# Load packages

# Core
library(tidyverse)
library(tidyquant)

Goal

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

Choose your stocks.

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

1 Import stock prices

symbols <- c("WMT", "UPS", "NOC", "OXY", "^GSPC")

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

2 Convert prices to returns (quarterly)

asset_returns_tbl <- prices %>%
    
    group_by(symbol) %>%
    
    tq_transmute(select     = adjusted, 
                 mutate_fun = periodReturn, 
                 period     = "quarterly",
                 type       = "log") %>%
    
    slice(-1) %>%
    
    ungroup() %>% 
    
    set_names(c("asset", "date", "returns"))

3 Assign a weight to each asset (change the weigting scheme)

# symbols
symbols <- asset_returns_tbl %>% distinct(asset) %>% pull()
symbols
## [1] "NOC"   "OXY"   "UPS"   "WMT"   "^GSPC"
# weights
weights <- c(0.15, 0.25, 0.3, 0.25, 0.05)
weights
## [1] 0.15 0.25 0.30 0.25 0.05
w_tbl <- tibble(symbols, weights)
w_tbl
## # A tibble: 5 × 2
##   symbols weights
##   <chr>     <dbl>
## 1 NOC        0.15
## 2 OXY        0.25
## 3 UPS        0.3 
## 4 WMT        0.25
## 5 ^GSPC      0.05

4 Build a 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: 20 × 2
##    date       portfolio.returns
##    <date>                 <dbl>
##  1 2013-03-28           0.0799 
##  2 2013-06-28           0.0913 
##  3 2013-09-30           0.0753 
##  4 2013-12-31           0.109  
##  5 2014-03-31           0.00610
##  6 2014-06-30           0.0393 
##  7 2014-09-30           0.00113
##  8 2014-12-31           0.0362 
##  9 2015-03-31          -0.0376 
## 10 2015-06-30           0.0138 
## 11 2015-09-30          -0.0414 
## 12 2015-12-31           0.0456 
## 13 2016-03-31           0.0521 
## 14 2016-06-30           0.0763 
## 15 2016-09-30          -0.00608
## 16 2016-12-30           0.0346 
## 17 2017-03-31          -0.0292 
## 18 2017-06-30           0.0229 
## 19 2017-09-29           0.0844 
## 20 2017-12-29           0.0823

5 Plot: Portfolio Histogram and Density

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

What return should you expect from the portfolio in a typical quarter?

You could expect a typical return of about 8% on investment