# 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("UAL", "AAL", "LUV")

prices <- tq_get(x    = symbols,
                 get  = "stock.prices",
                 from = "2020-01-01",
                 to   = "2024-12-31")

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] "AAL" "LUV" "UAL"
# weights
weights <- c(0.4, 0.3, 0.3)
weights
## [1] 0.4 0.3 0.3
w_tbl <- tibble(symbols, weights)
w_tbl
## # A tibble: 3 × 2
##   symbols weights
##   <chr>     <dbl>
## 1 AAL         0.4
## 2 LUV         0.3
## 3 UAL         0.3

4 Build a portfolio

# ?tq_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: 19 × 2
##    date       portfolio.returns
##    <date>                 <dbl>
##  1 2020-06-30           0.0434 
##  2 2020-09-30           0.00441
##  3 2020-12-31           0.231  
##  4 2021-03-31           0.333  
##  5 2021-06-30          -0.118  
##  6 2021-09-30          -0.0511 
##  7 2021-12-31          -0.133  
##  8 2022-03-31           0.0436 
##  9 2022-06-30          -0.298  
## 10 2022-09-30          -0.0937 
## 11 2022-12-30           0.0926 
## 12 2023-03-31           0.100  
## 13 2023-06-30           0.176  
## 14 2023-09-29          -0.298  
## 15 2023-12-29           0.0418 
## 16 2024-03-28           0.0938 
## 17 2024-06-28          -0.121  
## 18 2024-09-30           0.0569 
## 19 2024-12-30           0.382

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?

  1. In a typical quarter, I can expect a return of about 4% from this portfolio. However, according to the plot, it would not be unusual to expect returns anywhere between -10% and 15%.