# 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
symbol <- asset_returns_tbl %>% distinct(asset) %>% pull()
symbols
## [1] "SPY" "EFA" "IJS" "EEM" "AGG"
# 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 SPY        0.25
## 2 EFA        0.25
## 3 IJS        0.2 
## 4 EEM        0.2 
## 5 AGG        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,
                 rebalance_on = "months")

portfolio_returns_tbl
## # A tibble: 60 × 2
##    date       portfolio.returns
##    <date>                 <dbl>
##  1 2013-01-31          0.0308  
##  2 2013-02-28         -0.000870
##  3 2013-03-28          0.0187  
##  4 2013-04-30          0.0206  
##  5 2013-05-31         -0.00535 
##  6 2013-06-28         -0.0229  
##  7 2013-07-31          0.0412  
##  8 2013-08-30         -0.0255  
##  9 2013-09-30          0.0544  
## 10 2013-10-31          0.0352  
## # … with 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) +
    
    labs(x = "returns",
         title = "Portfolio Returns Distribution")

Histogram & Density Plot

portfolio_returns_tbl %>% 
    
    ggplot(mapping = aes(x = portfolio.returns)) +
    geom_histogram(fill = "cornflowerblue", binwidth = 0.005) + 
    geom_density() + 
    
    # Formatting 
    scale_x_continuous(labels = scales::percent_format()) + 

    labs(x = "returns",
         y = "distribution", 
         title = "Portfolio Returns Distribution")