# Load packages

# Core
library(tidyverse)
library(tidyquant)

Goal

Collect individual returns into a portfolio by assigning a weight to each stock

five stocks: “TTWO”, “ADBE”, “CAT”, “NVDA”, “NOK”

from 2012-12-31 to 2017-12-31

1 Import stock prices

symbols <- c("TTWO", "ADBE", "CAT", "NVDA", "NOK")

prices <- tq_get(x = symbols,
                 get = "stock.prices",
                 from = "2012-12-31",
                 to = "2017-12-31")

2 Convert prices to returns

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

symbols <- asset_returns_tbl %>% distinct(asset) %>% pull()
symbols
## [1] "ADBE" "CAT"  "NOK"  "NVDA" "TTWO"
# weights
weights <- c(0.2, 0.2, 0.2, 0.2, 0.2)
weights
## [1] 0.2 0.2 0.2 0.2 0.2
w_tbl <- tibble(symbols, weights)
w_tbl
## # A tibble: 5 × 2
##   symbols weights
##   <chr>     <dbl>
## 1 ADBE        0.2
## 2 CAT         0.2
## 3 NOK         0.2
## 4 NVDA        0.2
## 5 TTWO        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,
                 rebalence_on = "months")

portfolio_returns_tbl
## # A tibble: 20 × 2
##    date       portfolio.returns
##    <date>                 <dbl>
##  1 2013-03-28           0.0726 
##  2 2013-06-28           0.0204 
##  3 2013-09-30           0.193  
##  4 2013-12-31           0.0872 
##  5 2014-03-31           0.0792 
##  6 2014-06-30           0.0651 
##  7 2014-09-30           0.00850
##  8 2014-12-31           0.0448 
##  9 2015-03-31          -0.0354 
## 10 2015-06-30           0.0245 
## 11 2015-09-30           0.0246 
## 12 2015-12-31           0.162  
## 13 2016-03-31           0.0245 
## 14 2016-06-30           0.0856 
## 15 2016-09-30           0.210  
## 16 2016-12-30           0.161  
## 17 2017-03-31           0.101  
## 18 2017-06-30           0.212  
## 19 2017-09-29           0.198  
## 20 2017-12-29           0.0797

5 Plot

Histogram & Density Plot

portfolio_returns_tbl %>%
    
    ggplot(mapping = aes(x = portfolio.returns)) +
    geom_histogram(fill = "cornflowerblue", binwidth = 0.01, color = "tomato") +
    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 your portfolio in a typical quarter?

Based on my histogram, I should have an average of around a 5% gain every quarter. This is because that is where the apex shows on the density line. The minimum quarter was around -4%, where the maximum quarter is around 22%.