# Load packages

# Core
library(tidyverse)
library(tidyquant)

Goal

Collect individual returns into a portfolio by assigning a weight to each stock

five stocks: “SPY”, “EFA”, “IJS”, “EEM”, “AGG”

from 2012-12-31 to 2017-12-31

1 Import stock prices

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

prices <- tq_get(x = symbols,
                 from = "2012-12-31",
                 to = "2017-12-31")

2 Convert prices to returns

asset_returns_tbl <- prices %>%
  
  group_by(symbol) %>%
  
  tq_transmute(select = adjusted,
               mutate_fun = periodReturn,
               period = "monthly",
               type = "log") %>%
  
  slice(-1) %>%
  
  ungroup() %>%

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

3 Assign a weight to each asset

#symbols
symbols <- asset_returns_tbl %>% distinct(asset) %>% pull()
symbols
## [1] "AGG" "EEM" "EFA" "IJS" "SPY"
#weights
weights <- c(0.25, 0.25, 0.2, 0.2, 0.1)
weights
## [1] 0.25 0.25 0.20 0.20 0.10
w_tbl <- tibble(symbols, weights)
w_tbl
## # A tibble: 5 × 2
##   symbols weights
##   <chr>     <dbl>
## 1 AGG        0.25
## 2 EEM        0.25
## 3 EFA        0.2 
## 4 IJS        0.2 
## 5 SPY        0.1

4 Build a portfolio

# ?tq_portfolio

portfolio_returns_tbl <- asset_returns_tbl %>%
    
  tq_portfolio(assets_col = asset,
               returns_col = returns,
               weights = w_tbl,
               rebalence_on = "months")

portfolio_returns_tbl
## # A tibble: 60 × 2
##    date       portfolio.returns
##    <date>                 <dbl>
##  1 2013-01-31           0.0204 
##  2 2013-02-28          -0.00220
##  3 2013-03-28           0.0127 
##  4 2013-04-30           0.0173 
##  5 2013-05-31          -0.0113 
##  6 2013-06-28          -0.0233 
##  7 2013-07-31           0.0342 
##  8 2013-08-30          -0.0231 
##  9 2013-09-30           0.0513 
## 10 2013-10-31           0.0305 
## # ℹ 50 more rows

5 Plot

Scatterplot

portfolio_returns_tbl %>%
  
  ggplot(mapping = aes(x = date, y = portfolio.returns)) +
  geom_point(color = "cornflowerblue") +
  
  # Formatting
  scale_x_date(date_breaks = "1 year",
               date_labels = "%Y") +
  
  # Labeling
  labs(y = "monthly returns",
       x = NULL,
       title = "Portfolio Returns Scatter")

Histogram

portfolio_returns_tbl %>%
  
  ggplot(mapping = aes(x = portfolio.returns)) + 
  geom_histogram(fill = "cornflowerblue", binwidth = 0.005, color = "yellow") +
  
  labs(x = "returns",
       title = "Portfolio Returns Distribution")

Histogram & Density plot

portfolio_returns_tbl %>%
  
  ggplot(mapping = aes(x = portfolio.returns)) +
  geom_histogram(fill = "cornflowerblue", binwidth = 0.01) +
  geom_density() +
  
    
  # Formatting
  scale_x_continuous(labels = scales::percent_format()) + 
    
  labs(x = "returns",
       y = "distribution",
       title = "Portfolio Returns Distribution")