# 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("XOM", "SHEL", "BP", "CVX")

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 <- asset_returns_tbl %>% distinct(asset) %>% pull()
weights <- c(0.30,0.10,0.20,0.40)
w_tbl <- tibble(symbols, weights)
w_tbl
## # A tibble: 4 × 2
##   symbols weights
##   <chr>     <dbl>
## 1 BP          0.3
## 2 CVX         0.1
## 3 SHEL        0.2
## 4 XOM         0.4

4 Build a portfolio

portfolio_returns_tbl <- asset_returns_tbl %>%
    tq_portfolio(assets_col   = asset, 
                 returns_col  = returns, 
                 weights      = w_tbl, 
                 rebalance_on = "quarters")
portfolio_returns_tbl
## # A tibble: 20 × 2
##    date       portfolio.returns
##    <date>                 <dbl>
##  1 2013-03-28           0.0289 
##  2 2013-06-28           0.00194
##  3 2013-09-30           0.00124
##  4 2013-12-31           0.138  
##  5 2014-03-31          -0.00748
##  6 2014-06-30           0.0825 
##  7 2014-09-30          -0.0971 
##  8 2014-12-31          -0.0706 
##  9 2015-03-31          -0.0444 
## 10 2015-06-30          -0.00815
## 11 2015-09-30          -0.169  
## 12 2015-12-31           0.0452 
## 13 2016-03-31           0.0499 
## 14 2016-06-30           0.144  
## 15 2016-09-30          -0.0393 
## 16 2016-12-30           0.0753 
## 17 2017-03-31          -0.0642 
## 18 2017-06-30           0.00698
## 19 2017-09-29           0.0883 
## 20 2017-12-29           0.0725

5 Plot: Portfolio Histogram and Density

portfolio_returns_tbl %>%
    ggplot(mapping = aes(x = portfolio.returns)) + 
    geom_histogram(fill = "wheat4", binwidth = 0.01) + geom_density() + 
    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? In any typical quarter you should expect a return of approximately 2%