Week 5: Code along 4

CHAPTER 2 Returns: ASSET PRICES TO RETURNS

# Load packages

# Core
library(tidyverse)

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ ggplot2   3.5.2     ✔ tibble    3.3.0
## ✔ lubridate 1.9.4     ✔ tidyr     1.3.1
## ✔ purrr     1.1.0     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(tidyquant)

## Registered S3 method overwritten by 'quantmod':
##   method            from
##   as.zoo.data.frame zoo 
## ── Attaching core tidyquant packages ─────────────────────── tidyquant 1.0.11 ──
## ✔ PerformanceAnalytics 2.0.8      ✔ TTR                  0.24.4
## ✔ quantmod             0.4.28     ✔ xts                  0.14.1── Conflicts ────────────────────────────────────────── tidyquant_conflicts() ──
## ✖ zoo::as.Date()                 masks base::as.Date()
## ✖ zoo::as.Date.numeric()         masks base::as.Date.numeric()
## ✖ dplyr::filter()                masks stats::filter()
## ✖ xts::first()                   masks dplyr::first()
## ✖ dplyr::lag()                   masks stats::lag()
## ✖ xts::last()                    masks dplyr::last()
## ✖ PerformanceAnalytics::legend() masks graphics::legend()
## ✖ quantmod::summary()            masks base::summary()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

Goal

Take raw prices of five individual stocks and transform them into monthly returns five stocks: “SPY”, “EFA”, “IJS”, “EEM”, “AGG”

1 Import stock prices

# Choose stocks

symbols <- c("SPY", "PPTA", "NVDA", "IBM", "TSLA")

# Using tq_get() ----
prices <- tq_get(x = symbols,
                 get = "stock.prices",
                 from = "2015-12-31",
                 to = "2019-12-31")

## Warning: There was 1 warning in `dplyr::mutate()`.
## ℹ In argument: `data.. = purrr::map(...)`.
## Caused by warning:
## ! x = 'PPTA', get = 'stock.prices': Error in getSymbols.yahoo(Symbols = "PPTA", env = <environment>, verbose = FALSE, : Unable to import "PPTA".
## cannot open the connection
##  Removing PPTA.

2 Convert prices to returns

asset_returns_tbl <- prices %>%

    # Calculate monthly returns
    group_by(symbol) %>%
    tq_transmute(select = adjusted,
                 mutate_fun = periodReturn,
                 period = "monthly",
                 type = "log") %>%
    slice(-1) %>%
    ungroup() %>%

    # remane
    set_names(c("asset", "date", "returns"))

# period_returns = c("yearly", "quarterly", "monthly", "weekly")

## 3 Make plot

``` r
asset_returns_tbl %>%

    ggplot(aes(x = returns)) +
    geom_density(aes(col = asset), alpha = 1, show.legend = FALSE) +
    geom_histogram(aes(fill = asset), alpha = 0.45, binwidth = 0.01) +
    facet_wrap(~asset, ncol = 1, scales = "free_y") +
    guides(fill = "none") +

    labs(title = "Monthly Returns since 2013",
         x = "distribution",
         y = "monthly returns") +
    theme_update(plot.title = element_text(hjust = 0.5))

```