# 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("RGR", "AMZN", "TSLA")
prices <- tq_get(x    = symbols, 
                 get  = "stock.prices",
                 from = "2012-12-31",
                 to   = "2024-10-2")

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] "AMZN" "RGR"  "TSLA"
# weights
weights <- c(0.25, 0.2, 0.1)
weights
## [1] 0.25 0.20 0.10
w_tbl <- tibble(symbols, weights)
w_tbl
## # A tibble: 3 × 2
##   symbols weights
##   <chr>     <dbl>
## 1 AMZN       0.25
## 2 RGR        0.2 
## 3 TSLA       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: 48 × 2
##    date       portfolio.returns
##    <date>                 <dbl>
##  1 2013-03-28           0.0499 
##  2 2013-06-28           0.105  
##  3 2013-09-30           0.144  
##  4 2013-12-31           0.0682 
##  5 2014-03-31          -0.0483 
##  6 2014-06-30           0.00416
##  7 2014-09-30          -0.0374 
##  8 2014-12-31          -0.0857 
##  9 2015-03-31           0.102  
## 10 2015-06-30           0.104  
## # ℹ 38 more rows

5 Plot: Portfolio Histogram and Density

portfolio_returns_tbl %>%
    
    ggplot(mapping = aes(x = portfolio.returns)) +
    geom_histogram(fill = "yellow4", binwidth = 0.01) +
    geom_density() +
    
    
    # Formatting
    scale_x_continuous(labels = scales::percent_format())

    labs(x     = "Returns",
         y     = "Distribution",
         title = "Portfolio Histogram and Density")
## $x
## [1] "Returns"
## 
## $y
## [1] "Distribution"
## 
## $title
## [1] "Portfolio Histogram and Density"
## 
## attr(,"class")
## [1] "labels"

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

You should be able to get about a 5% return in a typical quarter