# 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("AMZN", "HD", "TSLA", "NFLX", "GOOG")
prices <- tq_get(x = symbols,
                 get = "stock.prices",
                 from = "2012-12-31",
                 to = "2017-12-31")

2 Convert prices to returns (quarterly)

asset_return_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_return_tbl %>% distinct(asset) %>% pull()
symbols
## [1] "AMZN" "GOOG" "HD"   "NFLX" "TSLA"
#weights
weights <- c(0.25, 0.20, 0.20, 0.20, 0.15)
weights
## [1] 0.25 0.20 0.20 0.20 0.15
w_tbl <- tibble(symbols, weights)
w_tbl
## # A tibble: 5 × 2
##   symbols weights
##   <chr>     <dbl>
## 1 AMZN       0.25
## 2 GOOG       0.2 
## 3 HD         0.2 
## 4 NFLX       0.2 
## 5 TSLA       0.15

4 Build a portfolio

portfolio_returns_tbl <- asset_return_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           0.223  
##  2 2013-06-28           0.231  
##  3 2013-09-30           0.190  
##  4 2013-12-31           0.125  
##  5 2014-03-31          -0.0104 
##  6 2014-06-30           0.0695 
##  7 2014-09-30           0.0313 
##  8 2014-12-31          -0.0689 
##  9 2015-03-31           0.0854 
## 10 2015-06-30           0.169  
## 11 2015-09-30           0.0887 
## 12 2015-12-31           0.157  
## 13 2016-03-31          -0.0623 
## 14 2016-06-30          -0.00986
## 15 2016-09-30           0.0740 
## 16 2016-12-30           0.0329 
## 17 2017-03-31           0.151  
## 18 2017-06-30           0.0915 
## 19 2017-09-29           0.0531 
## 20 2017-12-29           0.0946

5 Plot: Portfolio Histogram and Density

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 Histogram & Density")

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

In a typical quarter you should expect a return of upwards of 9%. The next most frequent returns are -1%, 4%, and 7%. Taking these into account, I would assume I would receive a return of around 4%-9% per quarter.