118 
##  8 SPY   2012-08-31  0.0247 
##  9 SPY   2012-09-28  0.0250 
## 10 SPY   2012-10-31 -0.0184 
## # ℹ 290 more rows

Step 3: Plot Returns

asset_returns_tbl %>%
  ggplot(aes(x = returns)) +
  geom_histogram(aes(fill = asset), binwidth = 0.01, alpha = 0.3, show.legend = FALSE) +
  geom_density(aes(color = asset), show.legend = FALSE) +
  facet_wrap(~asset, ncol = 1) +
  labs(
    title    = "Distribution of Monthly Returns, 2012–2016",
    x        = "Monthly Returns",
    y        = "Frequency",
    caption  = "Monthly return is higher for SPY and IJS than for AGG and EEM."
  )