# 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 ("LULU", "NKE", "UA")
prices <- tq_get(x = symbols,
                 from = "2019-12-31",
                 to = "2025-12-31")

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
symbol <- asset_returns_tbl  %>% distinct(asset) %>% pull()
symbol
## [1] "LULU" "NKE"  "UA"
# weights
weights <- c(0.35, 0.45, 0.20)
#combine tibble 
w_tbl <- tibble(symbol, weights)


#view result
w_tbl
## # A tibble: 3 × 2
##   symbol weights
##   <chr>    <dbl>
## 1 LULU      0.35
## 2 NKE       0.45
## 3 UA        0.2

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: 22 × 2
##    date       portfolio.returns
##    <date>                 <dbl>
##  1 2020-03-31          -0.333  
##  2 2020-06-30           0.270  
##  3 2020-09-30           0.153  
##  4 2020-12-31           0.157  
##  5 2021-03-31          -0.0284 
##  6 2021-06-30           0.131  
##  7 2021-09-30          -0.00255
##  8 2021-12-31           0.0570 
##  9 2022-03-31          -0.149  
## 10 2022-06-30          -0.369  
## # ℹ 12 more rows

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? The stocks are pretty even across the board in terms of distribution with an exception at about 6% of returns earning twice as much distribution as the other percentages.