# 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("TM", "SBUX", "AEO", "BBW")
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] "AEO"  "BBW"  "SBUX" "TM"
# weights
weights <- c(0.25, 0.25, 0.2, 0.1)
weights
## [1] 0.25 0.25 0.20 0.10
w_tbl <- tibble(symbols, weights)
w_tbl
## # A tibble: 4 × 2
##   symbols weights
##   <chr>     <dbl>
## 1 AEO        0.25
## 2 BBW        0.25
## 3 SBUX       0.2 
## 4 TM         0.1

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           0.0866 
##  2 2013-06-28           0.0703 
##  3 2013-09-30           0.0102 
##  4 2013-12-31           0.0285 
##  5 2014-03-31           0.00443
##  6 2014-06-30           0.0800 
##  7 2014-09-30           0.0562 
##  8 2014-12-31           0.123  
##  9 2015-03-31           0.0879 
## 10 2015-06-30          -0.0266 
## 11 2015-09-30           0.0197 
## 12 2015-12-31          -0.0902 
## 13 2016-03-31           0.0199 
## 14 2016-06-30          -0.0155 
## 15 2016-09-30          -0.0277 
## 16 2016-12-30           0.0406 
## 17 2017-03-31          -0.126  
## 18 2017-06-30           0.00307
## 19 2017-09-29           0.00925
## 20 2017-12-29           0.0948

5 Plot: Portfolio Histogram and Density

Histogram & Density plot

portfolio_returns_tbl %>%
    ggplot(mapping = aes(x = portfolio.returns)) +
    geom_histogram(fill = "tomato", binwidth = 0.02) +
    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?

We should expect a 1% - 3% return.